• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
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    • 专利摘要:
    test device. it is a testing apparatus for performing an assay, wherein the testing apparatus comprises a receptacle (2) containing a reagent, wherein the reagent is reactive to an applied test sample by developing a color variation or pattern; a portable device (1), for example a mobile phone or a laptop-type computer, comprising a processor and an image capture device (3), wherein the processor is configured to process data captured by the image capture device. image and output a test result for the applied test sample.
    公开号:BR112013025223B1
    申请号:R112013025223-5
    申请日:2012-03-30
    公开日:2021-09-08
    发明作者:Neil Polwart
    申请人:Albagaia Limited；
    IPC主号:
    专利说明:

    The present invention relates to carrying out a test with a mobile device such as a mobile phone. In particular, but not exclusively, the invention relates to capturing and processing test test data with a mobile phone.
    An assay, such as a bioassay or immunoassay, is a procedure in molecular biology to test or measure the activity of a drug or a biochemical in an organism or an organic sample. Chemical, biochemical and microbiological assays based on the development of a color change or a variation in color hue within a defined area of an usually solid substrate are well known in various fields including industrial, clinical, environmental analysis. -ental and microbiological.
    Two common examples of such tests are pH indicator papers and home pregnancy tests. Typically, a color change or the appearance of a feature in the test is visually assessed by the test operator with the naked eye. In the case of a pH indicator, the color change is judged by comparison with a reference scale often located on the test container. In the case of a home pregnancy test, the presence or absence of a colored line at a known location on the test strip indicates the test result.
    These general concepts are widely applied in simple, fast, easy-to-use, and low-cost testing as well as lab-based testing. However, variations in operator visual acuity can make it difficult to obtain accurate results, particularly when the result is close to the detection limit or when it needs to be matched to a sliding hue scale to qualify the results. The precision, accuracy, reproducibility and repeatability of such tests may be compromised to the point that only qualitative or semi-qualitative results are possible in such tests. Even when qualitative test results are acceptable, there is typically no formal record indicating that the test took place for quality or evidential purposes.
    It is desirable to provide a test apparatus that does not rely on the operator's visual acuity. It is desirable to provide a test apparatus that provides quantitative test results rather than just qualitative ones.
    It is known to use an electro-optical instrument, in which the test is placed to be electronically interrogated. However, such instrumentation is often complex and custom designed for the specific application and consequently incurs significant hardware, firmware and software development costs. The resulting apparatus is also often relatively large and therefore of limited portability.
    It is desirable to provide a testing apparatus that is readily available, portable and/or applicable to a multitude of different tests.
    Many common consumer electronic devices, such as mobile phones, can be used to capture and process images and to output or store the image data or share the image data over a network such as a Wi-Fi or wireless network. telecommunications. Processing of the image data is carried out through the device using various processing techniques to produce good quality images. There is often a change in the techniques used. Processing is not set up to output just an image with the most realistic color representation.
    In accordance with the present invention, there is provided a testing apparatus for performing an assay, wherein the testing apparatus comprises: a receptacle containing a reagent, wherein the reagent is reactive to an applied test sample by developing a color variation or pattern, a portable device comprising a processor and an image capture device, wherein the processor is configured to process data captured by the image capture device and output a test result to the test sample applied.
    The portable device may comprise a mobile phone, PDA, digital camera, laptop or the like. The image capture device can comprise a camera.
    The testing apparatus can be configured to perform an immunoassay, such as a lateral flow immunoassay. The tester can be configured for detection of Legionella bacteria.
    The reagent can be solid. Alternatively, the reagent can be liquid.
    The test apparatus may be operable to transmit one or both of the data and the test result over a network.
    The processor can be configured to measure the developed pattern or color variation. Alternatively, the testing apparatus may include a remote processing device, such as a central computer, to measure the developed color or pattern variation and calculate the test result. The handheld device can be configured to transmit the data to the remote processing device and receive and output the calculated test result.
    The remote processing device can be adapted to store one or both of the data and the test result. The remote processing device can be adapted to store one or both of the data and test result from a plurality of assays or portable devices.
    The handheld device or the remote processing device can be configured to process the data and test result from a plurality of assays or handheld devices to calculate one or more parameters or group values, such as an average value, a standard deviation value, a trend function, or similar. The processor can be adapted to output the group or parameter value.
    The handheld device can be configured to modify the image to optimize the color representation of the image.
    The handheld device can be configured to apply correction and/or filtering to an image to remove electronic or optical noise from the image. The handheld device can be configured to discard irrelevant portions of the image to reduce processing time. The processor can be configured to reject images that are of inadequate quality.
    The handheld device can be configured to control one or more of the device's brightness, contrast, gain, color balance and flash adjustments during capture to achieve an optimized image for subsequent processing. The processor can be adapted to apply corrections for brightness, contrast, sharpness and color balance after image acquisition.
    The processor can be adapted to convert a color image to a grayscale image or a black and white image.
