Method and device for determining the concentration of at least one analyte in a body fluid - Patents.com

Abstract

Disclosed are a method and an apparatus for determining the concentration of at least one analyte in a body fluid, a determination method for determining a color expectation range (132) for assessing the validity of a color value obtained in a color reaction-based analytical measurement, and a measurement method for performing a color reaction-based analytical measurement by using a mobile device (112) having a camera (114) and a processor (130). Further disclosed is a determination system (110) for determining a color expectation range (132) for assessing the validity of a color value obtained in a color reaction-based analytical measurement. The determination system comprises a training set (116) of optical test strips having a reagent test area (120). At least two of the training optical test strips are good optical test strips (122) and at least two are bad optical test strips (124).

Description

[Technical field]

[0001] The present invention relates to a determination method for determining a color expectation range for evaluating the validity of color values ​​obtained in an analytical measurement based on a color reaction. Furthermore, the present invention relates to a measurement method for performing an analytical measurement. Furthermore, the present invention relates to a determination system and a mobile device, as well as a computer program, a computer readable storage medium, and a kit. The method, the system, the mobile device, the computer program, the computer readable storage medium, and the kit may be used in particular in medical diagnostics for quantitatively or qualitatively detecting one or more analytes in one or more body fluids, such as for example detecting glucose in blood and / or in interstitial fluid. However, other fields of application of the present invention are also feasible. [Background technology]

[0002] In the field of medical diagnostics, one or more analytes must often be detected in a sample of a body fluid, such as blood, interstitial fluid, urine, saliva, or other types of body fluids. Examples of analytes to be detected are glucose, triglycerides, lactate, cholesterol, or other types of analytes typically present in these body fluids. Depending on the concentration and / or presence of the analyte, appropriate treatments may be selected as required. Without narrowing the scope, the invention may be described in particular with respect to blood glucose measurement. However, it should be noted that the invention may also be used for other types of analytical measurements using test elements.

[0003] Generally, devices and methods known to those skilled in the art utilize test elements and / or strips that contain one or more test chemicals that can perform one or more detectable detection reactions, such as optically detectable detection reactions, in the presence of an analyte to be detected. For the test chemicals contained in the test elements and / or strips, reference may be made, for example, to J. Hoenes et al.: The Technology Behind Glucose Meters: Test Strips, Diabetes Technology & Therapeutics, Volume 10, Supplement 1, 2008, S-10 to S-26. Other types of test chemistries are also possible and may be used to implement the present invention.

[0004] In analytical measurements, especially those based on color reactions, one technical challenge is the evaluation of the color change resulting from the detection reaction. In addition to the use of dedicated analytical devices such as handheld blood glucose meters, the use of commonly available electronic devices such as smartphones and portable computers or other mobile devices has become increasingly common in recent years. Thus, the cameras of these mobile devices can be used to measure the color change of the detection reaction in the test elements and / or test strips. In contrast to measurements in laboratories and measurements performed using dedicated pairings of analytical measurement devices with test elements and / or test strips, various influences must be taken into account when using mobile computing devices such as smartphones. As an example, lighting conditions, positioning, vibrations, electronic defects, or other more or less uncontrollable influences should be taken into account. In general, by utilizing color standards for photometric measurements, procedures can be used that involve mathematically correcting and / or compensating for the results of such influences on the color change.

[0005] US Patent No. 11,112,406 describes a method for providing an immunoassay test result, comprising collecting at least one biologic with a test device, binding the biologic to particles on a binding pad of a test strip to generate an immunocomplex, binding an antigen or antibody of the immunocomplex to an antigen or antibody of a test line, providing a software application stored on a mobile device having a camera, capturing an image of the test device including a color mosaic having at least one color value corresponding to a positive test result, comparing the color value of the image of the test line with the color value of the image of the color mosaic, determining whether the color value of the image of the test line is within a predetermined range of at least one color value of the image of the color mosaic corresponding to a positive test result, and presenting the test result on a viewing screen.

[0006] China Patent No. 104969068 describes a method and apparatus for performing color-based reaction testing of biological materials. The method includes capturing and interpreting digital images of unexposed and then exposed instruments in an automatically calibrated environment. The instruments include a Unique Identification (UID) label, a Reference Color Bar (RCB) that provides a standardized color sample for image color calibration, and several test-specific sequences of Chemical Test Pads (CTPs). The method further includes locating the instruments in the images, extracting the UID, extracting the RCB, and locating multiple CTPs in each image. In addition, the method reduces image noise in the CTP and automatically calibrates the images according to illumination measurements performed on the RCB. In addition, the method determines test results by comparing the colors of the CTP images to those of a Manufacturer Interpretation Color Chart (MICC). The method displays these results in a graphical or quantified mode.

[0007] EP 2 916 117 describes color quantification of chemical test pads and titration of analytes that can be performed under various lighting conditions. In one embodiment, the lighting conditions at the time of digital image capture are estimated and used to select a set of reference colors, and the quantified colors from the set of reference colors are compared and the titration is determined. In another embodiment, multiple comparisons under different lighting conditions are made and the result with the highest confidence level is selected to determine the titration.

[0008] US Patent Publication No. 2015 / 0247874 describes a method for detecting the presence of an analyte in a sample. The method includes selecting an aptamer selective for the analyte and binding the aptamer to nanoparticles. The free nanoparticles are perceived as a first color and the aggregated state is perceived as a second color. The sample is introduced to the aptamer bound to the nanoparticles to promote aggregation of the nanoparticles. The colorimetric change is analyzed and the aggregated state of the nanoparticles is achieved in the presence of the analyte in the sample.

[0009] US Patent Application Publication No. 2011 / 076695 describes an immunoassay analysis device that can distinguish between normal color development due to specific immune reaction and abnormal color development due to causes other than specific immune reaction in a measurement area of ​​a sample analysis tool. The immunoassay analysis device includes an optical detection unit and a determination unit. The optical detection unit includes an optical signal measurement unit for measuring optical signals at each of two or more different wavelengths including a main wavelength for detecting color changes due to specific immune reaction and sub-wavelengths other than the main wavelength. The determination unit includes a discrimination unit for comparing the optical signals at the two or more different wavelengths and discriminating between color changes due to specific immune reaction and color changes due to causes other than specific immune reaction based on a predetermined comparison criterion.

[0010] US Patent Application Publication No. 2020 / 386672 describes a calibration method for calibrating a camera for detecting an analyte in a sample. A plurality of different color coordinate systems and a set of test samples are provided. The test samples are applied to a test element having a test area for generating an optically detectable response. An image of the colored test area is acquired using a camera, and color coordinates of the image are generated. The generated color coordinates are converted to a set of measured densities using a set of encoding functions. The set of measured densities is compared to known densities of the test sample, and a best matching color coordinate system of the plurality of color coordinate systems is determined. A best matching encoding function of the plurality of encoding functions is also determined.

[0011] US 2017 / 073728 describes an analytical device for detecting at least one analyte in a sample, in which in the measurement of the analyte at least an electrical or optical property of at least one test chemical of a test element that may be altered by the presence of the analyte is recorded, and the analytical device may also perform at least one quality measurement on the at least one test chemical, such as a recorded intrinsic luminescence, from which a conclusion is drawn about the quality of the test chemical and thus the test element. A method for detecting at least one analyte in a sample including a quality measurement of at least one test chemical of a test strip is also disclosed.

[0012] Despite the advantages achieved by known methods and devices, some technical challenges still exist. In particular, user-dependent effects such as incorrect handling and / or improper storage of the test elements and / or test strips, or other more or less uncontrollable user-dependent handling errors, can result in undetected color changes. Such undetected color changes can lead to inaccurate analytical measurements when determining the concentration of an analyte based on a color reaction. Problem to be solved

[0013] It would therefore be desirable to provide methods and apparatus that at least partially address the above-mentioned technical problems, and in particular, that allow for detection of color changes caused by mishandling and / or improper handling by a user. Summary of the Invention

[0014] This problem is addressed by a determination method for determining a color expectation range for evaluating the validity of color values ​​obtained in an analytical measurement based on a color reaction, and a measurement method for performing the analytical measurement.Furthermore, it is addressed by a determination system, a mobile device, a computer program, a computer readable storage medium and a kit having the features of the independent claims.Advantageous embodiments, which may be realized alone or in any combination, are listed in the dependent claims as well as in the entire specification.

[0015] When used below, the terms "having", "comprises" or "includes" or any grammatical variants thereof are used in a non-exclusive manner. These terms may therefore refer both to the situation where, apart from the features introduced by these terms, no further features are present in the entity described in this context, and to the situation where one or more further features are present. As an example, the expressions "A has B", "A comprises B" and "A includes B" may refer both to the situation where no other elements are present in A apart from B (i.e., the situation where A is exclusively composed of B), and to the situation where, apart from B, one or more further elements are present in entity A, such as element C, elements C and D, or even further elements.

[0016] Furthermore, it should be noted that the terms "at least one" or "one or more" or similar expressions indicating that a feature or element may be present more than once are typically used only once when introducing each feature or element. In the following, in most cases, when referring to each feature or element, the expressions "at least one" or "one or more" will not be repeated, despite the fact that each feature or element may be present more than once.

