HK40116947A - Methods and devices for determining the concentration of at least one analyte in a bodily fluid - Google Patents

Description

Method and apparatus for determining the concentration of at least one analyte in body fluids

Technical Field

This invention relates to a method for determining at least one color expectation range for assessing the plausibility of hypothetical reaction time values. The invention further relates to a measurement method for performing analytical measurements based on color-forming reactions. Furthermore, the invention relates to a determination system and a mobile device, and to computer programs, computer-readable storage media, and reagent kits. The method, system, mobile device, computer program, computer-readable storage media, and reagent kit can be specifically used in medical diagnostics to, for example, quantitatively or qualitatively detect one or more analytes in one or more body fluids and/or bodily fluids, such as for detecting glucose in blood and/or interstitial fluid. However, other application areas of the invention are also possible.

Background Technology

In the field of medical diagnostics, in many cases, it is necessary to detect one or more analytes in bodily fluid samples such as blood, interstitial fluid, urine, saliva, or other types of bodily fluids. Examples of analytes to be detected are glucose, triglycerides, lactate, cholesterol, or other types of analytes commonly present in these bodily fluids. If necessary, appropriate treatment may be selected based on the concentration and/or presence of the analyte. Without narrowing its scope, the invention can be specifically described with respect to blood glucose measurement. However, it should be noted that the invention can also be used for other types of analytical measurements using test elements.

Generally, apparatus and methods known to those skilled in the art utilize test elements and/or test strips comprising one or more test chemicals, wherein the one or more test chemicals are capable of performing one or more detectable detection reactions, such as optically detectable detection reactions, in the presence of the analyte to be detected. For information on test chemicals contained in test elements and/or test strips, see, for example, J. Hoenes et al.: The Technology Behind Glucose Meters: Test Strips, Diabetes Technology & Therapeutics, Vol. 10, Supplement 1, 2008, pp. 10-26. Other types of test chemicals are also possible and can be used in carrying out this invention.

In analytical measurements, specifically those based on color-forming reactions, a technical challenge lies in evaluating the color changes caused by the detection reaction. In recent years, in addition to the use of dedicated analytical devices such as handheld blood glucose meters, the use of general-purpose electronic devices such as smartphones and laptops or other mobile devices has become increasingly prevalent. Therefore, cameras included in these mobile devices can be used to measure the color changes of the detection reaction in test elements and/or test strips. In contrast to laboratory measurements and measurements performed using dedicated analytical measurement devices paired with test elements and/or test strips, various influences need to be considered when using mobile computing devices such as smartphones. For example, lighting conditions, location, vibration, electronic defects, or other more or less uncontrollable influences must be considered. Generally, procedures can be used that involve mathematically correcting and/or compensating for the consequences of such influences on color changes by utilizing a color reference used for photometric measurements.

US2020/0249220 A1 describes a method for detecting a urine test strip from an image of the test strip. The disclosed method includes: receiving input an image of the urine test strip, the image being an image of the urine test strip including first and second markers; detecting the first and second marker images in the urine test strip image; detecting a region between the first and second marker images in the urine test strip image; and detecting the test pad and colorimeter in the urine test strip image by matching a target region representing the positions of a test pad and a colorimeter in the urine test strip image with the region between the first and second marker images.

US 9,787,815 B2 describes a method for acquiring collection points of analytes on a test strip and selecting quantitative markers using a smartphone. This method involves imaging a test strip on which a colorimetric reaction of the target sample has already occurred due to illumination of the test strip by the smartphone. The smartphone includes a smartphone app and smartphone accessories that provide an imaging environment independent of the smartphone platform used, either externally isolated or internally dark. The results can then be quantitatively presented or converted into more consumer-friendly measurements (positive, negative, above average, etc.), displayed to the user, stored for later use, and communicated to locations where practitioners can provide additional review. Furthermore, social media integration can allow device results to be disseminated to specific audiences, compared with others for healthy living, competed in health-based games, and used for video creation and other applications.

