devices for calculating physiological data, respiratory assistance, test used in a titration job, bl

专利摘要:
DEVICES FOR CALCULATING PHYSIOLOGICAL DATA, FOR DIAGNOSIS OF CHRONIC HEART FAILURE, RESPIRATORY ASSISTANCE, TEST USED IN A TITLING WORK, BLOOD PRESSURE TEST, OXYGEN SUPPLY AND MONITORING SYSTEM a detection test for comfort level, including sleep quality, that is measurable at home without requiring brainwave or electrocardiogram measurements. The respiratory waveform of an individual during sleep is continuously measured and recorded by the flow of respiratory gas, etc., and is transformed into a Fourier window at each measurement time to generate a frequency spectrum, and a bandwidth is extracted. including a respiratory rate. The index indicating the regularity of the individual's breathing period is also calculated at each time point during sleep, and the time dependence of this index during sleep is plotted as a graph. A medical device includes a sleep assessment system equipped with a control means to carry out control, so that a sleep cycle repeated in a cycle of about 90 minutes is clearly observed if the comfort level, including (... ).
公开号:BR112012003140B1
申请号:R112012003140-6
申请日:2010-08-11
公开日:2021-07-06
发明作者:Hidetsugu Asanoi
申请人:Hidetsugu Asanoi；Heartlab, Inc.；
IPC主号:

专利说明:

