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    • 专利摘要:
    A method of retrieving operating data from a person's brainwave measuring device, comprising: acquiring a measurement signal on the measuring device (100), a first testing step to determine whether a primary connection can be established between the measuring device and a data processing server (200), if a primary connection can be established, a step of primary transfer of operating data from the measuring device to the server, otherwise a second step test for determining whether a secondary connection can be established between the measuring device and a portable relay device (300), if a secondary connection can be established, a step of secondary transfer of operating data from the measuring device to the portable device relay, a third test step to determine whether a tertiary connection can be established between the portable relay device and the server, if a tertiary connection can be established, a tertiary transfer step of the operating data of the portable relay device to the server.
    公开号:FR3045257A1
    申请号:FR1562080
    申请日:2015-12-09
    公开日:2017-06-16
    发明作者:De Brugiere Quentin Soulet；Hugo Mercier；Olivier Tranzer；Adrien Catanas
    申请人:Dreem；
    IPC主号:
    专利说明:

    Method and system for retrieving operating data from a brain wave measuring device
    FIELD OF THE INVENTION
    The present invention relates to methods and systems for retrieving operating data from a device for measuring brain waves of a person.
    BACKGROUND OF THE INVENTION
    Devices are known for measuring a person's brain waves, especially during a period of sleep, work or leisure of the person.
    Such measuring devices usually comprise a helmet or headband provided with electrodes for measuring an encephalogram, and for example an electromyogram. The measurement device is worn by the person over a period of time, for example a user's sleep period for a sleep tracking device. Such devices can furthermore act on the cerebral functioning of the user, for example by means of sensory stimulators, for example sound stimulation means.
    WO 2015/17563 describes an example of such a device for measuring the brain waves of a person.
    In order to process the data, in particular the electroencephalogram signals, collected by such a measurement device, it is usually necessary to call on a processing server because the calculation power and the memory required are important. In addition, a processing server makes it possible to centralize the data collected by a plurality of measurement devices and to preserve and process the data resulting from a series of acquisitions. It is thus possible to implement learning algorithms or statistical calculations for example.
    Even when it is not used, the device for measuring brain waves is often kept in the room where the acquisition usually takes place, for example during the day on a bedside table in the bedroom. a sleep tracking device.
    We also note that access to the Internet is not always guaranteed in the different rooms of a house. Thus, in particular, the wireless router of a Wi-Fi network is frequently found in a living room of the dwelling which can be far from the bedroom. This can be chosen by the user for practical and economic reasons, so limit the number of Wi-Fi routers, or because the user wants to limit its exposure to electromagnetic radiation during sleep.
    As a result, the measuring device can, in practice, have significant difficulties in communicating with the Internet and therefore with the processing server. Retrieving operating data from a person's brainwave measurement device on a data processing server can thus be tricky and delayed unless the user is regularly required to perform a manual data transfer operation. , which is obviously binding and time-consuming for the latter.
    The present invention is intended in particular to improve this situation.
    SUMMARY OF THE INVENTION To this end, the invention firstly relates to a method of recovering operating data from a device for measuring the brain waves of a person on a data processing server, which is specifically intended to be used. implemented by a system comprising a data processing server, a portable relay device and a device for measuring the brain waves of a person, the method comprising at least: a) a work step in which, during a during the working period, a measurement signal (S) representative of a physiological signal of the person (P) is acquired by means of the measuring device, and said measurement signal is stored in a memory of said measuring device, which is ) a first connection test step, implemented after said work period, during which it is determined whether a primary connection can be established between the measuring device and the server of t c) if a primary connection can be established, a step of primary transfer of operating data from the measuring device to the data processing server, by means of said primary connection, said operating data being determined from the measurement signal, b2) if a primary connection can not be established, a second connection test step, in which it is determined whether a secondary connection can be established between the measuring device and the portable relay device, c2 ) if a secondary connection can be established, a step of secondary transfer of operating data from the measuring device to the portable relay device, by means of said secondary connection, said operating data being determined from the measurement signal b3) if a secondary transfer step has been implemented, a third connection test step, during which determines whether a tertiary connection can be established between the portable relay device and the data processing server, c3) if a tertiary connection can be established, a tertiary transfer step of the operating data of the portable relay device to the server data processing, by means of said tertiary connection.
    In preferred embodiments of the invention, one or more of the following provisions may also be used: the portable relay device is a device transportable by a user, in particular a base , a mobile phone, a smartphone, a tablet or a laptop; the primary connection, the secondary connection and the tertiary connection each comprise a wireless communication; the primary connection is implemented by means of a local wireless network connected to a wide area network, in particular an enterprise wireless network or a home wireless network connected to the Internet network; the secondary connection is a wireless connection between the brain wave measuring device and the portable relay device, in particular an ultrasonic connection or a radio frequency connection such as a Bluetooth connection or a near-field communication; the tertiary connection is implemented at least in part by means of a wireless network such as a cellular network or a local wireless network connected to the Internet network, notably a network of business-connected wireless networks. internet or a home wireless network connected to the Internet; the portable relay device is moved between the secondary transfer step and the tertiary transfer step; the second connection test step comprises a first test sub-step during which it is determined whether a radio frequency connection can be established between the brain wave measuring device and the portable relay device, if a radio frequency connection can be established, the secondary connection is a radio frequency connection, if a radio frequency connection can not be established, a second test sub-step in which it is determined whether an ultrasonic connection can be established between the measuring device brainwaves and the portable relay device, if an ultrasonic connection can be established, the secondary connection is an ultrasonic connection; the operating data transmitted from the brain wave measuring device to the data processing server during the primary transfer step comprise raw measurement data including the measurement signal; the operating data transmitted during the secondary transfer step and the tertiary transfer step comprise processed measurement data, preferably do not include the measurement signal (S), and even more preferably said operating data. have a size at least ten times smaller than a size of the raw measurement data including the measurement signal (S); the processed measurement data are determined by implementing a predefined pattern recognition algorithm in the measurement signal, in particular slow wave patterns, sleep spindle patterns, waking patterns and / or patterns; associated with the movements of the person, and said processed measurement data includes indicators relating to said predefined patterns, including a start time, a duration, a frequency and / or a magnitude of a predefined pattern and / or a number or frequency predefined patterns during the work period; during the working step, an acoustic signal (A), audible by the person and synchronized with a predetermined temporal wave pattern (Ml) of the person, is transmitted and the operating data transmitted. during the primary transfer step comprise at least one pacing parameter selected from a list comprising a start time, a duration, an amplitude, a spectrum and / or a reference of an acoustic stimulation pattern, preferably the Operation data transmitted during the secondary transfer step and during the tertiary transfer step also include the at least one pacing parameter. The invention also relates to a system comprising a data processing server, a portable relay device and a device for measuring the brain waves of a person, in which the measuring device comprises suitable acquisition means, during a work period, acquiring at least one measurement signal representative of a physiological signal of the person (P), a memory capable of storing said measurement signal, and communication means capable of determining whether a connection primary can be established between the measuring device and the data processing server,. transferring data from the measuring device to the data processing server by means of a primary connection, determining whether a secondary connection can be established between the measuring device and the portable relay device, and. transferring data from the measuring device to the portable relay device by means of a secondary connection, wherein the portable relay device comprises communication means adapted to. determining whether a tertiary connection can be established between the portable relay device and the data processing server,. transferring data from the portable relay device to the data processing server by means of a tertiary connection. The subject of the invention is also a device for measuring the brain waves of a person who is specifically intended to be integrated into a system as described above, the device comprising acquisition means suitable, during a work period, for acquiring at least one measurement signal representative of a physiological signal of the person (P), a memory capable of storing said measurement signal, and - communication means adapted to. determining whether a primary connection can be established between the brainwave measuring device and a data processing server of a system according to claim 13, transferring data from the brain wave measuring device to said data processing server by means of a primary connection, determining whether a secondary connection can be established between the brain wave measuring device and a portable relay device of a system according to claim 13, and transferring data from the brain wave measuring device to said portable relay device by means of a secondary connection.