EP 2916117 A1 describes a colorimetric quantification and titration of an analyte using a chemical test pad, which can be performed under different illumination conditions. In one embodiment, the illumination conditions are estimated, a digital image is captured under these conditions, and a set of reference colors is selected using the image, from which the quantified colors are compared to determine the titration. In another embodiment, multiple comparisons are performed under different illumination conditions, and the result with the highest confidence level is selected to determine the titration.

EP 1963828 B1 describes a method for measuring the concentration of an analyte contained in a biological fluid sample. In this method, a test strip is provided, comprising at least one test point and at least one reference color portion covering a white color and/or a color scale. The fluid sample is brought into contact with the test point, and a color indicator is positioned on the test point according to the concentration of the analyte. A camera is placed on the test strip. At least one measurement of the relative position between the camera and the test strip is detected and compared to a set range. If the measurement deviates from the set range, the camera is moved relative to the test strip to reduce the deviation. A color image, at least on which the color indicator and the reference color portion are represented, is detected by means of the camera. An image area assigned to the color indicator and the color matching portion is located, and a color value of the image area is determined. Based on the color value, the concentration of the analyte in the sample is determined using a predefined comparison value.

US2015/0241358 A1 describes an apparatus for automated testing and diagnostics of a test paddle in one embodiment. The apparatus includes a personal computing device comprising: a camera that captures images of the test pads of the test paddle over time; a processor coupled to the camera; and a display device coupled to the processor. The processor analyzes the color change of each test pad over time to determine the color trajectory of each test pad over time. The processor compares the color evolution trajectory of each test pad with a color correction curve for each test pad to determine the analyte concentration of the tested biological sample, such as urine. During the analysis performed by the processor, the display device displays a user interface with the analyte concentration results in response to the analysis over time.

US2014/065647 A1 describes a system and method for rapid determinations for spatiotemporal analysis.

EP 3667301 A1 describes a method and system for determining the concentration of an analyte in a body fluid sample, and a method and system for generating a software-implemented module.

US2021/299651 A1 describes a multifactor urine testing system that can be adjusted according to light and time.

US2017/098137 A1 describes a method, apparatus, and system for detecting and identifying damaged reagent pads by quantifying color changes caused by exposure to harsh environments.

Despite these advantages achieved through known methods and apparatus, several technical challenges remain. Specifically, user-related influences, such as incorrect handling practices and/or improper time specifications for sample application, or other more or less uncontrollable user-related handling errors, can lead to undetected color changes. When determining analyte concentrations based on color-forming reactions, such undetected color changes can result in incorrect analytical measurements.

Problems to be solved

Therefore, it is desirable to provide methods and apparatus that at least partially address the aforementioned technical challenges. Specifically, it is desirable to provide methods and apparatus that allow the detection of color changes caused by erroneous and/or inappropriate user processing.

Summary of the Invention

This problem is solved by a determination method that identifies at least one color expectation range for assessing the reasonableness of the hypothetical reaction time value, and by a measurement method that performs analytical measurements based on the color-forming reaction. Further, it is solved by a determination system, mobile device, computer program, computer-readable storage medium, and kit having the features of the independent claims. Advantageous embodiments that can be implemented individually or in any combination are set forth in the dependent claims and throughout the specification.

As used below, the terms “have,” “contain,” or “include,” or any grammatical variations thereof, are used in a non-exclusive manner. Thus, these terms can refer either to a situation where no other features exist in the entity described in this context besides those introduced by these terms, or to a situation where one or more other features exist. For example, the statements “A has B,” “A includes B,” and “A contains B” can refer to a situation where no other elements exist in A besides B (i.e., where A is solely and uniquely composed of B); or to a situation where one or more other elements (such as element C, element D, or even other elements) exist in entity A besides B.