[Technical Field]
[001] The present invention relates to a device for calculating respiratory waveform information, a device that assesses comfort level, including sleep quality, a device for calculating physiological data, a computer program for calculation, using respiratory waveform information, a computer program to assess comfort level, including an individual's sleep quality, a respiratory assist device, a device to cure chronic heart disease, an inspection device to be used in titration , a blood pressure testing device, a blood pressure testing computer program, a polysomnography testing device and the like, and particularly providing a configuration that enables the safe assessment of a comfort level, including the quality of sleep of a patient. individual without requiring tests in patients admitted to a medical institution, simplifying and facilitating the configuration. ration of the prior art. [Fundamentals of Art]
[002] The assessment of sleep quality, which is one of the comfort levels of an individual, is important in diagnostic and medical treatment of various diseases.
[003] Including a period of being awake, a human's sleep includes six stages, that is, an awakening period, a REM period (Rapid Eye Movement: period of sleep during which eye movement is noted), a NREM period (non-REM), first stage (initial slanted sleep stage), an NREM period, second stage (slanted sleep stage), an NREM period, third stage (moderate sleep stage), and an NREM period, fourth stage (deep sleep stage).
[004] In a normal sleep, when entering a sleep state of the awakening period, the transition from a sleep state is repeated three cycles in one night, each cycle being typically 90 minutes or 60 to 120 minutes in general, called a sleep cycle (ultradian rhythm), and each cycle includes a part or all of the stages described above in the REM period and the NREM period, where the depth of sleep cyclically (periodically) changes with each cycle, and also changes with a tendency to gradually change from a deep sleep state, in the early sleep stage, to a light sleep, full-night sleep.
[005] Therefore, the comfort level, including sleep quality, is estimated based on whether the repeated sleep cycle in this ultradian rhythm is clearly noted or in each cycle, whether the cyclic sleep stage transition is clearly noted in each cycle or if the depth of sleep gradually changes from the early stage of sleep to a light end stage of full-night sleep.
[006] In a sleep with an unfavorable quality, the ultradian rhythm is not clear in the transition from the sleep state, and there may be a case where a deep sleep stage is not found in the early sleep stage, however, on the contrary , the deep sleep stage enters the final stage, for example.
[007] There are several diseases that cause obstruction in good quality sleep, and in OSAS (Obstructive Sleep Apnea Syndrome), for example, a part of a patient's tongue during sleep shrinks by gravitational force and physically blocks the pathways air, which obstructs breathing and causes awakening, and prevents entry into a stage of deep sleep.
[008] Also, CSR (Cheyne-Stokes Breathing), considered to be found in approximately 40% of patients with CHF (congestive heart failure), also causes a drop in comfort level, including sleep quality.
[009] CSR is the breath in which after a small breath tidal volume gradually increases, the tidal volume gradually decreases, and respiratory interruption (apnea of approximately 10 to 20 seconds) occurs and then the similar cycle is repeated .
[0010] A factor causing the occurrence of CSR in CHF patients is understood below.
[0011] The respiratory center of the brain performs respiratory control by detecting the partial pressure of CO2 in the blood at a normal time. The CHF patient has high brain sensitivity to CO2 partial pressure while being awake and in a state of hyperventilation.
[0012] However, during sleep this sensitivity is somewhat recovered and diminished, and unless the partial pressure of CO2 in the blood rises more than on awakening (ie, apnea), breathing is not initiated, and the CSR described above occurs.
[0013] The symptom of Cheyne-Stokes Breathing is frequently seen in CHF and is accompanied by sleep disturbance, caused by a state of nocturnal hypoxia and awakening. The state of nocturnal hypoxia and awakening causes an increase in pulmonary artery pressure and sympathetic nerve activity, decreases exercise tolerance, and worsens the prognosis.
[0014] As described above, since the comfort level, including sleep quality, is decreased due to various diseases, it is necessary to estimate the comfort level, including sleep quality of an individual, and use the result for diagnosis and treatment.
[0015] First, a prior art method of assessing comfort level, including sleep quality, will be described.
[0016] In the past, in order to assess comfort level, including sleep quality, the following sleep test was performed using a device called PSG (Polysomnography) (hereafter this sleep test is called "PSG" or “PSG test”) was conducted in general. PSG is a test in which medical personnel quantitatively assess sleep depth (sleep stage), sleep fragmentation, presence of awakening reactions and the like, measuring respiratory flows, snoring sound, blood oxygen saturation (SpO2) , brain waves, electromyograms, eye movement, and the like, through an individual's period of sleep.
[0017] Medical personnel identify the cyclical period of sleep from a change in brain waveform, for example, using the result of measuring the PSG and making assessments through a method such as discrimination between the REM period and the NREM period, due to the presence of eye movement and surface electromyography. These PSGs are described in the following Patent Document 1 and Patent Document 2, for example.
[0018] Also, although different from PSG, Patent Document 3 describes a method, as indicated in paragraph 0023, in which respiratory data and movement data, such as rolling in each sleep stage of an individual, are accumulated in advance using the PSG, and the current sleep stage is identified only from the breathing data and the movement data in a test not using the PSG. Running the PSG is necessary to create initial data for identification, and the identification accuracy is an important result in the work of identifying the sleep stage from the measurement data.
[0019] Next, a prior art technology relating to the observation and detection of Cheyne-Stokes respiration will be described.
[0020] In detecting Cheyne-Stokes respiration, the PSG described above has been used in general. That is, brain waves, eye movement, respiratory flows, thoracoabdominal movement ventilation, arterial oxygen saturation, electrocardiogram (including heart rate) and the like are measured during the night's sleep period using PSG, and if gradual increase and gradual decrease in respiratory flows and respiratory efforts are found to occur repeatedly during NREM sleep 1 to 2 (light sleep) by the measurement result report, the medical personnel make a diagnosis that the occurrence of Cheyne-Stokes respiration is suspected or similar.
[0021] For the purpose of simplified and safe discovery of such Cheyne-Stokes respiration, Teijin Limited proposed a biological information monitoring device in which medical personnel can observe the Cheyne-Stokes respiration symptom from a result of analysis of the measurement result of an altered state of the autonomic nerve, based on the alternating heart rate analysis and the measurement results of respiratory flows and respiratory efforts (ventilation movement), and the configuration is described in Patent Document 4.
[0022] However, these prior art technical configurations for detecting Cheyne-Stokes respiration are all used so that medical personnel observe the physiological data and detect Cheyne-Stokes respiration. That is, although Cheyne-Stokes respiration is recognized as an important risk factor in chronic heart failure, a setting to automatically detect the occurrence of Cheyne-Stokes respiration has not been proposed until now. [List of Quote] Patent Document
[0023] Patent Document 1: Japanese Patent No. 2950038
[0024] Patent Document 2: Unreviewed Japanese Patent Application Publication No. 2004-305258
[0025] Patent Document 3: Unreviewed Japanese Patent Application Publication No. 2008-301951
[0026] Patent Document 4: Unreviewed Japanese Patent Application Publication No. 2004-283194 [Summary of the Invention] [Technical problem]
[0027] Since the PSG described above requires brainwave measurement, the size of a PSG device in use is large and needs to be installed in a medical institution and also since high-level manipulation is required in the Attaching an Electrode To detect brain waves in an individual, a professional engineer performs the attachment work and the individual to which the electrode has been attached cannot move easily.
[0028] Thus, to undergo PSG, an individual needs to be hospitalized in a dedicated medical institution or in a dedicated testing facility, called a sleep laboratory, with a three-day and two-night program (the first night for the PSG testing and the second night to determine prescription for treatment) and, in many cases, undergo testing at such medical institutions. PSG, which is an overnight test, requires hospitalization and preparation of sophisticated/complicated devices, including a brainwave testing division and manipulation by professional engineers, and thus the problem of increased test cost cannot be solved.
[0029] Also, with the technology described in Patent Document 3, the PSG execution is required to create initial data for identification, and the work, in which the device automatically performs the sleep stage identification from the measurement data , has a problem of validity and accuracy of the identification algorithm.
[0030] Furthermore, if arrhythmia, which is often found in CHF patients, is included in the data, accurate assessment is difficult.
[0031] In addition, there has been a technical problem that the work of identifying an observation peak of an electrocardiogram waveform by a professional engineer is necessary, and the attachment of an electrode for measuring the electrocardiogram requires precision and skills and , thus, the fixation of a test device in a medical institution is necessary.
[0032] Also, in prior art technologies, a configuration where a medical personnel can observe a comfort level, including sleep quality and the occurrence of Cheyne-Stokes respiration directly based on physiological elements only of the waveforms of respiratory flow, which are important physiological data of an individual in sleep, or a setting of automatic assessment or automatic extraction of them, is not described at all.
[0033] The present invention was made in view of the above circumstances and is intended to provide a device to be used for assessing the level of comfort, including the quality of sleep safely and simply without requiring testing in inpatients and using only the forms and calculate respiratory waveform information to be used in Cheyne-Stokes respiration symptom detection, a device to assess comfort level, including sleep quality, a device to calculate physiological data, a computer for calculation using respiratory waveform information, a computer program to assess the comfort level, including the individual's sleep quality, a respiratory assist device, a device to treat chronic heart disease, a test device used for a titration job, a blood pressure testing device, a computer program to conduct r a blood pressure test, and a polysomnography testing device. [Solution to Problem]
[0034] The present invention provides, in order to solve the above problems, a device to calculate respiratory waveform information described in 1) to 42) below, a device to assess the level of comfort, including the quality of sleep, a device for calculating physiological data, a computer program for calculating using respiratory waveform information, a computer program for assessing comfort level, including the individual's sleep quality, a respiratory assist device, a device for treating chronic heart disease, a testing device used for a titration job, a blood pressure testing device, a computer program to conduct a blood pressure test, and a polysomnography testing device.
[0035] 1) A device for calculating respiratory waveform information, comprising (1) measuring means, which measures a change in an individual's respiratory flow for a predetermined measurement period, including sleep; (2) means of calculating, which performs calculation, including the following steps A to C with respect to the waveform of the respiratory flow measured by the measuring means; and (3) output means, which performs at least any processing of displaying, printing or sending out of the device the information of a calculation result made by the calculating means: Step A: A step of creating a frequency spectrum in each time, sequentially performing the Window Fourier transform with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; Step B: A step of creating an index indicating the regularity of an individual's respiratory cycle in the Fourier window time at the respective times: and Step C: A step of creating waveform information indicating a temporal change of the index as the information of the calculation result.
[0036] 2) A device for calculating respiratory waveform information, comprising (1) measurement means, which measures a change in an individual's respiratory flow for a predetermined measurement period; (2) means of calculating, which performs calculation, including the following steps A to C, with respect to the respiratory flow waveform measured by the measuring means; and (3) output means, which performs at least any processing of displaying, printing or sending out of the device the information of a calculation result made by the calculating means: Step A: A step of creating a frequency spectrum in each time, sequentially performing Window Fourier transform with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; Step B: A step of creating an index indicating regularity of an individual's respiratory cycle in the Fourier window time of the respective times; and Step C: A step of creating the waveform information indicating a temporal change of the index as the calculation result information.
[0037] 3) A device for calculating respiratory waveform information, described in 1) or 2), in which the index indicating the regularity of the respiratory cycle is set as a value in inverse proportion to a standard deviation of frequency variation respiratory in a certain period.
[0038] 4) A device for calculating respiratory waveform information described in 1) to 3), further comprising a step of creating at least any information of (a) a waveform indicating a temporal change; (b) a maximum value; (c) an average value; and (d) time from sleep onset to the time when the maximum value is reached of ultradian rhythm power included in the waveform indicating temporal change of the index indicating regularity of the respiratory cycle as information of a result of the calculation.
[0039] 5) A device for calculating respiratory waveform information, in which an operation performed by the measuring means of (1), described in any of 1) to 4), is performed by a shape recording meter. respiratory waveform, and an operation performed by the calculating means of (2) and the output means of (3), described in any one of 1) to 4), is performed by a respiratory waveform analysis device based on the waveform recorded in the respiratory waveform recording meter.
[0040] 6) A device for calculating respiratory waveform information described in 5), wherein the respiratory waveform information recorded in the respiratory waveform recording meter is transmitted to the shape analysis device waveform, via a recording medium or a communication path.
[0041] 7) A device for assessing a comfort level, including sleep quality, comprising (1) measuring means, which measures a change in an individual's respiratory flow for a predetermined measurement period including sleep; (2) means of calculating, which performs calculation, including the following steps A to C with respect to the waveform of the respiratory flow measured by the measuring means; and (3) means of assessment, which produces assessment of the comfort level, including sleep quality based on the size of a numerical value of at least any one of (a) a maximum value; (b) an average value; and (c) time from sleep onset to the time when the maximum value is reached of ultradian rhythm power included in the waveform indicating the temporal change of an index indicating regularity of the respiratory cycle obtained by means of calculating: Step A: One step of creating a frequency spectrum on each occasion by sequentially performing Window Fourier transform with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; Step B: A step of creating an index indicating regularity of an individual's respiratory cycle in the Fourier window time of the respective times; and Step C: A step of creating the waveform information indicating a temporal change of the index as the calculation result information.
[0042] 8) A device for assessing a comfort level, including sleep quality, in which an operation performed by the measuring means of (1) described in 7) is performed by a respiratory waveform recording meter , and an operation performed by the calculating means of (2) and the output means of (3), described in 7), is performed by a respiratory waveform analysis device based on the waveform recorded in the meter. respiratory waveform recording.
[0043] 9) A device for assessing a comfort level, including sleep quality described in 8), wherein respiratory waveform information recorded in the respiratory waveform recording meter is transmitted to the device of respiratory waveform analysis via a recording medium or a communication path.
[0044] 10) A device for calculating physiological data, comprising measuring means that measures physiological data of an individual for a predetermined measurement period; creating means, which creates an index at each measurement time indicating stability of the measured value at each measurement time during the measurement period, and creates data of a temporal change of the index during the measurement period; and output means, which performs output processing of at least any displaying, printing or sending out of the device the created data.
[0045] 11) A device for calculating physiological data, in which an operation performed by the measuring means described in 10) is performed by recording physiological data measurement, and an operation performed by the creating means and the output means, described at 10, it is performed by a physiological data analysis device based on the waveform recorded in the physiological data recording meter.
[0046] 12) A device for calculating physiological data described in 11), wherein the physiological data information recorded in the physiological data recording meter is transmitted to the physiological data analysis device via a recording medium or a path of communication.
[0047] 13. A device for calculating respiratory waveform information, comprising at least (1) measurement means, which measures a change in an individual's respiratory flow for a predetermined measurement period, including sleep; (2) means of calculating, which performs calculation including the following steps A and B with respect to the respiratory waveform of the respiratory flow measured by the measuring means; and (3) output means, which performs at least any output processing of displaying, printing or sending out of the device the information of a calculation result made by the calculating means: Step A: A step of creating a spectrum of frequency at each time, sequentially performing the Window Fourier transform with a starting point offset by a predetermined offset time interval, with respect to the respiratory waveforms; Step B: A step of extracting and creating a specific frequency domain power waveform from the respiratory flow waveform, which is power waveform data in a specific frequency domain changing over time, from a frequency spectrum at each time obtained in Step A as the calculation result information.
[0048] 14) A device for calculating respiratory waveform information, described in 13), wherein the specific frequency domain includes a respiratory frequency of a human body.
[0049] 15) A device for calculating respiratory waveform information, described in 13) or 14), wherein the specific frequency region includes a frequency of occurrence of the Cheyne-Stokes respiratory symptom of a human body.
[0050] 16) A device for calculating respiratory waveform information, described in any one of 13) to 15), wherein the means of calculating further creates and outputs a waveform obtained by extracting a caused noise component by the measurement performed by the respiratory flow waveform measurement means.
[0051] 17) A device for calculating respiratory waveform information, described in any one of 13) to 16), further comprising means for selecting arbitrary time in the measurement period of a specific frequency domain power waveform submitted to outbound processing; and means to further create (A) waveform information, which amplifies the specific frequency domain power waveform in a neighboring region, including selected time and/or information (B) of the region's frequency spectrum neighbor, including the selected time as the calculation result information.
[0052] 18) A device for calculating respiratory waveform information, wherein an operation performed by the measuring means described in any one of 13) to 17) is performed by a respiratory waveform recording meter, and a The operation performed by the calculating means and the output means, described in any one of 13 to 17, is performed by a respiratory waveform analysis device based on the waveform recorded in the respiratory waveform recording meter.
[0053] 19) A device for calculating respiratory waveform information, described in 18), wherein the respiratory waveform information recorded in the respiratory waveform recording meter is transmitted to the respiratory waveform analysis device. respiratory waveform via a recording medium or a communication path.
[0054] 20) A computer program for performing calculation using respiratory waveform information, comprising (1) a measurement step, wherein the measurement means measures an individual's respiratory flow for a predetermined measurement period, including sleep; (2) a calculating step, wherein the calculating means performs calculations including the following steps A to C with respect to the respiratory flow waveform measured by the measuring step; and (3) an output step, wherein the output means performs at least any processing of displaying, printing or sending out of the device information of a calculation result made by the calculating means; Step A: A step of creating a frequency spectrum at each time, sequentially performing Window Fourier transformation with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; and Step B: A step of creating an index indicating regularity of an individual's respiratory cycle in the Fourier window time of the respective times; and Step C: A step of creating waveform information indicating a temporal change of the index as the calculation result information.
[0055] 21) A computer program for performing calculation using respiratory waveform information, described in 20), wherein the step of calculating performs the calculation, further comprising a step of creating information from at least any one of (a ) a waveform indicating a temporal change; (b) a maximum value; (c) an average value; and (d) time from sleep onset to the time when the maximum value is reached of ultradian rhythm power included in the waveform indicating the temporal change of an index indicating regularity of the respiratory cycle.
[0056] 22) A computer program to be run to assess a comfort level, including the sleep quality of an individual, comprising (1) a measurement step in which the measuring means measures a change in a respiratory flow of the individual for a predetermined measurement period, including sleep; (2) a calculating step, wherein the calculating means performs calculation including the following steps A to C with respect to the waveform of the respiratory flow measured in the measuring step; and (3) an assessment step, in which the assessment means assesses the comfort level, including sleep quality based on the size of a numerical value of at least any one of (a) a maximum value; (b) an average value; and (c) time from sleep onset to the time when the maximum value of ultradian rhythm power is reached included in a waveform indicating the temporal change of an index indicating regularity of the respiratory cycle obtained by the step of calculating: Step A: One step of creating a frequency spectrum at each time, sequentially performing the Window Fourier transform with a starting point offset by a predetermined offset time interval, with respect to the respiratory waveforms; Step B: A step of creating an index indicating the regularity of an individual's respiratory cycle in the Fourier window time of the respective times: and Step C: A step of creating waveform information indicating a temporal change of the index as the information of the calculation result.
[0057] 23) A computer program for performing calculation using respiratory waveform information, comprising at least (1) a measurement step, wherein the measuring means measures a change in the respiratory flow of an individual for a predetermined period measurement, including sleep; (2) a calculating step, wherein the calculating means performs calculations including the following steps A to B with respect to the respiratory flow waveform measured by the measuring step; and (3) an output step, wherein the output means performs at least any processing of displaying, printing or sending out of the information device a calculation result made by the calculating means; Step A: A step of creating a frequency spectrum at each time, sequentially performing Window Fourier transformation with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; and Step B: A step of extracting and creating a specific frequency domain power waveform from the respiratory flow waveform, which is data from a temporal change of power in a specific frequency domain of the following (A) or (B), and/or the waveform extracted from the following (C) of a frequency spectrum at each time obtained in Step A as information of the calculation result: (A) A frequency range including the respiratory frequency of a body ; (B) A frequency range including the frequency of generation of the Cheyne-Stokes respiration of a human body; (C) A waveform obtained by extracting a noise component, originated by the measurement performed in the respiratory waveform measurement step.
[0058] 24) A respiratory assistance device, comprising compressed air supply means, configured to supply compressed air with a pressure higher than atmospheric pressure, and capable of changing the supply pressure outwards; duct means connected to the feed side out of the compressed air feed means; and mask means, provided at the other end of the duct means and attached to a patient for treatment by supplying compressed air to the patient, the respiratory assistance device continuously supplying compressed air to the patient in a sleep state through the means of mask, further comprising: (1) means of obtaining biological information, which continuously obtains biological information from the patient to whom the compressed air is supplied; and (2) control means, which alters and controls the supply pressure out of the compressed air supply means in one direction to improve the comfort level, including the patient's sleep quality, using biological information obtained as above. , in which the biological information is the information regarding the patient's respiratory waveform, and the means of control performs change and control of the outward feeding pressure based on a temporal change of an index indicating regularity of an individual's respiratory cycle , the respiratory cycle being continuously obtained.
[0059] 25) A device for treating chronic heart diseases, comprising compressed air supply means configured to supply compressed air with a pressure higher than atmospheric pressure and capable of changing the supply pressure outwardly; duct means connected to the supply side out of the compressed air supply means; and mask means, provided at the other end of the duct means and attached to a patient for treatment, to supply compressed air to the patient, the device being configured to continuously supply compressed air to the patient in a sleep state through the mask means , further comprising: (1) a means of obtaining biological information that continuously obtains biological information from the patient to whom the compressed air is supplied; and (2) control means, which alters and controls the supply pressure out of the compressed air supply means in one direction to improve the comfort level, including the patient's sleep quality, using biological information obtained as above. , in which the biological information is the information regarding the patient's respiratory waveform, and the means of control performs change and control of the outward feeding pressure based on a temporal change of an index indicating regularity of an individual's respiratory cycle , the respiratory cycle having been continuously obtained.
[0060] 26) A device described in 24) or 25), in which the compressed air supply means is configured to automatically change and control the supply pressure outwards, so that the pulmonary ventilation of the patient under treatment and/ or the respiratory rate of the patient being treated comes close to a certain value determined in advance.
[0061] 27) A device in which the operation performed by the biological information obtaining means (1), described in any one of 24) to 26), is performed by a respiratory waveform recording meter, and the operation performed by the control means (2), described in any one of 24) to 26), is performed by a device to change/control an out supply pressure based on the waveform recorded in the waveform recording meter respiratory.
[0062] 28) A device described in 27), wherein respiratory waveform information recorded in the respiratory waveform recording meter is transmitted to the device to change/control a supply pressure outward through a recording medium or a communication path.
[0063] 29) A testing device used in a titration work, comprising a respiratory assist device provided with compressed air supply means, which feeds compressed air outward at a pressure higher than atmospheric pressure, means of duct connected to the supply side to the outside of the compressed air supply means, and a mask half, provided at the other end of the duct means and fixed to a patient undergoing treatment to supply compressed air to the patient, the respiratory assistance device being configured to continuously supply compressed air to the patient through the mask means at a constant pressure, or at a variable pressure wherein a medical personnel determines at least any one of (1) a compressed air pressure value; (2) a pattern of changing the compressed air pressure value; and (3) selecting the plurality of respiratory assist devices to be suitable for treatment, further comprising: sensing means, which continuously detects respiratory waveform information from the patient being treated; means of calculating, which calculates an index indicating regularity of the patient's respiratory cycle by respiratory information; and output means, which performs at least any one of displaying, printing, and emitting to the outside, so that a temporal change of the compressed air pressure and a temporal change of the index indicating the regularity of the respiratory cycle can be observed simultaneously.
[0064] 30) A testing device used in a titration job, in which the operation performed by the detection means, described in 29), is performed by a respiratory waveform recording meter, and the operation performed by the means calculating and the output means, described at 29), is performed by a respiratory waveform analyzing device based on the waveform recorded in the respiratory waveform recording meter.
[0065] 31) A testing device used in a titration work, described in 30), wherein the respiratory waveform information recorded in the respiratory waveform recording meter is transmitted to the respiratory waveform analysis device. respiratory waveform through a recording medium or a communication path.
[0066] 32) A blood pressure sensing device, comprising (1) respiratory flow measurement means, which measures a change in the respiratory flow of an individual for a first predetermined measurement period; (2) means of calculating, which performs calculation, including the following steps A to C, with respect to the respiratory flow waveform measured by the respiratory flow measuring means and outputs the result as information; (3) blood pressure value measuring means, which measures a temporal change of an individual's blood pressure value for a second predetermined measurement period, having a period equal to the first predetermined period; and (4) output means, which performs at least any processing of displaying, printing or sending, outside the device, the output calculation result information, and the trend information of the measured blood pressure value in a capable mode. of comparison with each other: Step A: A step of creating a frequency spectrum at each time, sequentially performing Window Fourier transform with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; Step B: A step of creating an index indicating regularity of an individual's respiratory cycle in the Fourier window time of the respective times; and Step C: A step of creating waveform information indicating a temporal change of the index as the calculation result information.
[0067] 33) A blood pressure testing device, described in 32), wherein the first predetermined measurement period and/or the second predetermined measurement period is configured to include a period during the subject's sleep.
[0068] 34) A blood pressure testing device, in which the operation performed by the respiratory flow measurement means, described in 32) or 33), is performed by a respiratory waveform recording meter, and/or the operation performed by the blood pressure value measuring means is performed by a blood pressure value recording meter, and the operation performed by the calculating means and output means, described in 32) or 33), is performed by an analyzing device based on the waveform recorded in the respiratory waveform recording meter and/or the value recorded in the blood pressure value recording meter.
[0069] 35) A blood pressure testing device, described in 34), wherein the respiratory waveform information recorded in the respiratory waveform recording meter and/or the blood pressure value recorded in the blood pressure value recording meter, is transmitted to the analysis device via a recording medium or a communication path.
[0070] 36) A blood pressure testing device, comprising (1) blood pressure value measuring means, which measures and obtains a blood pressure value of a subject in accordance with an acquisition command; (2) a respiratory flow measurement means, which measures a temporal change in the individual's respiratory flow; (3) calculating means, which performs calculation including the following steps A to C, with respect to the respiratory flow waveform measured by the respiratory flow measuring means; and (4) means of creating obtain command, which creates the obtain command if an index indicating regularity of a respiratory cycle, described in the following step B included in the information calculated by the calculation means, exceeds a threshold value determined in advance: Step A : A step of creating a frequency spectrum at each time, sequentially performing window Fourier transformation with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; Step B: A step of creating an index indicating the regularity of an individual's respiratory cycle in the Fourier window time of the respective times; and Step C: A step of creating waveform information indicating a temporal change of the index as the calculation result information.
[0071] 37) A blood pressure testing device, described in any one of 32) to 36), wherein the index indicating the regularity of the respiratory cycle is set as a value in inverse proportion to a standard deviation of frequency variation respiratory in a certain period.
[0072] 38) A computer program for performing a blood pressure test, comprising (1) a step in which the respiratory flow measurement means measures a change in an individual's respiratory flow for a first predetermined measurement period; (2) a step in which the calculating means performs calculation, including the following steps A to C with respect to the waveform of the respiratory flow measured by the respiratory flow measuring means; (3) a step in which the blood pressure measuring means measures a change in a subject's blood pressure value by a second predetermined measurement period having a period equaled with the first predetermined period; and (4) a step in which the output means performs at least any processing of displaying, printing or sending to the outside of the device the information of the calculation result made and the information of the change of the measured blood pressure value in a capable way. of comparison with each other: Step A: A step of creating a frequency spectrum at each time, sequentially performing Window Fourier transform with a starting point offset by a predetermined offset time interval with respect to the respiratory waveforms; Step B: A step of creating an index indicating the regularity of an individual's respiratory cycle in the Fourier window time of the respective times; and Step C: A step of creating waveform information indicating a temporal change of the index as the calculation result information.
[0073] 39) A computer program to perform a blood pressure test of 38), in which the index indicating the regularity of the respiratory cycle is set as a value in inverse proportion to a standard deviation of respiratory rate variation in a certain time course.
[0074] 40) A polysomnography testing device comprising measuring means, which measures a blood pressure value of an individual.
[0075] 41) A blood pressure testing device comprising (1) measuring means, which measures a change of a single part of or a plurality of physiological data of an individual by a first predetermined measurement period, including sleep ; (2) determining means, which continuously determines whether or not the individual is in a slow-wave sleep state at each measurement time based on physiological data measured by the measurement means; (3) blood pressure value measuring means, which measures a change in blood pressure value in the subject for a second predetermined measurement period, having a period equal to the first predetermined measurement period; and (4) output means, which performs at least any processing of displaying, printing or sending out of the device the determination result information and the measured blood pressure value change information in a manner capable of comparison with each other. .
[0076] 42) A blood pressure testing device, comprising (1) blood pressure value measuring means, which measures and obtains a blood pressure value of a subject in accordance with an acquisition command; (2) measurement means, which measures a change of a single part of or a plurality of physiological data of the individual; (3) determination means, which continuously determines whether or not the individual is in a slow-wave sleep state at each measurement time based on the physiological data measured by the measurement means; and (4) the obtain command creating means, which creates the obtain command if the determining means determines that the individual is in the slow wave sleep state.
[0077] 43) An oxygen supply device for supplying oxygen gas for suction or concentrated oxygen gas for suction, comprising (1) biological information obtaining means, which continuously obtains biological information from a target patient to whom the gas is supplied; and (2) a control means, which alters and controls a gas supply flow in one direction, to improve the patient's comfort level using the biological information obtained.
[0078] 44) An oxygen supply device, described in 43), wherein that biological information is information regarding a patient's respiratory waveform, and the control means performs supply flow control, based on the respiratory cycle stability information obtained by the information regarding this respiratory waveform.
[0079] 45) An oxygen supply device, described in 44), further comprising respiratory synchronization means, which performs gas supply control according to the air inspired by the user based on a signal from a sensor that detects a state of at least the inspired air or the exhaled air by the patient, in which the control means obtains the information regarding the respiratory waveform based on the sensor signal.
[0080] 46) An oxygen supply device, described in any one of 43) to 45), wherein a gas supply source is any one of the following (A) to (D) provided on the interior or exterior of the device : (A) Medium that separates oxygen in air and creates concentrated oxygen gas; (B) A high pressure gas container, which compresses and stores oxygen gas and discharges it according to one operation; (C) A liquid oxygen container, which stores liquefied oxygen gas and discharges it as oxygen gas according to operation; and (D) Piping means, having one end connected to the high pressure gas container and the other end to the oxygen supply device.
[0081] 47) A test system, comprising a sensor means, which detects a state of inspired air and/or expired air of an individual; first creating means, which creates the individual's respiratory waveform information based on an output signal from the sensing means; and second creating means, which creates respiratory cycle stability information from the created respiratory waveform information.
[0082] 48) Patient monitoring system comprising a sensor means, which detects a state of inspired air and/or expired air of an individual; first creating means, which creates the individual's respiratory waveform information based on an output signal from the sensing means; second creation means, which creates respiratory cycle stability information from respiratory waveform information; and transmitting means and receiving means, which transmit/receive the respiratory waveform information and/or the respiratory cycle stability information via a communication path.
[0083] 49) Medical equipment system, comprising medical equipment installed in a patient's home or in a medical institution; and a transmission terminal connected to or incorporated in the medical equipment, the transmission terminal obtaining information from the medical equipment and transmitting it to a receiving terminal installed in a location away from the medical equipment through a communication means, in which the information transmitted includes respiratory waveform information, obtained by sensing the patient's state of inspired air and/or exhaled air based on an output signal from the sensor means incorporated within or provided separately from the medical equipment, and/or information on the stability of respiratory cycle, taken from the respiratory waveform information created as above.
[0084] 50) A medical equipment system described in 49), wherein the transmitted information further includes operating information of the medical equipment.
[0085] Each of the configurations described above can be combined with each other as long as they do not depart from the main point of the present invention. [Advantages of the Invention]
[0086] The present invention with the above configuration exerts the marked advantages of providing a device that calculates respiratory waveform information used to assess a comfort level, including sleep quality, and detect Cheyne-Stokes breathing symptoms reliably and simply without requiring inpatient testing and using only respiratory waveforms, a device that assesses a comfort level including sleep quality, a device to calculate physiological data, a computer program to perform calculation using shape information waveform, a computer program to assess the level of comfort including an individual's sleep quality, a respiratory assist device, a device for treating chronic heart disease, a testing device used in a titration job, a blood pressure testing device, a computer program for a blood pressure test uine, and a polysomnography testing device. [Brief Description of Drawings]
[0087] Fig. 1 is a configuration diagram of a sleep assessment system based on the respiratory waveform according to the present invention.
[0088] Fig. 2 is a schematic diagram illustrating a principle when the system of Fig. 1 performs measurement.
[0089] Fig. 3 is an example of a waveform measured using the system in Fig. 1.
[0090] Fig. 4 is an example of a waveform measured using the system in Fig. 1.
[0091] Fig. 5 is an example of a waveform measured using the system in Fig. 1.
[0092] Fig. 6 is a waveform diagram to explain a method of creating a noise waveform using the system of Fig. 1.
[0093] Fig. 7 is a waveform diagram illustrating a time shift of a plurality of indices created using the system of Fig. 1.
[0094] Fig. 8 is a schematic diagram to explain a principle for calculating a variable index using the system in Fig. 1.
[0095] Fig. 9 is a diagram to explain a typical example of good quality sleep using a brain wave SWA waveform and a temporal shift of a sleep stage.
[0096] Fig. 10 is a schematic diagram to explain a principle of calculating a standard deviation of a respiratory cycle, using the system in Fig. 1.