[0017] Furthermore, when used hereinafter, the terms "preferably", "more preferably", "particularly", "more particularly", "particularly", "more particularly" or similar terms are used with optional features without limiting the possibilities of alternatives. Features introduced by these terms are therefore optional features and are not intended to limit the scope of the claims in any way. The invention may be implemented by using alternative features, as would be understood by a person skilled in the art. Similarly, features introduced by "in an embodiment of the invention" or similar expressions are intended to be optional features without any limitations regarding alternative embodiments of the invention, without any limitations regarding the scope of the invention, and without any limitations regarding the possibilities of combining the features introduced in such a way with other optional or non-optional features of the invention.

[0018] In a first aspect of the present invention, a determination method is disclosed for determining a color expectation range for evaluating the validity of color values ​​obtained in an analytical measurement based on a color reaction. The determination method includes the following steps, which may be performed in a given order as an example. It should be noted, however, that a different order may generally be possible. Furthermore, it may be possible to perform one or more of the method steps once or repeatedly. Furthermore, two or more method steps may be performed simultaneously or overlapping in time. The determination method may include further method steps that are not listed.

[0019] The method of determination is as follows: a) providing a training set of optical test strips, each optical test strip having a reagent test area; b) providing a training set of bodily fluid samples and applying at least one of the bodily fluid samples to a reagent test area of ​​each optical test strip in the training set of optical test strips; c) acquiring, by at least one mobile device having at least one camera, a training set of images, the training set of images including images of at least a portion of each of the reagent test areas of the training set of optical test strips having a sample of bodily fluid applied thereto, at least two of the optical test strips being good optical test strips and at least two of the optical test strips being bad optical test strips; d) determining, from the images of the training set of images, a training set of color values, the training set of color values ​​including at least one color channel related to the coloring of the reagent test area of ​​each optical test strip of the training set of optical test strips, in particular by using at least one processor, more particularly a processor of a mobile device; e) deriving a color expectation range from the training set of color values ​​for at least one color channel, the color expectation range defining an expected range of color values ​​for a good optical test specimen; Includes.

[0020] As used herein, the term "analytical measurement based on a color reaction" is a broad term and should be given its general and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically, but not limited to, refer to the quantitative and / or qualitative determination of at least one analyte in any sample or aliquot of a body fluid by using a color reaction. For example, the body fluid may include one or more of blood, interstitial fluid, urine, saliva, or other types of body fluid. The result of the determination of the analyte may be, by way of example, the concentration of the analyte and / or the presence or absence of the analyte to be determined. Specifically, by way of example, the analytical measurement may be a blood glucose measurement, and thus the result of the analytical measurement may be, for example, a blood glucose concentration. In particular, an analytical measurement result value, such as the concentration of an analyte in a body fluid, may be determined by the analytical measurement by using a color reaction, such as a color change reaction, depending on the quantitative and / or qualitative presence or absence of the analyte in the body fluid.

[0021] For example, the bodily fluid may include one or more of blood, interstitial fluid, urine, saliva, or other types of bodily fluid. Thus, the term "sample of bodily fluid" may specifically refer to any aliquot or aliquot portion of a biological fluid, either directly or derived from the bodily fluid, such as by one or more pre-processing steps, such as centrifugation. As an example, a sample of bodily fluid may be a droplet of bodily fluid taken from a human body, such as a droplet of blood and / or interstitial fluid produced by puncturing an area of ​​the person's skin, such as with a lancet or needle. A sample of bodily fluid may also be referred to simply as a sample.

[0022] In analytical measurements based on color reactions, optical test strips are used in particular. As used herein, the term "optical test strip" is a broad term and should be given its general and ordinary meaning to those skilled in the art and should not be limited to a specific or special meaning. The term may specifically, but not exclusively, refer to any element or device configured to perform a color change detection reaction. An optical test strip may also be referred to as a test strip or a test element, and all three terms may refer to the same element. An optical test strip may specifically have a reagent test area (also referred to as a test area and / or test field) that includes at least one test chemical for detecting at least one analyte. In particular, the test chemical may be configured to undergo a color change due to the presence of the analyte, e.g., to change color. The color change may depend, for example, on the concentration of the analyte in a sample of bodily fluid. In particular, the reagent test area may have a visually detectable edge, such as a detectable lip and / or border, that distinguishes the reagent test area from the rest of the optical test strip. By way of example, the optical test strip may comprise at least one substrate, such as at least one carrier, on which at least one test field is applied or incorporated. In particular, the optical test strip may further comprise at least one white area, such as a white field, particularly adjacent to the reagent test area, surrounding or encircling the reagent test area. In particular, the contrast between the reagent test area and the white area surrounding the reagent test area may be sufficient to allow detection of the edge and / or border of the reagent test area, particularly visual detection, for example by using image recognition techniques. Additionally or alternatively, the substrate or carrier may itself be or include a white area. By way of example, at least one carrier may be in the form of a paper strip, thereby making the test element a test strip. These test strips are commonly used and available. A test strip may carry a single reagent test area or multiple test areas with the same or different test chemicals.

[0023] As used herein, the term "color value obtained in an analytical measurement based on a color reaction" is a broad term and should be given its general and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically refer to, but is not limited to, a numerical representation of the color of a reagent test area of ​​an optical test strip used in an analytical measurement. In particular, the term "color value" may specifically refer to any numerical representation, such as a numerical representation of the color of a reagent test area of ​​a test strip resulting from a color change detection reaction of a test chemical. In particular, the color numerically indicated by the color value may be correlated to the concentration of the analyte of the sample of bodily fluid applied to the respective optical test strip. Thus, by way of example, the color, and therefore the color value, may be correlated to a blood glucose level and / or blood glucose concentration.

[0024] As used herein, the term "assessing validity" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically, but not limited to, refer to a process of quantitatively and / or qualitatively determining the reliability and / or probability of an element and / or data. As an example, the validity may be assessed by using one or more characteristic parameters and / or characteristics of the element and / or data. These one or more characteristic parameters and / or characteristics may be compared to one or more conditions, either individually or according to a predetermined combination. Thus, as an example, the validity of a color development value may be assessed by using one or more characteristic parameters and / or characteristics of an expected feature, specifically by using a color expectation range as outlined in more detail below. Specifically, the color development value may be compared to a color expectation range, such as one or more comparison values, reference values, or standard values, and the comparison may be a qualitative or quantitative comparison and may result in a binary result, such as "valid" or "invalid" / "not valid". However, in addition, or alternatively, the comparison may yield a quantitative result, such as a number indicating a degree of relevance.

[0025] As used herein, the term "color expectation range" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically refer to a continuous and / or discrete range in which colors of a sub-color space are expected and / or predicted to be located, such as, but not limited to, at least a portion of a possible color space. Thus, by way of example, the color expectation range may be one or more of a two-dimensional or three-dimensional region of a color space that includes at least one of a comparison value, a reference value, and / or a standard value. Thus, the color expectation range may be or include a continuous region and / or corridor that includes at least one expected color value. However, in addition to or instead of this, the color expectation range may be or include a collection of discrete expected colors, for example including discrete comparison values, reference values, and / or standard values. The color expectation range, particularly a two-dimensional or three-dimensional color expectation range, may have any form and / or shape.

[0026] Therefore, as used herein, the term "determination method for determining color expectation range for evaluating the validity of color values ​​obtained in analytical measurements based on color reaction", also referred to simply as "determination method", is a broad term and should be given its general and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. This term may specifically refer to, but is not limited to, a method for determining color expectation range as defined above. In particular, this term may refer to a method for determining and / or confirming at least one range that defines an expected range of color values, particularly for good test strips as further outlined below, i.e., a method for determining and / or confirming such a range as a result.

[0027] As used herein, the term "training set" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a specific or special meaning. The term may specifically refer to, but is not limited to, a plurality of elements having known and / or predetermined differences and / or similarities. In particular, the training set may be used to train a trainable model, such as a model that can be further trained and / or updated based on additional information gleaned from the training set.

[0028] The term "training set of optical test pieces" may specifically, but is not limited to, refer to a plurality of optical test pieces as defined above. In particular, the training set of optical test pieces provided in step a) includes a plurality of optical test pieces, e.g., optical test pieces that are identical in structure and / or design. As an example, for a plurality of optical test pieces included in the training set of optical test pieces, at least one feature and / or characteristic of the one or more optical test pieces may be known and / or predetermined, such that differences between one or more optical test pieces of the training set of optical test pieces may be known and / or predetermined.

[0029] As used herein, the term "faulty optical test strip" is a broad term and should be given its general and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically, but not exclusively, refer to an optical test strip as defined above, in which at least one function of the optical test strip, such as the color change detection reaction of the reagent test area, may be at least partially defective and / or changed beyond an acceptable degree. In particular, a faulty optical test strip may be an optical test strip in which handling and / or storage requirements have been ignored. Thus, by way of example, a faulty optical test strip, in contrast to a good optical test strip, may show a faulty and / or incorrect color, in particular for the color change detection reaction, when used in an analytical measurement, e.g., not resulting in a correct concentration of the analyte. In particular, a faulty optical test strip may be a test strip in which at least one parameter falls outside a predetermined or determinable tolerance range that defines a good optical test strip. The parameter may be an intrinsic or extrinsic parameter. Here, the intrinsic parameters may refer, by way of example, to characteristics of the optical test strip itself, while the extrinsic parameters may refer, by way of example, to parameters representative of the handling of the optical test strip or the use of the optical test strip. Thus, a defective test strip may be defective itself and / or may become defective due to improper handling. Improper handling may refer, by way of example, to storage conditions, and thus the extrinsic parameters may refer, by way of example, to parameters representative of one or more storage conditions, such as storage temperature and / or storage time. Additionally or alternatively, improper handling may refer to the time elapsed since application of at least one sample of at least one bodily fluid to the optical test strip (particularly to at least one reagent test area). As an example, the time elapsed between application of the sample to the reagent test area and acquisition of at least one image including at least a portion of the at least one reagent test area to which the sample was applied may have to be within a predetermined tolerance.Thus, the optical test piece fails as soon as the time falls outside of an acceptable range, such as, for example, as soon as the time elapsed since application of the sample passes the time window during which an acceptable measurement can be made (i.e., at least one image should be acquired).