    According to one embodiment, the arrangement further comprises transmission means adapted to emit an acoustic signal, audible by the person, and synchronized with a predetermined temporal pattern of the brain wave of the person.
    Thanks to these arrangements, among other things, the recovery of operating data of the device for measuring brain waves of a person on a processing server is facilitated, is less restrictive for the user, requires displacement of the measuring device , or particular action of the user, is more reliable and is not delayed.
    DESCRIPTION OF THE FIGURES Other features and advantages of the invention will emerge during the following description of several of its embodiments, given by way of non-limiting examples, with reference to the accompanying drawings.
    In the drawings: FIG. 1 is a schematic view of a device for measuring brain waves of a person according to one embodiment of the invention; FIG. 2 is a block diagram of a system according to a embodiment of the invention comprising a measuring device, a portable relay device and a data processing server, FIG. 3 is a block diagram of a primary connection and a primary transfer of operating data between the device of the invention. measurement and the data processing server of the system of FIG. 2, during the implementation of a method according to one embodiment of the invention, FIG. 4 is a block diagram of a secondary connection and a a secondary transfer of operating data between the measuring device and the portable relay device of the system of FIG. 2, during the implementation of a method according to one embodiment of the invention, FIG. 5 is a block diagram of a tertiary connection and a tertiary transfer of operating data between the portable relay device and the data processing server of the system of FIG. 2, during the implementation of a According to one embodiment of the invention, FIG. 6 is a flowchart illustrating an embodiment of a method for recovering operating data from a person's brainwave measurement device on a server. data processing according to one embodiment of the invention; FIG. 7 illustrates a cerebral slow wave temporal shape, an acoustic signal and predefined temporal patterns according to an exemplary embodiment of the invention.
    In the different figures, the same references designate identical or similar elements.
    DETAILED DESCRIPTION
    As illustrated in particular in Figures 2 and 6, the invention relates to a system 1 comprising a device 100 for measuring the brain waves of a person, a data processing server 200 and a portable relay device 300.
    The system 1 is able to implement a method for retrieving operating data from the device for measuring the brain waves of a person P on the data processing server which is notably illustrated in FIG. 6.
    The device 100 is illustrated in Figures 1 and 2 and is for example adapted to be worn by the person P, for example on the head of the person P. For this purpose, the device 100 may comprise one or more support elements 120 apt at least partially surround the head of the person P so as to be maintained there. The support elements 120 take for example the shape of one or more branches that can be arranged so as to surround the head of the person P to maintain the device 100.
    The device 100 can also be divided into one or more elements, able to be worn on different parts of the body of the person P, for example on the head, wrist or on the torso.
    The device 100 comprises means 130 for acquiring at least one measurement signal and at least one memory 160. The device 100 may also include means 150 for analyzing the measurement signal. The device 100 may finally comprise transmission means 140 designed to emit an acoustic signal audible by the person P as will be described later.
    The device is for example adapted to be worn by the person P during a work period that may extend over a period of several minutes to several hours, for example at least eight hours.
    By "work period" is meant a period during which the measuring device is active and implements a predefined work operation, for example an acquisition of a measurement signal S representative of a physiological signal of the Person P. The person P may be inactive, for example asleep during the work period. The measuring device can further implement other operations, for example analysis or data transmission, out of the work period.
    The work period may for example correspond to a sleep period of the person P, especially when the measuring device is a monitoring device and / or sleep stimulation.
    The device 100 may further include a battery 180. The battery 180 may in particular be able to supply the acquisition means 130, the transmission means 140 and the analysis means 150, the memory 160 and the communication module 7. .
    The battery 180 is for example able to provide energy without being recharged over the entire period of work, for example over a period of several hours without having to be recharged, for example at least eight hours.
    The device 100 can in particular operate autonomously during the work period.
    By "autonomous" is meant that the device can operate during the work period, and in particular implement brainwave acquisition and / or stimulation operations as described below, without communicating with the processing server. 200, in particular without communicating with the processing server 200. In particular it is meant that the device can operate during the work period without having to be recharged with electrical energy and without the need to be structurally connected to an external device such as a fixing element or a power supply.
    In this way the device 100 is adapted to be used in the daily life of a person P without imposing particular constraints.
    To enable the implementation of the acquisition and / or stimulation of the brain wave operations, the acquisition means 130, the transmission means 140, the analysis means 150 and the memory 160 are moreover functionally connected between them and able to exchange information and orders. For this purpose, the acquisition means 130, the transmission means 140, the analysis means 150 and the memory 160 are mounted on the support element 120 so as to be close to one another so that the communication between these elements 130, 140, 150, 160 is particularly fast and at high speed. The battery 180 can also be mounted on the support element 120.
    The memory 16 0 may be permanently mounted on the support member 120 or may be a removable module, for example a memory card such as an SD card (acronym for the term "Secure Digital").
    The memory 160 is able to record operating data of the device 100 which will be detailed in the remainder of the description and may comprise at least one of the following elements: raw measurement data comprising a measurement signal S acquired by the means 130, processed measurement data determined from the measurement signal S.
    The memory 160 is able to be updated dynamically during the operation of the device 100. The working step is illustrated in FIG. 6 and can thus firstly comprise a substep of acquisition of at least one measurement signal S by means of the acquisition means 130.
    The measurement signal S can in particular be representative of a physiological electrical signal E of the person P.
    The physiological electrical signal E may for example comprise an electroencephalogram (EEG), an electromyogram (EMG), an electrooculogram (EOG), an electrocardiogram (ECG) or any other biosignal measurable on the person P. For this purpose, the means of acquisition 130 comprise for example a plurality of electrodes 130 adapted to be in contact with the person P, and in particular with the skin of the person P to acquire at least one measurement signal S representative of a physiological electrical signal E of the person P.