[0097] Fig. 11 is an example of each waveform frequency spectral graph in a selected time domain created by the system in Fig. 1.
[0098] Fig. 12 is each index graph of a first case.
[0099] Fig. 13 is each index graph of the first case.
[00100] Fig. 14 is each index graph of the first case.
[00101] Fig. 15 is each index graph of the first case.
[00102] Fig. 16 is each index graph of the first case.
[00103] Fig. 17 is each index graph of a second case.
[00104] Fig. 18 is each index graph of the second case.
[00105] Fig. 19 is each index graph of the second case.
[00106] Fig. 20 is each index graph of the second case.
[00107] Fig. 21 is each index graph of the second case.
[00108] Fig. 22 is each index graph of a third case.
[00109] Fig. 23 is each index graph of the third case.
[00110] Fig. 24 is each index graph of the third case.
[00111] Fig. 25 is each index graph of the third case.
[00112] Fig. 26 is each index graph of the third case.
[00113] Fig. 27 is each index graph of a fourth case.
[00114] Fig. 28 is each index graph of the fourth case.
[00115] Fig. 29 is each index graph of the fourth case.
[00116] Fig. 30 is each index graph of the fourth case.
[00117] Fig. 31 is each index graph of the fourth case.
[00118] Fig. 32 is each index graph of a fifth case.
[00119] Fig. 33 is each index graph of the fifth case.
[00120] Fig. 34 is a configuration diagram of a CPAP device according to the present invention.
[00121] Fig. 35 is a configuration diagram of a sleep introducing device according to the present invention.
[00122] Fig. 36 is a configuration diagram of a massaging device according to the present invention.
[00123] Fig. 37 is a configuration diagram of a blood pressure measuring system according to the present invention.
[00124] Fig. 38 is a schematic diagram of a graph output by the system of Fig. 37.
[00125] Fig. 39 is a summary device configuration diagram exemplifying a variable pressure adsorption type oxygen concentration device, which is an embodiment of the present invention.
[00126] Fig. 40 is a diagram illustrating an example of a medical support system of this embodiment. [Best Mode for Carrying Out the Invention]
[00127] An optimal configuration, according to an embodiment of the present invention, which is a sleep assessment system based on a respiratory waveform (hereinafter also referred to as this system or the sleep assessment system), will be described below with reference to the attached drawings.
[00128] A sleep assessment device of this embodiment has the primary purpose of creating and outputting waveform information based on an individual's respiratory waveform so that medical personnel make a diagnosis based on this information of waveform.
[00129] Also, in the following description, including each variation, a sleep assessment device, as a specialized embodiment for the purpose of analyzing the respiratory waveform, is focused, however, technical aspects and advantages described here are not limited for the purpose of analyzing the respiratory waveform. It is possible to use the device for analyzing other physiological data of a human body, and apart from a measured value as a cycle of the respiratory waveform of the following description, the configuration of this embodiment can also be applied to a cycle or amplitude and on other measured values of other physiological data. The specific configurations of these applied configurations can be sufficiently understood by the description of this embodiment.
[00130] Also, although the setting in which an individual's physiological data during sleep is used is most important when an individual's body state is observed using physiological data such as a respiratory waveform, when the device performs an automatic evaluation, or when medical equipment or the like is automatically controlled using the result of the automatic evaluation, it is just an example of several embodiments. Even if the physiological data of an individual in an aroused state is used during the day or at night, the specific advantages of the present invention, illustrated in each of the embodiments below, can be shown. [Sleep assessment device configuration based on respiratory waveform]
[00131] This evaluation system 1 is, as illustrated in a configuration diagram in Fig. 1, provided with a portable respiratory waveform recording meter 2 and a respiratory waveform analysis device 3.
[00132] The portable respiratory waveform recording meter 2 is a portable device that can record a respiratory waveform and it is preferable that the device is typically loaned by a medical institution for an individual, so that the individual can continuously record and maintain a waveform recorded in a night sleep at home and then the device is transported to the medical institution. For example, a biological information monitor “Morpheus set (registered trademark) R” (Teijin Pharma Limited, owner of marketing authorization, medical equipment authorization No 21300BZY00123000, medical control equipment category, medical equipment maintenance and control specified ) employs a pressure sensor (nasal cannula) to detect an airflow/snoring, and this equipment can be used configured to finely detect apnea, hypopnea, and snoring.
[00133] Needless to say, respiratory waveform recording can be performed in a medical institution, and recorded waveform data can be recorded on a recording medium, such as a flash memory, a magnetic disk, a disk optical and the like, and transported or transmitted via a communication path to a device that conducts the analysis. The communication path includes the Internet communication network, a dedicated communication line, a dial telephone line and the like, whether wired or wireless.
[00134] In order to perform the above functions, the portable respiratory waveform recording meter 2 has a respiratory air flow sensor 2-1 to be attached to the skin surface in the vicinity of the subject's nasal cavity, one unit a 2-2 respiratory waveform detection amplification unit, an A/D conversion unit 2-3, a memory unit 2-4, which records and maintains the respiratory waveform as a digital signal, and an A/D terminal. output 2-5, which inputs the respiratory waveform digital data from memory unit t2-4 to the outside.
[00135] The 2-1 respiratory air flow sensor is a thermal sensor fixed to the vicinity of the individual's nasal cavity and differentiates the temperature of a respiratory air flow from the outside air temperature, for example, and measures and detects the temperature of the respiratory air flow, in order to measure the presence and intensity of the air flow through this individual's breathing.
[00136] As a configuration to measure the breathing air flow of an individual, a method of resistance change based on the deformation of a strip-shaped member due to a breathing air flow, a configuration of a mill structure. wind using rotation by airflow and the like can be used, except the thermal sensor, as long as the presence and intensity of the breathing airflow can be detected.
[00137] Particularly, the use of a respiratory pressure measuring sensor provided with a piezoelectric film of PVDF (polyvinylidene fluoride) is a preferable mode than a pressure sensor that detects respiration.
[00138] In addition, the respiratory operation (ventilation movement) of the individual can be measured and recorded by not directly measuring the respiratory air flow, but by measuring the tension caused by the extension of a band wrapped around the chest or stomach of the subject by breathing movement, or by providing a pressure measurement sensor on a mat placed under the subject.
[00139] These various respiratory sensors are attached to a predetermined part of a patient in order to detect the patient's respiratory airflow or respiratory efforts (ventilation movement) of the patient, and the medical institution shall provide guidance on the method of fixation in advance to the patient before testing. However, when compared to fixing an electrode for electrocardiogram measurement in a specific position on the patient's chest epidermis, the approval of position, direction and the like for fixing the respiratory sensor is higher than in the case of a sensor for electrocardiogram, and it is easy for a patient or the patient's family to attach the sensor according to the guidance of the medical institution and obtain a correct measured value.
[00140] Furthermore, in recent years, instead of detecting a respiratory operation by attaching some means of measurement to an individual as above, many types of non-contact respiratory sensors have been proposed, which emit electromagnetic waves to the individual from from a distant position and detect the subject's body movement or breathing operation by analyzing reflection waves.
[00141] For example, in the document “Microwave respiratory sensor for evaluation”, which is posted on the World Wide Web and can be accessed (http://www.3.ocn.ne.jp/mwlhp/kokyu.PDF), a Non-contact respiratory sensor using microwave is described, describing its configuration, principle and advantages as “weak microwave impulses being emitted to an individual from a high gain directional antenna. Microwave pulses, reflected on the individual's skin surface through bedding and clothing, are received as a micromotion reflection signal by a highly sensitive receiver for a gate time. By specifying accurate antenna directivity detection space and remote gate reception, higher micromotion sensor sensitivity can be realized without being affected by disturbance. A demonstration device for evaluation has a sensing distance of approximately 2 m and a circle with a diameter of approximately 60 cm, but an oval sensing surface covering a bed width can be realized by antenna design.”, “once that this is an accepted microwave micromovement sensor to obtain a microradio standard requiring no qualification, there is no problem of obtaining a license and the like for commercialization. The electric field strength of microwave radiation is not greater than the electric field strength of satellite broadcasting and does not harm human bodies. Non-contact detection of micromovement on the skin surface can be done without being affected by bedding or clothing, and no load is applied to the individual. Using a lining material such as a patch plate with less microwave loss of passage, the device can be installed above the lining and no physiological load is applied to the individual. When compared to a Doppler-type micromotion detection method, higher sensitivity can be realized without being affected by disturbance by specifying the sensing distance and sensing range, and no mutual interference occurs, even if a plurality of devices is installed in close proximity.”
[00142] Similarly, Japanese Unanalyzed Patent Application Publication No. 2002-71825, which is a document known and entitled as "human body detecting device using microwave", describes a human body detecting device using microwave, employing a microwave as a transmission wave in life scenarios, such as in a dressing table, a bathroom, a kitchen, a shower area and the like, comprising a single antenna that receives the microwave, detection means that detects the microwave received by the antenna, comparison means comparing an output of the shift component detecting means with a predetermined position, and means for detecting the presence of a human and the biological information of a human by a signal from the comparing means, the body detection device human using a microwave described above, wherein the sensing means is provided with a Doppler sensor that detects Doppler switching from a reflection wave to transmission, the device. human body detection device using a microwave described above, wherein the signals obtained by the detection means and the comparison means are signals synchronized with pulses from a human, and the human body detection device using a microwave described above, in that the signals obtained by the detection means and the comparison means are signals synchronized with a human breathing operation.
[00143] Similarly, Unreviewed Japanese Patent Application Publication No. 2005-237569, which is a document known and entitled "portable measuring device, health management system and health management method", describes that "a transmission unit 11a of a microwave Doppler sensor 10a, illustrated in Fig. 2, transmits a microwave to a user Pa (See Fig. 1). Here, the transmission unit 11a transmits the microwave to the vicinity of the user's heart Pa (See Fig. 1). The microwave has properties being transmitted through cotton or nylon, which is the material of the user's clothing Pa (See Fig. 1) and reflected by the body surface and metal. A receiving unit 12a receives a reflection wave. Here, the reflection wave is the microwave reflected on the body surface in the vicinity of the user's heart Pa (See Fig. 1). An amplification unit 15a receives the microwave signal by transmission unit 11a. The amplification unit 15a receives the reflection wave signal from the receiver unit 12a. The amplification unit 15a amplifies the microwave signal and the reflection wave signal. A calculation unit 16a receives a signal relating to the microwave from the amplification unit 15a, via a processing unit 13a. Here, the microwave signal is a signal obtained by amplifying the microwave signal. The calculation unit 16a receives a signal relating to the reflection wave from the amplification unit 15a, via the processing unit 13a. Here, the signal referring to the reflection wave is a signal obtained by amplifying the reflection wave signal. The calculation unit 16a calculates the change information (See Fig. 7). The change information (See Fig. 7) is the information regarding a change of signal referring to the reflection wave with respect to the signal referring to the microwave. An extraction unit 14a receives the change information (See Fig. 7) from the calculation unit 16a, via the processing unit 13a. The extraction unit 14a extracts the swath information based on the shift information (See Fig. 7). Band information is information of a predetermined frequency band (See P1 to P4 in Fig. 7). An analysis unit 17a receives the track information (See P1 to P4 in Fig. 7) from the extraction unit 14a, via the processing unit 13a. The analysis unit 17a analyzes body micromovement by the user's heart rate Pa (See Fig. 1), based on the range information (See P1 to P4 in Fig. 7). As a result, the analysis part 17a analyzes the heart rate information (See Fig. 8) based on the range information (See P1 to P4 in Fig. 7). Here, the heart rate information (See Fig. 8) is information regarding a degree of tension. A determination unit 18a receives the heart rate information (See Fig. 8) from the analysis unit 17a, via the processing unit 13a. The determination unit 18a determines the user's anomaly Pa (See Fig. 1) based on the heart rate information (See Fig. 8). If the determination unit 18a determines that the user Pa (See Fig. 1) has an anomaly, the processing unit 13a receives the heart rate information (See Fig. 8) from the analysis unit 17a and supplies it to a device. 20th exit. Along with that, the processing unit 13a refers to a storage device 40a, receives identification information 41a from the storage device 40a and supplies the identification information 41a to the output device 20a. If the determination unit 18a determines that the user Pa (See Fig. 1) has no anomaly, the processing unit 13a does not supply any information to the output device 20a. A transmission output unit 21a of output device 20a receives heart rate information (See Fig. 8) and identification information 41a from microwave Doppler sensor 10a. The transmission output unit 21a transmits the heart rate information (See Fig. 8) and the identification information 41a to a control center 60 via a wireless telephone line. The other mobile phones 50b, ... are similar to a mobile phone 50a.”, and respiration can be detected by breathing operation instead of heart rate operation using this setting.
[00144] Similarly, the unanalyzed Japanese Patent Application Publication No. 2005-270570, which is a document known and entitled as “biological information monitoring device”, describes “a device that monitors the information of a living body by obtaining the surface displacement information of the living body in a non-contact manner, comprising means that generate high frequency electromagnetic waves and radiate them into space, means that detect the electromagnetic waves scattered over the surface of the living body, and means that calculate the temporal fluctuation of the positional displacement on the living body surface of a state of propagation of electromagnetic waves, further comprising a means to calculate characteristic degrees of vibration, such as pulsation, respiration and the like of temporal fluctuation as biological information, an information monitoring device biological information described above, in which the biological information is obtained by the pulse, d wave and pulse, respiration, electrocardiographic wave, blood pressure or analysis thereof, a biological information monitoring device described above, in which the high frequency electromagnetic waves are millimeter waves in the terahertz range (30 GHz to 30 THz) and information about the living body surface is obtained through clothing made of organic fibers or the like, a biological information monitoring device, described in any of the above, in which the high frequency electromagnetic waves are repeatedly generated short pulses and a half-bandwidth pulse rate is 33 psec or less, a biological information monitoring device described above, in which the temporal fluctuation of positional displacement at various points on the living body is calculated simultaneously by the means that calculates the temporal fluctuation of positional displacement on the body surface live from electromagnetic waves, and a state of propagation of the characteristic degree. As calculated from the temporal fluctuation through the living body can be detected, a biological information monitoring device, described above, further comprising a storage medium in which the mental and physical states of a living body are determined using the characteristic degree stored in advance. , a characteristic degree in which an output signal, obtained by the means that calculates the biological information, is continuously stored, and an actual signal emitted by the means that calculates the biological information, a biological information monitoring device described above, in which the mental and physical states to be determined are a health state such as blood pressure, degree of arterial sclerosis and the like, obtained by pulse vibration analysis, and the breath vibration analysis and the result of the determination are directly displayed in letters or sound or presented at a terminal via a network, a biological information monitoring device, description above, in which the mental and physical states to be determined are an emotional state, such as degree of relaxation, degree of tension, emotions and the like, obtained by pulse rate analysis and breath rate analysis, and the result of determination is fed again to a mechanical device or an electronic device, in order to be used as a control signal of an interface that operates the mechanical device or electronic device, and the biological information monitoring device, described above, in that the biological information monitoring device is incorporated at a point, such as a washtub, toilet, chair or the like, where a human stays for a certain period of time, and the biological information is obtained remotely in a non- fixed in point”. So these settings can be used. The inclusion of configurations using the non-contact breathing sensor within the scope of the present invention applies to all examples.
[00145] The respiratory waveform analysis device 3 similarly constituting this sleep assessment system 1 is performed by a personal computer system typically including a display screen or a printer and a computer program installed on the computer to perform the operation, and the device is installed in a medical or similar institution, in which the respiratory waveform recording meter 2, for which the acquisition of the respiratory waveform of an individual has been completed, is connected, the form data Respiration waveform data are transmitted, and the calculation using the respiration waveform data is performed according to procedures that will be described later. In addition, respiratory waveforms or a temporal (temporal) waveform change, which is the result of the calculation based on the respiratory waveform, is displayed on a display screen in a time series or printed by a printer, or both are performed, so that a medical staff looking at the screen display or print result can assess sleep. In order to perform these functions, the respiratory waveform analysis device 3 is provided with a 3-1 input end for collecting respiratory waveform digital data from the outside, a 3-2 memory unit which temporarily records and maintains collected data, an analysis unit 3-3 which displays the recorded data and performs a calculation operation employing these, which will be described later, a display unit 3-4 which displays data in time series, which is the calculation result output from the 3-3 analysis unit on the display screen, a 3-5 print unit which similarly prints the output time series data and a 3-6 data transmission end which transmits the output data from calculation to the outside. [Respiratory waveform analysis device operation]
[00146] Next, an operation of a respiratory waveform calculation performed by the respiratory waveform analysis device 3, which is a characteristic configuration of this system 1, will be described.
[00147] The analysis part 3-3, provided in the respiratory waveform analysis device 3, extracts the respective frequency domains as follows, for example, from a plurality of Fourier spectra at the time it becomes a point of starts each Fourier window period obtained by running Fast Fourier Transform changing the time in five seconds to a Fourier window period of 5-minutes from the entered respiratory waveforms and creates and emits a temporal change of a form of wave with 50 second change interval: 0.11 to 0.5 Hz (corresponding to the respiratory rate range) 0.012 to 0.04 Hz (corresponding to the Cheyne-Stokes respiratory rate range)
[00148] The above operation will be described in detail and, in Fig. 2, schematically illustrating the waveform analyzed or generated by this system 1 at each stage, the raw respiratory waveform, including various frequency components, is like illustrated in Fig. 2A, while the analysis unit 3-3 determines the window time tFFT of a starting point 2a of this waveform, or specifically a 5 minute 2b1 transformation window, for example, and performs the transformation. Fast Fourier (FFT) for the waveform included in this section. The tFFT window time is not limited to 5 minutes, but can be chosen from a wide range of 30 seconds to 30 minutes, for example, as long as a temporal change in the power of the target frequency range in the individual's sleep period can be observed. As a result of the run, a Fourier 2c1 spectrum of the waveform in this section is created.
[00149] Next, the 3-3 analysis unit similarly determines a Fourier transform 2b2 window of the tFFT window time from a shifted position in the forward time direction by TS shift time or specifically by 50 seconds, for example , from the 2A starting point of the waveform and perform fast Fourier transform again and, as a result, get a 2C2 Fourier spectrum in this section.
[00150] Similar to the window time, the TS changeover time is not limited to 50 seconds, but can be chosen from a wide range of 2 seconds to 5 minutes, for example, as long as a temporal change of power can be observed. of target frequency range in the individual's sleep period.
[00151] Similarly, a Fourier spectrum is created by executing fast Fourier transform in the respective Fourier transform windows obtained by changing the starting point of the Fourier transform window by a multiple TS shift time integral and this operation continues to the point end of the Fourier transform window reach a 2D end point of the respiratory waveform. In a real calculation operation, the respiratory waveform is measured for a predetermined measurement period, including the individual's sleep time for one night or 8 hours, for example, and the 2a starting point of the waveform corresponds to the start time of the measurement period, while the 2d endpoint corresponds to the end time of the measurement period.
[00152] Then, the analysis unit 3-3 extracts 0.11 to 0.5 Hz (corresponding to the respiratory rate range), 0.012 to 0.04 Hz (corresponding to the Cheyne-Stokes respiratory rate range), for example, or other frequency domains at frequencies included in each Fourier spectrum for the entire plurality of Fourier spectra obtained by the above operation, and obtains a power by changing the waveform of a specific frequency domain (hereinafter also referred to as specific frequency wave) 2e, which is a waveform obtained by plotting the power over time of the starting point of the respective Fourier windows, that is, a waveform illustrating how the power of the specific extracted frequency range changes from according to the time in sleep.
[00153] In specific frequency waveform extraction, only any of the frequency domains can be selected and extracted or other frequency domains can be used. Also, the frequency domains illustrated above are all examples and may be changed where appropriate to put the present invention into practice, and the above description is not limiting.
[00154] The temporal change waveform of this specific frequency power is a waveform illustrating changes in the respiration rate component, a Cheyne-Stokes respiration rate component, or a frequency component of a noise component caused by measurement over time for a period from the respiratory waveform measurement start time to the measurement end time or 8 hours, for example.
[00155] Therefore, a medical personnel, who will make a diagnosis of the individual's state during sleep, can clearly observe the temporal change of breathing power during sleep, presence of Cheyne-Stokes breathing and a temporal change of power, and the presence of a noise component caused by the measurement and a temporal change of power based on direct and physiological fundamentals of the respiratory waveform data, which are important physiological data linked to the individual's sleep state, the temporal change of these is observed. specific frequency waveforms, which are offset on a screen or printed and can be visually recognized.
[00156] In addition, the physiological data required for observation can be sufficiently obtained through a channel of a respiratory waveform, and there is no hassle problem in placing a large number of electrodes in contact, without separation as in electrocardiography or a sensor unit required to be attached as an electrode by medical personnel, but measurement is relatively easy.
[00157] As a result, rather than the inpatient test method imposing a great burden of cost and time on the individual and society as a whole, which is PSG, the great advantages described above can be obtained by conducting the test using this system for the purpose of a screening test prior to such inpatient testing.
[00158] Also, this system can be configured to have the following functions in addition to the above functions. When the measured respiratory waveform is displayed on the display part 3-4, a waveform extracted from the respiratory rate or a waveform from which the Cheyne-Stokes frequency is extracted is observed by medical personnel in order of making various diagnoses, there may be a case where data from a specific measurement time domain, rather than the total measurement period, are to be extended, and the neighboring region, including its neighbor time, i.e., the time selected needed to be particularly observed.
[00159] Thus, in this system 1, a first operator selects the time to be displayed in an enlarged manner by moving a cursor over the display unit 3-4 or by displaying the specific time of the waveform printed on the outside and inputting the time by a fixed keyboard or similar.
[00160] The 3-3 analysis unit can be configured to create a frequency spectrum of this respiratory waveform, as above, at the selected time or in its vicinity, i.e. in the neighboring region, including the selected time and a diagram zoom of each zoomed waveform with a short time interval and the like, and to similarly display, print or output it to the outside. [Case data]
[00161] A process of creating each waveform extracted from the range and each calculation waveform from the original measured respiratory waveforms will be described with exemplified waveform data. The following numerical values are just examples and execution with appropriate change is possible.
[00162] (a) Original respiratory sensor output waveform: Org Resp (Fig. 3A)
[00163] The lateral axis indicates the start time of the measurement and the unit is the hour. The vertical geometric axis indicates the size of the measured power (the same applies to the following).
[00164] The sampling frequency of these original respiratory sensor output waveforms is 16 Hz.
[00165] (b) original measured respiratory waveform obtained by four averaging measurements: Resp4,Res (Fig. 3B)
[00166] In order to suppress unexpected noise involved in the sample, after four measured data are averaged, and this-4Hz waveform is used as an original waveform for subsequent stripe extraction and data processing.
[00167] That is, this corresponds to an unprocessed respiratory waveform in Fig. 2A described above.
[00168] (c) Cycle waveform of respiratory operation: mean lung power (Fig. 3C)
[00169] This is a 0.11 to 0.5 Hz component, which is a high frequency domain corresponding to the respiratory rate range of the original measured Resp respiratory waveform obtained by averaging the four measurements being extracted and the average power of the 0.08Hz range before and after cycling to its maximum power. By tracking and observing the temporal change of this waveform, a temporal change in the size of an individual's breathing operation can be known.
[00170] This respiratory operation cycle waveform, average lung power, and the following normalized Cheyne-Stokes respiratory power waveform, CSR/average lung power, corresponds to waveform 2e changing the power of the specific frequency domain in Fig. 2B.
[00171] (d) Normalized Cheyne-Stokes respiratory power waveform: CDSR/mean lung power (Fig. 4D).
[00172] This is a waveform obtained by extracting a range from 0.012 to 0.04 Hz corresponding to the CSR cycle range of the original measured respiratory waveform Resp4 obtained by averaging four measurements. The waveform is divided by the average lung power of the waveform power of the breath and normalized cycle operation.
[00173] (e) Cheyne-Stokes breath generation assessment grade: CS grade (Fig. 4E)
[00174] The Cheyne-Stokes breathing power normalized above is classified into 6 degrees from 0 to 5, for example, according to amplitude size, and a temporal change of degree is displayed.
[00175] (f) Normalized noise component power waveform: average noise/lung power (Fig. 4F)
[00176] This is a waveform detected by the respiratory sensor described above, but not caused by a flow of breathing air and illustrating a temporal change of the noise component. This noise component is caused by an individual's body movement, for example, and a temporal change in the size of the individual's body movement during sleep can be observed. In addition, a body movement sensor, pressure treadmill, body movement detection band, or similar, except the respiratory sensor, is not required.
[00177] As a method of creating this noise component waveform, a specific frequency can be extracted, however, in this embodiment, the respiratory waveform Res4 is still subjected to the moving average for smoothing, and a part still projecting from the smoothing waveform is detected to create the waveform.
This method will be described by referring to Figs. 5 and 6.
[00179] Fig. 5 illustrates the respiratory sensor output waveform obtained by calculating the average of four measurements (Res4) and the smoothing waveform submitted to the moving average of the past 5 seconds of this Res4 (smooth) in one juxtaposed way. A portion of the waveform measured through the entire sleep period is taken and illustrated, where the lateral geometric axis indicates elapsed time (Sec, scale 104).
[00180] Fig. 6 further illustrates a method of creating a noise component waveform (Noise), in which a casing (base) over the bottom of the respiratory sensor output waveform, obtained by calculating the average of four measurements (Res4) is created first, and the smoothing (smooth) waveform is subtracted from this base, and the result is the noise waveform (Noise).
[00181] That is, in light from the smoothing waveform (Smoothing) indicating the trend of the respiratory waveform, the sensor output moving away from this trend is extracted as a part of noise.
[00182] Fig. 4F illustrates a temporal change of the Noise/average lung power of the normalized noise component power waveform in the sleep period, obtained by being divided by the mean lung power, described above, and normalized.
[00183] (g) respiratory cycle variation index: var (Fig. 7G)
[00184] Next, the respiratory cycle variation index, var, to see a temporal change in the individual's respiratory cycle variation will be described by referring to Fig. 8.
[00185] In Fig. 8, first, the above described respiratory operation cycle waveform, mean lung power, is schematically illustrated. As defined above, the range is 0.11 to 0.50 Hz as illustrated. The lateral axis of Fig. 8 indicates a frequency and the vertical axis indicates power.
[00186] Here, a peak frequency found in mid-lung power, that is, a central frequency of the respiratory cycle, is defined as HF (high frequency), and regions defined as 0.08 Hz wide on both sides HF bands are defined as centerband regions (B). And a region, having lower frequencies than the centerband region, is defined as a left sideband region (A), while a region having higher frequencies than the centerband region is defined as a sideband region. right (C).
[00187] Here, if the variation of the individual's respiratory cycle is large, in the spectral diagram of Fig. 8, a quotient obtained by dividing the value obtained by integrating the spectral power of the left side band region (A) and the right sideband region (C), that is, regions A and C with respect to frequency, by a value obtained by integrating the entire spectral power, that is, regions A, B and C with respect to frequency must be larger. This value is called an index of variation (var) of the respiratory cycle, and the temporal change of an actually measured value is illustrated in Fig. 7G.
[00188] (h) Standard deviation of the respiratory cycle: RespHzSD (Fig. 7H)
[00189] Next, two selected indices of an approach different from the above-described index of variation respiratory cycle VAR will be described, in order to observe a temporal change in the variation of the individual's respiratory cycle.
[00190] The inventor has obtained the following finding when making sleep assessment diagnoses for a large number of cases using the individual's respiratory waveform measurement information.
[00191] As described first, a cycle made up of six types of sleep stages is repeated approximately three times in a night, typically with approximately a 90-minute sleep cycle, and a change in physiological data in each cycle can be clearly observed by a slow wave component (SWA: Slow Wave Activity) of the brain waves as below. In the case of an individual whose comfort level, including sleep quality, has deteriorated for some causes, such as sleep apnea, it is recognized by the inventor's examination that the sleep stage cycle interrupts SWA and cannot be clearly observed.
[00192] Fig. 9 explains a relationship between the slow wave component (SWA) of brain waves and the sleep stage for the case of an individual having a good level of comfort, including sleep quality, using a typical pattern. The lateral axis indicates measurement time and represents the entire sleep period for one night (8 hours in the illustration). As clearly known from Fig. 9, the temporal change in the cyclically repeated sleep stage is synchronized with a power shift of SWA and particularly the power of SWA becomes maximum in stage IV where sleep is deepest.
The data in Figs. 3 to 7 that were described above are created by the same respiratory sensor output waveform of the same individual found to have no heart disease and a good level of comfort, including sleep quality, but the data in Fig. 9 is not this individual's data, however, shows a typical example.
[00194] The inventor has paid attention to the breathing operation of the sleeping individual and found that if attention is paid to the small change in the respiratory cycle obtained by measurement or, in other words, stability of the respiratory rate or regularity of the respiratory cycle, the observation of this sleep cycle and therefore the assessment of the comfort level, including sleep quality, can be made, which resulted in the completion of the present invention. In the following, the phrase “regularity of a respiratory cycle” is used including properties of small change in the respiratory cycle and stability of the respiratory rate.
[00195] Using the system described above as a respiratory cycle range, the average lung power of the breath cycle waveform described above is extracted, for example, from the breath waveform obtained by measurement . By calculating a mean value (X bar) of the first respiratory rate, and further calculating the standard deviation (SD) of the respiratory rate using a known statistical method, the size of the change in the respiratory cycle can be known. Furthermore, by acquiring an inverse number of the standard deviation (SD), the stability of the respiratory cycle can be expressed. Instead of using the mean value (X bar) of the respiratory rate, other indices such as the peak respiratory cycle frequency (HF) described above can be used.
[00196] The inverse number of the standard deviation of the measured respiratory waveform is referred to as the RSI (Respiratory Stability Index) here. By graphically illustrating the RSI so that a temporal change of sleep in one night can be known, medical personnel can observe and easily determine that the sleep cycle is clearly expressed, and the comfort level, including sleep quality , is good, or evident observation cannot be made and comfort level, including sleep quality, is poor, or automatic determination can be made by a diagnostic device from regularity.
[00197] On the other hand, in a method of recording and observing a temporal change in the respiratory rate or a temporal change in a heart rate while an individual is sleeping, for example, which is a different configuration than this embodiment of the present invention, these waveforms of changes do not match the slow wave component (SWA) change of the brain wave and thus it is already known that this method is not suitable for assessment of comfort level, including sleep quality.
[00198] Thus, in a one variation system of the present invention, as described above, a plurality of Fourier spectra of time, which is a starting point of each Fourier window period obtained by performing Fast Fourier Transform (FFT) , changing the time from 5 seconds of the Fourier window period to 5 minutes of the entered respiratory waveform, a frequency domain from 0.11 to 0.50 Hz, including 0.4 Hz, which is a typical respiratory cycle from a human body, it is extracted.
[00199] Furthermore, in the variation system of the present invention, the analysis part 3-3 calculates an average value (X bar) and a standard deviation (SD) of the frequency included in the respiratory rate range for each Fourier window obtained with the above-described change interval of 50 seconds.
[00200] Fig. 7H illustrates a standard deviation of an individual's conventional respiratory cycle RespHzSD. The RSI described above, which is an inverse number of this SD, is calculated for each Fourier window period having a change interval of 50 seconds, a graph indicating a temporal change of the RSI in which its power is plotted on the orthogonal geometric axis. for the geometric time axis, is created, and this can be displayed, printed or outputted to the outside as information of the calculation result. By looking at this RSI chart, the stability of the sleep cycle and therefore the comfort level, including sleep quality, can be easily observed and diagnosed.
[00201] Fig. 7I similarly illustrates the standard deviation of an individual's conventional respiratory cycle RespHzSD.
[00202] The meaning of the observation of the RSI described above will be qualitatively described from another point of view.
[00203] In Fig. 10, schematically illustrating a frequency spectrum of the average lung power of the cycle waveform of the respiratory operation, for example, which is a frequency spectrum after extraction of the respiratory frequency, the frequency spectrum in a state in which sleep is deep, an individual's breathing is weak, the frequency shift is smaller, and a breathing operation is stable is, as illustrated in a graph 10a, so that the width of the wrap shape around the mean value of the fxbar-s frequency is small, and its standard deviation expressed as fSDs is also considered to be small.
[00204] On the other hand, in a state where sleep is more superficial, the respiratory operation becomes rapid, the respiratory rate changes to a higher average frequency value fxbar-r, and the respiratory rate fluctuation also becomes becomes larger, and thus the amplitude of the shape of the wrap is enlarged, and the standard deviation fSD-r of this state also becomes larger.
[00205] Therefore, as described above, examining a temporal change of the RSI, which is an inverse number of the standard deviation, a regular period (graph 10a) and an irregular period (graph 10b), as illustrated in Fig. 10, can be visually observed and diagnosed easily.
[00206] The numerical values described above for the Fourier window periods are only examples and capable of running on other values when appropriate, and as for the above-described method of calculating the RSI using the inverse number of the standard deviation, an index obtained by others methods of calculating indicating the regularity of the respiratory cycle can also be used, and they are also a part of the present invention.
[00207] Also, as illustrated in Fig. 10, it can be thus configured that SD, RSI and the like are calculated using only the peak data up to 95% of the respiratory rate graph and data lower than 5% are eliminated in order to suppress the influence of noise.
[00208] Furthermore, as described above, in addition to displaying each graph waveform during an individual's entire night's sleep period, it can be thus configured for a medical staff to specify a time domain in which the staff requires that the waveforms of the graph be particularly magnified and observed, and that the waveform of each graph in the time domain and a frequency distribution (spectrogram) of each waveform in the displayed time domain can be produced.
[00209] Fig. 11 is an example thereof, and since a medical staff observes each waveform through the entire sleep region and selects a specific region with particularly large CSR, as illustrated in Fig. 11(2) in each waveform graph in the selected region for 300 seconds and as illustrated in Fig. 11(1), a spectrogram of each waveform of this selected time domain can be displayed. According to Fig. 11, it can be visually recognized easily that the spectral power of the CSR is large in (1) and that the CSR waveform cyclically repeats increase/decrease in (2). That is, CSR is found in the individual in this region.
[00210] Since the selection configuration of a specific time domain employing means of operation and displaying a spectrogram and a power waveform in that region, as described above, can be easily performed by a known technology, its detailed description will be omitted in order to avoid inconvenience. [Small wave analysis]
[00211] Next, in the waveform generated based on the respiratory waveform described above, a result of comparing and examining cases particularly using RSI (Respiratory Stability Index) will be described.
[00212] Prior to the description, in the target waveform analysis similar to RSI, a small wave analysis, which is a mathematical method of accurately analyzing for the power of a specific frequency component, such as an ultradian rhythm or a physiological cycle Basic sleep (approximately 90 minutes) changes over time, will be described as preparation.
[00213] As a traditional analysis method for an irregularly continuous signal system, including a biological signal, Fourier analysis has been well known.
[00214] Fourier analysis is, as described in detail in the following known document 1, for example, an analysis in which a Fourier-series expansion method of a function having a cycle is further expanded to a non-periodic function, the in order to express an arbitrary irregular continuous signal series by superposition, including infinite order of a functional waveform having a periodicity of a sine waveform and self-similarity.
[00215] Known Document 1: “Introduction to Digital Signal Processing” by Kennichi Kido, p. 13 to 15, (issued on July 20, 1985, by Maruzen)
[00216] That is, a function x(t), having time t present in an infinite interval about the geometric axis of time as a variable, and a function X(f), having a frequency f present in an infinite interval about a frequency axis as a variable, can be selected so that the following expression 1 and expression 2 apply, and these two expressions in this case are referred to as a Fourier transform pair, and X(f) is referred to as Fourier transform of x(t).