[0030] Thus, in general, a faulty optical test specimen may be, but is not limited to, an inherently faulty or inherently faulty optical test specimen and / or a test specimen that has been improperly handled, for example, by using the test specimen in an improper manner, such as not capturing the respective images at the proper time, etc. Two fault situations are generally considered herein, and may occur in combination. I. Optical test specimens that are themselves defective, for example due to degradation, poor material properties, the influence of deleterious environmental effects such as humidity, expiration of shelf life, etc.; and / or II. Optical test strips that are defective due to improper handling and / or use, such as being used in a measurement performed with one or more measurement parameters outside at least one acceptable range, capturing at least one image including at least a portion of at least one test area of ​​the optical test strip at an inappropriate time outside of an acceptable range of time, such as an elapsed time between application of a sample and acquisition of an image that is greater than a maximum delay, and / or a disposable optical test strip has already been used.

[0031] As used herein, the term "good optical specimen" is a broad term and should be given its general and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically refer to, but is not limited to, an optical specimen as defined above, where the integrity of the optical specimen is not compromised and / or damaged. In particular, a good optical specimen may be an optical specimen where handling and / or storage requirements have been taken into account. In particular, the term good optical specimen may refer to an optical specimen as defined above, where the optical specimen is not inherently or inherently defective, and / or has been handled correctly, i.e., handled in a proper manner, e.g., each image is captured at the proper time. In particular, a good optical specimen may be or include an optical specimen that has been handled correctly and is not inherently or inherently defective.

[0032] As an example, the color expectation range determined in the determination method may be or may include at least one range that defines an expected range of color values ​​for good optical test strips. In particular, the color expectation range may not include, i.e., skip or exclude, color values ​​for bad optical test strips, i.e., bad measurements, from the training set of color values, as an example. Thus, the color expectation range may skip and / or exclude color values ​​expected for bad optical test strips.

[0033] As used herein, the term "training set of samples of bodily fluid" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically refer to, but is not limited to, a plurality of samples having at least one known and / or predetermined concentration of an analyte, for example determined in a laboratory environment. In particular, the training set of samples of bodily fluid may include a plurality of samples of bodily fluid as defined above, where for one or more of the plurality of samples, a value of the result of a quantitative and / or qualitative analytical measurement, such as the concentration of at least one analyte in the sample, is known. In particular, the number of samples included in the training set of samples may be different from the number of optical test strips in the training set of optical test strips. However, in the alternative, the number of samples in the training set of samples may be the same as the number of optical test strips in the training set of optical test strips.

[0034] As used herein, the term "mobile device" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a specific or special meaning. The term may specifically refer to, but is not limited to, a mobile electronic device, more specifically a mobile communication device such as a mobile phone or a smartphone. Additionally or alternatively, the mobile device may refer to a tablet computer or another type of portable computer having at least one camera. Furthermore, as outlined below, the mobile device may optionally comprise further elements, such as one or more processors.

[0035] As used herein, the term "camera" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically, but not limited to, refer to an apparatus having at least one imaging element configured to record or capture spatially resolved one-dimensional, two-dimensional, or three-dimensional optical data or information. As an example, a camera may include at least one camera chip, such as at least one CCD chip and / or at least one CMOS chip, configured to record an image. As used herein, but not limited to, the term "image" may specifically relate to data recorded using a camera, such as a plurality of electronic readings from an imaging device, such as the pixels of a camera chip.

[0036] Thus, the term "training set of images" may specifically relate to a plurality of images, i.e. a plurality of image data recorded using a camera, such as a camera as defined above. In particular, a training set of images may refer to a plurality of images, e.g. a stack of digital images, of at least a portion of one or more of the reagent-testing areas of a training set of optical test strips. As an example, the training set of images may include an image of each of the reagent-testing areas of the training set of optical test strips, where, for example, one or more of the samples of bodily fluid have been applied to the reagent-testing areas, e.g., prior to capture of the images. In particular, the training set of images may be used to determine a training set of color values ​​for the reagent-testing areas of the training set of optical test strips, such as a plurality of color values ​​for the training set of optical test strips. One or more of the images of the training set of images may be of more than one reagent-testing area. Thus, as an example, the number of images of the training set of images may be different from the number of optical test strips in the training set of optical test strips. However, it may also be possible for the number of images in the training set of images and the number of optical test strips in the training set of optical test strips to be equal. Specifically, as an example, the training set of images may include, for example, a separate image for each of the reagent-testing regions of the training set of optical test strips.

[0037] The camera may comprise, besides at least one camera chip or imaging chip, further elements such as one or more optical elements, for example one or more lenses. By way of example, the camera may be a fixed focus camera with at least one lens fixedly adjusted relative to the camera. However, in the alternative, the camera may comprise one or more variable lenses that may be automatically adjusted or manually adjusted. The invention is particularly applicable to cameras commonly used in mobile applications, such as notebook computers, tablets, or mobile phones, particularly smartphones. Thus, in particular, the camera may be part of a mobile device that comprises, besides at least one camera, one or more data processing devices, such as one or more data processors. However, other cameras are also feasible.

[0038] The camera may be specifically a color camera. Thus, for example, for each pixel, color information may be provided or generated, such as color values ​​of three colors R, G, B, also referred to as color channels. A larger number of color values, such as four color values ​​R, G, G, B, for each pixel, is also feasible. Color cameras are well known to those skilled in the art. Thus, as an example, a camera chip may consist of three or more different color sensors, such as color recording pixels, one pixel for red (R), one pixel for green (G), and one pixel for blue (B). For each pixel, such as R, G, B, a value depending on the intensity of the respective color may be recorded by the pixel, such as a digital value in the range of 0 to 255. Instead of using three colors, such as R, G, B, four may be used, such as R, G, G, B, as an example. The color sensitivity of the pixel may be generated by a color filter or may be generated by an appropriate intrinsic sensitivity of the sensor element used for the camera pixel. These techniques are generally known to those skilled in the art.

[0039] As used herein, the term "processor" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a specific or special meaning. The term may specifically, but not limited to, refer to any logic circuitry configured to perform the basic operations of a computer or system, and / or may generally refer to a device configured to perform calculations or logical operations. In particular, the processor may be configured to process the basic instructions that run the computer or system. By way of example, the processor may comprise at least one arithmetic logic unit (ALU), at least one floating point unit (FPU), such as a numeric coprocessor or numeric coprocessor, a number of registers, specifically registers configured to provide operands to the ALU and store results of operations, and memory, such as L1 and L2 cache memories. In particular, the processor may be a multi-core processor. In particular, the processor may be or comprise a central processing unit (CPU). Additionally or alternatively, the processor may be or comprise a microprocessor, and thus in particular the elements of the processor may be included on one single integrated circuit (IC) chip. Additionally or alternatively, the processor may be or comprise one or more application specific integrated circuits (ASICs) and / or one or more field programmable gate arrays (FPGAs), etc.

[0040] The processor, in particular the processor that may be used in step d) of the determination method, may be a separate processor separate from the mobile device, for example a stand-alone processor or a processor integrated in a computer or computer network. However, in the alternative, the processor may be integrated in the mobile device used in step c) to obtain the training set of images. Thus, in particular, the processor may be a processor of the mobile device.

[0041] As an example, a defective optical test strip may be defective due to either or both of a previous application of a fluid sample, such as a sample of a bodily fluid, and a previous exposure to at least one failure-inducing environment, for example, for more than 10 minutes, particularly more than 2 hours, and more specifically more than 1 day. In particular, an optical test strip may be defective or deemed defective due to a previous application of a fluid sample, such as by reapplication and / or double application to the optical test strip. In particular, an optical test strip that has already been used and / or an optical test strip that is subject to reuse may be deemed defective. Additionally or alternatively, a test strip may be deemed defective if it has previously been exposed to at least one failure-inducing environment, such as a failure-inducing environment that damages the optical test strip. In this way, a damaged optical test strip may be deemed defective. In particular, an optical test strip may be defective when exposed to a failure-inducing environment for more than 10 minutes, particularly more than 2 hours, and more specifically more than 1 day.

[0042] The defect-inducing environment may be, by way of example, an environment selected from the group consisting of a humid environment, specifically an environment having a humidity of more than 60%, more specifically an environment having a humidity of more than 80%, and a bright environment, specifically an environment having an illuminance of more than 1000 lm / m2, more specifically an environment having an illuminance of more than 1500 lm / m2.