    The physiological electrical signal E advantageously comprises an electroencephalogram (EEG) of the person P. For this purpose, in one embodiment of the invention, the device 100 comprises at least two electrodes 130 including at least one reference electrode 130a and at least one minus one EEG measuring electrode 130b.
    The device 100 may further comprise a ground electrode 130c.
    In a particular embodiment, the device 100 comprises at least three EEG measuring electrodes 130c, so as to acquire physiological electrical signals E comprising at least three electroencephalogram measurement channels.
    The EEG measuring electrodes 130c are for example disposed on the surface of the scalp of the person P.
    In other embodiments, the device 100 may further comprise an electrode for measuring the EMG and, optionally, an electrode for measuring EOG.
    The measurement electrodes 130 may be reusable electrodes or disposable electrodes. Advantageously, the measurement electrodes 130 are reusable electrodes so as to simplify the daily use of the device.
    The measuring electrodes 130 may be, in particular, dry electrodes or electrodes covered with a contact gel. The electrodes 130 may also be textile or silicone electrodes.
    The acquisition means 130 may also include measuring signal acquisition devices S not only electrical.
    A measurement signal S can thus be, in general, representative of a physiological signal of the person P.
    The measurement signal S can in particular be representative of a physiological signal of the non-electrical or non-completely electrical person P, for example a cardiac work signal, such as a heart rate, a body temperature of the person P or still further movements of the person P. For this purpose, the acquisition means 130 may comprise a heart rate detector, a body thermometer, an accelerometer, a breathing sensor, a bioimpedance sensor or a microphone.
    The acquisition means 130 may also include measurement signal acquisition devices S representative of the environment of the person P.
    The measurement signal S can thus be representative of a quality of the air surrounding the person P, for example a carbon dioxide or oxygen level, or a temperature or a level of ambient noise.
    Finally, the acquisition means 130 may include user input devices allowing the person P to enter information. For example the user can indicate a subjective index of night quality. The measurement signal S can then be representative of information provided by the person P.
    The measurement signal S thus obtained can thus constitute raw measurement data within the meaning of the present description.
    Furthermore, in one embodiment of the invention, the substep of acquisition of the measurement signal S also comprises a pretreatment of the measurement signal S.
    The pretreatment of the measurement signal S may comprise, for example at least one of the following pretreatments: a frequency filter, for example a frequency and / or wavelet filtering of the measurement signal S in a range of temporal frequencies of interest , for example a frequency range in a range from 0.3 Hz to 100 Hz, frequency and / or wavelet filtering of parasitic frequencies of the measurement signal S, for example able to filter at least one parasitic frequency of measurement signal S, for example a spurious frequency belonging to a frequency range from 0.3 Hz to 100 Hz, - elimination of predefined artifacts of the measurement signal S.
    The pretreatment of the measurement signal S may also comprise pretreatments such as: amplification, for example an amplification of the measurement signal S by a factor ranging from 10 -3 to 10 -6, and / or sampling of the measurement signal S by means of an analog-digital converter suitable, for example, for sampling the measurement signal S with a sampling rate of a few hundred Hertz, for example 256 Hz or 512 Hz.
    Such pretreatment of the measurement signal S may for example be implemented by an analog module or a digital module of the acquisition means 130. Thus, in particular, the acquisition means 130 may comprise active electrodes capable of producing one pretreatments detailed above.
    The measurement signal S obtained as a result of the pretreatment may also constitute raw measurement data in the sense of the present description. The working step of the present method may also include a substep of processing the measurement signal S.
    The sub-step of processing the measurement signal S makes it possible in particular to determine processed measurement data.
    To implement this substep of processing, the device comprises analysis means 150 able to analyze the measurement signal S.
    The analysis means 150 may, for example, implement one or more predefined pattern recognition algorithms on the measurement signal S, for example slow wave patterns, spindle patterns, patterns of complex K, or patterns associated with waking and / or patterns associated with the movements of the person.
    The processed measurement data can thus comprise indicators relating to said predefined patterns, for example a start time, a duration, a frequency and / or a predefined pattern amplitude and / or a predefined pattern number or frequency during of the work period.
    The processed measurement data may also comprise other synthetic data determined from the measurement signal S, for example average values of the signal, spectral averages or other digital indicators that can be determined from the measurement signal S.
    The processed measurement data may also include higher level indicators such as sleep phases or awakening or microreveil times.
    The processed measurement data can also comprise the lossy compressed measurement signal, for example a wavelet compression. By "raw measurement signal" is meant the measurement signal S and possibly the measurement signal compressed by a compression algorithm without loss, for example an entropic compression type zip.
    The processed measurement data is thus determined from the measurement signal S and may in particular not include the raw measurement signal S itself. In this way, the processed measurement data may be smaller than the size of the raw measurement data, for example a size at least ten times smaller than the size of the raw measurement data or at least 100 times smaller, especially at least ten times smaller than the size of the measurement signal S.
    In a first exemplary embodiment, a frequency spectrum of the measurement signal S can be determined. The predefined shapes are then determined from a variation of energy of the frequency spectrum in predefined frequency bands such as for example a frequency band of the alpha waves (8 12 Hz), beta (> 12 Hz), delta ( <4Hz) or theta (4 7 Hz).
    Frequency spectrum energy in one or more of said frequency bands can be calculated, for example using a short-term fast fourier transform.
    In another exemplary embodiment, possibly combinable with the first exemplary embodiment indicated, the predefined shapes can be determined directly in the temporal form of the measurement signal S, in particular by searching for one or more predefined patterns in the measurement signal S .
    Thus, for example, slow oscillations and complexes can be detected by searching for consecutive zeros spaced less than about one second apart and seeking a maximum peak to peak.
    When said peak-to-peak maximum exceeds a certain threshold, then a slow wave pattern or complexK can be identified.
    The analysis means 150 can also analyze a measurement signal S representing a level of muscular work, for example an electrooculogram. In this case, the analysis means 150 can for example calculate a sliding average of a variation of the movement of the eyes.
    The analysis means 150 can also implement an automatic identification algorithm from the measurement signal S. Such an automatic identification algorithm is for example defined during a preliminary automatic learning step.
    By "automatic identification algorithm" is meant an algorithm adapted to automatically identify and classify patterns in measurement data, for example by associating a class with them, based on qualitative or quantitative rules characterizing the measurement data.
    Said class associated with the measurement data may be selected from a class database, or may be an interpolated value from a class database.
    A "class" can thus be for example an identifier, for example an alphanumeric identifier of a predefined pattern, or a numerical value, where appropriate an integer or real value.
    The class obtained can identify a predefined pattern in the measurement signal S, for example identify a K-complex pattern or a spindle.