    The handheld device can be configured to compare two images and output the test result at least partially based on the comparison.
    The handheld device can be configured to capture a plurality of images, each using a different exposure setting. The handheld device can be configured to combine a plurality of images.
    The processor can be adapted to correct the image for any rotational misalignment or distortion.
    The processor can be adapted to determine a degree of error associated with any rotational misalignment or distortion to correct the image.
    The degree of error can be determined by comparing the image features with a known geometry of the receptacle. Alternatively or additionally, the handheld device may include one or more orientation sensors such as accelerometers and the degree of error is determined based on the signal from the orientation sensors.
    The tester can be configured to prevent image capture when the degree of error is greater than a predetermined value. The tester can be configured to prevent image capture when the signal from the orientation sensors matches an orientation that is outside a predetermined range or value.
    The processor can be adapted to sum one or more pixel values in an identified region of interest.
    The processor can be adapted to identify test line positions. The processor can be adapted to perform peak search within the region of interest.
    The processor can be adapted to quantify test size or control lines that use a peak height or peak area. The quantified size can be used to determine a concentration measurement for the test. The processor can be adapted to determine a control peak. A test peak can be determined by comparing it to the control peak.
    The handheld device can be configured to transmit and/or store associated data along with the data. Associated data may comprise one or more of: an image capture date or time, geolocation data for the assay performed, image capture device settings, reagent data, and user generated data.
    Reagent data can comprise one or more of: a lot number, an expiration date, and calibration information. Reagent data can be provided in the receptacle. Reagent data may be presented in the form of a package or a label. Reagent data can be provided in the form of written information that is readable through the handheld. The handheld device can be adapted to interpret written information using optical character recognition or the like. Alternatively, the reagent data can be in the form of a one- or two-dimensional barcode.
    User-generated data may comprise spreadsheet or database data, image or sound files, typed or written text, or the like.
    The handheld device can be adapted to display instructions or directions to the user for performing the test and/or interpreting the test result. The handheld device can be adapted to provide substantially real-time response to the user during image capture. The answer can be related to one or more of the position, orientation and settings used. The handheld device can be configured to automatically capture the image.
    Displayed instructions or guidance may comprise pre-processing steps, incubation intervals, and the like. The portable device may include a countdown timer to determine the time of test durations.
    The handheld device can be configured to read reagent data such as an incubation time. The handheld device can only be configured to allow the user to capture the image after the test, once the incubation time has elapsed.
    The handheld can be configured to display a template or guide overlay that shows the reagent outline and/or one or more regions of interest. The answer may be in the form of: a change in appearance, such as guide color or template overlay, or an audio or tactile indication that an image has been acquired.
    The processor can be configured to use contrasting colors or distinct objects to process data captured by the image capture device and output the test result. Contrasting colors or distinct objects can be provided by the receptacle.
    Embodiments of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Figure 1 is a perspective view of a testing apparatus according to the invention, Figure 2 is a view of a (a) sandwich test and a competitive test, Figure 3 is a view of a test with (a) a control line and a test line, (b) a test line but no control line, (c) a plurality of test lines and a control line, all on a single test strip, (d) a plurality of test lines and control lines on separate test strips mounted within a common housing, and Figure 4 is a view of a test with tests (a) presented in "dip stick" format, (b) in which the test strip protrudes beyond the housing in one direction, (c) contained in a housing, the tests contained in a housing, where part or all of the housing is colored to increase image contrast when processed and (d) which tags are included in a housing to facilitate image processing.
    Figure 1 shows a test apparatus for performing an assay. The testing apparatus comprises a receptacle containing a reagent in the form of a test strip and a portable device in the form of a mobile phone 1 having a processor and an image capture device or camera 3.
    The mobile phone 1 can be used to capture and process images and then share the resulting data over telecommunications networks such as the internet. It is, therefore, possible to avoid the requirement for a specialist, order-to-order hardware and use of a readily available mobile and small consumer electronic device such as the mobile phone 1 to record and quantify the results obtained in the style chemical product. test strip and immunoassay devices 2.
    In addition, the device has the ability to store the time, geolocation (eg GPS coordinates) and any other information obtained from the extended functionality of the device 1 and associated peripherals in addition to any visually captured data (with the camera 3), orally (as a sound file) or through written or typed notes. Such information can be stored on device 1 for later retrieval, sent automatically or at the request of users to a Laboratory Information Management System (LIMS), or other centralized database.
    In addition to measuring the response of test 4, device 1's image capture functionality can be used to capture and process other information about test 2, such as lot numbers, expiration dates, or even calibration information displayed on the test itself. test or, for example, on test packaging or labels 5. Such information may be provided in the form of written information (interpreted through optical character recognition) or in the form of standard or modified one- or two-dimensional bar codes.