Furthermore, it should be noted that the terms "at least one," "one or more," or similar expressions indicating that a feature or element may exist once or more are generally used only once when introducing the corresponding feature or element. In the following text, in most cases, when referring to the corresponding feature or element, the expressions "at least one" or "one or more" will not be used repeatedly, even though the corresponding feature or element may exist only once or more.

Furthermore, as used below, the terms “preferredly,” “more preferably,” “particularly,” “more particularly,” “specifically,” “more specifically,” or similar terms are used in combination with optional features without limiting the possibility of alternatives. Therefore, features introduced by these terms are optional features and are not intended to limit the scope of the claims in any way. As those skilled in the art will recognize, the invention can be practiced using alternative features. Similarly, features introduced by “in one embodiment of the invention” or similar expressions are intended to be optional features without limiting alternative embodiments of the invention, without limiting the scope of the invention, and without limiting the possibility of combining features introduced in this way with other optional or non-optional features of the invention.

In a first aspect of the invention, a method is disclosed for determining at least one color expectation range for evaluating the reasonableness of assumed reaction time values used in analytical measurements based on color-forming reactions. The method includes the following steps, which, as an example, may be performed in a given order. However, it should be noted that a different order is also possible. Furthermore, one or more method steps may be performed once or repeatedly. Further, two or more method steps may be performed simultaneously or in a timely overlapping manner. The method may include other method steps not listed.

The determination method includes:

a) Provide an optical test strip training set, where each optical test strip has a reagent testing area;

b) Provide a training set of body fluid samples and apply at least one of the body fluid samples to the reagent test area of each optical test strip in the optical test strip training set;

c) Capture an image training set using at least one mobile device having at least one camera, the images

The training set includes:

- A first image training subset, comprising at least a portion of images of at least some of the reagent test areas of the optical test strip training set to which a body fluid sample has been applied, captured at an in-time capture time value, the capture time value referring to the time elapsed between the application of the sample and the capture image in step b).

- At least one second image training subset, the at least one second image training subset comprising at least some of at least a portion of images of at least some of the reagent test areas of the optical test strip training set to which a body fluid sample has been applied, captured at a delayed capture time value;

d) Specifically, by using at least one processor, more specifically, the processor of the mobile device, a color formation value training set is determined from the images of the image training set, the color formation value training set including color formation values of at least one color channel, the color channel being used for color formation of the reagent test area of the optical test strip training set for timely capture time values and delayed capture time values; and

e) Derive from the color formation value training set at least one color expectation range for at least one color channel, the color expectation range defining the expected range of color formation values for timely capture time values and permissible delayed capture time values, wherein for permissible delayed capture time values, the delay d does not exceed at least one predefined expiration threshold _dmax .

As used herein, the term "analytical measurement based on color-forming reaction" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, the qualitative and/or quantitative determination of at least one analyte in any sample or aliquot of a body fluid using a color-forming reaction. For example, body fluids may include one or more of blood, interstitial fluid, urine, saliva, or other types of body fluids. As an example, the result of analyte determination may be the concentration of the analyte and/or the presence or absence of the analyte to be determined. Specifically, as an example, the analytical measurement may be a blood glucose measurement, thus yielding, for example, a blood glucose concentration. In particular, analytical measurement results, such as the concentration of an analyte in a body fluid, can be determined via an analytical measurement using a color-forming reaction, such as a color change reaction in response to the quantitative and/or qualitative presence or absence of an analyte in the body fluid.

For example, body fluids may include one or more of blood, interstitial fluid, urine, saliva, or other types of body fluids. Therefore, specifically, the term "body fluid sample" may refer to any aliquot or unequal fraction of a biological fluid that is directly a body fluid, or that is obtained from a body fluid through one or more pretreatment steps, such as centrifugation. As an example, a body fluid sample may be a drop of body fluid collected from a human body, such as a drop of blood and/or interstitial fluid, obtained, for example, by piercing a portion of the skin with a scalpel, needle, etc. Body fluid samples may also be simply referred to as samples.