    Such an automatic identification algorithm can for example implement a neural network, a support vector machine (or wide-margin separator), a decision tree, a random forest of decision trees, a genetic algorithm or further factor analysis, linear regression, Fisher discriminant analysis, logistic regression, or other known methods of classification.
    Such an algorithm may include a plurality of parameters that define the qualitative or quantitative rules from which the automatic identification algorithm can automatically detect and classify the measurement data. Such parameters are, for example, the weights of certain neurons or of all the neurons for an algorithm implementing a network of neurons. The parameters of the automatic identification algorithm may for example be predefined during a supervised automatic learning step, or more or less determined automatically, for example by the implementation of a semi automatic learning step. -supervised, partially supervised, unsupervised or by reinforcement. The class database may also be predefined during such a learning step. Such an automatic learning step can be implemented from a measurement data learning sample.
    Finally, the working step may comprise a sub-step of transmitting an acoustic signal A constituting an operation for stimulating the brain waves of the person P. For this purpose, the device 100 may comprise transmission means 140 designed to emit an acoustic signal A, audible by the person, and synchronized with a predetermined time pattern of the brain wave Ml of the person if it is judged that the person is in a state of aptitude for stimulation. For this purpose, the transmission means 140 comprise, for example, at least one acoustic transducer 110 and a control electronics 190. The control electronics 190 is particularly capable, in real time, of being able to receive acquisition means 130 on the measuring signal S and controlling the transmission by the acoustic transducer 110 of an acoustic signal A synchronized with a predefined temporal pattern T of a slow cerebral wave of the person P.
    By "soft real-time" is meant an implementation of the stimulation operation such as temporal constraints on this operation, in particular on the duration or repetition frequency of this operation. , are respected on average over a predefined total implementation period, for example a few hours. In particular, the implementation of said operation may at times exceed said temporal constraints as long as the average operation of the device 100 and the average implementation of the method respects them over the total predefined implementation time. In particular, time limits may be predefined beyond which the implementation of the stimulation operation must be stopped or paused.
    To allow such a flexible implementation in real time, a maximum distance between the acquisition means 130, the transmission means 140, the analysis means 150 and the memory 160 may be less than about one meter and preferably less than a few tens of centimeters. In this way, a sufficiently fast communication between the elements of the device 100 can be guaranteed.
    The acquisition means 130, the transmission means 140, the analysis means 150 and the memory 160 may for example be housed in the cavities of the support element 120, clipped onto the support element 120 or else fixed to the support member 120 for example by gluing, screwing or any other suitable fastening means. In one embodiment of the invention, the acquisition means 130, the transmission means 140, the analysis means 150 and the memory 160 may be mounted on the support member 120 removably.
    Without an advantageous embodiment of the invention, the control electronics 190 is functionally connected to the acquisition means 130 and to the acoustic transducer 110 via wire links 170. In this way, the exposure of the control electronics 190 is reduced. the person P to electromagnetic radiation.
    The acoustic transducer or transducers 110 are able to emit an acoustic signal A stimulating at least one inner ear of the person P.
    In a first embodiment, an acoustic transducer 110 is an osteophonic device stimulating the inner ear of the person P by bone conduction.
    This osteophonic device 110 may for example be able to be placed close to the ear, for example above as illustrated in Figure 1, in particular on a skin area covering a cranial bone.
    In a second embodiment, the acoustic transducer 110 is a speaker stimulating the inner ear of the person P through an ear canal leading to said inner ear.
    This speaker may be disposed outside the ear of the person P or in the ear canal.
    The acoustic signal A is a modulated signal belonging at least partially to a frequency range audible by a person P, for example the range from 20 Hz to 30 kHz. The control electronics 190 receives the measurement signals S acquisition means 130, possibly pretreated as detailed above.
    If the measurement signals S received by the control electronics 190 are not pretreated, the control electronics 190 may in particular implement one and / or the other of the pre-treatments detailed above. The control electronics 190 is then able to implement a brain wave stimulation operation of the person P, an operation which will now be described in more detail.
    Brain waves can in particular be slow brain waves.
    By "cerebral slow wave" is meant in particular a cerebral electrical wave of the person P having a frequency of less than 5 Hz and greater than 0.3 Hz. By "cerebral slow wave", it is possible to hear a cerebral electrical wave of the person P having a peak to peak amplitude of, for example, between 10 and 200 microvolts. In addition to the very low frequency waves below 1 Hz, cerebral slow waves are also understood to mean, in particular, delta waves of higher frequencies (usually between 1.6 and 4 Hz). A cerebral slow wave can still be understood to mean any type of wave having the characteristics of frequency and amplitude mentioned above. For example, the phase 120 sleep waves referred to as "K-complexes" may be considered as slow brain waves for the invention.
    In general, the implementation of the invention may for example take place during a sleep phase of the person P (as identified for example in the AASM standards, acronym for "American Academy of
    Sleep Medicine "), for example a deep sleep phase of person P (commonly known as stage 3 or stage 4) or during other phases of sleep, for example during light sleep of the person (usually called stage 2) . The invention can also be implemented during an awakening phase, sleep or awakening of the person P. Brain waves can then differ from slow brain waves.
    In order to implement the brain wave stimulation operation, the control electronics 190 is for example suitable, from the measurement signal S, for firstly determining a temporal shape F of a cerebral slow wave C such that illustrated in Figure 7.
    In a first embodiment, the time form F is a series of sampled points of amplitude values of the measurement signal S, possibly pre-processed as mentioned above, said series of measurement points possibly being interpolated or resampled.
    In a second embodiment, the temporal form F is a series of amplitude values generated by a phase locked loop, or phase locked loop, (commonly referred to as PLL, acronym for the English term "Phase locked loop"). ").
    The phase-locked loop is such that the instantaneous phase of the temporal form F at the output of said loop is slaved to the instantaneous phase of the measurement signal S.
    The phase locked loop can be implemented by analog means or digital means.
    It is thus clear that the temporal form F is a representation of the brain wave C which can be obtained directly or can be obtained by a phase-locked loop which makes it possible to obtain a cleaner signal. In particular, the instantaneous phase of the temporal form F and the cerebral wave C are synchronized temporally. In the present description, the term "brain wave C" is therefore used to mean the values taken by the temporal form F. From this temporal form F, the control electronics 190 is able to determine at least one time instant I synchronizing between a predetermined time pattern C slow brain wave C and a predefined temporal pattern M2 of the acoustic signal A.
    Then, the control electronics 190 is able to control the acoustic transducer 110 so that the predefined temporal pattern M2 of the acoustic signal A is emitted at the timing instant I of synchronization.
    The predefined temporal pattern Ml of cerebral slow wave C is therefore a pattern of amplitude and / or phase values of the temporal form F which represents the cerebral slow wave C. In particular, the predefined temporal pattern M1 may be a succession of phase values of the temporal form F and may therefore be in particular independent of the absolute value of the amplitude of the time form F.