    This invention differs from known methods in that it uses only the embedded hardware of device 1, which does not require external hardware or modifications to the electronic components or infrastructure of device 1. An important development is the inclusion of processing on device 1, which allows device 1 to be operated alone without internet or phone connection, if desired, and also respond "in real time" to the user about position, orientation and image quality so that the operator can quickly capture an image of adequate quality before the window of opportunity for a valid test result may have elapsed. Processing directly on the device allows maximum image quality to be used. "Pre-filters" can be applied to discard irrelevant portions of the image so that processing time is minimized.
    When the dynamic range of the resulting image is inadequate for the detection limit, or when limitations in exposure settings in the lighting medium force the dynamic range to be too poor, it may be desirable to capture multiple images at ex settings. - different positions and then combine these into a single higher dynamic range “virtual” image by using appropriate algorithms to reorient the images between frames and to discard unwanted or low-value data.
    Device 1 functionality can also be used to display user advice or guidance based on test results, either from a knowledge base stored on device 1 or by directing the user to the appropriate internet sources.
    Additionally, data can be processed to observe trends or patterns in measurements.
    The image processing software on the device is provided as commonly described as an “application”. Ancillary software can be integrated with image processing to facilitate use, record keeping or storage of results. Colorimetric test results can be quantified and/or recorded using a mobile phone 1 by simply providing the image processing software.
    Similar principles can be applied to many different test formats. They are described below in two broad groups, 1 the tests in which the sample flows over the test, which forms a color change in a specific localized region of the test 2 and 2 the tests in which the color change 24 is not located and is then compared to a graph or a reference scale 25. APPLICATIONS FOR SIDE FLOW TESTING
    Lateral Flow Tests and their fabrication are well known to those skilled in the art. Assays are commercially available for a wide range of substances for small species from chemicals to microbiological contaminants. The principles, fabrication and operation of such devices have been previously described in detail. The technology is applicable to any assay based on the interaction of a ligand with an analyte, which results in a temporary or permanent change of color, tone or hue with a specific spatial region of a test, resulting from flow through the length of a strip of test directed by capillary action. The detection method can be based on interactions involving, an antibody, an antigen, a hapten, a protein, a polynucleotide (which includes, but is not restricted to DNA and RNA), a cell, a fragment of cell, a bacterium, a spore, a virus, a prion or a virion.
    The use of a camera 1 equipped mobile phone to quantify the results of such tests is applicable to a wide range of lateral flow tests, which include, but are not restricted to: - both sandwich tests 6 and competitive tests 7, - tests with one control line and one test line 8, tests with one test line but no control line 9, tests with a plurality of test lines and one control line, all on a single strip of test 10, tests with a plurality of test lines and control lines on separate test strips mounted within a common housing 11, - tests using colored particles as binding label 12, - tests using nanoparticles as colored label 12, assays using nanoparticles in the size range 1 to 1,000 nm, assays using nanoparticles in the size range 2 to 100 nm, assays using nanoparticles in the size range 10 to 80 nm, assays using metallic nanoparticles that substantially comprises one or more elements that exhibit localized surface plasmonic resonance, such elements include: copper, silver, aluminum, gold, platinum, palladium, chromium, niobium, rhodium and iridium, - assays using colored polymeric particles as binding label 12, tests in which the polymeric particles are mainly composed of latex, tests in which the polymeric particles are mainly composed of polystyrene, tests in which the polymeric particles are mainly composed of a polyolefin, tests in which the polymeric particles are mainly composed of nylon, - tests in which the color is formed directly or indirectly by the interaction of an enzyme with a substrate, - tests in which the colored binding label 12 is substantially one of the following colors: red, blue, yellow, black or combinations thereof , - tests presented in "dip stick" format (ie without any plastic housing 13 or in which the test strip protrudes beyond the housing in one direction 14), tests contained in a housing 2, tests contained in a housing, where the housing is mainly formed of plastic, tests contained in a housing, where the housing is made substantially of cardboard or paper, tests in which part or all of the housing is produced from a transparent material through which the result needs to be seen, - tests contained in a housing, in which part or all of the housing is colored 15 to increasing the contrast of the image when subsequently processed, tests in which the indications 16 are included in a housing to facilitate image processing.
    After adding a sample to a lateral flow test and allowing the test to run for a predetermined time, the test will typically form one or more distinct lines 17 perpendicular to the capillary flow direction along with the test. Other patterns, such as stitches, are also used in some tests. Most commercial use lateral flow assays consist of at least a test line 4 and a control line 18. However, the invention is sufficiently adaptable that it can be modified to another test format or format.
    The optical density (or color intensity) of test line 4 is related to the level of analyte 19 in the sample. In a sandwich assay, optical density can be linearly proportional to analyte concentration over a certain range. In a competitive assay, optical density may be inversely proportional to analyte concentration.