[0043] Step d) may further comprise labeling the color values ​​of the training set of color values ​​with information about whether each optical test strip of the training set of optical test strips was bad or good. As used herein, the term "labeling" is a broad term and should be given its general and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may specifically refer to, but is not limited to, a process of linking and / or connecting information. In particular, information about whether each optical test strip was bad or non-bad, i.e., good, may be linked and / or connected to the color values. Labeling may specifically be taken into account in step e). In particular, labeling may be taken into account when deriving a color expectation range from the color values ​​for good optical test strips, i.e., to distinguish which of the color values ​​of the training set of color values ​​are determined to relate to good optical test strips and which are determined to relate to bad optical test strips.

[0044] In step e), the color expectation range may include at least 80% of the color values ​​for the good optical specimens of the training set of optical specimens. Specifically, in step e), the color expectation range may include at least 85% of the color values ​​for the good optical specimens of the training set of optical specimens. More specifically, in step e), the color expectation range may include at least 90% of the color values ​​for the good optical specimens of the training set of optical specimens. More specifically, in step e), the color expectation range may include at least 95% of the color values ​​for the good optical specimens of the training set of optical specimens. More specifically, in step e), the color expectation range may include at least 97% of the color values ​​for the good optical specimens of the training set of optical specimens. More specifically, in step e), the color expectation range may include at least 99% of the color values ​​for the good optical specimens of the training set of optical specimens.

[0045] As an example, the color expectation range may be or may include at least one polygon. In particular, the color expectation range may be or may include a two-dimensional polygon, the edges of which may correspond to color values ​​in a two-dimensional color space, such as at least two color planes. Additionally or alternatively, the color expectation range may be or may include a three-dimensional polyhedron, the edges of which may correspond to color values ​​in a three-dimensional color space. Additionally or alternatively, instead of edges corresponding to color values, the edges may be spaced apart from the color values ​​such that the polygon and / or polyhedron may enclose at least 80%, specifically at least 85%, more specifically at least 90%, more specifically at least 95%, more specifically at least 97%, and more specifically at least 99% of the color values ​​corresponding to the good optical specimens of the training set of optical specimens.

[0046] In particular, the derivation in step e) may comprise determining an envelope that includes at least 80%, particularly at least 85%, more particularly at least 90%, more particularly at least 95%, more particularly at least 97%, and more particularly at least 99% of the color values ​​for good optical test pieces of the training set of optical test pieces, and further extending the envelope by a predetermined safety factor.

[0047] As used herein, the term "envelope" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a specific or special meaning. The term may specifically, but not exclusively, refer to an element and / or entity that encompasses and / or contains at least one set of data. In particular, the envelope may encompass at least 80%, specifically at least 85%, more specifically at least 90%, more specifically at least 95%, more specifically at least 97%, more specifically at least 99% of the color values ​​for good optical specimens of a training set of optical specimens, for example in at least one color plane and / or color space, and the envelope may be determined mathematically and / or graphically.

[0048] In particular, step e) may comprise, in particular in a subsequent step, expanding the envelope by a predefined safety factor. The safety factor may be pre-determined and / or pre-set, in particular a safety factor taking into account the size and / or volume of the envelope. By way of example, the safety factor may be or may include a function that depends on the envelope, i.e. the size and / or volume of the envelope. By way of example, the envelope may be expanded such that the size and / or volume of the expanded envelope exceeds the size and / or volume of the envelope by at least 1.1 times, in particular at least 1.2 times, more particularly at least 1.5 times. By way of example, the envelope may be expanded such that 99% or 100% of the color development values ​​determined for the good optical test strips are enclosed. Additionally or alternatively, the safety factor may take into account deviations in the distribution of color development values, such as the standard deviation σ of the color development values ​​for the good optical test strips of the training set of optical test strips. Thus, by way of example, the envelope may be expanded by a factor such that it spans a region of at least 4σ, preferably at least 5σ, and more preferably at least 6σ.

[0049] The expansion may in particular be an evenly distributed expansion, such as a uniform and / or uniform expansion of the envelope. As an example, a uniform expansion of the envelope may be performed when the color values ​​are evenly distributed within the envelope. However, a non-uniformly distributed expansion is also possible. In particular, the envelope may be non-uniformly and / or non-uniformly expanded, i.e. based on and / or depending on a weighted distribution of the color values ​​within the envelope.

[0050] Step e) may specifically include using at least one machine learning algorithm, in particular by training a trainable model using a training set of color values. As used herein, the term "machine learning algorithm" is a broad term and should be given its general and ordinary meaning for the skilled person, and should not be limited to a special or special meaning. The term may specifically refer to a mathematical model that is trainable, for example, but not limited to, by using a record of training data including training input data and corresponding training output data. In particular, the training output data of a record of training data may be the result expected to be generated by the machine learning algorithm when the training input data of the same record of training data is given as input. As an example, the deviation between this expected result and the actual result generated by the algorithm may be observed and evaluated by a "loss function". This loss function may be used as a feedback to adjust the parameters of the internal processing chain of the machine learning algorithm. The machine learning algorithm may include decision trees, naive Bayes classification, nearest neighbors, neural networks, convolutional neural networks, generative adversarial networks, support vector machines, linear regression, logistic regression, random forests, and / or gradient boosting algorithms. As an example, the machine learning algorithm may be trained by using a training set of color values ​​as input data and corresponding information about each optical specimen, i.e., whether the optical specimen is a bad optical specimen or a good optical specimen, as output data. In particular, the machine learning algorithm may be or may comprise a trainable color expectation range model, i.e., a model describing the shape and / or form of the color expectation range, and feedback for adjusting parameters of the model's internal processing chain may be based, in particular, on a quantitative or qualitative determination of whether the color values ​​corresponding to a good optical specimen are within the color expectation range. Other forms of feedback may also be possible.

[0051] In step d) color generation values ​​are determined for at least two color channels, in particular at least two color channels selected from the group consisting of the green channel (G), the blue channel (B) and the red channel (R). In particular, in step e) a color expectation range is derived for the at least two color channels for which color generation values ​​have been determined in step d).

[0052] Furthermore, the method may include a step f) of attaching at least one optical test strip of the training set of optical test strips to a color reference card comprising a plurality of color reference fields with known reference color values. In particular, step f) may be performed before step c). Furthermore, at least one image of the set of images acquired in step c) may further show at least a portion of the color reference card, in particular one or more of the color reference fields. As used herein, the term "color reference card" is a broad term and should be given its common and ordinary meaning to those skilled in the art and should not be limited to a special or special meaning. The term may refer in particular to any item having a plurality of color reference fields with known color or optical properties arranged on at least one surface, such as, but not limited to, having a plurality of colored fields with known reference color values. Furthermore, the color reference card may comprise a plurality of gray reference fields with known gray levels. As an example, the color reference card may be a flat card having a plurality of color reference fields with known color values ​​and a plurality of gray reference fields with known gray levels on at least one surface and / or comprising at least one substrate on which such reference fields are arranged. The substrate may specifically have a flat surface on which the color reference fields and the gray reference fields are arranged. As an example, the substrate may be or include one or more of a paper substrate, a cardboard substrate, a plastic substrate, a ceramic substrate, or a metal substrate. Laminate substrates are also possible. The substrate may be, as an example, sheet-like or flexible. However, it should be noted that the substrate may be implemented in an article of use, such as a wall of a box, a vial, a container, a medical consumable such as a test strip, etc. Furthermore, the color reference card may be fully or partially integrated into the optical test strip. At least one image of at least a portion of the reagent test area of ​​the optical test strip may fully or partially include an image of at least a portion of the color reference card.

[0053] In a further aspect of the present invention, a measurement method is disclosed, which performs an analytical measurement based on a color reaction by using a mobile device having a camera and a processor. The measurement method includes the following steps, which may be performed in a given order, as an example. However, it should be noted that a different order may generally be possible. Furthermore, it may be possible to perform one or more of the method steps once or repeatedly. Furthermore, two or more method steps may be performed simultaneously or overlapping in time. The measurement method may include further method steps that are not listed.

[0054] The measurement method is as follows: i) providing at least one optical test strip having at least one reagent test area; ii) applying a sample of the bodily fluid to a reagent test area of ​​the optical test strip; iii) acquiring, by using a camera, at least one image of at least a portion of the reagent test area to which the bodily fluid has been applied; iv) determining, particularly using a processor, a color value of at least one color channel related to the color development of the reagent test area by using the image; v) comparing, for at least one color channel, the color development value with a color expectation range determined by carrying out a method according to any one of the preceding claims; vi) if the color value is outside the color expectation range, deeming the color value invalid and aborting the measurement method; vii) if the color value is within the color expectation range, deeming the color value valid and using the color value to determine the concentration of the analyte in the sample of bodily fluid; Includes.

[0055] For the definition of the measurement method, reference may be made to the description of the determination method as outlined above or in more detail below. In particular, the same type of optical test strip may be used to carry out the measurement method as the determination method outlined above. Thus, by way of example, the optical test strip provided in step i) of the measurement method may be of the same or at least similar type as the multiple optical test strips of the training set of optical test strips provided in step a) of the determination method as outlined above or in more detail below. However, the sample of bodily fluid may be a sample of bodily fluid from a user, the concentration of the analyte of which is to be determined and therefore may not be known in advance.

[0056] The measurement method may further comprise an intensity check, such as checking whether the intensity of the color value is above or below at least one intensity threshold. In particular, if the color value is outside a predefined intensity range, e.g. below a lower intensity threshold or above an upper intensity threshold, the measurement method may be aborted.