    The predefined temporal pattern M1 may also be a succession of relative values of the amplitude of the temporal form F. Said relative values are, for example, relating to a maximum amplitude of the predefined or stored temporal form F.
    In one embodiment of the invention, the predefined temporal pattern M1 may thus for example correspond to a local temporal maximum of the cerebral slow wave C, a local temporal minimum of the cerebral slow wave C or else a predefined succession of c at least one local temporal maximum and at least one local temporal minimum of the cerebral slow wave C.
    The predefined temporal pattern M1 may also correspond to a portion of such a maximum, minimum or of such a succession, for example a rising edge, a falling edge or a plateau.
    In the same manner, the predefined temporal pattern M2 of the acoustic signal may be a pattern of amplitude and / or phase values of the acoustic signal A.
    In a first embodiment, the acoustic signal is for example an intermittent signal as illustrated in FIG. 7. This intermittent signal is for example emitted during a period of time less than a period of a slow cerebral wave. The duration of the intermittent signal is for example less than a few seconds, preferably less than one second.
    In an example given for purely indicative and non-limiting, the acoustic signal A is for example a type 1 / f pink noise pulse with a time duration of 50 to 100 milliseconds with a rise and fall time of a few milliseconds. Still in a nonlimiting manner and to fix the ideas, in this example, the predefined temporal pattern Ml of cerebral slow wave C can for example correspond to a rising edge of a local maximum of the cerebral slow wave C. The temporal motif predefined M2 of the acoustic signal A can then be for example a rising edge of the pink noise pulse. In this example, the timing instant I of synchronization between the predefined temporal pattern Ml of cerebral slow wave C and the predefined temporal pattern M2 of the acoustic signal A can for example be defined so that the rising edge of the pink noise pulse A and the rising edge of the local maximum of the cerebral slow wave C are synchronized, that is to say concomitant.
    In another embodiment, the acoustic signal A may be a continuous signal. The duration of the acoustic signal A may then in particular be greater than a period of the cerebral slow wave C. By "continuous signal" is meant in particular a signal of great duration in front of a period of the cerebral slow wave C.
    In this embodiment, the acoustic signal A may be modulated temporally in amplitude, frequency or phase and the predefined temporal pattern M2 of the acoustic signal A may then be such a temporal modulation.
    Alternatively, the continuous acoustic signal A may not be modulated temporally, for example in a manner that will now be described.
    The device 100 may comprise at least two acoustic transducers 110, in particular a first acoustic transducer 110a and a second acoustic transducer 110b as illustrated in FIG. 2. The first acoustic transducer 110a is able to emit an acoustic signal A1 stimulating a right inner ear of the person P. The second acoustic transducer 110b is able to emit an acoustic signal A2 stimulating a left inner ear of the person P.
    In particular, the first and second acoustic transducers 110a, 110b can be controlled in such a way that the acoustic signals A1 and A2 are binaural acoustic signals A. For this purpose, the acoustic signals A1 and A2 may for example be continuous signals. different frequencies.
    Such acoustic signals A1, A2 are known to generate intermittent pulses in the brain of the person P, in particular called binaural beats.
    Still in a nonlimiting manner and to fix the ideas, in this example, the predefined temporal pattern M1 of cerebral slow wave C may, for example, again correspond to a rising edge of a local maximum of the cerebral slow wave C The predefined temporal patterns M2 of the acoustic signals A1, A2 can moreover be ranges of the acoustic signals A1, A2 corresponding temporally to said intermittent pulses generated in the brain of the person P. In this example, the time instant I of synchronization between the predefined temporal pattern M1 of cerebral slow wave C and the predefined temporal patterns M2 of the acoustic signals A1, A2 may for example be defined so that an intermittent pulse generated in the brain of the person P is synchronized temporally with the rising edge of the local maximum of the cerebral slow wave C.
    Fig. 7 illustrates an example of predefined time patterns M1 and M2. One and / or the other among a sound level, a duration, a spectrum and a temporal pattern M2 of the acoustic signal A can be predefined and recorded in the memory 160 of the device 100.
    Said one and / or other of a sound level, a duration, a spectrum and a temporal pattern M2 of the acoustic signal A can form operating data of the device 100.
    More specifically, the operating data may comprise one or more pacing parameters selected from a list comprising a start time, a duration, an amplitude, a spectrum and / or a reference of an acoustic stimulation pattern of the acoustic signal A.
    The acoustic signal A can thus be transmitted according to said operating data.
    According to the embodiments and according to the selected time pattern Ml, different embodiments can be envisaged for determining the time instant I of synchronization.
    Likewise, one and / or the other of a brain wave phase of the person and a predefined temporal wave pattern Ml of the person P can be predefined and stored in the memory 160 of the device 100.
    Said one and / or another of a brain wave phase of the person and a predefined temporal wave pattern Ml of the person P can form operating data of the device 100.
    The acoustic signal A can thus be emitted so as to be synchronized according to said operating data.
    Furthermore, in order to determine the time instant I, the control electronics 190 may, for example, compare the amplitude values of the measurement signal S, possibly filtered and / or normalized, with an amplitude threshold.
    In the example given above, which is purely nonlimiting, the predefined temporal pattern Ml of cerebral slow wave C corresponds to a rising edge of a local maximum of the cerebral slow wave C. A temporal instant I then corresponds to a time instant of exceeding the amplitude threshold, or a predefined duration immediately following such an overrun time. The control electronics 190 can thus control the acoustic transducer 140 so that the predefined temporal pattern M2 of the acoustic signal A is synchronized temporally with said time instant I.
    It is well understood that the speed of communication between the acquisition means 130, the acoustic transducer 110 and the control electronics 190 makes it possible in particular to ensure reliable synchronization and optimum implementation of the stimulation operation.
    In an embodiment in which the time form F is a series of amplitude values generated by a phase locked loop, it is possible to determine said time instant I from said phase locked loop, by threshold detection or by predicting future values of time form F.
    In this embodiment, the temporal form F may in particular be less noisy than the measurement signal S and allow a facilitated determination of the time instant I of synchronization. In this way, it is thus easier to use the phase values of the temporal form F to identify the time instant I.
    As illustrated in FIG. 6, once the work step is over, the method according to the invention can then comprise a first connection test step.
    This first connection test step can thus be implemented after the work period.
    This first connection test step is illustrated in Figure 3 in particular.
    During the first connection test step, it is determined whether a primary connection 710 can be established between the measuring device 100 and the data processing server 200. For this purpose, the measuring device 100 may comprise communication 199 and the data processing server 200 may also include communication means 299.
    The communication means 199, 299 of the measuring device 100 and the data processing server 200 may be able to determine whether a primary connection can be established between the measuring device 100 and the data processing server 200, and to be transferred. data from the measuring device 100 to the data processing server 200, by means of such a primary connection.