    Optical density or some other color intensity measurement can be made through the use of an image captured on readily available cameras 3, such as those found embedded in mobile phones, tablet-type PCs, netbook-type computers, laptop computers and other devices. consumer electronics 1. Image 20 can be processed through software included with device 1. The exact steps and sequence of steps required to analyze an image 20 from a particular test may vary, but in general are prone. to include some or all of the following: (1) identify the location and orientation 21 of the test strip/housing 2 in image 20. (2) identify the location of the resulting region 22 within the test strip/housing. (3) identify the presence/absence of control line 18. (4) identify the expected location of test line 4. (5) identify the magnitude of test line 4, if any. (6) compare the magnitude of test line 4 with the magnitude of control line 18 or some other reference point to calculate the test result on a real or arbitrary scale.
    The software can then store, display or distribute this data through the use of other functions and the connectivity built into the consumer device. The software may attach timestamps, user identities, geographic locations, or other user-defined information to the data for further analysis and quality control.
    The software can upload data to a central database such as a Laboratory Information Management System or other data repositories. The software or database can be used to trigger certain actions, such as responding to a problem identified through an individual measurement or trend, alerting a user or other interested parties to a result or trend or providing content ( via the web, email or other communication systems that include offline communication) relevant to the test results obtained. Targeted information may include marketing, advertising or promotional material both now and at some future date based on the outcome of the results.
    The software can integrate with other services on the device or over the internet such as calendars to provide reminders of regular testing patterns as required.
    The software can apply correction or filters to an image to remove electronic or optical noise from the image. Many standard noise filters are known to those skilled in the art. Simple noise filters can simply involve the convolution of two matrices.
    The software can control device brightness, contrast, gain, color balance and flash adjustments during capture to achieve an optimized image for subsequent processing. The software can capture a "non-optimal" image and apply corrections to brightness, contrast, sharpness and color balance after image acquisition.
    The software can discard areas of the image that do not contain useful data to facilitate faster processing on the device.
    The software can convert a color image to a grayscale image or some other form of representation to facilitate faster processing on the device.
    The software can convert part or all of the image into a black and white i-image (binary array) to speed up processing, for example in determining the location and edges of the region of interest 22. By identifying the relevant portions of the image and calculating any necessary rotation correction the software can then revert to part or all of the original image file for more detailed processing.
    The software can automatically reject images that are of inadequate quality to produce useful results.
    The software can guide the user during image capture to assist the user in capturing a proper image, for example, correctly orienting the device, correctly focusing the device, and getting adequate lighting. A possible solution to simplify the processing is to display a template or guide overlay that shows the outline of the test strip and/or the region of interest (or simply a rectangle of correct proportions). If the image can be processed to fit in near real-time, then the correct orientation can be indicated on the screen and image capture started automatically. An option for this interactive response is to change the model's color, guide marks or overlay, for example, changing from red (no suitable image) to green (suitable image), thereby avoiding additional “clumping” on the display. Similarly, the software can provide the user with an audio or tactile indication that an image has been acquired, for example, by playing a simulated “camera shutter sound”, a simple beep or activating a vibrating alert built into the device.
    The software can also provide the user with information about the use and operation of the test, eg pre-processing steps, incubation intervals, etc. The software can even force the user to allow full incubation time by capturing images before and after testing.
    The software may include a countdown timer to time test durations.
    Contrasting colors, for example, in the test strip housing and distinct housing formats can simplify image processing. When there is no housing or the housing is a similar color to the test strip, it may be preferable to place the test strip against a contrasting background during image capture.
    The software can capture information about, for example, the form or test strip that is used, its expiration date, or the batch-to-batch variation in text sensitivity based on data printed on the strip or packaging, of a code of one- or two-dimensional bar 26 on the device or of some form of reference color printed on the strip. Such data can be stored with eventual test results. Similar processes can be used to identify physical locations (eg with bar code marked features) or patients or test users to speed up and reduce data entry errors. Barcode capture occurs simultaneously with the test strip image capture or immediately before or after.
    The test strip or housing can be located in the image by scanning from top to bottom and left to right for an object of approximately the correct proportions. The test strip or housing proportions will normally be well defined and highly repeatable and thus pre-loaded into the device. Features or patterns on the housing or test strip can then be used to verify recognition.
    The scale of the image can then be estimated by comparing the known dimensions of the test strip or housing to the observed characteristics of the test.
    Device orientation can be determined from any asymmetry in the test strip, housing shape, print or patterns in the housing or test strip, or it may be imperative to the user when capturing the image.
    Standard image processing algorithms can be applied to correct any rotational misalignment or distortion. Rotational misalignment can be corrected more simply by examining a region of the image that should have a straight edge of contrast (for example, the edge of a housing) and which determines the disorientation of the horizontal. The entire image can then be rotated using one of several established algorithms that will be known to those skilled in the art. For example, rotation by offset or rotation by area mapping. Rotation by shift is approximately sixty times faster than rotation by area mapping, but it can cause distortion in the image.
    Correcting images for tilt, perspective, distortion, etc. requires that the degree of error be known or estimated. This can be achieved by measuring distinct contours in reference to the geometry of the test housing. Alternatively or additionally, sensors built into the device can provide this information. For example, considering that the test substrate is horizontal (for example, on a table or bench), accelerometers inside a phone can indicate the degree of disorientation of the device from the same plane, thereby facilitating software fix. Likewise, these accelerometers could be used to prevent image capture if the device is not oriented within an acceptable range of angles.