[00217] That is, the Fourier transformation pair indicates a relationship between x(t) and X(f) when the waveform x(t), which is a function of time t, is expressed as a collection of exponential functions complex exp(j2πft) of a complex amplitude X(f), which is a function of the frequency f (here, since the frequency domain is a complex region, the complex exponential function is used instead of a real sinusoidal function or of a real cosine function). The Fourier transform indicated in expression 1 is to acquire the frequency function by the time function, and the inverse Fourier transform, indicated in expression 2, is to acquire the time function by the frequency function. That is, the function having the time domain as a variable region is converted to a function having the time domain as a variable region by means of the Fourier transform.
[00218] Fourier analysis, which is an analysis method using the Fourier transform described above, is to produce frequency analysis of the function waveform as a target analysis on its entire variable region and thus is extremely effective in a analysis of a discontinuous signal, in which a location trend on the geometric time axis is not a problem, however, as illustrated in the following known document 2, if used for an analysis of a discontinuous signal having a specific characteristic, there is a a difficult problem to solve, and small wave analysis has now been proposed as a means of analyzing it.
[00219] Known Document 2: "What is Wavelet Transform" by Michio Yamada, ("Mathematical Science", December 1992, pp. 11-14, Saiensu-sha Co., Ltd.)
[00220] According to the known document 2 above, the Fourier spectrum, which is the frequency domain information obtained by the Fourier transformation, lost information regarding time and, thus, it is difficult to find a correspondence relationship between the spectrum and the local phenomenon.
[00221] For example, even if the frequency increases with time monotonically, it is impossible to determine the trend of frequency change by spectrum alone. Also, even if a spectrum clear power law appears only in the data having clear local similarity at each time, that is, in the vicinity of the respective times, if the time with different similarity is mixed in the time series, the clear power law spectrum cannot be expected, and it is substantially impossible to determine similarity characteristics by spectrum format.
[00222] Such natural disadvantages of Fourier transform are caused, since they are a function whose null-space integral exp(j2πft) is uniformly expanded.
[00223] Thus, a Fourier transform method limiting the transformation target data to a local part on the geometric time axis (Window Fourier transform) could be used, however, due to the uncertainty principle of Fourier analysis, there are a problem that accuracy cannot be improved at the same time for time and frequency. That is, the window Fourier transform corresponds to a situation where periodicity and similarity are both partially destroyed and localized.
[00224] On the other hand, in the small wave transform, the Fourier transform is localized with some periodicity interruption while the similarity is strictly maintained.
[00225] This small wave transformation does not have high frequency resolution, however, it is extremely suitable for local similarity analysis of locality data and similarity of the core function. Small wave analysis can be considered a tool that replaces periodicity in Fourier analysis by location.
[00226] Specific small wave analysis procedures will still be described according to the description of the known document 2 and, in the case of one dimension, a function Φ(t) is selected, and this is called small wave analyze or small wave mom. The description of qualitative conditions that must be satisfied by this Φ(t) is “a function that attenuates far enough and fast enough”. As a specific example of small waves to analyze, a plurality of small waves including Mexican Hat function have been proposed and currently used in analysis.
[00227] Using this small wave of analyze, a function system (collection consisting of a large number of functions) with two parameters, as in the following expression 3, is created, and this is called small wave:

[00228] The small wave is made up of mutually similar functions and when compared to the Fourier transform, A plays a role in a period (an inverse frequency number), but B is a time parameter and there is no corresponding in the Fourier transform .
[00229] Continuous small wave transformation, in the case where parameters a and b are continuous, it can be considered to have used the small wave of analyze above (Expression 3) as the null space of integral exp(j2πft) in the Fourier transformation, and the forward transform and inverse transform are present similarly to Fourier transform, which are expressed by the following expressions 4 and 5, respectively:


[00230] Here, T(a, b) is called a small wave (continuous) transformation of the target function for analysis f(t), and also called the “small wave coefficient” thereafter.
[00231] In the continuous small wave transformation, an expression similar to the Parseval relation in the Fourier analysis is applied, and the following isometric form, that is, the following expression 7, which is a relational expression of the “Equipartition law of energy ” applies:

[00232] From this expression 7, it is possible to discuss the characteristics of a time series, defining that the “energy of a frequency component 1/a in time b” is |T(a, b)|2. Also, such usage can be considered that |T(a, b)|2 (this is referred to as “power”) to be displayed on an ab plane such as a bird's eye view or a color plot, for example, and several phenomena included in the time series can be classified using patterns found here.
[00233] That is, by applying the small wave transformation to the waveform to be analyzed, the small wave coefficients corresponding to the respective points in two variable spaces, which are frequency 1/a and time b, are calculated, and using these small wave coefficients, power can be calculated as an energy index with respect to each frequency 1/a and time b.
[00234] Also, in the following known document 3, an application of small wave analysis, or particularly a discontinuous signal detection function, is described.
[00235] Known Document 3: “Wavelet Analysis ~ Birth/Development/Application” by Ryuichi Ashino, Shizuo Yamamoto, p. 23 to 25 and 131 to 133 (issued June 5, 1997, Kyoritsu Shuppan Co., Ltd.)
[00236] Considering an application of small wave analysis, the most important function is the detection of a discontinuous signal. Discontinuous signals found in natural phenomena are extremely small and, moreover, covered by noise. Small wave transformation has an ability to detect this discontinuity of signals. This is because an absolute value of the small wave coefficient at a discontinuous point on the geometric time axis is larger than the other points, and the discontinuous point can be detected.
[00237] As described above, small wave analysis is considered to work effectively in analyzes of complex discontinuous signal waveforms in which various frequency components are superimposed with a location trend, and the inventor paid attention to this point and obtained the discovery described below and the present invention. [Cases]
[00238] Comparison results using RSI and ultradian rhythm power shift waveforms and other analysis results for groups of two cases or four cases in total will be described below. The groups of two cases are as follows: Case group I (healthy group) Number of cases: 1 (first case, Figs. 12 to 16) Heart disease: no notable CSR: none Sleep quality: Favorable Case group II (sick group) Number of cases: 3 (second case, Figs. 17 to 21, third case, Figs. 22 to 26, and fourth case, Figs. 27 to 31) Heart diseases: chronic heart failure Notable CSR: Yes Quality of sleep: unfavorable
[00239] The pathosis of cases included in case group II (sick group) is as follows: Second case: NYHA Class I, BNP = 47 pg/ml Third case: NYHA Class II, BNP = 115 pg/ml Fourth case : NYHA Class III, BNP = 1000 pg/ml
[00240] Here, NYHA is the classification of the grade of a heart failure symptom determined by the New York Heart Association (NYHA), and the severity of heart failure is classified into four classes as follows: NYHA Class I: No symptoms and none limitation in usual daily life. NYHA Class II: Mild to medium limitation in daily life. No symptoms at rest, but fatigue/palpitation/shortness of breath and/or angina occur in usual behaviors. NYHA Class III: Marked limitation in daily life. No symptoms at rest, but the symptom occurs even during less than ordinary activity, such as walking on flat ground. NYHA Class IV: Some symptoms even in extremely mild activity. Heart failure/angina symptoms could occur even at rest.
[00241] Also, the BNP (brain natriuretic peptide) test is a test to measure an amount of hormone secreted from the heart (mainly from the ventricles) into the blood if a load is applied to the heart, and the higher this BNP value is, greater load is considered to be applied to the heart. Clinically, this test is useful for diagnosis/prognosis of cardiac infarction or heart failure, and the test can only measure heart disease by blood test.
[00242] The determination of heart disease pathosis using the BNP test value is as follows: 18.4 pg/ml or less: Within a standard range. 18.5 ph/ml or more: Exceeding the standard range. The value rises with the deterioration of the pathosis.
[00243] Also, in Figs. 12 to 31, to explain each case, the following graphs explaining the features of the present invention are illustrated in common for each case: (i) Brain wave SWA trend: a trend graph of the data obtained by calculating SWA, described above, brainwaves for 5 minutes and running them repeatedly for up to 8 hours by switching for 50 seconds. Therefore, the sampling frequency of this graph is 50 seconds each (0.02 Hz). (ii) Respiratory Cycle RSI Trend: A trend graph of the data obtained by calculating the above-described RSI of the respiratory curve for 5 minutes and running it repeatedly for up to 8 hours by switching over 50 seconds. Therefore, the sampling frequency of this graph is 50 seconds each (0.02 Hz).
[00244] A wrap obtained by filtering the waveform is added to both (i) and (ii) so that the rhythm of the waveform trend can be easily seen. (iii) Frequency distribution of brain wave SWA and respiratory cycle RSI
[00245] Frequency analysis by MEM (Maximum Entropy Method) is applied to the SWA and RSI data (0.02 Hz) for approximately 8 hours, and major vibration components included in these time series signals are extracted. Emphasis is placed on frequency domain grasp, which is normalized by the respective maximum power of the illustration. (iv) Brainwave SWA autocorrelation function
[00246] The autocorrelation function of the above SWA waveform, that is, a change of correlation coefficient by switched comparison between SWA and the illustrated waveforms. Presence of an important latent rhythm in the waveform is to be statistically demonstrated.
[00247] In order to clarify the description by omitting duplicate illustrations, (xi) and (xii) are omitted in the first case and (ix) and (x) are omitted in the second to fourth cases. (v) Respiratory cycle RS autocorrelation function
[00248] Similarly, the autocorrelation function of the RSI waveform, that is, a change of the correlation coefficient by switched comparison of the RSI waveforms, is illustrated. (vi) Mutual correlation functions of brainwave SWA and respiratory cycle RSI
[00249] A correlation coefficient change by switched comparison of SWA waveform and RSI waveforms is illustrated. This is a graph that statistically demonstrates whether or not the correlation between them is high. (vii) Brain wave SWA trend.
[00250] The waveform in (i) is made within a continuous waveform. (viii) Ultradian power shift included in brain wave SWA trend
[00251] An ultradian rhythm power change, included in the waveform (vii), is illustrated in a graph using the small wave analysis method described above. That is, an average power value at 0.0001 to 0.0003 Hz (90 minute cycle) is tracked, and a change in sleep depth is illustrated. (ix) RSI trend of the respiratory cycle.
[00252] The waveform in (ii) is made in a continuous waveform. (x) Ultradian power change included in respiratory cycle RSI trend
[00253] A brain wave ultradian rhythm power change SWA included in waveform (ix) is illustrated in a graph using the small wave analysis method described above. That is, an average power value at 0.0001 to 0.0003 Hz (90 minute cycle) is tracked, and a change in sleep depth is illustrated. (xi) Ultradian power shift included in brainwave SWA trend
[00254] Same as (viii). (xii) Ultradian power change included in respiratory cycle RSI trend
[00255] Same as (x).
[00256] From each of the graphs (i) to (xii), relating to the first to the fourth case, the following points are found:
[00257] First, from (i) and (ii), it is clearly observed that the time phases of the brain wave trend SWA and the respiratory cycle RSI trend equal each other. Similarly, from these data, it is understood that breathing is regularly stabilized when a certain depth of sleep is achieved, and the regularity of breathing is constant (the regularity has reached the upper limit) even if the sleep gets deeper. It is predicted that there is a SWA threshold value for RSI to become regular during sleep. This is because RSI does not react when the most direct SWA peak appears in the first case.
[00258] Subsequently, from (iii), the ultradian rhythm of 0.0001 to 0.0003 HZ (cycle approximately 90 to 100 minutes) is clearly found in both the brain wave SWA trend and the respiratory cycle RSI trend.
[00259] Also, from (iv), (v), and (vi), it was found that in the autocorrelation function, both the brain wave SWA trend and the respiratory cycle RSI trend have periodicity, and that the cycle is from approximately 90 to 100 minutes from the peak interval of the autocorrelation function waveform and equals the ultradian rhythm. The maximum correlation of both in the mutual correlation function shows a high value of approximately 0.9, which means that both are closely related to each other.
[00260] The most important point to be noted is that the periodicities of the ultradian rhythm, included in the SWA trend of the brain wave and the RSI trend of the respiratory cycle, are higher in healthy people and that when the NYHA class continues and heart disease becomes more serious, the expression of periodicity becomes small. This can be known from a difference in the size of a peak found in the autocorrelation function of the respective trend waveforms.
[00261] Also, if data from a healthy sleeping person (first case) is compared with data from a patient with heart failure (second to four cases), the respective aspects of brain wave SWA and respiratory cycle RSI are found, and the following features of interest can be understood:
[00262] Brainwave SWA increases its power according to the depth of sleep, however the RSI of the respiratory cycle is expected to have something similar to a threshold value in which the sleep regularity in depth is not less than a certain level. , becomes clear. This is because the RSI respiratory cycle suddenly becomes regular in some degree of sleep and cannot be more regular than that (regularity has an upper limit value).
[00263] Therefore, once the peak size in the respiratory cycle RSI becomes constant to some degree or more, it is likely that the maximum value cannot be easily found with small wave analysis such as in the SWA brain wave.
[00264] Particularly, in the case of deep sleep throughout the night, as in a healthy person, the small wave of the respiratory cycle RSI is considered to easily show the ultradian power as a broad trapezoid (first case).
[00265] Preferably, the respiratory cycle RSI is considered to easily peak, equating the deep sleep sometimes found in a severely ill patient with the sleep disorder (second and third cases).
[00266] From the above, the respiratory cycle RSI is considered to reflect deep sleep at a certain level or more (non-REM sleep, requiring comparison with depth).
[00267] The above consideration was made in a comparison between the brain wave SWA trend and the respiratory cycle RSI trend of each case as a main point of view.
[00268] Next, attention is paid to a change in the trend of the RSI of each case's respiratory cycle and the ultradian rhythm power included there, and a difference between the case I group (healthy group) and the case II group (sick group) will be considered.
[00269] If these two groups are compared based on the viewpoint of the illustrated RSI change and the ultradian rhythm power, the following differences between the groups are striking. Therefore, using the RSI, a change in the ultradian rhythm waveform, or both, it is possible to discriminate between the “group without chronic heart failure or marked CSR and with a favorable sleep quality” and the “group with heart failure chronic and marked CSR and an unfavorable sleep quality” by diagnosis.
[00270] Particularly evident differences are as follows: [Table 1]
[Change of index by oxygen administration]
[00271] At the end of the description using the cases, the fifth case will be described using Figs. 32 and 33.
[00272] This fifth case is affected with chronic heart failure, marked Cheyne-Stokes respiration is noted, and sleep quality is poor.
[00273] Fig. 32 illustrates a change during sleep of the RSI and the ultradian rhythm of this patient from the fifth case before the administration of an oxygen treatment.
[00274] Fig. 33 also illustrates a change during sleep of the RSI and the patient's ultradian rhythm of the fifth case after oxygen treatment is started, in which 90% oxygen is continuously administered.
[00275] Comparing Figs. 32 and 33, it is clearly understood that after oxygen administration is started, the RSI value increases and also a time domain in which the RSI value is remarkably large, that is, a time domain in which the respiratory cycle of the patient is stable and sleep is deep, it is expanded when compared to that before administration.
[00276] Furthermore, similarly comparing both Figures, it is understood that the size of the ultradian power has increased, than that before administration, and it is also understood from this point that the patient's sleep quality was improved by the administration of oxygen. [Variation No. 1 - Application in telemedicine]
[00277] In putting the present invention into practice, there may be several variations other than the above embodiment.
[00278] For example, instead of the configuration where a respiratory waveform is measured and recorded by a portable respiratory waveform measuring device and then transported to a medical institution, the present invention can be put into practice in a telemedicine system, in which the respiratory waveform is directly transmitted to an analyzer device, via a communication path or by a configuration in which not only a change of each frequency component in the respiratory waveform is displayed, but evaluation Automatic is made (however, the defined diagnosis is made by a medical staff) in a controlled manner according to the number, size, brightness or position of the peaks. [Variation #2 - Breath Rate Stability Change Display]
[00279] Next, a configuration having particular importance as a variation of the system in the present invention will be described.
[00280] The inventor has obtained the following finding in the production of sleep assessment diagnoses of a large number of cases using the respiratory waveform measurement information of individuals as above.
[00281] As described above, in sleep, 6 types of sleep stages are typically repeated with a 90-minute cycle three times a night, and a change in physiological data in each cycle can be clearly observed by SWA (Wave Activity Slow) of the brain wave as follows. It is understood that, in the case of an individual whose comfort level, including sleep quality, has decreased due to some event, such as apnea, the cycle of sleep stages in SWA is interrupted and cannot be clearly observed.
[00282] Thus, a breathing operation of an individual during sleep is focused, and paying attention to the variation in the respiratory cycle obtained by measurement or, particularly, in the stability of the respiratory cycle, it is likely that the observation of this sleep cycle and , therefore, the assessment of the comfort level, including sleep quality, can be performed.
[00283] The stability of the respiratory cycle can be indicated as follows: a range of a respiratory cycle is extracted from the respiratory waveform obtained by measurement; first, an average value (X bar) of the respiratory rate is calculated; second, a standard deviation (Sd) of the respiratory rate is calculated using a known statistical method; and an inverse number of this standard deviation (Sd) is calculated.
[00284] Similar to the embodiment described above, the inverse number of the standard deviation of the measured respiratory waveform is called RSI (Respiratory Stability Index) here. By plotting this RSI so that a temporal change in sleep for one night is known, medical personnel should be able to easily determine through observation whether the sleep cycle is clearly displayed and whether the comfort level, including the sleep quality is good, or if the sleep cycle cannot be clearly observed and the comfort level, including sleep quality, is poor.
[00285] Thus, in the variation system of the present invention, the configuration in which the respiratory waveform introduced a frequency range from 0.1 to 0.5 Hz, including 0.4 Hz, which is a typical respiratory cycle of a human body, is extracted from a plurality of Fourier spectra in time which becomes a starting point of each Fourier window period obtained by performing fast Fourier transformation (FFT) switching the time for 5 seconds in the window period 5-minute Fourier is the same as the configuration described above.
[00286] In addition, in the variation system of the present invention, the analysis part 3-3 calculates the mean value (X bar) and the standard deviation (Sd) of the frequency included in the respiratory rate range for each Fourier window obtained with the switching interval of 50 seconds, creates a graph indicating a temporal change of the RSI, in which the RSI, which is an inverse number of this Sd, is calculated for each Fourier window period, having this switching interval of 50 seconds, and plotted on the geometry axis orthogonal to the time axis, and displays, prints or outputs this to the outside as the calculation result information.
[00287] By looking at this RSI chart, the clarity of the sleep cycle and therefore the comfort level, including sleep quality, can be easily observed and diagnosed. [Variation No. 3 - Device that automatically assesses comfort level, including sleep quality]
[00288] The variation described above is a method in which the RSI index indicating the regularity of the respiratory cycle is calculated from an inverse number of the standard deviation of the respiratory rate and the like, and a temporal change of this RSI is displayed, so that a medical staff observe and diagnose it.
[00289] However, once an RSI trend graph, in the case where the comfort level, including sleep quality, is good and the sleep cycle is clearly displayed, is known, it is possible to automatically determine the level of comfort, including sleep quality, from the obtained SRI trend graph.
[00290] Specifically, they include the size of a peak of the RSI graph, an area held by the graph with the geometric axis of time, that is, an integral value of time of the RSI graph, predicted the rise time of the trend graph, that is, the departure time deviation from a period of respiratory stability, a degree of figural displacement from a geometric numerical value of the RSI graph, in the case where the comfort level, including the individual's ideal sleep quality, or an individual in general is good, and similar. Others can also be used.
[00291] Of these approaches, using the configuration of the sleep assessment system 1 of the present invention, an automatic assessment configuration of the comfort level, including sleep quality, can be easily obtained, and the detailed description of the specific configuration will be omitted.
[00292] Next, as another variation of the present invention, an example where sleep assessment technology, based on the respiratory waveform analysis described above, is specifically applied to a treatment device used for a treatment of a patient, will be described. [Variation No. 4 - Embodiment of the invention regarding the positive airway pressure respiratory assist device]
[00293] First, an embodiment wherein the present invention is applied to a positive airway pressure respiratory assist device, which is a treatment device for sleep apnea syndrome (hereinafter SAS), caused by obstruction airway, (hereinafter also referred to as a “CPAP device” or a “respiratory assistance device” will be described.
[00294] In the example referring to the CPAP device, which will be described below, the control of supply pressure out of a gas to be supplied to a patient is performed by a control unit provided inside the device.
[00295] A configuration in which a device that supplies a gas to a patient and a device that controls the supply pressure are not integrally formed, but provided separately, has already been introduced on the market. Thus, other than the configuration in which a function unit that supplies a gas, and a function unit that performs supply pressure control, are integrally provided within the CPAP device, as will be described below, the supply control can be performed by a separate device, and the configuration will be described below, including also such variation within range.
[00296] The CPAP device is a positive airway pressure respiratory assist device, in which the atmospheric air pressure is reinforced by approximately 30 cmH2O and supplied to a nasal cavity unit, using a nasal mask as a means respiratory aid.
[00297] In detail, this is a medical instrument provided as a method of treatment means for sleep apnea syndrome, in which reinforced air is fed into the airway through the nasal cavity unit, the interior of the airways. airway is maintained at a positive pressure and the airways are made to flow through the airways in order to prevent a drop in blood oxygen concentration due to respiratory arrest caused by obstruction of the airway unit. The specific configuration of the CPAP device is described in Japanese Patent Laid-Open No. 7-275362, for example.
[00298] Sleep apnea syndrome (SAS) is a collective name for a disease in which apnea is intermittently repeated during sleep and, as a result, various symptoms such as daytime sleepiness are presented.
[00299] Apnea is defined as airway arrest for 10 seconds or more, and in relation to SAS, in the case of apnea of 30 times or more during sleep for 7 hours a night, if an apnea index AI ( number of apnea times per 1 hour of sleep) is AI >5 (time/hour) or, in actual clinical use, the apnea hypoapnea index (AHI), where hypopnea is added to apnea, is used.
[00300] Apnea hypoapnea index: the number of times of apnea and hypopnea added together per hour of sleep.
[00301] Hypopnoea: A state in which the airway is not completely closed but becomes narrow and the amount of ventilation becomes small. Ventilation drop of 50% or more, accompanied by a drop in oxygen saturation (SpO2) of 3% or more.
[00302] SAS is classified by the causes of the type of obstruction (also referred to as occlusive) (Obstructive Sleep Apnea = OSA, the upper airways are obstructed during sleep and the airways are interrupted, and the breathing movements of a wall of the body chest and an abdominal wall are found even during apnea, but a paradoxical movement in which movements are opposite to each other is shown), type of center (also referred to as central) (Central Sleep Apnea = CSA, due to functional anomaly of the respiratory center, stimulus for a respiratory muscle is lost during sleep, mainly in the REM period and becomes apnea), and a mixed type of OSA and CSA (starts with central apnea and moves to obstructive apnea in the second half in many often classified as an obstructive apnea).
[00303] Patients to be treated by the CPAP device among them are OSA patients.
[00304] OSA develops, as apnea or hypopnea occurs due to occlusion of the upper airways.
[00305] The causes of occlusion are (A) morphological anomaly (fat deposition on the airways due to obesity, swollen tonsils, macroglossia, nasal septum deviation, adenoid, micrognathia (maxilla is small) and the like, and (B) functional anomaly (the strength to hold the muscles making up the airway is diminished).
[00306] Deep sleep (non-REM sleep) is seen at the beginning of the healthy person's sleep pattern, but in OSA patients, the oxygen in the blood decreases due to apnea, the intrapleural pressure becomes negative, an awakening reaction occurs repeatedly during sleep, and deep sleep cannot be obtained and thus symptoms such as daytime drowsiness are presented.
[00307] For such OSA patients, the CPAP device supplies air with a certain positive pressure through a nasal mask and expands the upper airway and, as a result, performs an apnea avoidance operation by resolving the airway obstruction. The pressure to expand the airway (also referred to below as a “positive pressure”) differs depending on patients.
[00308] For respiratory attenuation, such as CSA characteristically found in specific diseases such as heart failure, other than CPAP that maintains a certain level of pressure (positive pressure) of compressed air applied to the patient's airway, auxiliary artificial respiratory devices, such as a device that has two different pressures, respectively, for the patient's expiratory period and inspiratory period (referred to as Bilevel-PAP), and such a device that monitors the patient's respiratory status (presence, airflow level , interval, and the like) for all this time and apply optimal pressure, although changing it all the time (referred to as automatically controlled auxiliary ventilation of the servo type) could be used, and the optimal pressure is different depending on the patients or symptoms.
[00309] Whatever the method, the positive pressure level is determined as a prescription based on the doctor's findings. Such a configuration that the comfort level, including sleep quality, of the target patient for treatment is directly assessed and the optimal positive pressure level is determined in order to maintain the favorable comfort level, including sleep quality, has no been known.
[00310] In order to solve these prior art problems, a CPAP device 21a of this embodiment has, as illustrated in Fig. 34, the following configuration.
[00311] First, a 21b CPAP device main body is a configured device capable of variable control of the positive pressure level and has a 21b-1 compressor that generates compressed air and feeds it out, to the outside of the device, and a CPAP 21b-2 control unit, which performs the control operation of the main body of the CPAP 21b device, including the pressure change control (positive pressure level) of the compressed air fed out by the compressor 21b-1.
[00312] Compressed air (positive pressure air), fed out of the main body of the CPAP device 21b, is supplied through a mask 21f, via a duct 21e, into the patient's airway.
[00313] For the configuration of the main body of the CPAP 21b device, the prior art configuration already described can be used, except the characteristic configuration described below.
[00314] A 21d breath sensor is similar in configuration to the breath sensor of the sleep assessment system 1.
[00315] A sleep state analysis unit 21c is provided separately from or integrally with the main body of the CPAP device 21b and has a respiratory waveform detection amplification unit 21c-1, which receives and amplifies the output of the 21d respiratory sensor, and an AD 21c-2 conversion unit, which digitizes the analog output, a 21c-3 memory unit, which accumulates information from the digitized waveforms in order to make them accessible, and an analysis unit of the sleep state 21c-4, which will be described below.
[00316] The sleep state analysis unit 21c-4 can obtain the digitized signal of the detected waveform inputted into the respiratory sensor 21d as above, sequentially perform Fourier transform in the Fourier window period, and create a time shift of a signal extracted from a respiratory rate range and the RSI obtained on a real-time basis.
[00317] The principle of operation of the CAP device 21a of this embodiment is as follows.
[00318] In sleep, 6 types of sleep stages are typically repeated with a 90-minute cycle three times a night, and a change in physiological data in each cycle can be clearly observed by the SWA (Slow Wave Activity) of the wave brain, as follows. It is understood that, in the case of an individual whose comfort level, including sleep quality, has decreased due to some event, such as apnea during sleep, the cycle of sleep stages in SWA is interrupted and cannot be clearly observed.
[00319] Thus, a breathing operation of an individual during sleep is focused, and paying attention to the variation in the respiratory cycle obtained by measurement or, particularly, in the stability of the respiratory cycle, it is likely that the observation of this sleep cycle and , therefore, the assessment of the comfort level, including sleep quality, can be performed.
[00320] The stability of the respiratory cycle can be indicated as follows: a range of a respiratory cycle is extracted from the respiratory waveform obtained by measurement; first, an average value (X bar) of the respiratory rate is calculated; second, a standard deviation (Sd) of the respiratory rate is calculated using a known statistical method; and an inverse number of this standard deviation (Sd) is calculated.
Similar to the embodiment described above, the inverse number of the standard deviation of the measured respiratory waveform is called RSI (Respiratory Stability Index) here. By plotting this RSI so that a temporal change in sleep for one night is known, medical personnel should be able to easily determine by observation whether the sleep cycle is clearly displayed and whether the comfort level, including the sleep quality is good, or if the sleep cycle cannot be clearly observed and the comfort level, including sleep quality, is poor, and at the same time control the positive pressure air pressure using the configuration of the above-described automatic assessment device of the comfort level including sleep quality, so that the temporal change obtained from the individual's RSI is closer to the temporal change of good quality sleep, positive pressure air is supplied to the patient in the optimal CPAP treatment condition, according to individual patients or according to the patient's state of the day, and the optimal sleep state can be obtained.
[00322] This positive pressure level control is effective if feedback control is performed. Concerning the 21c-4 sleep state analysis unit and the 21b-2 CPAP control unit, the analysis and a change of the positive pressure level can be performed at a single or several time points during sleep, or the control can be continued so that the optimal positive pressure level is obtained based on real time, monitoring the time by changing the RSI waveform all the time.
[00323] Also, this positive pressure level control can be performed in a method where the control is performed only as a test to determine the patient's positive pressure level in that case only, or in a method where the control is run at all times if the OSA patient is treated using this CPAP 21a device.
[00324] As a target patient for whom treatment is given using the CPAP 21a device, a patient with sleep apnea syndrome was described above similarly to the case where the CPAP device, having the prior art configuration, was employed .
[00325] On the other hand, the CPAP device 21a, with the features of the configuration, according to the embodiment of the present invention, can expand the target for a patient with chronic heart disease or particularly for a patient with heart failure , in addition to the above patient with sleep apnea syndrome.
[00326] That is, treatment using Bilevel-PAP assisting a respiratory pump function for a patient with chronic heart disease, or particularly for a patient with heart failure, is known to improve hemodynamics.
[00327] However, patients with chronic heart disease have excessively high parasympathetic nerve activity, due to heart failure or the like, that is, in an excited state, and many of them have sleep onset disorder and, in such a situation, the Bi-PAP treatment requiring the attachment of a mask could further deteriorate the comfort level, including the sleeper's sleep quality, and its long-term use tends to be avoided.
[00328] In order to resolve this situation using the CPAP device 21a of this embodiment, a respiratory waveform analysis result can be fed back, and the pressure level and pressure waveform are adjusted so that night use becomes possible, thereby performing long-term treatment.
[00329] Then, in a positive airway pressure respiratory assist device of this embodiment, except the CPAP device, whose pressure applied to a patient is constant or the Bilevel-PAP having only two phases of pressure change, if configured based on an auxiliary automatic control ventilator (Adaptive Servo Ventilator: ASV) that performs automatic control, so that both or one of a patient's lung ventilation and respiratory rate are closer to a predetermined amount determined in advance by applying it. if an optimal pressure for the moment, while changing it and monitoring the patient's breathing state (presence, airflow level, interval and the like) all the time, the advantage of the present invention is further improved, which will be Described below.
[00330] In normal breathing (8 to 15 times per minute), the heart rate increases on inspiration and decreases on expiration. Since this respiratory cavity arrhythmia (change in heartbeat caused by respiration) completely disappears if the cardiac vagus nerve is blocked by atropine, it is understood that cardiac vagal activities are mainly involved.
[00331] One of the causes why vagal activities are impaired in synchronization with the inspiration phase is the central mechanism whereby cardiac vagal activities are suppressed by interference from the respiratory center (Hamlin RL, Smith CR, Smetzer DL. Sinus arrhythmia in the dogs. Am J Physiol 1966; 210:321-328. Shykoff BE, Naqvi SJ, Menon AS, Slutsky AS. Respiratory sinus arrhythmia in dogs. J Clim Invest 1991; 87: 1612-1627.)
This is based on the fact that increased heart rate in synchronization with diaphragmatic nerve activities on inspiration is found even if there is no movement of the lungs or chest cage.
[00333] On the other hand, as a peripheral mode causing respiratory heart rate fluctuation, cage effects are known in which vagal nerve activities are blocked in synchronization with inspiration due to the afferent introduction of stretch receptors in the lungs. In fact, in a lung implant patient, in which the vagal efferent is maintained but the vagal afferent of the lungs is blocked, cardiac respiratory fluctuation is known to clearly weaken (Tara BH, Simon PM, Dempsey JA, Skatrud JB, Iber C. Respiratory sinus arrhythmia in humans: an obligatory role for vagal feedback from the lungs. J Appl Physiol 1995; 78; 638-645.).
[00334] Therefore, as described above, in the CPAP device that performs control using respiratory pressure as an index, if a cycle or amount of ventilation of a respiratory operation of a patient under treatment is not constant, but fluctuates in a process of sleep, it could affect a change in respiratory rate.
[00335] However, in the servo-type automatic control auxiliary ventilator, as described above, since the control is performed so that both or one of the patient's lung ventilation and respiratory rate is closer to a predetermined value in advance by applying an optimal pressure at the time, while changing and monitoring the breathing status of the patient being treated (presence, airflow level, interval and the like) at all times, if this servo-type automatic control auxiliary ventilator is used, the control using the ventilator becomes possible, so that the fluctuation in the operating cycle, or the pulmonary ventilation in the breathing operation of the patient in sleep, becomes relatively smaller.
[00336] Therefore, if the positive airway pressure respiratory assist device of this embodiment, having the characteristics described above, is configured based on the servo-type automatic control auxiliary ventilator, the control can be performed using whether an index indicating regularity of the patient's respiratory cycle or temporal change in the RSI, for example, so that the comfort level, including sleep quality, can be improved. Since the control circuit is formed only via the patient's respiratory rate, control is direct and response to control is improved. As a result, a sleep assessment result with higher accuracy is obtained and control using the result can be realized, thus the specific advantages for this embodiment, i.e. provision of better quality sleep for a patient in treatment can be further improved when compared to other types of CPAP devices (types other than the servo-type automatic control auxiliary ventilator).
[00337] The servo-type automatic control auxiliary fan described above was introduced to the market by Teijin Pharma Limited under the product name “AutoSet (Trade Mark) CS” in 2007,
[00338] The "AutoSet (Trade Mark) CS", described above, has the technical characteristics of its configuration covered by patents, patent applications or similar in countries cited below using abbreviations:
AU 691200, AU 697652, AU 702820, AU 709279, AU 724589, AU730844, AU731800, AU 736723, AU 734771, AU 750095, AU 750761, AU 756622, AU 761189, EP 2002306200, CA 2263126, 1318307, JP 3635097, JP 3737698, NZ 527088, US 4944310, US 5199424, US 5245995, US 5522382, US 5704345, US 6029665, US 6138675, US 6152129, US 6240921, US 6279569, US 6363933, US 6367439, US 6398739 US 6425395, US 6502572, US 6532959, US 6591834, US 6659101, US 6945248, US 6951217, US 7004908, US 7040317, US 7077132. [Embodiment of the invention relating to a testing device used for titration of respiratory assistance device]
[00340] Next, an embodiment of the invention relating to a testing device, which is an embodiment of the present invention described above and is effective in use for titration of respiratory assist device, including CPAP, will be described.
[00341] Respiratory assist device titration is a work performed by medical personnel to determine an appropriate pressure (treatment pressure) of the respiratory assist device, such as CPAP, and the detailed description will be given in the information “Kobe Kyodo Hospital - Sleep Apnea Syndrome”, accessible on the World Wide Web http://homepage3.nifty.com/SAS-kyo/titration.pdf#search=”tritation”.
[00342] There is a method (manual titration: manual pressure adjustment) in which a respiratory assist device operating pressure is started from the minimum pressure, while the sleep polygraphy (PSG) test is being conducted throughout the At night, the operating pressure is adjusted while the breathing state is observed and the pressure is manually changed in order to be increased/decreased so that apnea, hypopnea and snoring are resolved in each state of apnea or hypoxia in turn being observed , and the minimum pressure at which the patient's sleep state becomes favorable and the breathing disorder is ultimately resolved is the optimal pressure (treatment pressure). This method is a job requiring remarkable all-night observation work, and there is also a self-titrating method, in which human work is saved using an Auto-CPAP device, that is, a device that automatically changes and records the pressure.
[00343] Also, except for the methods of performing the titration work for an individual in sleep as a target, as above, there is a method in which medical equipment, such as a respiratory assist device admitted to be used, is attached to a the individual on awakening and the suitability of the medical device for the individual or the adjustment conditions are determined through experimental use for a short period of time.
[00344] In the following description, not only the titration work for the sleeping individual, but also the titration work for the waking individual, as above, are collectively referred to as "titration" and described.
[00345] The present invention realizes improvement in the accuracy and working efficiency of the titration work more favorably adapted to the physiology of human bodies and, specifically, the operating pressure of the respiratory assist device supplied to an individual in sleep or awakening is manual or automatically changed, and a time change of the operating pressure is recorded, and also the subject's respiratory waveform is continuously recorded, and a time change of the RSI waveform, described above, is created and recorded.
[00346] The operating pressure and the temporal change of the RSI can be observed by medical personnel who perform the titration based on a real time, so that they can be used for diagnosis, or the waveforms can be recorded, or the waveform can later be created based on the recorded data so that it is displayed on a monitor device, printed by a printing device, or transmitted abroad.
[00347] Medical personnel compare the operating pressure change waveform to and the RSI waveform, which can be simultaneously observed, and changing the operating pressure every 5 minutes, for example, if the RSI waveform RSI change according to which one has the maximum value, medical personnel can determine the operating pressure at that time as the appropriate treatment pressure. This is because the behavior of a human body's respiratory operating cycle is directly governed by the center of the brain and there are few disturbing elements, and the effect of applying pressure from the respiratory assist device can be observed more directly when compared to the observation of other physiological information or heart rate, for example, and thus the accuracy of the titration can be further improved.
[00348] In addition, medical personnel can determine the appropriate device for treating at least any one of (1) a compressed air pressure value; (2) compressed air pressure value change pattern; and (3) selecting a device from a plurality of respiratory assist devices, i.e., a CPAP device, a Bi-level PAP device, an ASV (Servo-Type Automatic Control Auxiliary Ventilator) and the like described above.
[00349] Also, once the behavior of the respiratory cycle is observed, appropriate titration can also be done through observation during awakening, not only in sleep, and the titration can be completed in a short time during treatment of the patient. ambulatory, without requiring hospitalization or home-visit treatment in the patient's home, and thus a burden on the patient can be reduced and the medical economic effects can be improved.
[00350] The titration according to the present invention is effective not only for CPAP, but also for various respiratory assist devices that feed out pressurized air or other respiratory gases in the patient's spontaneous breathing, but the titration described above using With prior art technologies, it is only effective for measuring for titration, and if a change in symptom occurs, the patient must be hospitalized again, and the titration must be performed again.
[00351] Otherwise, by performing the titration, according to the embodiment of the present invention, as described above, the sleep quality or the comfort level can be directly assessed and, thus, the titration can be arbitrarily performed by the switching operation initiated by the patient himself at the desired time, such as changing the symptom not only in the hospital but also at home, for example, so that an optimal condition, according to the symptom, can be found and automatically determined. [Embodiment of the invention regarding the sleep induction device]
[00352] Next, an example in which the present invention is adapted for a sleep-inducing device for the purpose of achieving favorable sleep by inducing an insomniac or a healthy person to a sleep state, will be described as another way of carrying out the present invention.
[00353] In this type of sleep-inducing device, as described in Japanese Patent No. 386826, for example, sound is emitted from a speaker to a patient who is going to sleep and, analyzing the content of a patient's operation who operated a joy stick in response to the sound, the sound emitted is selected and controlled so that the patient can go to sleep as soon as possible.
[00354] Also, Japanese Patent Laid-Open No. 2003199831 describes a device that emits ultrasonic waves from a speaker embedded in a pillow, and sequentially changing the mode of the ultrasonic waves over time, the target is first felt. if relaxed and then gradually induced to sleep.
[00355] However, according to these prior art technological configurations, although some physical stimulation, such as sound or ultrasonic waves, is provided to the target, the physical stimulation is determined in advance as a program, or selected by evaluating the progress of the sleep from an operation of the target that has not yet fallen asleep, and an optimal physical simulation mode is not selected using feedback control while the comfort level, including the target's sleep state or sleep quality, is directly assessed .
In contrast, a sleep inducing device 22a of this embodiment has the following configuration exemplified in Fig. 35.
[00357] First, a physical stimulation device 22b is configured to provide some physical stimulus such as light, sound, ultrasonic waves, heat, wind, images, odor, contact stimulation, electrical stimulation, magnetic stimulation or the like from a unit 22b-1 output for a target going to sleep, and the physical stimulation mode can be changed by a function of a 22b-2 physical stimulation control unit. For example, if the physical stimulation is light, the intensity, wavelength (color), flicker presence or interval, area, shape or position of a light-emitting body or, in addition, even the presence of light emission may be changed.
[00358] If the physical stimulation is sound, its intensity, wavelength (musical intensity), sound emitting pattern or interval, sound emitting direction or position or, in addition, even the presence of sound emission can be changed .
[00359] A 22d breath sensor has a similar configuration to the sleep assessment system breath sensor described above 1.
[00360] A sleep state analysis unit 22c is provided separately from or integrally with the physical pacing device 22b, and has a respiratory waveform detection amplification unit 22c-1, which receives and amplifies the output of the respiratory sensor 22d, an AD conversion unit 22c-2, which digitizes the analog output, a memory part 22c-3, which accumulates digitized waveform information in order to be made accessible, and a state analysis unit of sleep 22c-4, which will be described below.
[00361] The sleep state analysis unit 22c-4 can obtain a digitized signal of a detected waveform inputted by the respiratory sensor 22d as described above, sequentially perform Fourier transform in the Fourier window period and create an extraction signal of the respiratory rate range, and a temporal change of the RSI, described above, for example, obtained from that based on a real time.
[00362] Therefore, the analysis part is configured to control the operating conditions of the sleep inducing device 22a, monitoring the temporal change of the RSI and the like, so that the comfort level, including sleep quality, is even improved. [Form of realization of the invention regarding the massaging device]
[00363] Next, an example where the present invention is adapted for a massaging device, which automatically performs a massaging operation with a mechanical fixation unit to the target, will be described as another embodiment of the present invention.
[00364] Like these types of massaging devices, Japanese Patent Laid-open No. 2007-89716 describes a massaging device of a kind of parallel connecting mechanism, in which the movement of a treatment element is stably controlled with good reproducibility in vertical direction, right and left range directions, and forward/retreat direction, independently with respect to a human body, so that a desired massaging movement can be made by the treatment element.
[00365] Also, Japanese Patent Laid-Open No. 2003310679 describes a foot massager comprising a foot press bag having an in-line unit for a calf that is formed substantially in the shape of a boot to be brought into close contact. with the calf, heel, and toe at the same time and having an open/closeable joint unit in order to be opened when a leg is inserted by the finger; an air fill bag body attached to the substantially entire surface of a skin material of the foot press bag 2; an air pump that supplies and discharges air to and from the air fill bag body; and a connecting tube, which connects an air supply/discharge hole provided in the bag body and air filler, and the air pump.
[00366] However, according to these prior art technological settings, the massage pattern is determined in advance as a program or is selected based on the subjective comfort or discomfort of the massage target, and an optimal massage pattern is not selected using feedback control is used, although the physiological state of the target is directly assessed.
[00367] In contrast, a massager 23a, which is of this embodiment, has the following configuration as exemplified in Fig. 36.
[00368] First, a main body massager 23b has a massage stimulation unit 23b-1 and a standard massage control unit 23b-2.
[00369] The massage stimulation unit 23b-1 has a configuration to perform the massage operation using accessories such as a roller, a hand, an air cuff and the like for the massage target and specifically the similar accessories those of known massaging devices can be used.
[00370] Massage pattern control unit 23b-2 changes and controls the massage mode performed by massage stimulation unit 23b-1 and controls all operations, including the presence of a massage operation, resistance and patterns of the massage and the like.
[00371] The breathing sensor 23b has the configuration that has already been described.
The sleep state analysis unit 23c is provided separately from or integrally with the physical stimulation device 23b and has a waveform detection amplification unit 23c-1, which receives and amplifies an output from an oximeter a pulse waveform 23d, an AD conversion unit 23c-2, which digitizes the analog output, a memory unit 23-c, which accumulates digitized waveform information in order to be made accessible, and a state analysis unit. sleep 23c-4, which will be described below.
[00373] The sleep state analysis unit 23c-4 can obtain a digitized signal of the detected waveform inputted by the respiratory sensor 23d as described above, sequentially perform Fourier transform in the Fourier window period and create an extraction signal from the respiratory rate range, and a temporal change of the RSI, described above, for example, obtained from that based on real time.
[00374] Therefore, the analysis part is configured to control the operating conditions of the massager 23a, monitoring the change of RSI and the like, so that the comfort level, including sleep quality, is further improved.
[00375] [Embodiment of the invention regarding the blood pressure measurement system]
[00376] Next, an example in which the present invention is adapted to a blood pressure measurement system, to measure a blood pressure of an individual with favorable reliability and reproducibility and in a simplified way, will be described as another embodiment of the present invention.
[00377] According to a guideline regarding the diagnosis and treatment of circulatory diseases by Kazuyuki Shimada, et al., 1998-1999 joint research report "Guideline relating to the use of a standard of 24-hour blood pressure meter (ABPM)" ( Japanese Circulation Journal Vol. 64, Suppl. V, 2000. Hereinafter referred to as “guideline”), a blood pressure value of a human body fluctuates under various conditions, such as during activity, at rest, in sleep and the like, and it is known that these blood pressures are not necessarily correlated with casual blood pressure in an examination room.
[00378] As also stated in the above Guideline, a 24-hour blood pressure measurement method (ambulatory blood pressure monitoring: ABPM method) is used for measuring a blood pressure value of a hypertensive patient. 1) If blood pressure in an examination room or at home substantially fluctuates; 2) White layer hypertension (blood pressure is normal in daily life, but hypertension is presented in a medical setting with good reproducibility and repeatedly) is suspected. 3) Drug refraction hypertension 4) Indication of hypotension during administration of antihypertensive drugs; and 5) Hypertension is indicated early in the morning.
[00379] The ABPM method is roughly a method of conducting blood pressure measurement over a period, including sleep, typically at 15 to 30 minute intervals, by attaching a blood pressure meter to an individual.
[00380] Assessment of nocturnal blood pressure is possible only by this ABPM method.
[00381] Reliability and accuracy of the blood pressure value measured at night is described in the Guideline as follows:
[00382] “Night sleep blood pressure can be measured only by the ABPM method. The term “night” includes a physiological state of sleep. However, nighttime blood pressure does not necessarily equal sleep blood pressure. Also, blood pressure is different depending on the sleep phase based on brain waves, so blood pressure is lowest in the slow wave sleep phase (deep sleep) and the greatest blood pressure fluctuation is found in the REM sleep. Therefore, even at night, if an awakening time domain is long, nighttime blood pressure is considerably higher than genuine sleep pressure.
[00383] In particular, the elderly person often wakes up to urinate at night, and this should be considered in the assessment. Also, since the ABPM method is conducted using upper arm cuff pressurization, those who first receive the ABPM method could be awakened or have shallow sleep and have increased blood pressure due to pressurization, and particularly patients with sleep disturbance are reported to be awake during cuff pressurization and to have increased blood pressure (14/4 mmHg).
[00384] Since nighttime blood pressure fluctuates with sleep depth, its reproducibility is not necessarily satisfactory. Thus, a method is proposed in which circadian blood pressure is divided into two square wave phases of daily blood pressure (high BP) and nighttime blood pressure (low BP), and nighttime blood pressure (BP min) is estimated reproducibly favored by a method of calculating square waves of optimal two phases (square wave fit) and a method of cumulative addition (cumulative sums). Tochikubo et al. proposes the nighttime stochastic “baseline blood pressure value” derived from the correlation equation between heart rate and blood pressure and minimum heart rate”.
[00385] That is, in the case of a sleeping individual's blood pressure (at night), the depth of sleep affects the measured value.
[00386] Thus, for the purpose of measuring the individual's blood pressure value with favorable reproducibility, in order to measure the individual's blood pressure value in a deep sleep state in the non-REM period, the slow wave sleep period (non-REM sleep) of the individual is diagnosed and specified by changing the above-described brainwave SWA waveforms using a large-scale testing device, such as a polysomnography test (PSG test) performed during hospitalization, as described above, for example, and the blood pressure measured value during the slow wave sleep period can be employed, or the blood pressure measuring device can be controlled in order to perform the blood pressure measuring operation under knowledge that the individual is in the current slow-wave sleep period. By setting as above, the blood pressure value can be stably measured after medically confirming that the subject is in the slow wave sleep state based on the subject's physiological data.
[00387] However, the PSG test requires hospitalization, as described above, and not a test performed by the individual sleeping at home without an overload.
[00388] Also, several methods are proposed in which the basal blood pressure value at night is estimated from statistical methods, however the individual's blood pressure value in the basal state cannot be directly measured in the first place.
[00389] With the blood pressure measurement system 24a, according to this embodiment of the present invention, paying attention to the index indicating the stability of the respiratory cycle or RSI described above, for example, the blood pressure value of the Individuals in the non-REM period can be directly measured by a simplified method that can be conducted at home without requiring hospitalization.
Referring to Fig. 37, the configuration of the blood pressure measuring system 24a of this embodiment will be described. This system 24a is provided with a respiratory waveform recording meter 24b, which may be configured to be portable, a blood pressure value recording meter 24c, which may also be configured to be portable, and an analysis device. 24d, which is performed by a personal computer or similar.
[00391] The respiratory waveform recording meter 24b is preferably a device that can record the respiratory wave and may also be configured to be portable, and is typically lent by a medical institution for an individual, so that the individual can continuously record and maintain the sleep waveforms recorded for one night at home, and the recorded waveforms are transported to the medical institution thereafter.
[00392] It goes without saying that the recording of respiratory waveforms can be done in the medical institution or the data of the recorded waveforms can be carried in a flash memory or the like and transported or supplied via a communication path to a device for perform analysis, i.e., the 24d analysis device.
[00393] In order to perform the above-described functions, the respiratory waveform recording meter 24d has a respiratory air flow sensor 24b-1 attached to the skin surface in the vicinity of the subject's nasal cavity, an amplification unit a respiratory waveform detection unit 24b-2, an A/D conversion unit 24b-3, a memory unit 24b-4, which records and maintains the respiratory waveform as a digital signal, and an output terminal 24b -5, which outputs the digital respiratory waveform data from memory unit 24b-4 to the outside.
[00394] The 24b-1 respiratory air flow sensor can be a thermal sensor that is fixed to the vicinity of the individual's nasal cavity and measures the presence or intensity of the air flow per breathing of this individual, measuring and detecting after discriminating the breathing air flow temperature and the other outside air temperature, or it may be a method of changing resistance caused by deformation of a strip-shaped member of the breathing air flow, a method using rotation of a windmill structure of air flow or any other types, as long as the presence and intensity of the respiratory air flow can be detected, for example.
[00395] Particularly, the use of a pressure-measuring breath sensor provided with a piezoelectric PVDF (polyvinylidene fluoride) film is a preferable mode than a breath-detecting pressure sensor.
[00396] In addition, the respiratory operation (ventilation movement) of the individual can be measured and recorded by not directly measuring the respiratory air flow, but by measuring the tension caused by the extension of a band wrapped around the chest or stomach of the subject by breathing movement, or by providing a pressure measurement sensor on a treadmill below the subject.
[00397] These various respiratory sensors are attached to a predetermined part of a patient in order to detect the patient's respiratory airflow or respiratory efforts (ventilation movement) of the patient, and the medical institution shall provide guidance on the method of fixation for the patient before the test. However, when compared to fixing an electrode for electrocardiogram measurement in a specific position on the patient's chest epidermis, the approval of position, direction and the like for fixing the respiratory sensor is higher than in the case of a sensor for electrocardiogram, and it is easy for a patient or the patient's family to attach the sensor according to the guidance of the medical institution and obtain a correct measured value.
[00398] Furthermore, in recent years, instead of detecting a respiratory operation by attaching some means of measurement to an individual as above, many types of non-contact respiratory sensors have been proposed, which emit electromagnetic waves to the individual from from a distant position and detect the subject's body movement or breathing operation by analyzing reflection waves.
[00399] As described above, it goes without saying that as a respiratory sensor, a sensor to detect a respiratory operation based on the result of analyzing the individual's reflection waves of radiated electromagnetic waves, such as those described in the document "Microwave respiratory sensor for evaluation”, which is posted on the World Wide Web and can be accessed (http://www3.ocn.ne.jp/mwlhp/kokyu.PDF), Japanese Unreviewed Patent Application Publication No. 2002-71825, which is also a document known and described as "human body detecting device using microwave", Japanese Patent Application Unanalyzed Publication No. 2005-237569, which is also a known document, and Japanese Patent Application Unanalyzed Publication No. 2005 -270570, which is a document known and described as “biological information monitoring device”.
[00400] Also, the blood pressure value recording meter 24c of this system 24a is a device that measures the blood pressure of an individual and can be configured based on the measurement principle similar to that of the known automatic blood pressure meter, including the device used in the 24-hour blood pressure measurement method described above (ABPM).
[00401] The specific measurement principle is that the following method of measuring indirect stethoscopic blood pressure is automated.
[00402] That is, a cuff is attached to the individual's arm or the like, the cuff pressure is applied at approximately an average value of the blood pressure predicted by the individual's condition or approximately 100 mmHg (millimeter of mercury), for example, and it is confirmed that Korotkoff noises can be heard. If Korotkoff noises are heard, the cuff pressure is increased until they are not heard and then the cuff pressure is slowly decreased while the display is observed. The first pulse sound to be heard is the first phase of Korotkoff noises, and by reading the scale of this time point, the maximum blood pressure is obtained. Then the sound, which suddenly changes to be heard clearly, indicates the second phase. The tone changes again, which indicates the third phase. The time point when Korotkoff noises are no longer heard indicates the lowest blood pressure.
[00403] In order to conduct measurement based on this principle, the blood pressure value recording meter 24c is provided with a cuff 24c-1. The 24c-1 cuff is provided with a cuff unit, which applies pressure to the arm or the like, and with a sound sensing unit (microphone) for auscultation.
[00404] The 24c-1 cuff can be configured not only by a microphone method (KM), in which a manual auscultation method is replaced by a microphone and a blood pressure is automatically measured by determining blood vessel sounds (noise of Korotkoff), as described above, but also by an oscillometric (OS) method, in which blood pressure is measured by analyzing a pressure pulsation (oscillation) caused by cuff pressure pulse pressure or any other alternative methods.
[00405] Also, blood pressure value detection control unit 24c-2 performs cuff pressurization pressure control, hearing and Korotkoff noise analysis, all pressurization control based on Korotkoff noises analyzed and the acquisition and feeding outside the blood pressure value measured by the above procedures, in order to have the 24c-1 cuff performing the operations described above.
[00406] The measurement of the blood pressure value is continuously made through a period including sleep at night. The time interval for blood pressure measurement is typically 15 to 30 minutes.
[00407] The AD conversion unit 24c-3 converts the blood pressure value obtained in analog value to a digital signal, and the memory unit 24c-4 has an interface function, temporarily storing the digitized blood pressure value and sending it to the outside. Sending the digital blood pressure value data to the analyzer 24d can be done via a communication path or by a method of supplying a medium in which the data is stored in a portable memory medium and the medium is fixed .
[00408] The analyzer 24d, which similarly constitutes this blood pressure measuring system 24a, is performed by a personal computer system typically including a display screen and a printer and a computer program, which is installed on the computer and performs the operation, and the analyzer device is installed in a medical or similar institution, where the individual's respiratory waveform data and blood pressure value data are transmitted or the medium is supplied as described above, and according to the procedures that will be described later, the calculation is done using the respiratory waveform data. In addition to the respiratory waveforms, a (temporal) waveform change, which is the result of calculation based on the respiratory waveforms, and a change in the blood pressure value to be compared with the respiratory waveform change , are displayed on the basis of the display screen in a time series, printed by a printer or both are performed and, as a result, a medical personnel looking at the screen display or the printed result can diagnose the blood pressure value. basal.
[00409] The 24-d analyzer device that performs these functions is provided with a 24d-1 input terminal, which collects in digital data the respiratory waveform from the outside, a 24d-7 input terminal, which collects in data digitally the blood pressure value similarly from the outside, a 24d-2 memory unit, which records and keeps the data collected once, a 24d-3 analysis unit, which displays the recorded data and performs a calculation operation using those that a 24d-4 display unit will be described later, which displays a respiratory cycle stability index which is the result of the calculation output from the 24d-3 analysis unit or the time series data such as the value of blood pressure changing the waveform on a display screen, a 24d-5 printing unit, which prints the similarly output time series data, and a 24d-6 data sending terminal, which sends the time series data from time for the outdoors. [Analyzing Device Operation]
[00410] Subsequently, operations such as calculation of respiratory waveform, comparable blood pressure value output and the like, performed by the analyzer 24d, which is a characteristic configuration of this system 24a, will be described.
[00411] The above-described analysis unit 24d-3, provided in the analyzer 24d, extracts the above-described cyclic waveform of respiratory operation, mean lung power, for example, as a range of the respiratory cycle from the waveforms values obtained by measurement, according to the similar principle to the sleep assessment device 1 based on the respiratory waveform described using Fig. 1. First, an average value (X bar) of the respiratory rate and the standard deviation (SD) of the respiratory rate is further calculated using a known statistical method so that the size of the fluctuation of the respiratory cycle can be known. Furthermore, by taking an inverse number of this standard deviation (SD), the stability of the respiratory cycle can be indicated.
[00412] Instead of using the mean value (X bar) of the respiratory rate, other indices, such as the peak frequency of the respiratory cycle (Respiratory Stability Index) described above, can be used.
[00413] Similar to the other embodiments described above, the inverse number of the standard deviation of the respiratory waveform is referred to as RSI (Respiratory Stability Index). By plotting this RSI so that the temporal change of sleep for one night can be known, medical personnel looking at the graph can easily judge whether the sleep cycle is clearly indicated and whether the level of comfort, including quality sleep is good, or if the sleep cycle cannot be observed and the comfort level, including sleep quality, is poor. Also, in the RSI change waveform, where the sleep cycle can be clearly observed, it can be detected that, in the time domain where the RSI value is large, the individual is in the current non-REM period, that is, in a deep sleep state.
[00414] In Fig. 38, schematically explaining the graph issued by this system 24a, in the form of display, printing and the like, the lateral geometric axis indicates the measurement time of the individual's physiological data, and the vertical geometric axis indicates the sizes of the RSI and the blood pressure value.
[00415] The RSI and the blood pressure value are displayed by superimposing them vertically, using the same measurement time for the two types of physiological data, so that the RSI and the blood pressure value for the same time can be observed by comparison.
[00416] The observer, who sees the graph illustrated in Fig. 38, first observes a waveform of shifting RSI 25a, identifies the time domain with large RSI (Ta to Tb, 25a-1 in Fig. 38) and understands that the individual is in a state of deep sleep in this domain.
[00417] Subsequently, the observer observes a blood pressure value change waveform 25b-1 in Ta to Tb at the same time as the blood pressure value change waveform 25b, and can determine that the low value of blood pressure in this domain should be used as the basal blood pressure.
[00418] As a result, without using large-scale testing equipment such as PSG, or without relying on indirect means such as statistical means, the individual's blood pressure value in the deep sleep state can be obtained, and basal blood pressure can be measured with favorable reproducibility, high accuracy and ease.
[00419] Thus, in the system of the present invention, as already described, of a plurality of Fourier spectra of time, which becomes a starting point of each Fourier window period obtained by performing fast Fourier transformation (FFT) changing the time in 5 seconds
[00420] for a Fourier window period of 5 minutes from the entered respiratory waveform, a frequency domain from 0.11 to 0.50 Hz, including 0.4 Hz, which is a typical respiratory cycle of a human body , is extracted. Furthermore, in the variation system of the present invention, the analysis part 24d-3 calculates the mean value (X bar) and a standard deviation (SD) of the frequency included in the respiratory rate range for each Fourier window obtained with the interval of 50 second change. And so it is set up that the RSI described above is calculated by the inverse number of the standard deviation and displayed in a mode where comparison can be made with the blood pressure value.
[00421] The respiratory waveform and blood pressure value are preferably measured in parallel at the same time, however if they share a period when they match, it is only necessary to configure that the data of both can be compared and evaluated in the matched period , and the measurement periods for both may be different.
[00422] Also, the system can be used so that the respiratory waveform and blood pressure value are continuously measured, by the method described above, for the individual not only in the sleep state at night, but on awakening, and the blood pressure value is measured when the RSI is large, that is, when the individual's physiological state is in a stable period.
[00423] The configurations of these embodiments can be expanded and the same also applied to the following variations. [Blood pressure measurement system variation]
[00424] In the above-described embodiment, blood pressure measurement is described to be taken continuously during an individual's sleep with typical measurement intervals of 15 to 30 minutes similar to the ABPM method.
The automatic blood pressure meter measures blood pressure by pressurizing and tightening a cuff on the subject's arm, and the measurement is likely to wake up the subject.
[00426] Thus, as a variation of the above-described embodiment of the present invention, instead of continuous blood pressure measurement for a sleeping individual, it can be thus configured that blood pressure measurement using cuff pressurization is performed only when the RSI exceeds a pre-set threshold value and in a deep sleep state.
[00427] Alternatively, although the blood pressure measurement is made continuously in the sleep of the individual, it can be so configured that data storage of the measured blood pressure value to a memory, information transmission or output, such as display, is performed only if the RSI exceeds a pre-set threshold value. By configuring as above, memory capacity can be reduced, the risk of communication error in transmitting information can be decreased, and work efficiency can be improved by observing an observer of the waveform data.
[00428] Since the settings of these variations are the same as the blood pressure measurement system 24a described above, except for the difference described above, the description will not be repeated here in order to avoid inconveniences. [Application of the present invention to polysomnography test (PSG test)]
[00429] The blood pressure measurement system described above has the advantage that an operation at home is easy, based on the respiratory waveform that can be measured easily since the slow wave sleep state is known to change of the RSI, for example, as an index of stability of a respiratory cycle, so that the basal blood pressure value can be detected.
[00430] In putting the present invention into practice, the index and physiological data for known presence of the slow wave sleep state are not limited to the respiratory waveforms and the RSI index obtained from them.
[00431] For example, as described above, medical personnel can diagnose the depth of sleep, that is, the presence of slow wave sleep by changing the brain wave SWA waveforms and thus can be configured to continuously By measuring brain waveforms and blood pressure values in parallel over a period including sleep, medical personnel specify a time domain in which the individual is in a slow-wave sleep state based on changing sleep patterns. brain wave, or particularly brain wave SWA waveforms, and employs the blood pressure value measured in that domain as a baseline blood pressure value.
[00432] Alternatively, the blood pressure measurement system can thereby configure that an individual's brain waveforms are continuously measured over a predetermined period, including sleep, and the power of the SWA waveform waveform. The brain wave, which is a component obtained by extracting the low-frequency region, for example, is continuously monitored, and if the power of the brain wave SWA waveforms exceeds the pre-set threshold value, it is determined that the individual is in the current slow wave sleep state, and the measuring device automatically directs the blood pressure value measurement execution, so that the blood pressure value in the slow wave sleep region, that is, in the basal blood pressure value , can be automatically measured.
[00433] In addition, as the physiological data to detect the individual's slow-wave sleep state, a single or multiple pieces of physiological data, other than brain waveforms, can be employed, these various pieces of physiological data are continuously measured and displayed, respectively, or the device can be configured to automatically determine the presence of slow wave sleep by a predetermined condition in which these various pieces of physiological data are combined.
[00434] Since sleep can also be considered as a physiological and functional state of the brain, using a configuration in which brain waveforms are used for measurement, for example, the state of the brain itself can be observed and the baseline blood pressure value can be measured and determined as a confirmed diagnosis.
[00435] As a configuration that can be a basis for such an embodiment of the present invention, a polysomnography testing device (PSG testing device), which has been used to detect a slow wave sleep state of an individual, will be Described below.
[00436] The PSG testing device is a testing device that quantitatively calculates sleep depth (sleep stage), sleep fragmentation, presence of awakening reaction, sleep organization, sleep efficiency, and the like, along with the details of a respiratory state, measuring more detailed biological information from brain waves, electromyogram, eye ball movement and the like, in addition to basic items such as respiratory airflow, snoring sound, arterial oxygen saturation (SpO2) and the like.
[00437] In order to conduct the PSG test, a patient is hospitalized in a medical institution or in a dedicated testing facility called a sleep laboratory, fixed with various sensors, belonging to a test instrument called a polygraph measurement recording device. sleep (hereinafter referred to as a PSG testing device), on the patient's body parts and goes to sleep. During sleep, output signals from each of the sensors are continuously recorded onto a predetermined recording medium (a personal computer hard drive, a memory card, and the like).
[00438] The recorded data is analyzed in a manual analysis in which medical personnel directly analyze the test data or use a dedicated device called an automatic sleep polygraph analyzer. In the case of automatic analysis, a report is automatically created collecting assessments from a plurality of items. The plurality of assessment items includes the following items, for example: [Table 2] “PSG measurement examples and items”