    The communication means 199 may be mounted on the support element 120 in the manner described above for the acquisition means 130, the transmission means 140 and the analysis means 150. The communication means 199 may be controlled by an electronic device 100, for example the control electronics 190.
    The communication means 199 comprise in particular a wireless communication chip.
    The communication means 199 may thus comprise a radiofrequency communication module, for example a module capable of implementing a near-field communication, a Bluetooth communication and / or a Wi-Fi communication.
    By Bluetooth, we mean in particular the Bluetooth protocol and the protocol "Bluetooth Low Energy" (BLE).
    The communication means 199 may also include an ultrasonic communication module or an optical communication module, for example embedding a diode.
    The communication means 299 of the processing server 200 may for example be means of access to the Internet network, for example wired communication means such as an Ethernet card.
    The primary connection 710 may be a wireless connection, at least starting from the measuring device 100.
    For this, the primary connection 710 can be implemented by means of a local wireless network 400 connected to an extended network 500.
    The wide area network 500 is for example the internet network.
    The local wireless network 400 is for example a corporate wireless network or a home wireless network, in particular a Wi-Fi network connected to the Internet.
    The measuring device 100 can thus for example seek to connect to a home wireless network and, from this wireless network, seek to connect to the Internet, and by the same to the processing server 200 which can also be connected to the internet.
    The primary connection 710 may thus comprise a connection 711 of the measuring device 100 to a local wireless network 400, a connection 712 of the local wireless network 400 to an extended network 500, and a connection 713 of the wide area network 500 to the server data processing 200.
    The connection 711 between the measuring device 100 and the local wireless network 400 may notably be a wireless connection.
    If a primary connection can be established, then a primary transfer step can be implemented.
    This primary transfer step is illustrated in FIG. 3 in particular. The primary transfer step can be implemented by means of said primary connection. The primary transfer step includes transmitting operating data from the measurement device to the data processing server.
    The operating data can be determined from the measurement signal.
    The operating data transmitted from the brain wave measuring device to the data processing server during the primary transfer step may in particular comprise raw measurement data as described above, that is to say comprising the measurement signal S.
    If a primary connection can not be established, the method according to the invention may then include a second connection test step illustrated in FIG. 4 in particular.
    During this second connection test step, it is possible to determine whether a secondary connection 720 can be established between the measuring device 100 and the portable relay device 300.
    By "secondary connection" is meant that this secondary connection is implemented if the primary connection described above is not possible to implement, so it is a connection to ensure resilient operation of the system.
    The portable relay device 300 is a device transportable by a user and able to communicate with the measuring device and a wireless network.
    The portable device relay 300 is for example a base, a mobile phone, a smartphone, a tablet or a laptop.
    The portable relay device 300 may in particular comprise communication means 399.
    The communication means 399 of the portable relay device 300 may comprise a control chip and a radio-frequency wireless communication module comprising an antenna, an ultrasonic communication module comprising a microphone and / or an optical communication module comprising for example a diode.
    A radiofrequency wireless communication module of the communication means 399 may for example be a module capable of implementing a near-field communication, a Bluetooth communication and / or a Wi-Fi communication.
    If a secondary connection 720 can be established, the method can then include a step of secondary transfer of operating data from the measuring device 100 to the portable relay device 300.
    This secondary transfer step is illustrated in FIG. 4.
    The secondary connection 720 is a wireless connection between the measuring device 100 and the portable relay device 300. The secondary connection 720 may for example be an ultrasonic connection or a radio frequency connection, such as a Bluetooth connection or a communication in the field. close.
    More specifically, in a particular embodiment of the invention illustrated in particular in FIG. 6, the second connection test step may comprise a first test sub-step during which it is determined whether a radio frequency connection can be established. between the measuring device 100 and the portable relay device 300. Such a radio frequency connection may for example be a Bluetooth connection or a near-field communication.
    If such a radio frequency connection can be established, the secondary connection can then be a radio frequency connection.
    If such a radio frequency connection can not be established, a second test sub-step can be implemented in which it is determined during which it is determined whether an ultrasonic connection can be established between the measuring device 100 and the portable relay device. 300.
    If an ultrasonic connection can be established, the secondary connection is then an ultrasonic connection.
    In this particular embodiment, the communication means 399 of the portable relay device 300 may comprise both a radio frequency wireless communication module and an ultrasonic communication module. In a symmetrical manner, the communication means 199 of the measuring device 100 may comprise both a radio-frequency wireless communication module and an ultrasonic communication module.
    The secondary connection can thus be a wireless connection. The secondary transfer step can be implemented by means of said secondary connection. The secondary transfer step includes transmitting operating data from the measuring device 100 to the portable relay device 300.
    The operating data can be determined from the measurement signal.
    The operating data transmitted from the measurement device 100 to the portable relay device 300 during the secondary transfer step may comprise processed measurement data as described above. In particular, said operating data transmitted from the measuring device 100 to the portable relay device 300 may comprise only processed measurement data and not comprise the measurement signal S.
    Thus, for example, said operating data transmitted from the measuring device 100 to the portable relay device 300 may have a size at least ten times smaller than a size of the raw measurement data including the measurement signal S.
    In this way, it is possible to implement between the measurement device 100 and the portable relay device 300 a relatively fast local communication despite the limited data rates of the local communication protocols that are the Bluetooth connections, in the near field or by ultrasound .
    If a secondary transfer step has been implemented, the method may then comprise a third connection test step, during which it is determined whether a tertiary connection 730 can be established between the portable relay device 300 and the server data processing 200.
    This third connection test step is illustrated in FIG.
    By "tertiary connection" is meant that this tertiary connection is implemented if the primary connection described above is not possible to implement and if the secondary connection has been implemented, it is therefore a connection to ensure the resilient operation of the system.
    The tertiary connection 730 may be a wireless connection, at least from the portable relay device 300.
    For this, the tertiary connection 730 can be implemented by means of a wireless network 600 connected to an extended network 500.
    The wireless network 600 may be a cellular network such as a mobile telephone network.
    The wireless network 600 may also be a local wireless network, for example an enterprise wireless network or a home wireless network, in particular a Wi-Fi network connected to the Internet.
    The tertiary connection 730 may thus comprise a connection 731 of the portable relay device to a wireless network 600, a connection 732 of the wireless network 600 to an extended network 500, and a connection 733 of the wide area network 500 to the processing server. 200.
    The connection 731 between the portable relay device 300 and the wireless network 600 may in particular be a wireless connection.
    If a tertiary connection can be established, the method can then include a tertiary transfer step of the operating data of the portable relay device 300 to the data processing server 200, by means of said tertiary connection.
    The third connection test step and the tertiary transfer step of the operating data of the portable relay device to the data processing server can be implemented using the communication means 299, 399 of the portable relay device. 300 and the data processing server 200.