    With the test strip or housing boundaries defined by criteria such as contrast, the region of interest 22 containing the result can be identified from the geometric properties of the test or the particular housing.
    Image information obtained from near the contours of the test strip or resulting window can be discarded as artifacts are more commonly observed in these areas.
    By summing the pixel values in the columns within the region of interest, it is possible to significantly reduce noise in the data and obtain more robust results.
    When a test strip is contained in a housing, there is usually a positioning error, particularly along the geometric axis of the flow. The exact positions of the test and control lines may therefore not be precisely controlled in relation to the housing edges.
    Line positions can be found through "peak search" within the region of interest. A peak will be characterized by having a series of successive pixels with increasing values. By specifying limits on the expected position of peaks, minimum "intensity threshold" for peaks and peak width (eg by defining several successive pixels that need to increase) - it is possible to filter out "noise" or artifacts that are not real spikes. Control lines 18 in lateral flow tests will normally form characteristic strong peaks.
    Test lines in lateral flow tests can be found within an expected distance from the control line. Depending on the manufacturing process used, line separation can be tightly controlled. It will be possible to predict the line position from the overall scale of the image, using the known dimensions of the test strip or housing as a dimensional reference.
    The size of test and control lines can be quantified as either the peak height 27 or the peak area 28 (which both may or may not be measured against some corrected baseline 29). These values can be used directly to compute a concentration measurement for testing or can be subjected to further analysis.
    Lot-to-lot, test-to-test, sample-to-sample and i-illumination variations can, at least partially, be eliminated by measuring the relative size of the test peak compared to the control peak rather than the absolute values. For a system that uses an irrelevant control, the answer, R, can simply be thought of as: R = Test peak/Control peak.
    For a system that does not have an irrelevant control, and where, therefore, the control line intensity decreases as the test line intensity increases, the response can be considered as: R = Test peak/(Test peak + Control peak)
    From the measured response, an estimate of the concentration of analyte 19 can be obtained, for example, by comparing a known calibration curve, referring to a lookup or computation table that uses user-supplied parameters, or optically determining from the test strip, housing or packaging. EXAMPLE 1: QUANTIFICATION OF A SIDE FLOW DEVICE
    Standard methods for detecting Legionella bacteria (the causative agent of Legionnaires' Disease) in water are typically slow and laboratory-based. It has been previously shown that Legi-onella pneumophila serogroup 1 antigen can be detected in water through the use of a lateral flow immunoassay, which is simple enough to be performed in the field.
    The test is performed by adding a water sample to the test strip. The water first comes into contact with a fabric swab 29 impregnated with chemicals to adjust the pH and other properties of the sample, the sample is then disposed in a second swab 30 through capillary action. The second dressing is impregnated with antibody-coated gold nanoparticles (colored in red) specific for Legionella pneumophila serogroup 1. The second dressing is in contact with a nitrocellulose membrane that has antibodies bound in two narrow bands perpendicular to the direction of capillary flow. The first antibody band 4 is specific for Legionella bacteria, while the second is created against an irrelevant control (ie, a material that does not expect to be in the sample) attached to some of the gold particles 12. A large pad. absorbent 31 in contact with the nitrocellulose yarn atomizes water away from the nitrocellulose in order to maintain capillary flow.
    In addition to the water containing Legionella 19 antigen in the sample, the antigen binds to the 12 gold nanoparticles and then becomes sandwiched 6 between the antibody on the test strip and the 12 colored gold particles, which form a colored line of red to pink through the test. The irrelevant control particles bind as a second row 18 through the test, which acts as a control.
    The antigen level can be quantified by capturing an image 20, which identifies the region of interest 22 and processing that image through several steps to submit the relative area of the test line to the control line. In comparison to a known reference curve the approximate concentration of antigen can be estimated. APPLICATION FOR CHEMICAL/BIOCHEMICAL COLORIMETRIC TESTS
    In contrast to Lateral Flow Assays, where the color change appears at a specific location in the test, typically in chemistry/biochemistry or all colorimetric assays, the test strip 23 exposed to the sample will change color on exposure to the desired analyte . In some cases a smaller sample pad 24 will change color, while the rest of the device is left unchanged. Perhaps the most commonly known example of such tests is "pH paper," where the pH of a sample results in a color change that indicates the pH of the sample. However, such colorimetric indicator tests are used across a wide range of samples for a wide range of different markets, eg water quality testing (parameters include but are not restricted to pH, chlorine, alkalinity, iron, hardness , silica, nitrates, nitrites are all routinely measured using such approaches), medical/clinical diagnoses (parameters include but are not restricted to proteins, ketones, glucose and blood in urine), analysis soil (eg parameters include but are not restricted to pH, nutrients N/P/K) and food hygiene and processing (parameters include but are not restricted to detection of NAD/H NADP/H , quaternary ammonium and oil quality disinfectants).