[00439] Examples of PSG test device products include “Sleep Watcher E Series” (Teijin Pharma Limited Marketing Authorization Owner, Medical Equipment Authorization No. 21400BZY00026000, Medical Control Equipment Class, Specified Control Medical Equipment ).
[00440] This “Sleep Watcher E Series” is designed based on a brain wave meter and can measure up to 55 channels maximum and display fine waveform with a high sampling rate (512Hz maximum) and A/D resolution 14 bits. A pulse oximeter and pressure sensor are built into the main body, and such advantages are as long as operation is easy in a simple design, multiple test embodiments can be manipulated via LAN, and the system is expandable. The system can be easily expanded to a two-bed system via a CUBE and can handle digital video image input (optional). The system is capable of Japanese operations, and easy to understand, so that test/diagnostic work efficiency is improved, and various analysis results can be freely planned, including report layouts in rich text.
[00441] Also, the “Sleep Watcher E Series is capable of handling the following data as input test channels, that is, physiological data to be measured: AC electrode (sleep and brain wave diagnostic channel): 32 ch Input AC (breathing, limb movement channel): 8 ch DC input (posture and other channels): 4 ch Oximeter: 1 ch Pressure sensor: 2 ch External DC input (optional): 8 ch
[00442] These prior art PSG test devices do not include the blood pressure value of the physiological data to be measured.
[00443] The determination of brain wave stage is made based on the polygraph report, in which brain wave (EEG), eye movement (EOG), mental electromyogram (EMG) and the like are combined. As a standard for determining sleep stages, an international standard (Rechtshaffen & Kales, 1968) is established.
[00444] Therefore, it can thus be configured that, again using the blood pressure value as the target physiological data of measurement of an individual in sleep, in addition to the target physiological data of measurement of the prior art PSG test device, such as above, medical personnel can comprehensively analyze the plural parts of the physiological data, specify the blood pressure value in slow wave sleep, and determine the basal blood pressure value.
[00445] Alternatively, it can be so configured that the device automatically determines the presence of slow wave sleep under a predetermined condition, using one or a combination of a plurality of physiological data, and performs output such as display, printing or transmission of the presence of slow-wave sleep and the measured blood pressure value to the outside, so that they are contrasted with each other.
[00446] Alternatively, it can be thus configured that the measurement of the individual's blood pressure value is performed when the presence of slow wave sleep is automatically determined by the device.
[00447] Since specific configurations of these embodiments of the present invention are obvious from the configuration of the above described other embodiments of the present invention and the configuration of the PSG test device, the description will not be repeated in order to avoid inconvenience. [Application of the present invention to the oxygen concentrator]
[00448] Subsequently, as another aspect of the present invention, an embodiment of an oxygen supply device of the present invention, which assesses the physiological state of a human body or particularly a comfort level using the stability of a cycle respiratory and the like, will be described with reference to the accompanying drawings.
[00449] Fig. 39 is a schematic diagram of a device configuration exemplifying a pressure-variable adsorption type oxygen concentrator, which is an embodiment of the present invention.
[00450] An oxygen concentrator 1 of this embodiment is provided with a respiratory synchronization unit 210, which detects at least a patient's inspiration or expiration, and a control unit 401 as its characteristic configuration. The breath synchronization unit 201 exerts the function of reducing the amount of force required for the operation of the oxygen concentrator and reducing the size of the configuration of the oxygen concentrator used in prior art technologies as they are, by supplying concentrated oxygen gas only during the patient's inspiration period, and also plays the role of creating patient respiratory waveform information using the inspiration and expiration detection function. The control unit 401 calculates the respiratory cycle stability index called RSI, which was described above, from the obtained respiratory waveform information, continuously monitors a change of this RSI and controls the change of concentrated oxygen gas supply flow, changing the opening of the control valve 110, which controls the flow of concentrated oxygen gas entering in one direction to a state where the RSI becomes a higher value, that is, the level of patient comfort is improved. As a result, according to this embodiment, the optimal amount of oxygen gas, according to the actual physiological state of the patient, can be supplied more precisely, and since the addition of the new function to the oxygen concentrator mainly needs From a change of control program to the oxygen concentrator operation, the new sophisticated function can be added while the device remains simple and requiring only a low cost, without requiring the addition of large scale electronically controlled mechanisms or components.
[00451] The oxygen concentrator 1 of this embodiment, including an overlapped part with an oxygen concentrator having a breath synchronization function, according to prior art technology, will be described below.
[00452] In Fig. 39, which is a summarized configuration diagram of this embodiment, reference numeral 1 indicates an oxygen concentrator and reference numeral 3 indicates a user (patient) inhaling humidified oxygen enriched air (also referred to as “concentrated oxygen gas”). The oxygen concentrator, pressure float adsorption type 1, is provided with a HEPA 101 filter which removes fine dust, having passed through an air filter provided in a raw material air inlet, an inspiration silencer 102 , a compressor 103, a channel switching valve 104, an adsorption cylinder 105, a check valve 107, a product tank 108, a pressure control valve 109, flow adjustment means 110, and a pressure filter. particle 111. As a result, the concentrated oxygen gas, in which the oxygen gas is concentrated, can be manufactured by raw material air received from outside.
[00453] Also, in an oxygen concentrator enclosure, a humidifier (not shown), which humidifies the concentrated oxygen gas produced, the control part 401, which controls the compressor and channel switching valve 104, using a set value of the flow adjustment means 110 and the measured values of an oxygen concentration sensor 301 and a flow sensor 302, a compressor box 501, which isolates compressor noise, and a cooling fan 502, which cools the compressor, are incorporated.
[00454] First, the raw material air received from the outside is taken through the air inlet provided with the external air inlet filter 101, which removes foreign substances such as dust, and the inspiration silencer 102. On this occasion, approximately 21% oxygen gas, approximately 77% nitrogen gas, 0.8% argon gas, and 1.2% carbon dioxide and other gases are contained in normal air. In such a device, only oxygen gas is concentrated and taken as a breathing gas.
[00455] This removal of oxygen gas is performed by sequentially switching the target adsorption cylinder by the channel switching valve 104, between the adsorption cylinders in which adsorbent made of zeolite and the like, which selectively adsorb nitrogen gas molecules, is filled instead of oxygen gas molecules from the raw material air, while supplying the raw material air by pressurizing the raw material by compressor 103, and selectively adsorbing and removing approximately 77% of the nitrogen gas contained in the raw material air within the adsorption.
[00456] As such adsorption cylinders, a multiple cylinder type, formed of a cylindrical vessel filled with the adsorbent and generally having three cylinders or more, is used in addition to the single-cylinder and double-cylinder types, but in order to To manufacture oxygen-enriched air from raw material air continuously and efficiently, adsorption cylinders, of the multiple cylinder type, are preferably used. Also, like the compressor, an oscillating type air compressor is used, and rotation type air compressors, including a screw type, a rotary type, a spiral type and the like, are also used in some cases. The power supply of a motor that drives this compressor can be either AC or DC.
[00457] The concentrated oxygen gas, mainly composed of the unadsorbed oxygen gas in the adsorption cylinder 105, flows into the product tank 108, through the check valve 107 provided to prevent flow back into the adsorption cylinder.
[00458] Also, the nitrogen gas adsorbed by the adsorbent filled in the adsorption cylinder needs to be desorbed by the adsorbent in order to adsorb the nitrogen gas again by the newly introduced raw material air. Thus, the pressurized state performed by the compressor is switched by the channel switching valve to a reduced pressure state (an atmospheric pressure state or negative pressure state, for example), and the adsorbed nitrogen gas is desorbed in order to regenerate the adsorbent. In this desorption step, in order to improve the desorption efficiency, the concentrated oxygen gas can be reflowed as a purge gas from the product end side of the adsorption cylinder during the adsorption process or the product tank.
[00459] Since a large airflow sound is generally generated in nitrogen desorption, a 503 nitrogen exhaust noise silencer is generally used.
[00460] The concentrated oxygen gas produced by the raw material air is accumulated in the product tank 108. The concentrated oxygen gas accumulated in the product tank contains oxygen gas with a high concentration of 95%, for example, and is supplied to the humidifier (not shown), while the supply flow and its pressure are controlled by the pressure control valve 109, and the flow adjustment means 110 and concentrated humidified oxygen gas are supplied to the patient. Such humidifiers include a non-water supply type humidifier, which absorbs moisture from the outside air through a moisture-permeable membrane module, having a moisture-permeable membrane, and supplies it to the concentrated oxygen gas in a dry state, a bubbling type humidifier using water as a humidification source or a surface evaporation type humidifier can be used.
[00461] As the flow adjustment means 110, a control valve is used. If a first mode, in which a supply flow of the concentrated oxygen gas is manually adjusted, is selected, the opening of the control valve is controlled by the control part 401 through a raise/lower button 402 the supply flow of oxygen provided in the oxygen concentrator, and the flow is changed to a predetermined flow. Other than this first flow adjustment mode, as a second flow adjustment mode which is a feature of the present invention, the concentrated oxygen gas supply flow rate can be controlled by monitoring the stability of the respiratory cycle included in the respiratory waveform information, which is a type of biological information, in the direction in which the patient's comfort level is improved, in which the comfort level can be assessed based on the stability of the respiratory cycle. The two modes described above can be selected and operated by a patient or a patient aide by a selection operation of a 403 mode selection switch.
[00462] The breath synchronization part 201 is a main constituent element of this second mode of flow adjustment and a main element in carrying out the breath synchronization function, which performs reduction of an amount of force required for operation of the water concentrator. oxygen, size reduction of the oxygen concentrator configuration, and the like, supplying concentrated oxygen gas only during the patient's inspiration period. The breath synchronization function will be described first.
[00463] A highly sensitive pressure sensor (a semiconductor pressure sensor, for example), disposed in the breath synchronization unit 201, detects a slight negative pressure when the patient inhales the concentrated oxygen gas through a duct called a cannula, and the control unit 401 controls the opening/closing of the control valve 110 so that concentrated oxygen gas is supplied for the entire period or for a partial period of inspiration in the patient's breathing cycle based on the emitted signal of this sensor. This embodiment is configured so that the control valve 110 also works as a so-called on/off valve, however a control valve that determines a flow and a switching valve that switches gas cut/flow can be configured separately.
[00464] In general, inspiration takes up 1/3 and expiration takes up 2/3 of the breathing cycle time of a human creature, and supplying concentrated oxygen gas with a high flow on a continuous basis for the entire period or for a partial period of this inspiration period, oxygen concentration gas is supplied only when the patient actually inhales oxygen. Also, since the supply of concentrated oxygen gas is stopped in the expiration period, the amount of concentrated oxygen gas to be supplied to the patient is saved (conserved), and as a result, the degree of operating power is reduced, and the same oxygen gas supply can be realized with a smaller size oxygen concentrator configuration.
[00465] As described above, the breath synchronization unit 201 is provided with an internal pressure sensor and can detect the patient's inspiration/expiration ratio and, as a result, create the respiratory waveform information.
[00466] Then, in the oxygen concentrator 1 of this embodiment, examining the patient's respiratory cycle by the respiratory waveform information obtained as above, calculating stability as RSI, for example, described above, and continuously recording By changing the RSI, the 401 control unit can detect the physiological stability or comfort level of the patient and how it changes.
[00467] If the second supply flow adjustment mode is selected, the control unit 401 continuously monitors the change of the RSI and changes the opening of the control valve 110 so that the RSI becomes a higher value, that is, the patient's comfort level is improved and control the change in the supply flow of the concentrated oxygen gas.
[00468] For each patient, a doctor determines the amount of oxygen supply from the oxygen treatment as a prescription, but the amount of oxygen physiologically required by a human body is different depending on the activity state of the human body and other situations, and the prescribed flows are determined by the doctor with different values for the exercise period (when activities are intense), the rest period and the sleep period, respectively, for example, but according to this embodiment, the amount of Optimal oxygen gas is supplied according to the actual physiological state of the patient more precisely.
[00469] Also this embodiment is particularly useful when a patient walks while pulling a portable oxygen concentrator to go to the hospital or perform a walking exercise (rehabilitation).
[00470] It goes without saying that such control of the quantity of supply must be done under the instructions and control of doctors.
[00471] Also, according to this embodiment, since a respiratory pressure sensor, whose breath synchronization type oxygen concentrator is already equipped with, is used, another configuration for measuring the respiratory waveform does not it is necessary, and the configuration of the oxygen concentrator becomes simple and economical, which is an advantage.
[00472] This embodiment is capable of many variations being put into practice, except for the modes described above, and also correspond to the embodiments of the present invention.
[00473] For example, with the exception of the oxygen concentrator, the application of an oxygen gas cylinder or a device that supplies oxygen for inspiration from a liquid oxygen bottle is possible, and any application is possible, as long as continuous measurements of various types of physiological data, such as heart rate, cardiogram, brain waves, body temperature, blood oxygen saturation, respiratory volume, walking speed, blood pressure value, and the like, other than the respiratory waveform, may be made and the physiological state or comfort level of a human body can be assessed.
[00474] Also, as a sensor to obtain respiratory waveforms, other than the pressure sensor for the breath synchronization function, an airflow sensor, a temperature sensor, a sound sensor and the like can be used. [Application of the present invention to a medical equipment monitoring system and telemedicine system]
[00475] The following is an example where the present invention is applied to a medical equipment monitoring system that transmits operating and similar information from various types of medical equipment or, particularly, from an oxygen concentrator installed in the patient's home for a remote monitoring center or a telemedicine system, which transmits/receives physiological data, will be described based on the attached drawings.
[00476] A remote system that transmits measured physiological data (vital data) of a patient, such as blood pressure, body temperature, respiratory rate, blood oxygen saturation, and the like, to a receiving terminal, via a communication path or a so-called telemedicine system, has been used for remote diagnosis or an observational state of a patient.
[00477] However, the transmission of physiological stability or a comfort level index of a patient, rather than such direct physiological data to a receiving terminal via a communication path, or the creation of physiological stability or a level index of patient comfort based on physiological data received via the communication path, was not known or proposed either.
[00478] In system such as the Teijin Oxygen-concentrator Monitoring System (TOMS) (trademark), operated by Teijin Pharma Limited, the applicant of this application, in which an operating state of a medical equipment used by a patient at home or similar is monitored by a monitoring center, is proposed and currently used. A setting in which a function of transmitting a patient's physiological data, such as blood oxygen saturation, for example, is given to monitoring the operation of medical equipment so that the patient's condition can be observed by the health center. monitoring is also proposed. However, such non-direct transmission/reception and use of physiological data, but the transmission of physiological stability or a patient comfort level index to a receiving terminal via a communication path, or the creation of physiological stability or a Patient comfort level index based on physiological data received via the communication path has not been known or proposed either.
[00479] This embodiment is configured so that an index of physiological stability or comfort level of a patient, when exemplified by RSI, which is a respiratory cycle stability index, described above, or the physiological data used to create this index, can be transmitted.
[00480] If a monitoring center or medical personnel master such a physiological stability or comfort level of a patient, applications become possible, in which a patient state that cannot be known from simple measured values of physiological data , changing status and effects of treatment conducted in the patient's home, such as home oxygen treatment, can be confirmed, preventive maintenance is made possible by observing trends before the condition actually deteriorates, and the like.
[00481] Fig. 40 is a diagram illustrating an example of a medical support system of this embodiment.
[00482] In putting this embodiment into practice, it goes without saying that, without being limited to the configuration in which information, such as RSI, is placed within the medical equipment operation information monitoring system, as illustrated in Fig. 40 , the system can be configured primarily to transmit physiological data that the prior art telemedicine system or various index values created from the physiological data. These systems are configured in such a way that the patient's respiratory waveform information is obtained by the methods of measuring airflow, temperature change, lung or abdomen movement, body movement during sleep, center position change. gravity and the like, and the respiratory waveform information is sent via a communication path or converted to RSI before transmission and the RSI is transmitted via the communication path.
[00483] In Fig. 40, which is an example where the invention is applied to a medical equipment operation information monitoring system at patient sites 100 and 110, including the patient's home, elderly people's home, facility of child welfare, medical institution where patients are hospitalized or go for treatment and the like, a medical equipment 10, such as a medical oxygen concentrator, described above, used for home treatment, a communication terminal extension unit 12, connected to the medical equipment 10 via a communication cable 11 or the like, and a communication terminal main unit 14, capable of communicating information with the communication terminal extension unit 12, via a wireless communication medium or a medium. wired communication terminals or similar are installed. The communication terminal main unit 14 transfers the information to a server 20 at a data center 200 located remote from the medical device 10, via a public communication network, such as a public telephone line 150. server 20, a DB database that stores medical equipment and patient information and the medical equipment operating information is connected. This server 20 could be installed at a remote location from the patient's home or at a location away from the medical equipment of the medical institution.
[00484] The communication terminal extension unit 12 could be housed in an enclosure of the medical equipment 10 and connected via a communication link member. The main communication terminal unit 14 is connected to the public communication network 150 by connecting a telephone line cable 15 to a modular jack of a telephone installed in the patient's home. Thus, the main communication terminal unit 14 shares the public communication network 150 with communication equipment, such as a certain telephone installed in the patient's home.
[00485] In the normal state, the oxygen concentrator, which is the medical equipment 10, concentrates oxygen in the air and generates highly concentrated oxygen gas with a concentration of 90%, for example, and the patient inhales oxygen according to the prescription of a doctor. The medical equipment 10 creates the operating information, including when, for how long and how much oxygen has been supplied, for example, and outputs the information to the communication terminal extension unit 12. Then the main communication terminal unit. communication 14 obtains this operating information and transfers it to server 20 at the time of pre-established transfer. This transfer time is uniquely determined for each of the plurality of medical devices with a cycle of once in 24 hours, for example. By determining the transfer time for each of the plurality of medical devices, the concentrated transfer to the server is avoided. Also, since the main communication terminal unit 14 shares the public communication network 150 with the patient's home communication equipment, the transfer time is established by night time zones.
[00486] Medical equipment 10 creates emergency information if abnormality occurs. For example, the abnormality includes a case where the oxygen concentration value or oxygen flow becomes abnormal, or each component of medical equipment moves away from a stable or similar state. The emergency information is supplied to the main communication terminal unit 14 via the communication terminal extension unit 12. Thereafter, the main communication terminal unit 14 transfers the emergency information to the server 20 on the basis of a real time, without waiting for the transfer instant.
[00487] The operation of transmitting/receiving the medical equipment operation information of this medical equipment monitoring system has been described so far. As described above, the patient's respiratory waveform information can be obtained by the pressure sensor of the breath synchronization part of the oxygen concentrator or other sensor means. From this respiratory waveform information, respiratory cycle stability information or RSI, for example, can be created as described above. Since RSI and the like are indexes indicating the patient's comfort level, real-time monitoring of a patient's RSI at home at a remote location and accumulating and recording the information on server 20 using this medical support system , is extremely effective in observing the patient's condition, predicting the deterioration of the condition, checking the effects of treatment, oxygen treatment and the like.
[00488] Thus, this embodiment system is configured to transmit information such as RSI and the like in addition to operating information from medical equipment such as oxygen concentrator from the medical equipment side to the server side. Medical equipment is not limited to the oxygen concentrator, but any type of medical equipment that uses information such as RSI.
[00489] Various configurations can be designed for the system, and it is possible to transmit the respiratory waveform information to the server, so that the server can create the RSI or create and transmit the RSI on the medical equipment side or transmit the information if the RSI exceeds a specific threshold value.
[00490] The description of this embodiment is only an aspect and the number of main/extension units of the communication terminal can be a terminal or can be incorporated in the medical equipment.
[00491] Also, it goes without saying that the communication path for transmitting the information may be a mobile phone line or the information may be supplied to the server using a recording medium such as a USB memory.
[00492] Alternatively, information on how the RSI was changed and how much of the concentrated oxygen gas supply flow rate was at that time and the like, for a certain period such as a week or a day, can be concentrated into daily data in a written or on-screen report format so that medical personnel and the like can establish access. [Industrial Applicability]
[00493] According to the present invention, a device for calculating respiratory waveform information, used to assess comfort level, including sleep quality, and detect Cheyne-Stokes breathing syndrome reliably and simply without testing hospitalized and also using only respiratory waveforms, a device to assess the level of comfort, including sleep quality, a device to calculate physiological data, a computer program to make calculation using the shape information. respiratory waveform, a computer program to assess the comfort level, including the individual's sleep quality, a respiratory assist device, a chronic heart disease treatment device, a testing device used for titration work, a blood pressure test, a computer program to conduct a blood pressure test, a polysomnography testing device fia and the like are provided. [Reference Signal List] 1 sleep evaluation system (respiratory waveform information calculating device) 2-1 respiratory sensor (measurement means) 3-3 analysis unit (calculation means) 3-4 unit of display (output medium) 3-5 printer part (output medium) 3-6 output edge (output medium)