    The operating data transmitted from the portable relay device 300 to the data processing server 200 during the tertiary transfer step may be identical to the operating data transmitted from the measurement device 100 to the portable relay device 300 during the transmission. secondary transfer step.
    Alternatively, additional data may be added by the portable relay device 300 to the operating data transmitted from the measurement device 100 to the portable relay device 300 during the secondary transfer step to form the operating data transmitted from the portable device. relay 300 to the data processing server 200 during the tertiary transfer step. To this end, the portable relay device may include data processing means 310, including at least one computer chip.
    The processing server 200 can thus obtain a trace of the work period that has elapsed, even if it does not have the raw operating data.
    As can be seen above, the primary connection, the secondary connection and the tertiary connection can all be implemented, at least in part, by wireless communications.
    In a particular embodiment of the invention, the portable relay device 300 can be moved between the secondary transfer step and the tertiary transfer step.
    The portable relay device 300 may in particular wait to have access to the Internet network via a predefined channel to implement the tertiary transfer step.
    In particular, the third connection test step may consist in determining whether it is possible to establish, between the portable relay device and the data processing server, a tertiary connection which is a connection through a network. local wireless, for example a corporate wireless network or a home wireless network, especially a Wi-Fi network connected to the internet. If it is only possible to establish, between the portable relay device 300 and the data processing server 200, a tertiary connection which is a connection through a cellular network such as a mobile telephone network, the portable relay device 300 can then choose to wait to transmit the function data to the data processing server 200, so as to limit the costs for the user.
    In one embodiment of the invention in which the measuring device 100 also implements a brain wave stimulation operation, the operating data transmitted from the brain wave measuring device 100 to the data processing server 200 during of the primary transfer step may further comprise at least one pacing parameter selected from a list comprising a start time, a duration, an amplitude, a spectrum and / or a reference of an acoustic stimulation pattern.
    By "a reference of an acoustic stimulation pattern" is meant, for example, an alphanumeric identifier of a predefined stimulation pattern.
    In this embodiment, the operating data transmitted from the measurement device 100 to the portable relay device 300 during the secondary transfer step as well as the operating data transmitted from the portable relay device 300 to the data processing server. 200 during the tertiary transfer step may also include said at least one pacing parameter.
    In one embodiment of the invention, the data processing server 200 may be able to communicate with a plurality of measurement devices 100 respectively capable of being worn by a plurality of persons P.
    The data processing server 200 can thus receive a plurality of operating data respectively associated with the plurality of measurement devices 100.
    The data processing server 200 comprises processing means 210, for example one or more calculation chips 210, capable of performing a processing of the operating data, for example able to implement learning algorithms or statistical calculations. The data processing server can thus for example determine statistics or synthetic indices from the operating data.
    权利要求:
    Claims (15)
    [1" id="c-fr-0001]
    A method for retrieving operating data from a device (100) for measuring brain waves of a person on a data processing server (200), specially adapted to be implemented by a system (1) comprising a data processing server (200), a portable relay device (300) and a device (100) for measuring brain waves of a person, the method comprising at least: a) a work step in which during a work period, by means of the measuring device (100), a measurement signal (S) representative of a physiological signal (E) of the person (P) is acquired, and said measurement signal is stored in a memory (160) of said measuring device (100), bl) a first connection test step, implemented after said work period, during which it is determined whether a primary connection (710) can be established between the measuring device (100) and the server of tr a data connection (200), cl) if a primary connection can be established, a step of primary transfer of operating data from the measuring device (100) to the data processing server (200), by means of said primary connection ( 710), said operating data being determined from the measurement signal, b2) if a primary connection can not be established, a second connection test step, in which it is determined whether a secondary connection (720) can between the measuring device (100) and the portable relay device (300), c2) if a secondary connection can be established, a step of secondary transfer of operating data from the measuring device (100) to the portable device of relay (300), by means of said secondary connection (720), said operating data being determined from the measurement signal, b3) if a secondary transfer step has been implemented. vre, a third connection test step, in which it is determined whether a tertiary connection (730) can be established between the portable relay device (300) and the data processing server (200), c3) if a Tertiary connection can be established, a tertiary transfer step of the operating data of the portable relay device (300) to the data processing server (200), by means of said tertiary connection (730).
    [2" id="c-fr-0002]
    2. The method of claim 1, wherein the portable relay device (300) is a device transportable by a user, including a base, a mobile phone, a smartphone, a tablet or a laptop.
    [3" id="c-fr-0003]
    The method of any of claims 1 and 2, wherein the primary connection (710), the secondary connection (720) and the tertiary connection (730) each comprise wireless communication.
    [4" id="c-fr-0004]
    The method according to any one of claims 1 to 3, wherein the primary connection (710) is implemented by means of a local wireless network (400) connected to a wide area network (500), including a corporate wireless network or a home wireless network connected to the Internet.
    [5" id="c-fr-0005]
    The method of any one of claims 1 to 4, wherein the secondary connection (720) is a wireless connection between the brain wave measuring device (100) and the portable relay device (300), including a ultrasonic connection or radio frequency connection such as a Bluetooth connection or near field communication.
    [6" id="c-fr-0006]
    The method of any one of claims 1 to 5, wherein the tertiary connection (730) is implemented at least in part by means of a wireless network (600) such as a cellular network or a network. local wireless network connected to the Internet, including a wireless network connected to the Internet or a home wireless network connected to the Internet.
    [7" id="c-fr-0007]
    The method of any one of claims 1 to 6, wherein the portable relay device (300) is moved between the secondary transfer step and the tertiary transfer step.
    [8" id="c-fr-0008]
    The method according to any one of claims 1 to 7, wherein the second connection test step comprises a first test substep in which it is determined whether a radio frequency connection can be established between the measurement device. (100) brain waves and the portable relay device (300), if a radio frequency connection can be established, the secondary connection (720) is a radio frequency connection, if a radio frequency connection can not be established, a second sub-step of testing in which it is determined whether an ultrasonic connection can be established between the brain wave measuring device and the portable relay device, if an ultrasonic connection can be established, the secondary connection (720) is an ultrasonic connection.
    [9" id="c-fr-0009]
    The method of any one of claims 1 to 8, wherein the operating data transmitted from the brain wave measuring device (100) to the data processing server (200) during the primary transfer step comprises raw measurement data including the measurement signal (S).
    [10" id="c-fr-0010]
    The method according to any one of claims 1 to 9, wherein the operating data transmitted during the secondary transfer step and the tertiary transfer step comprise processed measurement data, preferably do not include the measurement signal (S), even more preferably in which said operating data has a size at least ten times smaller than a size of the raw measurement data including the measurement signal (S).