    A test strip can contain 32 or more 33 tests in a single test, which allows multiple chemical tests to be performed on a single device, or different test ranges to be covered with a single device.
    The test result is usually obtained by visually comparing the result to a reference chart 25, often printed or included in the package 34, 35.
    A camera 1-equipped consumer electronic device can be used to quantify the results of such tests by capturing the test strip image and processing the image's color/hue information. In order to correct for ambient light variations, it can be achieved more easily if the reference scale 25 is also captured in the same image. The software can then identify the correct portions of the image, along with any scale/label information 37 and derive the estimated concentration in the sample by color matching with the reference scale 25 and the exposed or working area of the strip. test 24. Optionally, the software can include a correction for differences in print or surface finishes, which are difficult to match with the naked eye.
    Image processing can be simplified if the test strips and the reference scale are placed on contrasting backgrounds and if any asymmetrical sharpness characteristics 38 are included in the packaging or label of the test and/or the reference scale, such as so that the correct orientation is more easily identified through the software.
    Color hue, or some other measurement of color, optical density, or hue can be made through the use of an image captured on readily available cameras 3, such as those found integrated into mobile phones, tablet PCs, desktop computers. type netbook, laptop and other consumer electronic devices 1. Image 20 can be processed through software included within device 1. The exact steps and sequences of steps required to analyze an image of a particular test may vary, but in general , are likely to include some or all of the following: (1) identifying the location and orientation of the test strip 32 and reference scale 25 in the image. (2) identify the location of the resulting region(s) 24 within the test strip. (3) measure the color or hue of the region of interest 24. (4) measure the color or hue of several points on the reference scale 25. (5) correlate the hue of the region of interest with the scale obtained from the reference scale.
    The software may then store, display or distribute this data through the use of other functions and connectivity built into the consumer's device. The software may attach timestamps, user identities, geographic locations, or other user-defined information to the data for further analysis and quality control.
    The software can upload data to a central database such as a Laboratory Information Management System or other data repositories. The software or database can be used to trigger certain actions, such as responding to an identified problem through an individual measurement or trend, alerting a user or other interested parties to a result or trend, or providing content (through web, email, or other communication systems that include offline communication) relevant to the test results obtained. Targeted information may include marketing, advertising or promotional material, both now and at some future date based on the outcome of the results.
    The software can integrate with other services on the device or over the internet, such as calendars to provide reminders of regular testing patterns as required.
    The software can apply correction or filters to an image to remove electronic or optical noise from the image. Many standard noise filters are known to those skilled in the art. Simple noise filters can simply involve the convolution of two matrices.
    The software can control device brightness, contrast, gain, color balance and flash adjustments during capture to achieve an optimized image for subsequent processing.
    The software can discard areas of the image that do not contain useful data to facilitate faster processing on the device.
    The software can convert a color image to a grayscale image, or some other form of representation to facilitate faster processing on the device.
    The software can convert part or all of the image into a black and white i-image (binary array) to speed up processing, for example in determining the location and edges of the region of interest. Having identified the relevant portions of the image and calculated any necessary rotation correction, the software can then revert to part or all of the original image file for more detailed processing.
    The software can automatically reject images that are of inadequate quality to produce useful results.
    The software can guide the user during image capture to assist the user in capturing a proper image, for example, correctly orienting the device, correctly focusing the device, and getting adequate lighting. One possible solution to simplify processing is to display a guide or template overlay that shows the test strip outline and/or the region of interest. If the image can be processed to fit in near real time, then the correct orientation can be indicated on the screen and image capture started automatically. One option for this interactive response is to change the model's color, outline, or guide marks, for example, changing from red (no suitable image) to green (adequate image), thereby avoiding “clumping” additional on the display. Similarly, the software can provide the user with an audio or tactile indication that an image has been acquired, for example by playing a simulated “camera shutter sound”, a simple beep or activating a built-in vibrating alert inside the device.
    The software can also provide the user with information about the use and operation of the test, eg pre-processing steps, incubation intervals, etc. The software can even force the user to allow the full incubation time by capturing images before and after testing.
    The software may include a countdown timer to determine test durations.
    Contrasting colors, for example, in the test strip housing and distinct housing formats can simplify image processing. When there is no housing or the housing is a similar color to the test strip, it may be preferable to place the test strip against a contrasting background during image capture.
    The software can capture information about, for example, the form or test strip that is used, its expiration date, or the batch-to-batch variation in text sensitivity based on data printed on the strip or packaging, of a code of one- or two-dimensional bar 26 on the device. Such data can be stored with eventual test results. Such data can be captured simultaneously with the test image or immediately before or after the test image. Similar processes can be used to identify physical locations (eg with bar code marked features) or test patients or users to speed up and reduce data entry errors.