权利要求:
Claims (12)
[0001]
1. Device (1) for calculating physiological data, comprising measurement means (2) configured to be operable to measure respiratory waveform data of an individual for a predetermined measurement period; creating means (3-3) configured to be operable to create an index at each measurement time indicating stability of a value measured by the measurement means (2) at each measurement time during said measurement period and operable to create data from a temporal change of the index during the measurement period; and output means (3-4; 3-5; 3-6) configured to be operable to perform output processing of at least any one of displaying, printing or sending out of the device said created data, characterized in that that the creation means (3-3) is configured to create a frequency spectrum of the respiratory waveform and the index created is an inverse of the standard deviation of the respiratory rate.
[0002]
2. Device (1) for calculating physiological data according to claim 1, characterized in that the measurement means (2) comprises a physiological data recording meter (2-4) and the creation means (3-3 ) and the output means (3-4; 3-5; 3-6) comprise a physiological data analysis device (3) configured to be arranged to perform operations based on the respiratory waveform data recorded in said meter of physiological data recording (2-4).
[0003]
3. Device (1) for calculating physiological data according to claim 2, characterized in that said physiological data recording meter (2-4) is configured to be arranged to transmit the recorded respiratory waveform data information to said physiological data analysis device (3) via a recording medium or a communication path (2-5, 3-1).
[0004]
4. Device (1) for calculating physiological data according to any one of claims 1 to 3, characterized by the fact that the data of a temporal change index is a trend of respiratory stability index known as RSI trend.
[0005]
5. Device (1) for calculating physiological data according to any one of claims 1 to 4, characterized in that a predetermined period of measurement is a predetermined period of measurement including sleep.
[0006]
6. Device (1) for calculating physiological data according to any one of the preceding claims, characterized in that it further comprises a determination means configured to be operable to automatically determine a sleep quality by comparing the data created with a data where a quality of sleep is good.
[0007]
7. Respiratory assistance device (21a), characterized in that it comprises: compressed air supply means (21b-1) configured to supply compressed air outward at a pressure higher than atmospheric pressure and configured to be capable of change the feed pressure out; duct means (21e) configured to have an end part thereof connected to the supply side out of said compressed air supply means (21b-1); and mask means (21f) configured to be provided at the other end of said duct means (21e) for securing to a patient (21d) for treatment, for supplying said compressed air to the patient (21d), said device for respiratory assistance (21a) being arranged to continuously supply said compressed air to the patient (21d) in a sleep state through said mask means (21f), and further comprising: a device (21c) for calculating physiological data as defined in claim 1, wherein the measurement means (21c-1, 21c-2, 21c-3) is configured to be operable to measure patient respiratory waveform data (21d) for a predetermined measurement period; and control means (21b-2) configured to receive the time change data of the index created by the creating means (21c-4), and to change and control the supply pressure out of said compressed air supply means ( 21b-1) so that the received data of the temporal change of the index comes close to a temporal change of the index during good quality sleep.
[0008]
8. Respiratory assistance device (21a) according to claim 7, characterized in that said control means (21b-2) is configured to perform automatic servo-type control of the supply pressure out of said supply means of compressed air (21b-1), so that fluctuation in the operating cycle or pulmonary ventilation in the patient's respiratory operation (21d) in sleep becomes relatively less.
[0009]
9. Test device used in a titration work, characterized in that it comprises the device (1) for calculating physiological data as defined in claim 1; and a respiratory assist device provided with compressed air supply means configured to be operable to supply compressed air with a pressure higher than atmospheric pressure outwardly, duct means configured to be connected to the supply side out of said compressed air supply means, and mask means configured to be provided at an end part of said duct means for attachment to a patient undergoing treatment, to supply said compressed air to the patient, the respiratory assistance device being configured to supply continuously said compressed air to the patient through said mask means at a constant pressure or at a variable pressure; and wherein the output means is further configured to perform at least one of displaying, printing and sending abroad so that a temporal change of the pressure of said compressed air and a temporal change of the index indicating the regularity of the respiratory cycle can be observed simultaneously.
[0010]
10. Blood pressure testing device, characterized in that it comprises the device (1) for calculating physiological data as defined in claim 1, blood pressure value measuring means configured to be operable to measure and obtain a blood pressure value of an individual according to a procurement command; and obtain command generating means configured to be operable to generate said obtain command if the index indicating stability of the measured pressure value exceeds a threshold value determined in advance.
[0011]
11. Oxygen supply device for supplying oxygen gas for suction or concentrated oxygen gas for suction, characterized in that it comprises the device (1) for calculating physiological data as defined in claim 1, configured to be operable to continuously obtain shape data respiratory waveform of a patient to whom the gas is supplied; and control means (401) configured to be operable to alter and control a supply flow of said gas in one direction to improve the patient's comfort level using data created by the device creation means (3-3) (1 ) to calculate physiological data.
[0012]
12. Patient monitoring system, characterized in that it comprises the device (1) for calculating physiological data as defined in claim 1; wherein the device comprises: a sensor means configured to detect a state of an individual's inspired air and/or exhaled air, first creating means configured to create the individual's respiratory waveform information based on an output signal of said sensor means; transmitting means and receiving means operable to transmit and receive the created index, and the created data of a temporal shift of the index to a location located distant from the device for calculating physiological data, via a communication path.