[0057] The measurement method may further comprise the step viii) of acquiring at least one image of at least a portion of the reagent test area to which no bodily fluid has been applied by using a camera. In particular, step viii) may be performed before step ii). Thus, by way of example, the measurement method may comprise acquiring at least one second image, in particular a blank image of the reagent test area to which no sample of bodily fluid has been applied.

[0058] Furthermore, the measurement method may include a step ix) of mounting the optical test strip on a color reference card that includes a plurality of color reference fields with known reference color values. The color reference card may in particular be of the same type as the color reference card optionally used in the determination method described above. In particular, step ix) may be performed before step iii) of the measurement method, and may also optionally be performed before step ii), in particular the image acquired in step iii) may further show at least a portion of the color reference card, in particular one or more of the color reference fields.

[0059] The application in step ii) may further include, in particular, the application by the user of the sample of bodily fluid to the reagent-testing area of ​​the optical test strip or confirmation that the sample of bodily fluid has been applied. Thus, by way of example, the application in step ii) may be and may include confirmation by the user that the sample of bodily fluid has been applied, i.e., for example, by pushing a button and / or other forms of confirmation by interacting with the mobile device. In particular, step ii) of the measurement method may include prompting the user to perform one or more of applying the sample of bodily fluid to the reagent-testing area of ​​the optical test strip and confirming the application of the sample of bodily fluid to the reagent-testing area of ​​the optical test strip. In particular, when performing step ii), the user may be prompted to apply the sample of bodily fluid and / or the user may be prompted to confirm the sample application, for example by providing a corresponding instruction on the display of the mobile device and / or as a voice instruction.

[0060] In a further aspect of the present invention, a determination system for determining a color expectation range for evaluating the validity of a color value obtained in an analytical measurement based on a color reaction is disclosed. The determination system comprises: A) at least one mobile device having at least one camera; B) a training set of optical test strips, each optical test strip having a reagent test area, at least two of the optical test strips being good optical test strips and at least two of the optical test strips being bad optical test strips; C) a training set of bodily fluid samples comprising a plurality of bodily fluid samples; D) at least one processor The processor includes: - taking a training set of images acquired by the camera that includes an image of at least a portion of each of the reagent test areas of the training set of optical test strips to which a bodily fluid sample has been applied; - determining a training set of color values ​​from the images of the training set of images, the training set of images including color values ​​for at least one color channel related to color development of the reagent test area of ​​each optical test strip of the training set of optical test strips; - deriving a color expectation range from the training set of color values, for at least one color channel, that defines an expected range of color values ​​for a good optical test specimen; It is configured as follows.

[0061] The processor of the decision system may be a separate processor separate from the at least one mobile device, for example a stand-alone processor or a processor integrated into a computer or computer network, although in the alternative the processor may be integrated into the mobile device.

[0062] The decision system is E) The optical test specimen may further comprise at least one color reference card configured to be removably attached, the color reference card comprising a plurality of color reference fields having known reference color values, and the images of the training set of images further depict at least a portion of the color reference card, in particular one or more of the color reference fields.

[0063] For the most part, the definition of the decision system may refer to the description of the decision method as described above or as outlined in more detail below. In particular, the decision system may be configured to execute the decision method described herein. In particular, the decision system may be configured to execute at least steps d) and e) of the decision method described herein.

[0064] Further disclosed and proposed herein is a computer program comprising instructions, which when executed by a decision system, in particular a decision system as described herein, causes the decision system to execute at least steps d) and e) of the decision method as described herein.In particular, the computer program may therefore comprise computer executable instructions, which are instructions for executing the decision method according to the invention in one or more of the embodiments contained herein, when the instructions are executed on the decision system, i.e., when executed on at least one processor of a decision system integrated in a computer or computer network, for example.In particular, the computer program may be stored on a computer readable data carrier and / or a computer readable storage medium.

[0065] Therefore, a computer-readable storage medium is further disclosed and proposed in the present specification, which, when executed by a decision system, in particular a decision system as described herein, causes the decision system to perform at least steps d) and e) of the decision method, also as described herein.

[0066] As used herein, the terms "computer-readable data carrier" and "computer-readable storage medium" may specifically refer to non-transitory data storage means such as a hardware storage medium having computer-executable instructions stored thereon. A computer-readable data carrier or storage medium may specifically be or comprise a storage medium such as a random access memory (RAM) and / or a read-only memory (ROM).

[0067] Further disclosed and proposed herein is a computer program product, which comprises program code means for executing the inventive decision-making method in one or more of the embodiments contained herein when the program is executed on a decision-making system, i.e. for example on at least one processor of a decision-making system integrated in a computer or a computer network. In particular, the program code means may be stored on a computer-readable data carrier and / or a computer-readable storage medium.

[0068] Further disclosed and proposed herein is a data carrier storing a data structure which, after being loaded into a computer or computer network, such as a working memory or main memory of the computer or computer network, can perform a decision method according to one or more of the embodiments disclosed herein.

[0069] Further disclosed and proposed herein is a computer program product, which has program code means stored on a machine-readable carrier for executing the determination method according to one or more of the embodiments disclosed herein when the program is executed on a computer or computer network. As used herein, a computer program product refers to a program as a tradeable product. The product can generally be present in any format, such as a paper format, or on a computer-readable data carrier and / or a computer-readable storage medium. In particular, the computer program product may be distributed over a data network.

[0070] Further disclosed and proposed herein is a modulated data signal containing instructions readable for a computer system or computer network to execute a determination method according to one or more of the embodiments disclosed herein.

[0071] In a further aspect of the present invention, a mobile device is disclosed having at least one camera and at least one processor. The mobile device is configured to perform at least steps iv) to vii) of the measurement method as described herein. Therefore, reference is made to the above description for the definition of terms, in particular with respect to the measurement method as described herein.

[0072] Further disclosed and proposed herein is a computer program, which comprises instructions for causing a mobile device having a camera and a processor, in particular as described herein, to perform at least steps iv) to vii) of the measurement method when the program is executed by the mobile device. Thus, in particular, the computer program may comprise computer executable instructions for performing the measurement method according to the invention in one or more of the embodiments contained herein, when the program is executed on a processor of the mobile device. In particular, the computer program may be stored on a computer readable data carrier and / or a computer readable storage medium.

[0073] Therefore, it is further disclosed and proposed herein a computer readable storage medium comprising instructions which, when executed by a mobile device having a camera and a processor, in particular a mobile device as described herein, cause the mobile device to perform at least steps iv) to vii) of the measurement method as also described herein.

[0074] Further disclosed and proposed herein is a computer program product, which has program code means for executing the measurement method according to the invention in one or more of the embodiments contained herein when the program is executed on at least one processor of a mobile device, i.e. for example a mobile device integrated in a computer or a computer network. In particular, the program code means may be stored on a computer readable data carrier and / or a computer readable storage medium.

[0075] Further disclosed and proposed herein is a data carrier storing a data structure which, after being loaded into a computer or computer network, such as a working memory or main memory of a computer or computer network, can perform the measurement method according to one or more of the embodiments disclosed herein.

[0076] Further disclosed and proposed herein is a computer program product having program code means stored on a machine-readable carrier for executing the measurement method according to one or more of the embodiments disclosed herein when the program is executed on a computer or computer network. As used herein, a computer program product refers to a program as a tradeable product. The product can generally be present in any format, such as a paper format, or on a computer-readable data carrier and / or a computer-readable storage medium. In particular, the computer program product may be distributed over a data network.

[0077] Further disclosed and proposed herein is a modulated data signal comprising instructions readable for a computer system or computer network to carry out a measurement method according to one or more of the embodiments disclosed herein.

[0078] In a further aspect of the present invention, a kit for determining the concentration of at least one analyte in a sample of a body fluid, in particular a sample of a user's body fluid, is disclosed. The kit comprises a mobile device as described above, in particular the mobile device is configured to perform at least steps iv) to vii) of the measurement method described herein. The kit further comprises at least one optical test strip having at least one reagent test area.

[0079] The method and device according to the invention provide a number of advantages over similar methods and devices known in the art. In particular, compared to methods and devices known in the art, the method and device described herein may increase the safety of the measurement. In particular, for example, the safety of the measurement may be increased by providing an effective fail-safe mechanism, since the color development value must be within the color expectation range, especially when performing the measurement method to determine the concentration of the analyte. Thus, in particular, the provided method and device may increase the safety of the measurement, since not all measured color values ​​are converted to the concentration of the analyte, such as, for example, blood glucose level. Instead, the method and device may make it possible to detect even subtle color changes and / or shifts that may be introduced by user handling, such as, for example, reapplication and / or double application to the test strip and / or reuse of the entire test strip. Furthermore, the proposed method and device may also make it possible to detect gross or sporadic mishandling, such as, for example, storing the optical test strip outside of its dedicated protective vial, for example in a wet or light environment.

[0080] Furthermore, the proposed method and device may improve the safety and accuracy of the measurement compared to known methods and devices. The method may in particular include preventing the determination of the concentration of the analyte in the body fluid when the validity assessment may not be met. Thus, the probability of erroneous and / or biased results of the analytical measurement may be reduced.