    The test strip or housing can be located in the image by sweeping from top to bottom and left to right for an object of approximately correct proportions. The test strip or housing proportions will normally be well defined and highly repeatable and thus pre-loaded into the device. The features or patterns on the housing or on the test strip can then be used to check recognition. The reference scale is likely to form a highly repeatable image format/shape image for use in image recognition.
    The scale of the image can then be estimated by comparing the known dimensions of the test strip or reference scale to the observed characteristics of the test.
    Device orientation can be determined from any asymmetry in the test strip, housing shape, print or patterns 38 on the test strip or package 34.35 or reference scale 25, included in the image, or it may be imperative to the user when capturing the image.
    Standard image processing algorithms can be applied to correct any rotational misalignment or distortion. Rotational misalignment can be corrected more simply by examining a region of the image that should have a straight edge of contrast (for example, the edge of a housing) and which determines the disorientation of the horizontal. The entire image can then be rotated using one of several established algorithms that will be known to those skilled in the art. For example, rotation by offset or rotation by area mapping. Rotation by shift is approximately sixty times faster than rotation by area mapping, but it can cause distortion in the image.
    With these test strip or housing boundaries defined by criteria such as contrast, the region of interest containing the result can be identified from the geometric properties of the test or the particular housing.
    Image information obtained from near the contours of the test strip or resulting window can be discarded as artifacts are more commonly observed in these areas.
    Averaging across the region of interest to significantly reduce noise in the data and obtain more robust results. Some measurement of error can be obtained by averaging across multiple "subzones" within the region of interest 24.
    In order to process the region of interest into one or more numerical values that will enable comparison or matching with the reference scale, it can be useful for the software to convert the pure pixel data into its red, green and blue components of both. the region of interest and the reference scale. With very simple color-based tests, this might be enough. When the test is likely to produce a variety of colors or when changes are subtle, it may be preferable to first convert the value to a scale more directly related to human color perception, such as the Munsell System, the CIE or Hunter systems. LAB. Since there is no absolute scale with which to do true comparison conversion for these systems it is unlikely to be easy, but comparing to a system based on such a representation and doing the same with the reference scale 25 in the same image, an estimate of where the value falls within the range may be possible.
    Although described above as test “strips” that use diffuse reflected light, the general approach is applicable to other colorimetric assays, where these assays may be measuring diffuse reflected light or transmitted light and may include vials, test tubes or crucibles. which contains liquids which are themselves colored, or which induce a color change in the container/vessel which is represented by the consumer electronic device 1. Similarly, while used in a diffuse color reflectance measurement of surfaces or materials can be matched with a reference chart, for other scientific or testing purposes that use the same general approach.
    Although specific embodiments of the present invention have been described above, it will be appreciated that deviations from the described embodiments may still be within the scope of the present invention. For example, while the present specification describes use with a usually solid substrate, it will be appreciated that this approach could easily be adapted to measure liquid samples contained in a vial, cell or other container. When the length of the path through the container is fixed and when it is placed against a suitable background (such as a white piece of paper), the color in the cell can be observed and compared to the reference samples. Likewise, formats such as 96- or 384-well plates, in which numerous experiments are performed in parallel, can be analyzed using this type of approach. Such a test may include assays for chemicals (eg, test for free chlorine that uses pink color formed in reaction with diethyl-p-phenylenediamine) or an immunoassay (eg, green color formed in the presence of horseradish peroxidase in enzyme-linked immunosorbent assays (ELISAs)).
    权利要求:
    Claims (15)
    [0001]
    1. A testing apparatus for performing an assay, the testing apparatus comprising: a receptacle (2) containing a reagent, wherein the reagent is reactive to an applied test sample by developing a color variation or pattern; a portable device (1) comprising a processor and an image capture device (3), wherein the processor is configured to process data captured by the image capture device (3) and to output a test result to the sample of applied test; characterized by the fact that the processor is adapted to correct the image (20) for any rotational misalignment or asymmetry; or the tester is configured to prevent image capture when the degree of error associated with any rotational misalignment or asymmetry for image correction is greater than a predetermined value.
    [0002]
    2. Apparatus according to claim 1, characterized in that the portable device (1) comprises a mobile phone, a PDA, a digital camera or laptop.
    [0003]
    3. Apparatus according to claim 1 or 2, characterized in that the test apparatus is configured to perform an immunoassay, for example a lateral flow immunoassay.
    [0004]
    4. Apparatus according to claim 3, characterized in that the test apparatus is configured to detect Legionella bacteria.
    [0005]
    5. Apparatus according to any one of claims 1 to 4, characterized in that the processor is configured to measure the variation in color or pattern developed.
    [0006]
    6. Apparatus according to any one of claims 1 to 5, characterized in that the test apparatus includes a remote processing device to measure the developed color or pattern variation and calculate the test result, and optionally in which: - the portable device (1) is configured to transmit the data to the remote processing device and to receive and output the calculated test result; - the remote processing device is adapted to store one or both of the data and the test result, and suitably where the remote processing device is adapted to store one or both of the data and the test result, suitably where the portable device (1) or the remote processing device is configured to process data and test result from a plurality of assays or portable devices (1) to calculate one or more group values or parameters.