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ES2823307T3|2021-05-06|

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US10195377B2|2019-02-05|

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US20190083723A1|2019-03-21|

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引用文献:

---

公开号 | 申请日 | 公开日 | 申请人 | 专利标题

---

---

JP2950038B2|1992-09-21|1999-09-20|松下電器産業株式会社|Sleep evaluation device|

---

JPH07275362A|1994-04-08|1995-10-24|Teijin Ltd|Respiration promoting device of air duct positive pressure type|

---

US6938619B1|2000-06-13|2005-09-06|Scott Laboratories, Inc.|Mask free delivery of oxygen and ventilatory monitoring|

---

JP2002071825A|2000-08-31|2002-03-12|Toto Ltd|Human body detecting device using microwave|

---

JP3868326B2|2001-11-15|2007-01-17|勝臣 魚田|Sleep introduction device and psychophysiological effect transfer device|

---

JP2003199831A|2001-12-28|2003-07-15|Nikken:Kk|Sleep introduction apparatus|

---

JP2003310679A|2002-04-22|2003-11-05|World Denshi Kogyo Kk|Massage device for leg and leg massage method using it|

---

JP2004283194A|2003-03-19|2004-10-14|Teijin Ltd|Biological information monitoring device and treatment system|

---

JP4205470B2|2003-04-02|2009-01-07|帝人株式会社|Inspection device, treatment system|

---

AU2004308537B2|2003-12-29|2010-09-16|ResMed Pty Ltd|Mechanical ventilation in the presence of sleep disordered breathing|

---

NZ591307A|2004-02-11|2012-06-29|Resmed Ltd|Session-by-session adjustment of a device for treating sleep disordered breathing|

---

JP2005237472A|2004-02-24|2005-09-08|七臣 ▲苅▼尾|Sphygmomanometry instrument|

---

JP2005237569A|2004-02-25|2005-09-08|Daikin Ind Ltd|Portable measuring equipment, health management system, and health management method|

---

JP4620959B2|2004-03-26|2011-01-26|キヤノン株式会社|Biological information monitor device|

---

US7717110B2|2004-10-01|2010-05-18|Ric Investments, Llc|Method and apparatus for treating Cheyne-Stokes respiration|

---

CN103083768B|2004-10-06|2016-07-06|瑞思迈有限公司|Method and apparatus for non-invasive monitoring of respiratory parameters in sleep disordered breathing|

---

EP2394572A3|2004-12-23|2012-05-09|ResMed Ltd.|Apparatus for detecting and discriminating breathing patterns from respiratory signals|

---

CN100518637C|2005-01-05|2009-07-29|深圳迈瑞生物医疗电子股份有限公司|Method and apparatus for monitoring human breathing mechanics parameters based on differential pressure flow sensor|

---

JP2008532587A|2005-02-22|2008-08-21|ヘルス−スマートリミテッド|Method and system for physiological and psychological / physiological monitoring and use thereof|

---

WO2006100544A1|2005-03-21|2006-09-28|Ecole Polytechnique Federale De Lausanne |Phase sensitive fourier domain optical coherence tomography|

---

JP4582642B2|2005-04-01|2010-11-17|株式会社タニタ|Sleep stage determination device|

---

WO2006133494A1|2005-06-14|2006-12-21|Resmed Limited|Methods and apparatus for controlling mask leak in cpap treatment|

---

JP4137107B2|2005-09-09|2008-08-20|学校法人帝京大学|Sleep apnea test device|

---

JP4508994B2|2005-09-16|2010-07-21|三菱電機株式会社|Flexible gear joint and method for manufacturing the same|

---

JP2007089716A|2005-09-27|2007-04-12|Matsushita Electric Works Ltd|Massaging apparatus|

---

JP4642626B2|2005-10-11|2011-03-02|博 中野|Apnea / hypopnea automatic detection device, detection method, program, and recording medium|

---

US7766840B2|2005-12-01|2010-08-03|Cardiac Pacemakers, Inc.|Method and system for heart failure status evaluation based on a disordered breathing index|

---

NZ607280A|2006-03-06|2014-06-27|Resmed Ltd|Method and apparatus for improved flow limitation detection of obstructive sleep apnea|

---

EP1884189A1|2006-08-03|2008-02-06|Pulsion Medical Systems AG|Apparatus and method for determining a physiologic parameter of a patient applying fourier transformation|

---

US20100095959A1|2006-10-17|2010-04-22|Michael Farrell|Device for ramped control of cpap treatment|

---

US8214007B2|2006-11-01|2012-07-03|Welch Allyn, Inc.|Body worn physiological sensor device having a disposable electrode module|

---

AU2008251011B2|2007-05-11|2015-02-05|ResMed Pty Ltd|Automated control for detection of flow limitation|

---

JP5073371B2|2007-06-06|2012-11-14|株式会社タニタ|Sleep evaluation device|

---

JP5451013B2|2007-09-06|2014-03-26|英次 麻野井|Apparatus, method, computer program, respiratory assistance device, respiratory assistance device for patients with chronic heart disease, sleep introduction device, massage device, testing device used for evaluating sleep quality|

---

JP5311330B2|2007-09-06|2013-10-09|学校法人大阪医科大学|Cardiac function diagnosis display system, display method, and display program|

---

KR20090060696A|2007-12-10|2009-06-15|한국전자통신연구원|Bio-signal measurement system and health management service method using by it|

---

US20100331715A1|2009-06-30|2010-12-30|Nellcor Puritan Bennett Ireland|Systems and methods for detecting effort events|

---

US20110009753A1|2009-07-10|2011-01-13|Yi Zhang|Respiration Rate Trending for Detecting Early Onset of Worsening Heart Failure|US20120092171A1|2010-10-14|2012-04-19|Qualcomm Incorporated|Mobile device sleep monitoring using environmental sound|

---

US9155853B2|2011-08-31|2015-10-13|General Electric Company|Systems and methods of adjusting ventilator modes and settings visually via a touchscreen|

---

EP3245945B1|2011-11-07|2020-07-22|ResMed Pty Ltd|Apparatus for providing ventilation to a patient|

---

GB201209413D0|2012-05-28|2012-07-11|Obs Medical Ltd|Respiration rate extraction from cardiac signals|

---

JP5960518B2|2012-06-04|2016-08-02|鉄男 菊池|Health management device|

---

US9888874B2|2012-06-15|2018-02-13|Hitachi, Ltd.|Stimulus presentation system|

---

US10159446B2|2012-09-04|2018-12-25|Gregg A. Dickerson|Medical gating using positive airway pressure devices|

---

WO2014047310A1|2012-09-19|2014-03-27|Resmed Sensor Technologies Limited|System and method for determining sleep stage|

---

US10492720B2|2012-09-19|2019-12-03|Resmed Sensor Technologies Limited|System and method for determining sleep stage|

---

DE102012219128B4|2012-10-19|2016-06-02|Pateca GmbH|Method and system for determining anatomical causes for the development of snoring sounds|

---

JP6219590B2|2013-04-18|2017-10-25|英次 麻野井|Diagnostic device and medical system|

---

CN111467644A|2013-07-08|2020-07-31|瑞思迈传感器技术有限公司|Method and system for sleep management|

---

FR3009184A1|2013-07-31|2015-02-06|Univ Sud Toulon Var|METHOD AND SYSTEM FOR IDENTIFYING RESPIRATORY ACTIVITY|

---

JP6432970B2|2013-09-27|2018-12-05|公立大学法人奈良県立医科大学|Respiration monitoring apparatus and respiration monitoring method|

---

JP2015075821A|2013-10-07|2015-04-20|横河電機株式会社|State diagnostic method and state diagnostic device|

---

EP2904969B1|2014-02-11|2022-01-05|Sorin CRM SAS|Device for treating the sleep apnea syndrome in a patient by kinaesthetic stimulation|

---

EP2905006B8|2014-02-11|2017-06-07|Sorin CRM SAS|Device for discriminating the stages of sleep of a patient|

---

JP6316063B2|2014-03-31|2018-04-25|学校法人慶應義塾|Information processing apparatus, information processing system, information processing method, and program|

---

CA2888394A1|2014-05-02|2015-11-02|University Health Network|Method and system for sleep detection|

---

CN103920215B|2014-05-04|2015-08-26|湖南明康中锦医疗科技发展有限公司|A kind of gas flow generator is supplied gas triggering method|

---

JP5636129B1|2014-05-16|2014-12-03|株式会社テクノリンク|Respiratory abnormality improvement device|

---

US9931483B2|2014-05-28|2018-04-03|Devilbiss Healtcare Llc|Detection of periodic breathing during CPAP therapy|

---

WO2016029226A1|2014-08-22|2016-02-25|The General Hospital Corporation|System and method for administering, monitoring and controlling biomimetic sleep|

---

CN105361885B|2014-08-26|2018-12-11|雃博股份有限公司|Respiratory waveform identification system|

---

EP2989979B8|2014-08-27|2022-02-16|Wellell Inc.|Respiratory waveform recognition method and system|

---

JP6315196B2|2014-09-19|2018-04-25|パナソニックＩｐマネジメント株式会社|Biological information detection device and bed|

---

US20160161307A1|2014-12-05|2016-06-09|General Electric Company|System and method for metering gas|

---

US10760934B2|2014-12-05|2020-09-01|Natural Gas Solutions North America, Llc|Using localized flow characteristics on electronic flow meter to quantify volumetric flow|

---

WO2016092433A1|2014-12-11|2016-06-16|Koninklijke Philips N.V.|System and method for determining spectral boundaries for sleep stage classification|

---

CN104586373A|2015-01-19|2015-05-06|张永江|Breath monitoring table used in cardiovascular medicine|

---

EP3261536A4|2015-02-27|2018-10-17|12th Man Technologies, Inc.|Digitally coached spirometry system and method|

---

US11247015B2|2015-03-24|2022-02-15|Ventec Life Systems, Inc.|Ventilator with integrated oxygen production|

---

US10315002B2|2015-03-24|2019-06-11|Ventec Life Systems, Inc.|Ventilator with integrated oxygen production|

---

CN106308801B|2015-06-29|2019-03-01|无锡智感星际科技有限公司|A method of human body respiration frequency is detected using smart phone|

---

EP3337388A1|2015-08-17|2018-06-27|ResMed Sensor Technologies Limited|Screener for sleep disordered breathing|

---

WO2017082165A1|2015-11-10|2017-05-18|日本電信電話株式会社|Respiration estimating method and device|

---

CN105232049A|2015-11-17|2016-01-13|北京怡和嘉业医疗科技有限公司|Cloud platform|

---

JP2016047305A|2015-11-30|2016-04-07|株式会社豊田中央研究所|Consciousness state estimation device and program|

---

CN105664314A|2015-12-31|2016-06-15|北京怡和嘉业医疗科技有限公司|Continuous positive airway pressure treatment parameter adjusting method and system and treatment system|

---

CN105595672A|2016-01-13|2016-05-25|上海乔马电子科技有限公司|Intelligent mattress system and method for accurately acquiring human body vital sign data on mattress|

---

FR3047654A1|2016-02-12|2017-08-18|Commissariat Energie Atomique|DEVICE FOR PRODUCING AN INDIVIDUAL RESPIRATORY SIGNAL REGULARITY REGULARITY FOR USE IN DETERMINING A INDIVIDUAL STATE|

---

CN105769122B|2016-03-16|2018-10-12|中国科学院电子学研究所|A kind of measuring apparatus of apnea hypopnea indexes|

---

JP6538599B2|2016-03-17|2019-07-03|富士フイルム株式会社|DIAGNOSTIC SUPPORT DEVICE, ITS OPERATION METHOD, AND OPERATION PROGRAM|

---

WO2017179699A1|2016-04-15|2017-10-19|オムロン株式会社|Biological information analysis device and system, and program|

---

WO2017182694A1|2016-04-22|2017-10-26|Nokia Technologies Oy|Controlling measurement of one or more vital signs of a living subject|

---

JP6268219B2|2016-05-17|2018-01-24|ミネベアミツミ株式会社|Respiratory waveform drawing system and biological information monitoring system|

---

US10773049B2|2016-06-21|2020-09-15|Ventec Life Systems, Inc.|Cough-assist systems with humidifier bypass|

---

US10987025B2|2016-12-20|2021-04-27|General Electric Company|Systems and methods for a respiratory sensor|

---

KR20180075832A|2016-12-27|2018-07-05|바이텔스 주식회사|Method and Apparatus for Monitoring Sleep State|

---

JP6520963B2|2017-01-20|2019-05-29|ダイキン工業株式会社|Oxygen concentrator|

---

CN108619597B|2017-03-17|2021-03-05|深圳市大雅医疗技术有限公司|Pressure compensation method for flow channel of breathing machine|

---

JP6829880B2|2017-03-27|2021-02-17|公立大学法人名古屋市立大学|Sleep assessment system, programs and storage media|

---

JP6891038B2|2017-05-15|2021-06-18|オムロン株式会社|Wearable devices and programs|

---

CN110612136A|2017-05-18|2019-12-24|帝人制药株式会社|Deterioration precursor device, oxygen concentration device, and deterioration precursor system|

---

JP6952500B2|2017-05-31|2021-10-20|日本光電工業株式会社|Bio-information processing device|

---

JP2018201782A|2017-06-02|2018-12-27|国立大学法人神戸大学|Phenomenon generation determination system and phenomenon generation determination method|

---

JP2019045320A|2017-09-01|2019-03-22|横河電機株式会社|Field apparatus, system, and waveform data output method|

---

CN108309286A|2017-12-15|2018-07-24|中国人民解放军第二军医大学第二附属医院|Sleep disturbance detects treatment system|

---

CN108245750A|2017-12-29|2018-07-06|湖南明康中锦医疗科技发展有限公司|A kind of control method, the device and system of Oxygen therapy apparatus output tolerance|

---

KR102075711B1|2018-01-15|2020-02-10|엘메카|Operating Reference Value Setting Method of the Suction Pump of Artificial Intelligence Type Autonomously Drived Based on Patient's Condition Information|

---

EP3533394A1|2018-02-28|2019-09-04|Löwenstein Medical Technology S.A.|Respiratory gas analyser for evaluating a respiratory gas|

---

JP2021524795A|2018-05-13|2021-09-16|サミール・サレハ・アフマド|Portable medical ventilator system using a portable oxygen concentrator|

---

KR102036087B1|2018-05-23|2019-10-25|주식회사 바이랩|Apparatus and method of measuring severity of sleep apnea|

---

JPWO2020071374A1|2018-10-02|2021-09-09|コニカミノルタ株式会社|Status monitoring device and status monitoring method|

---

TWI699199B|2018-12-20|2020-07-21|遠東科技大學|Abdominal breathing guider|

---

US20200230336A1|2019-01-17|2020-07-23|Covidien Lp|Ventilator-initiated decision support and waveform capture during ventilation|

---

CN110478595B|2019-07-17|2021-08-27|北京道贞健康科技发展有限责任公司|Biological feedback type deep relaxation navigation method and system|

---

CN110353874B|2019-08-01|2021-09-17|丽水澳中医疗设备有限公司|Sleep disordered breathing treatment system|

---

JP6800303B1|2019-12-02|2020-12-16|住友理工株式会社|Heart failure diagnostic device|

---

WO2021171266A1|2020-02-27|2021-09-02|Resmed Sensor Technologies Limited|Systems and methods for predicting alertness|

---

WO2021260652A1|2020-06-25|2021-12-30|ResMed Asia Pte. Ltd.|Connected oxygen therapy system for maintaining patient engagement in chronic respiratory disease therapy|

法律状态:
2020-02-27| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

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2020-02-27| B25A| Requested transfer of rights approved|Owner name: HIDETSUGU ASANOI (JP) ; HEARTLAB, INC. (JP) |

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2020-04-14| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|

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2021-05-18| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|

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2021-05-25| B25G| Requested change of headquarter approved|Owner name: HIDETSUGU ASANOI (JP) ; HEARTLAB, INC. (JP) |

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2021-07-06| B16A| Patent or certificate of addition of invention granted|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 11/08/2010, OBSERVADAS AS CONDICOES LEGAIS. PATENTE CONCEDIDA CONFORME ADI 5.529/DF, QUE DETERMINA A ALTERACAO DO PRAZO DE CONCESSAO. |

优先权:

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申请号 | 申请日 | 专利标题

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JP2009187759|2009-08-13|

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JP2009-187759|2009-08-13|

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PCT/JP2010/063892|WO2011019091A1|2009-08-13|2010-08-11|Device for calculating respiratory waveform information and medical device using respiratory waveform information|

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