    [11" id="c-fr-0011]
    The method of claim 10, wherein the processed measurement data is determined by implementing a predefined pattern recognition algorithm in the measurement signal, including slow wave patterns, sleep spindle patterns, patterns associated with the awakening and / or patterns associated with the movements of the person, and wherein said processed measurement data includes indicators relating to said predefined patterns, including a start time, a duration, a frequency and / or an amplitude of a predefined pattern and / or a number or frequency of predefined patterns during the work period.
    [12" id="c-fr-0012]
    The method according to any of claims 1 to 11, wherein during the working step, an acoustic signal (A), audible by the person, is furthermore transmitted and synchronized with a predefined temporal pattern of time. brain wave (Ml) of the person, and wherein the operation data transmitted during the primary transfer step comprises at least one pacing parameter selected from a list comprising a start time, a duration, an amplitude, a spectrum and / or a reference of an acoustic stimulation pattern, preferably wherein the operating data transmitted during the secondary transfer step and during the tertiary transfer step also comprise said at least one parameter of stimulation.
    [13" id="c-fr-0013]
    A system comprising a data processing server (200), a portable relay device (300) and a device (100) for measuring brain waves of a person, wherein the measuring device (100) comprises - acquisition means (130) capable, during a work period, of acquiring at least one measurement signal representative of a physiological signal of the person (P), - a memory (160) able to store said measurement signal, and - communication means (199) adapted to. determining whether a primary connection (710) can be established between the measuring device (100) and the data processing server (200),. transferring data from the measuring device (100) to the data processing server (200) by means of a primary connection (710), determining whether a secondary connection (720) can be established between the measuring device (100) and the portable relay device (300), and. transferring data from the measuring device (100) to the portable relay device (300) by means of a secondary connection (720), wherein the portable relay device (300) comprises communication means (399) adapted to. determining whether a tertiary connection (730) can be established between the portable relay device (300) and the data processing server (200),. transferring data from the portable relay device (300) to the data processing server (200) by means of a tertiary connection (730).
    [14" id="c-fr-0014]
    14. Measuring device (100) of brain waves of a person specifically intended to be integrated in a system (1) according to claim 13, the device comprising - acquisition means (130) suitable for a period of work , acquiring at least one measurement signal representative of a physiological signal of the person (P), - a memory (160) able to store said measurement signal, and - communication means (199) adapted to. determining whether a primary connection (710) can be established between the brainwave measuring device (100) and a data processing server (200) of a system (1) according to claim 13, transferring data from the measuring (100) brain waves at said data processing server (200) by means of a primary connection (710),. determining whether a secondary connection (720) can be established between the brainwave measuring device (100) and a portable relay device (300) of a system (1) according to claim 13, and transferring data from the measuring (100) brain waves at said portable relay device (300) by means of a secondary connection (720).
    [15" id="c-fr-0015]
    The device according to claim 14, further comprising transmitting means (140) adapted to emit an acoustic signal (A), audible by the person, and synchronized with a predetermined temporal pattern of the brain wave (Ml) of the nobody.
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    同族专利:
    公开号 | 公开日
    CN108604998A|2018-09-28|
    EP3387794B1|2020-10-21|
    US20180368717A1|2018-12-27|
    EP3387794A1|2018-10-17|
    FR3045257B1|2018-03-16|
    WO2017098185A1|2017-06-15|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20130231947A1|2000-05-30|2013-09-05|Vladimir Shusterman|Mobile System with Network-Distributed Data Processing for Biomedical Applications|
    US20140135612A1|2010-09-30|2014-05-15|Fitbit, Inc.|Portable Monitoring Devices For Processing Applications and Processing Analysis of Physiological Conditions of a User associated with the Portable Monitoring Device|
    WO2014138414A1|2013-03-06|2014-09-12|Simon Adam J|Form factors for the multi-modal physiological assessment of brain health|
    CN104434045A|2014-11-10|2015-03-25|深圳市华士精成科技有限公司|Regional group personnel health monitoring system|
    CN201790809U|2010-04-01|2011-04-13|陈浩然|Wireless multi-parameter short-long distance real-time monitoring system|
    CN103040463B|2013-01-15|2014-12-24|乔丹洋|Device and method for monitoring sleep brain waves|
    EP3027110A4|2013-07-30|2017-06-28|Emotiv Lifesciences, Inc.|Wearable system for detecting and measuring biosignals|
    CN103810254A|2014-01-22|2014-05-21|浙江大学|User behavior real-time analyzing method based on cloud terminal|
    CN103876711B|2014-03-27|2016-06-01|北京圣博亚科技有限公司|Wearable electronic and measuring of human health management system|
    CN204219626U|2014-11-07|2015-03-25|刘宝社|The multi-functional apparatus for curing insomnia of a kind of network|
    CN104679254B|2015-03-30|2018-02-16|四川盟宝实业有限公司|Sense the mobile phone interaction system of earphone in real time based on brain wave|USD859665S1|2017-10-25|2019-09-10|Dreem|Sensor|
    USD896972S1|2018-06-06|2020-09-22|BrainWaveBank Limited|Medical device|
    USD908664S1|2019-06-02|2021-01-26|Sens.Ai Inc.|Headset with biometric sensors|
    法律状态:
    2016-11-29| PLFP| Fee payment|Year of fee payment: 2 |
    2017-06-16| PLSC| Publication of the preliminary search report|Effective date: 20170616 |
    2017-10-30| PLFP| Fee payment|Year of fee payment: 3 |
    2018-01-19| CD| Change of name or company name|Owner name: RYTHM, FR Effective date: 20171212 |
    2018-12-27| PLFP| Fee payment|Year of fee payment: 4 |
    2019-12-13| PLFP| Fee payment|Year of fee payment: 5 |
    2020-12-21| PLFP| Fee payment|Year of fee payment: 6 |
    2021-09-03| CA| Change of address|Effective date: 20210728 |
    2021-11-30| PLFP| Fee payment|Year of fee payment: 7 |
    优先权:
    申请号 | 申请日 | 专利标题
    FR1562080|2015-12-09|
    FR1562080A|FR3045257B1|2015-12-09|2015-12-09|METHOD AND SYSTEM FOR RECOVERING OPERATING DATA OF A BRAIN WAVE MEASURING DEVICE|FR1562080A| FR3045257B1|2015-12-09|2015-12-09|METHOD AND SYSTEM FOR RECOVERING OPERATING DATA OF A BRAIN WAVE MEASURING DEVICE|
    PCT/FR2016/053307| WO2017098185A1|2015-12-09|2016-12-09|Method and system for recovering operating data of a device for measuring brain waves|
    EP16825813.5A| EP3387794B1|2015-12-09|2016-12-09|Method and system for recovering operating data of a device for measuring brain waves|
    CN201680080853.8A| CN108604998A|2015-12-09|2016-12-09|Method and system suitable for the operation data for retrieving brain wave measuring device|
    US16/060,834| US20180368717A1|2015-12-09|2016-12-09|Method and system for recovering operating data of a device for measuring brain waves|
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