    [0007]
    7. Apparatus according to any one of claims 1 to 6, characterized in that the portable device (1) is configured to modify the image in order to optimize the color representation of the image, for example by applying correction and / or filtering an image (20) to remove electronic or optical noise from the image.
    [0008]
    8. Apparatus according to any one of claims 1 to 7, characterized in that the portable device (1) is configured to discard irrelevant portions of the image (20) in order to reduce processing time, or in which the processor is set to reject images (20) that are of inadequate quality.
    [0009]
    9. Apparatus according to any one of claims 1 to 8, characterized in that the portable device is configured to control one or more of the device's brightness, contrast, gain, color balance and flash settings during the capture of in order to achieve an optimized image (20) for subsequent processing, for example, in which: the processor is adapted to apply corrections for brightness, contrast, sharpness and color balance after image acquisition; or the processor is adapted to convert a color image to a grayscale image or a black and white image.
    [0010]
    10. Apparatus according to any one of claims 1 to 9, characterized in that the portable device is configured to compare two images (20) and output the test result at least partially based on the comparison, or in that the device The handheld is configured to capture a plurality of images (20), each using a different exposure setting, and optionally to combine the plurality of images.
    [0011]
    11. Apparatus according to any one of claims 1 to 10, characterized in that the processor is adapted to determine a degree of error associated with any rotational misalignment or asymmetry to correct the image (20), appropriately, in which degree error is determined by comparing image aspects with a known geometry of the receptacle (2); or wherein the portable device (1) includes one or more orientation sensors and the degree of error is determined based on the signal from the orientation sensors.
    [0012]
    12. Apparatus according to claim 11, characterized in that the test apparatus is configured to prevent image capture when the signal from the orientation sensors corresponds to an orientation that is outside a predetermined range or value.
    [0013]
    13. Apparatus according to any one of claims 1 to 12, characterized in that the processor is adapted to sum one or more pixel values in an identified region of interest (22) or identify the positions of test lines (4 ), and optionally wherein the processor is adapted to perform epic search within the region of interest (22), in each case suitably the processor is adapted to quantify the test size (4) or the control lines (18) using a peak height or peak area, and optionally the quantified size is used to determine a concentration measurement for the test.
    [0014]
    14. Apparatus according to any one of claims 1 to 13, characterized in that the portable device (1) is configured to transmit and/or store associated data together with the data, and optionally wherein the associated data comprises one or more from: an image capture data or time; geolocation data for the test performed; image capture device adjustments; reagent data; and user-generated data; and suitably wherein the reagent data comprises one or more of: a lot number; an expiration date; and calibration information, wherein reagent data is suitably provided on the receptacle.
    [0015]
    15. Apparatus according to any one of claims 1 to 14, characterized in that the portable device (1) is configured to display a guide or template overlay showing the contour of the reagent and/or one or more regions of interest; and/or 15 wherein the processor is configured to use contrasting colors or distinct objects to process data captured by the image capture device and to output the test result, optionally wherein contrasting colors or distinct objects are provided by the receptacle.
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    同族专利:
    公开号 | 公开日
    GB201105474D0|2011-05-18|
    EP2646809B1|2018-08-29|
    US20180196037A1|2018-07-12|
    US20140154789A1|2014-06-05|
    JP2014514547A|2014-06-19|
    WO2012131386A1|2012-10-04|
    CN103649731B|2016-04-20|
    BR112013025223A2|2020-10-20|
    DK2646809T3|2018-12-10|
    PT2646809T|2018-11-27|
    EP3470825A1|2019-04-17|
    ES2696600T3|2019-01-17|
    JP2017215337A|2017-12-07|
    JP6480988B2|2019-03-13|
    RU2013148400A|2015-05-10|
    CA2857424A1|2012-10-04|
    KR102069752B1|2020-01-23|
    CA2857424C|2020-08-25|
    KR20190026943A|2019-03-13|
    US9903857B2|2018-02-27|
    KR101954783B1|2019-03-06|
    KR20140074256A|2014-06-17|
    RU2582268C2|2016-04-20|
    EP2646809A1|2013-10-09|
    CN103649731A|2014-03-19|
    JP6189286B2|2017-08-30|
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    法律状态:
    2020-11-03| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|
    2020-12-15| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|
    2021-06-22| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|
    2021-09-08| B16A| Patent or certificate of addition of invention granted [chapter 16.1 patent gazette]|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 30/03/2012, OBSERVADAS AS CONDICOES LEGAIS. |
    优先权:
    申请号 | 申请日 | 专利标题
    GBGB1105474.9A|GB201105474D0|2011-03-31|2011-03-31|Testing apparatus|
    GB1105474.9|2011-03-31|
    PCT/GB2012/050717|WO2012131386A1|2011-03-31|2012-03-30|Testing apparatus|
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