[0081] Furthermore, the proposed method and device may allow for improved user-friendliness and / or improved user convenience of analytical measurements by allowing to perform a safe analytical measurement by capturing only one image, for example instead of acquiring at least two images, one image before and one image after the application of the sample, etc. In particular, the proposed method and device may reduce the overall time required to perform an analytical measurement compared to known methods and devices.

[0082] In summary, without excluding further embodiments, the following embodiments can be envisaged: Embodiment 1: A method for determining a color expectation range for evaluating the validity of a color value obtained in an analytical measurement based on a color reaction, comprising: a) providing a training set of optical test strips, each optical test strip having a reagent test area, at least two of the optical test strips being good optical test strips and at least two of the optical test strips being bad optical test strips; b) providing a training set of bodily fluid samples and applying at least one of the bodily fluid samples to a reagent test area of ​​each optical test strip in the training set of optical test strips; c) acquiring, by at least one mobile device having at least one camera, a training set of images, the training set of images including images of at least a portion of one or more of the reagent test areas of the training set of optical test strips to which a sample of bodily fluid has been applied; d) determining, from the images of the training set of images, a training set of color values, the training set of color values ​​including at least one color channel related to the coloring of the reagent test area of ​​each optical test strip of the training set of optical test strips, in particular by using at least one processor, more particularly a processor of a mobile device; e) deriving a color expectation range from the training set of color values ​​for at least one color channel, the color expectation range defining an expected range of color values ​​for a good optical test specimen; A method of determining.

[0083] Embodiment 2: A method of determining as described in the preceding embodiment, wherein the defective optical test strip is defective due to one or both of a previous application of a fluid sample, particularly a sample of a bodily fluid, and a previous exposure to at least one defect-inducing environment for more than 10 minutes, particularly more than 2 hours, and more particularly more than 1 day.

[0084] Embodiment 3: The defect-inducing environment is a humid environment, specifically an environment having a humidity of more than 60%, more specifically an environment having a humidity of more than 80%, and a bright environment, specifically an environment having a humidity of less than 1000 lm / m 2 Illuminance exceeding 1500lm / m 2 3. The method of claim 1, wherein the environment is selected from the group consisting of environments having an illuminance greater than

[0085] Embodiment 4: The method of any one of the preceding embodiments, wherein step d) further comprises labeling the color values ​​of the training set of color values ​​with information about whether each optical test strip of the training set of optical test strips was bad or good, the labeling being specifically taken into account in step e).

[0086] Embodiment 5: In step e), the color expectation range includes at least 80%, specifically at least 85%, more specifically at least 90%, more specifically at least 95%, more specifically at least 97%, and more specifically at least 99% of the color values ​​for good optical test strips of the training set of optical test strips.

[0087] Embodiment 6: The method of any one of the preceding embodiments, wherein the derivation in step e) comprises determining an envelope that includes at least 80%, particularly at least 85%, more particularly at least 90%, more particularly at least 95%, more particularly at least 97%, and more particularly at least 99% of the color values ​​for good optical test strips of the training set of optical test strips, and further extending the envelope by a predetermined safety factor.

[0088] Embodiment 7: The method of any one of the preceding embodiments, wherein step e) comprises using at least one machine learning algorithm, in particular by training a trainable model using a training set of color development values.

[0089] Embodiment 8: A method according to any one of the preceding embodiments, wherein in step d) the color value is determined for at least two color channels, in particular for at least two color channels selected from the group consisting of a green channel, a blue channel, and a red channel.

[0090] Embodiment 9: A method according to the preceding embodiment, wherein in step e) a color expectation range is derived for at least two color channels for which color development values ​​have been determined in step d).

[0091] Embodiment 10: A determination method described in any one of the preceding embodiments, further comprising a step f) of attaching at least one optical test piece of the training set of optical test pieces to a color reference card including a plurality of color reference fields having known reference color values, wherein step f) is performed before step c), and at least one image of the set of images acquired in step c) further illustrates at least a portion of the color reference card, in particular one or more of the color reference fields.

[0092] Embodiment 11: A measurement method for performing an analytical measurement based on a color reaction by using a mobile device having a camera and a processor, comprising: i) providing at least one optical test strip having at least one reagent test area; ii) applying a sample of the bodily fluid to a reagent test area of ​​the optical test strip; iii) acquiring, by using a camera, at least one image of at least a portion of the reagent test area to which the bodily fluid has been applied; iv) determining, particularly using a processor, a color value of at least one color channel related to the color development of the reagent test area by using the image; v) comparing, for at least one color channel, the color development value with a color expectation range determined by performing the determination method according to any one of the preceding embodiments; vi) if the color value is outside the color expectation range, deeming the color value invalid and aborting the measurement method; vii) if the color value is within the color expectation range, deeming the color value valid and using the color value to determine the concentration of the analyte in the sample of bodily fluid; A measurement method including:

[0093] Embodiment 12: The measurement method of the preceding embodiment, further comprising step viii) of acquiring at least one image of at least a portion of the reagent test area to which no bodily fluid has been applied by using a camera, wherein step viii) is performed before step ii).

[0094] Embodiment 13: A measurement method according to any one of the previous two embodiments, further comprising a step ix) of attaching the optical test strip to a color reference card comprising a plurality of color reference fields with known reference color values, step ix) being performed before step iii) and optionally before step ii), and the image acquired in step iii) further showing at least a portion of the color reference card, in particular one or more of the color reference fields.

[0095] Embodiment 14: A measurement method described in any one of the preceding three embodiments, wherein step ii) includes prompting a user to perform one or more of applying a sample of the bodily fluid to a reagent test area of ​​the optical test strip and confirming application of the sample of the bodily fluid to the reagent test area of ​​the optical test strip.

[0096] Embodiment 15: A determination system for determining a color expectation range for evaluating the validity of a color value obtained in an analytical measurement based on a color reaction, comprising: A) at least one mobile device having at least one camera; B) a training set of optical test strips, each optical test strip having a reagent test area, at least two of the optical test strips being good optical test strips and at least two of the optical test strips being bad optical test strips; C) a training set of bodily fluid samples comprising a plurality of bodily fluid samples; D) at least one processor The processor includes: - taking a training set of images acquired by the camera that includes an image of at least a portion of each of the reagent test areas of the training set of optical test strips to which a bodily fluid sample has been applied; - determining a training set of color values ​​from the images of the training set of images, the training set of images including color values ​​for at least one color channel related to color development of the reagent test area of ​​each optical test strip of the training set of optical test strips; - deriving a color expectation range from the training set of color values, for at least one color channel, that defines an expected range of color values ​​for a good optical test specimen; A decision system configured to:

[0097] Embodiment 16: A decision system comprising: E) A determination system as described in the preceding embodiment, further comprising at least one color reference card configured to removably attach the optical test piece, the color reference card comprising a plurality of color reference fields having known reference color values, and the images of the training set of images further depict at least a portion of the color reference card, in particular one or more of the color reference fields.

[0098] Embodiment 17: A decision system as described in any one of the two preceding embodiments, configured to perform at least steps d) and e) of the decision method as described in any one of the preceding embodiments relating to the decision method.

[0099] Embodiment 18: A computer program comprising instructions, which when the program is executed by a decision system, in particular a decision system as described in any one of the preceding embodiments relating to a decision system, cause the decision system to perform at least steps d) and e) of the decision method as described in any one of the preceding embodiments relating to a decision method.

[0100] Embodiment 19: A computer-readable storage medium comprising instructions, which when executed by a decision system, in particular a system described in any one of the preceding embodiments relating to a decision system, cause the decision system to perform at least steps d) and e) of the decision method described in any one of the preceding embodiments relating to a decision method.

[0101] Embodiment 20: A mobile device having at least one camera and at least one processor and configured to perform at least steps iv) to vii) of the measurement method described in any one of the preceding embodiments relating to the measurement method.

[0102] Embodiment 21: A computer program comprising instructions, which when executed by a mobile device having a camera and a processor, in particular a mobile device as described in the preceding embodiments, cause the mobile device to perform at least steps iv) to vii) of the measurement method as described in any one of the preceding embodiments relating to the measurement method.

[0103] Embodiment 22: A computer-readable storage medium comprising instructions, which when executed by a mobile device having a camera and a processor, in particular a mobile device as described in any one of the preceding embodiments relating to a mobile device, cause the mobile device to perform at least steps iv) to vii) of the measurement method as described in any one of the preceding embodiments relating to a measurement method.

[0104] Embodiment 23: A kit for determining the concentration of at least one analyte in a body fluid sample, comprising the mobile device of embodiment 19, and further comprising at least one optical test strip having at least one reagent test area. [Brief description of the drawings]

[0105] Further optional features and embodiments are disclosed in more detail in the following description of the embodiments, preferably in conjunction with the dependent claims, in which each optional feature may be realized in an independent manner as well as in any possible combination, as understood by a person skilled in the art. The scope of the present invention is not limited by the preferred embodiments. The embodiments are illustrated diagrammatically in the figures, where identical reference numbers in these figures refer to identical or functionally equivalent elements.

[0106] [Figure 1] 1 shows an embodiment of a determination system and an embodiment of a kit. [Diagram 2] 1 shows an illustration of one embodiment of a determination method. [Diagram 3] 1 illustrates an embodiment of a color expectation range. [Figure 4] 1 illustrates an embodiment of a color expectation range. [Diagram 5] 1 shows diagrams of various embodiments of a measurement method; [Figure 6] 1 shows diagrams of various embodiments of a measurement method; [Figure 7] FIG. 1 shows an illustration of a diagram showing the relationship between actual blood glucose levels and blood glucose levels determined by using both a general method and system for determining blood glucose concentration and the present method and system. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0107] In Fig. 1, an embodiment of the determination system 110 is shown. The determination system 110 comprises at least one mobile device 112 having at least one camera 114. Furthermore, the determination system 110 comprises a training set of optical test strips 116. The training set of optical test strips 116 comprises a plurality of optical test strips 118, each of which has a reagent test area 120. At least two of the optical test strips 118 are good optical test strips and at least two of the optical test strips 118 are bad optical test strips. Thus, the training set of optical test strips 116 comprises at least two good optical test strips 122 and at least two bad optical test strips 124. Furthermore, the determination system 110 comprises a training set of bodily fluid samples 126 comprising a plurality of bodily fluid samples 128. In particular, for each of the bodily fluid samples 128 and for the training set of bodily fluid samples 126, the concentration of the analyte, for example the glucose concentration, may be known. Furthermore, the determination system 110 includes at least one processor 130. The processor 130 of the determination system 110 may be, for example, a separate processor 130. However, in the alternative, as shown in FIG. 1, the processor 130 may be integrated into the mobile device 112, and thus the processor 130 may be the processor 130 of the mobile device 112.

[0108] In the determination system 110, the processor 130 is configured to retrieve a training set of images including images captured by the camera 114 of the mobile device 112. In particular, the images of the training set of images may be images of at least a portion of each of the reagent test areas 120 of the optical test strips 118 of the training set of optical test strips 116 to which at least one bodily fluid sample 128 of the training set of bodily fluid samples 126 has been applied. Furthermore, in the determination system 110, the processor 130 is configured to determine a training set of color values ​​from the images of the training set of images. The training set of color values ​​includes color values ​​of at least one color channel related to the color development of the reagent test areas 120 of each optical test strip 118 of the training set of optical test strips 116. Further, in the determination system 110, the processor 130 may be configured to derive at least one color expectation range 132 (not shown in FIG. 1 ) from the training set of color values, for at least one color channel, that defines an expected range of color values ​​for a good optical test piece 122.

[0109] Furthermore, FIG. 1 shows an embodiment of a kit 134 configured to determine the concentration of at least one analyte in a bodily fluid sample 128. The bodily fluid sample 128 may specifically include a bodily fluid of a user, such as a sample with an unknown concentration of the analyte. In FIG. 1, such a sample is exemplarily shown at the right edge of the figure. The kit 134 includes at least one optical test strip 118 having at least one reagent test area 120. In FIG. 1, such an optical test strip 118, i.e., a single optical test strip 118, is exemplarily shown at the right edge of the figure. Furthermore, the kit 134 comprises a mobile device 112 having at least one camera 114 and at least one processor 130. As an example, the mobile device 112 of the kit 134 may be the same mobile device 112 as the mobile device 112 of the determination system 110. However, in an alternative, the kit 134 and the determination system 110 each comprise their own mobile device 114, i.e., a separate and distinct mobile device 112. The determining system 110 may in particular be configured to at least partially execute a determining method 136. An exemplary embodiment of the determining method 136 is shown in FIG. 2. The determining method 136 is configured to determine a color expectation range 132 that processes the validity of color values ​​obtained in an analytical measurement based on a color reaction. The determining method 136 includes the following steps: a) providing a training set 116 of optical test strips (indicated by reference numeral 138), where each optical test strip 118 has a reagent test area 120, at least two of the optical test strips being good optical test strips 122 and at least two of the optical test strips being bad optical test strips 124; b) providing a training set of bodily fluid samples 126 and applying at least one of the bodily fluid samples 128 to the reagent test area 120 of each optical test strip 118 in the training set of optical test strips 116 (indicated by reference numeral 140); c) acquiring, by at least one mobile device 112 having at least one camera 114, a training set of images (indicated by reference numeral 142), the training set of images including images of at least a portion of one or more of the reagent test areas 120 of the training set of optical test strips 116 to which a sample 128 of bodily fluid has been applied; d) determining, from the images of the training set of images, a training set of color values ​​including color values ​​of at least one color channel relating to the color development of the reagent test area 120 of each optical test strip 118 of the training set of optical test strips 116, in particular by using at least one processor 130, more particularly the processor 130 of the mobile device 112 (indicated by reference numeral 144); and e) deriving, from the training set of color values, a color expectation range 132 (indicated by reference numeral 146) that defines an expected range of color values ​​for good optical test specimens 122 for at least one color channel.

[0110] 3 and 4 show an exemplary embodiment of the color expectation range 132. As shown in FIG. 3, the color expectation range 132 may be or may include a polygon, such as, for example, a two-dimensional polygon in a color plane. For example, on the horizontal axis, the color plane may show color values ​​of a red channel 148, such as a relative red channel, and on the vertical axis, the color plane may show color values ​​of a green channel 150, such as a relative green channel. Additionally, FIG. 3 shows color values ​​of an exemplary training set of color values. As an example, at least 95% of the color values ​​corresponding to good optical test specimens 122, i.e., good color values ​​152, may be surrounded by the polygonal shape of the color expectation range 132, while a plurality of bad color values ​​154 corresponding to bad optical test specimens 124, preferably most or all of the bad color values ​​154 corresponding to bad optical test specimens 124, may be located outside the polygonal shape of the color expectation range 132.

[0111] As an example, poor color values ​​154 can be seen in FIG. 3 corresponding to different poor optical test strips 124, where some of the poor color values ​​154 may be poor color values ​​156 due to reuse of the optical test strip 118, i.e., due to double application and / or reuse that has become poor due to reapplication.

[0112] Reuse may occur, as an example, even in the case of a second blood application, i.e. with a significantly different blood glucose concentration. As an example, large measurement deviations may occur when applying a blood sample with a significantly lower blood glucose concentration. This may also refer to medically significant cases, when the actual low value cannot be recognized and a higher blood glucose result is presented instead. Another example of a reuse case may be when the first volume is insufficient and then a second measurement is performed with an appropriate volume of blood.

[0113] 3 further illustrates a case where a good color value 152 corresponding to a good optical test strip 122 may have been slightly mishandled by a user, however, the slightly mishandled optical test strip 118 does not become defective, resulting in a restored good color value 158. Such a restored good color value 158 may be a good color value 152 corresponding to a good optical test strip 122 that has been restored from an initial defect. As an example, it may be the case where an initial quantity shortage is corrected immediately, i.e., within minutes, specifically within 3 minutes. As another example, it may be the case where the optical test strip 118 is stored at 85% relative humidity and 23° C. outside a protective vial and / or in an open vial for only a short time, i.e., up to 72 hours. Such storage may still provide a correct measurement, i.e., a good color value 152. However, as an example, if the optical test strip 118 was stored in this environment for more than 72 hours, potentially up to 336 hours, then normal to high glucose concentrations, i.e., ≧100 mg / dl, may show only minor measurement deviations, while samples with lower glucose concentrations, i.e., <100 mg / dl, may show significant measurement deviations and thus be considered poor color values ​​154. Additionally, as shown in FIG. 3, not all of the recovered good color values ​​118 are bounded by the color expectation range 132.

[0114] Additionally or alternatively, as exemplarily shown in Fig. 4, the color expectation range 132 may be or include a three-dimensional form, such as a polyhedron. As an example, the color expectation range 132 may be formed by a polygon in a two-dimensional color space, such as a polygon in the color plane of the red channel 148 and the green channel 150, and may be extended in the third dimension, for example with reference to the blue channel 160, or intensity values, i.e. values ​​in the intensity dimension, for example the absolute intensity values ​​of the green channel 150 values. In particular, the color expectation range 132 may be bounded in the direction of the blue channel 160 by an upper surface 162 and a lower surface 164. Other forms and / or geometries of the color expectation range 132 may be possible.

[0115] In particular, the color expectation range 132 may be used to evaluate the likelihood of a color value obtained in an analytical measurement based on a color reaction. Such an analytical measurement may be performed by a measurement method 166. In particular, the mobile device 112, in particular the mobile device 112 of the kit 134, may be configured to at least partially execute the measurement method 166. An exemplary embodiment of the measurement method 166 is shown in Figures 5 and 6. The measurement method 166 includes the following steps: i) providing at least one optical test strip 118 having at least one reagent test area 120 (indicated by reference numeral 168); ii) applying a sample 128 of the bodily fluid to the reagent test area 120 of the optical test strip 118 (indicated by reference numeral 170); iii) acquiring, by using the camera 114, at least one image of at least a portion of the reagent test area 120 to which the bodily fluid 128 has been applied (indicated by reference numeral 172); iv) determining, in particular using the processor 130, a color value of at least one color channel relating to the color development of the reagent test area 120 by using the image (indicated by reference numeral 174); v) comparing, for at least one color channel, the color development value with the color expectation range 132 determined by executing the determination method 136 (indicated by reference numeral 176); vi) if the color value is outside the color expectation range 132, then considering the color value invalid and aborting the measurement method 166 (indicated by reference numeral 178); and vii) if the color value is within the color expectation range, then considering the color value as valid and determining the concentration of the analyte in the sample of bodily fluid by using the color value (indicated by reference numeral 180).

[0116] Another embodiment of the measurement method 166 is shown in FIG. 6. The starting point may be indicated by a black circle at the top of the figure. By way of example, the measurement method may further include an intensity check 182, such as a step of checking whether the intensity of the coloration value is above or below at least one intensity threshold. In particular, the measurement method may be stopped if the coloration value is outside a predefined intensity range, for example below a lower intensity threshold or above an upper intensity threshold. In particular, if the coloration value does not pass the intensity check, the coloration value may be considered invalid and thus the measurement method 166 may be stopped. By way of example, if the color expectation range 132 corresponds to the color expectation range 132 shown in FIG. 4, step v) 176 of the measurement method 166 may in particular include a separate step for comparing the coloration value with the color expectation range 132. By way of example, it may be checked whether the coloration value is above the lower plane 164, as indicated by reference number 184. Further, a check may be made as to whether the color value is below the upper plane 162, as indicated by reference numeral 186. Further, a check may be made as to whether the color value is within a polygonal shape in the color plane defined by the red channel 148 and the green channel 150, as indicated by reference numeral 188. If the color value fails any of the checks 184-188, the color value may be deemed invalid and the method may be aborted, according to step vi) 178. Optionally, after aborting the method, the measurement method 166 may further comprise indicating an error message 190.

[0117] Figure 7 shows an illustration of a diagram showing the relationship between actual blood glucose levels and blood glucose levels determined by using both the general method and system for determining blood glucose concentration and the present method and system. In particular, the diagram shown in Figure 7 shows the relationship between actual blood glucose levels 192 (in mg / dl) and measured blood glucose levels 194 (in mg / dl). In particular, the values ​​shown with crosses show the relationship in measurements made by known methods and devices, and the values ​​shown with circles show the relationship in measurements made using the present method and device.

[0118] Additionally, Figure 7 shows regions A-E of an error grid analysis that quantifies the clinical accuracy of a measured blood glucose concentration compared to the actual blood glucose concentration, specifically, regions A-E of the Parkes error grid. For example, blood glucose values ​​are within the following ranges: a) Region A contains values ​​within 20% of the reference sensor; b) Region B includes the outer 20% of values, but would not lead to inappropriate treatment; c) Area C contains values ​​that lead to unnecessary treatment; d) Area D contains values ​​that indicate failure to detect potentially dangerous hypoglycemia or hyperglycemia; e) Region E includes values ​​that may lead to confusion between hyperglycemia and hypoglycemia.

[0119] For further information regarding error grid analysis, one may refer to Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL: Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care 10:622-628, 1987.

[0120] 7 are based on the same sample, and in particular the same sample applied to the same optical test strip 118. In particular, the same optical test strip 118 was used to determine the blood glucose level in both measurements, and Table 1 shows the number of blood glucose levels determined for both measurements made using known methods and devices, and measurements made using the present method and device.

[0121] [Table 1]

[0122] Specifically, as can be seen in the figure, the measurements performed by the known method and apparatus provide blood glucose values ​​for all measurements, whereas the measurements according to the present invention do not provide blood glucose values ​​for the defective optical test strips. In particular, the number of misses when using the present method and apparatus is due to more measurements being aborted, e.g., due to a fail-safe error. [Explanation of symbols]

[0123] 110 Decision System 112 Mobile Devices 114 Camera 116 Optical Test Piece Training Set 118 Optical test pieces 120 Reagent Testing Area 122 Good Optical Test Pieces 124 Defective optical test piece Training set of 126 body fluid samples 128 Body Fluid Samples 130 processors 132 Color Expectation Range 134 Kit 136 Determination method 138 Step a) 140 Step b) 142 Step c) 144 Step d) 146 Step e) 148 Red Channel 150 Green Channel 152 Good color value 154 Poor color value 156 Poor color values ​​due to reuse 158 Good color value restored 160 Blue Channel 162 Upper plane 164 Lower plane 166 Measurement method 168 Step i) 170 Step ii) 172 Step iii) 174 Step iv) 176 Step v) 178 Step vi) 180 Step vii) 182 Strength Check 184 Check if the color value is above the lower plane 186 Check if the color value is below the upper plane 188 Check if color value is inside polygon 190 Show error message 192 Actual blood glucose level (mg / dl) 194 Measured blood glucose level (mg / dl)

Claims

1. A method for determining a color expectation range (132) for evaluating the validity of a color value obtained in an analytical measurement based on a color reaction, comprising: a) providing a training set (116) of optical test strips, each optical test strip (118) having a reagent test area (120); b) providing a training set of bodily fluid samples (126) and applying at least one of said bodily fluid samples (128) to the reagent test area (120) of each optical test strip (118) in said training set of optical test strips (116); c) acquiring, by at least one mobile device (112) having at least one camera (114), a training set of images including images of at least a portion of one or more of the reagent test areas (120) of the training set of optical test strips (116) to which a sample (128) of the bodily fluid has been applied, at least two of the optical test strips (118) being good optical test strips (122) and at least two of the optical test strips being bad optical test strips (124); d) determining a training set of color values ​​from the images of the training set of images, the training set of images including color values ​​for at least one color channel related to the color development of the reagent test area (120) of each optical test strip (118) in the training set of optical test strips (116); e) deriving, from the training set of color values, for the at least one color channel, the color expectation range (132) defining an expected range of color values ​​for a good optical test specimen (122); A method of determining.

2. The method of claim 1 , wherein the defective optical test strip (124) is rendered defective by one or both of a previous application of a fluid sample and a previous exposure to at least one defect-inducing environment for more than 10 minutes.

3. The method of claim 2 , wherein the defect-inducing environment is an environment selected from the group consisting of a humid environment and a bright environment.

4. 4. The method of claim 1, wherein step d) further comprises labeling the color values ​​of the training set of color values ​​with information about whether each optical test strip (118) of the training set of optical test strips (116) was bad or good.

5. The method of any one of claims 1 to 4, wherein in step e) the color expectation range (132) includes at least 80% of the color values ​​for the good optical test strips (122) of the training set of optical test strips (116).

6. The method of any one of claims 1 to 5, wherein the derivation in step e) comprises determining an envelope that includes at least 80% of the color values ​​for the good optical test pieces (122) of the training set of optical test pieces (116) and further extending the envelope by a predetermined safety factor.

7. The method of any one of claims 1 to 6, wherein step e) comprises using at least one machine learning algorithm.

8. A method of performing a color reaction-based analytical measurement by using a mobile device (112) having a camera (114) and a processor (130), comprising: i) providing at least one optical test strip (118) having at least one reagent test area (120); ii) applying a sample (128) of bodily fluid to the reagent test area (120) of the optical test strip (118); iii) acquiring, by using said camera (114), at least one image of at least a portion of said reagent test area (120) to which said bodily fluid has been applied; iv) determining a color value of at least one color channel relating to the color development of the reagent test area (120) by using the image; v) comparing, for said at least one color channel, said color value with a color expectation range (132) determined by executing a method according to any one of claims 1 to 7; vi) if said color value is outside said color expectation range (132), then said color value is deemed invalid and said measurement method is discontinued; vii) if said color value is within said color expectation range (132), then said color value is deemed valid and said color value is used to determine the concentration of an analyte in said sample of bodily fluid; A measurement method including:

9. 9. The method of claim 8, further comprising step viii) of acquiring at least one image of at least a portion of the reagent test area (120) to which the bodily fluid has not been applied by using the camera (114), step viii) being performed prior to step ii).

10. 10. The method of claim 8 or 9, further comprising the step of attaching the optical test strip (118) to a color reference card including a plurality of color reference fields having known reference color values, step ix) being performed before step iii), and the image acquired in step iii) further showing at least a portion of the color reference card.

11. A determination system (110) for determining a color expectation range (132) for evaluating the validity of color values ​​obtained in an analytical measurement based on a color reaction, comprising: A) at least one mobile device (112) having at least one camera (114); B) a training set (116) of optical test strips, each optical test strip (118) having a reagent test area (120), at least two of the optical test strips being good optical test strips (122) and at least two of the optical test strips being bad optical test strips (124); C) a training set of bodily fluid samples (126) comprising a plurality of bodily fluid samples (128); D) at least one processor (130); wherein the processor (130) - taking a training set of images acquired by said camera (114) including an image of at least a portion of each of the reagent test areas (120) of said training set of optical test strips (116) to which said bodily fluid sample (128) has been applied; - determining a training set of color values ​​from images of the training set of images, the training set of images including color values ​​for at least one color channel relating to color development of the reagent test area (120) of each optical test strip (118) in the training set of optical test strips (116); - deriving, from said training set of color values, for said at least one color channel, said color expectation range (132) defining an expected range of color values ​​for a good optical test specimen (122); A decision system (110) configured to:

12. E) at least one color reference card configured to removably mount to the optical test strip (118), the color reference card comprising a plurality of color reference fields having known reference color values, and the images of the training set of images further depict at least a portion of the color reference card.

13. The decision system (110) according to claim 11 or 12, wherein said decision system (110) is configured to perform at least steps d) and e) of the decision method according to any one of claims 1 to 7.

14. A mobile device (112) comprising at least one camera (114) and at least one processor (130) and configured to perform at least steps iv) to vii) of the measurement method according to any one of claims 8 to 10.

15. 15. A kit (134) for determining a concentration of at least one analyte in a bodily fluid sample (128), comprising the mobile device (112) of claim 14 and further comprising at least one optical test strip (118) having at least one reagent test area (120).

Images