In analytical measurements based on color-forming reactions, optical test strips are specifically used. As used herein, the term "optical test strip" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. The term can specifically refer to (but is not limited to) any element or device configured to perform a color change detection reaction. An optical test strip can also be referred to as a test strip or a test element, where all three terms can 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, containing at least one test chemical substance for detecting at least one analyte. Specifically, the test chemical substance may be configured to cause a color change, for example, a change in color due to the presence of the analyte. The color change may, for example, depend on the concentration of the analyte in a bodily fluid sample. Specifically, the reagent test area may have visually detectable edges, such as detectable borders and/or boundaries, thereby contrasting the reagent test area with the rest of the optical test strip. As an example, an optical test strip may include at least one substrate, such as at least one carrier, having at least one test field applied thereto or integrated therein. Specifically, an optical test strip may further include at least one white area, such as a white field, specifically adjacent to, for example, surrounding or enclosing the reagent test area. Specifically, the contrast between the reagent test area and the white area surrounding it may be sufficient to allow visual detection of the edges and/or borders of the reagent test area. Additionally or alternatively, the substrate or carrier itself may be or may include a white area. As an example, at least one carrier may be strip-shaped, thus making the test element a test strip. These test strips are commonly used and available. An optical test strip may have a single reagent test area or multiple test areas containing the same or different test chemicals.

As used herein, the term "hypothetical reaction time value used in analytical measurements based on color-forming reactions" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term can refer to, but is not limited to, a numerical indication of the estimated reaction time in an analytical measurement. Specifically, a reaction time value can refer to the time elapsed for a color change reaction to occur in the reagent test area of an optical test strip. As an example, the hypothetical reaction time value may be provided by the user, such as the user performing the analytical measurement. Specifically, in a measurement, information such as the time it takes for the sample to be applied to the reagent test area may be required from the user, allowing for the assumption and/or prediction of a reaction time value (also referred to as a hypothetical reaction time value). Specifically, a hypothetical reaction time value can refer to the assumed and/or estimated time between the application of the sample to the reagent test area and the measurement, i.e., between triggering the color change reaction and capturing an image of the reagent test area. Therefore, as an example, a hypothetical reaction time value may also be referred to as a hypothetical capture time value, such as hypothetical values for capture time values, as will be outlined below. As used herein, the term "hypothetical reaction time value," or synonymously, the term "hypothetical capture time value," is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term can refer to, but is not limited to, a numerical indication of a hypothetical and/or predicted reaction time (i.e., the time during which a chemical reaction, specifically a color change reaction, has occurred). In particular, a hypothetical reaction time value can refer to the time during which a chemical reaction occurs, and therefore may also be referred to as the chemical reaction time and/or color change reaction time. Specifically, a hypothetical reaction time value can be an estimated and/or predicted time value, for example, based on user-provided instructions. Therefore, a hypothetical reaction time value may differ from the actual reaction time that may have elapsed in the color change reaction of the reagent test area. In analytical measurements, a hypothetical reaction time value can be used to determine analyte concentration from color formation values. Additionally or alternatively, a hypothetical reaction time value can refer to a numerical indication of a hypothetical and/or predicted reaction time range, i.e., the time range during which a chemical reaction, specifically a color change reaction, has occurred. Therefore, as an example, instead of indicating a numerical value in time, such as "18 seconds," it is assumed that the reaction time value can additionally or alternatively indicate a numerical range of time, such as a time range, for example, "within 1 minute" or "between 13 and 45 seconds."

The term "color formation value" can refer to any numerical indication of the color of the reagent test area of a test strip, such as a numerical representation, specifically generated by a color change detection reaction of the test chemical substance. Specifically, the color numerically indicated by the color formation value can be correlated with the analyte concentration of the bodily fluid sample applied to the corresponding optical test strip. Thus, as an example, color, and therefore the color formation value, can be correlated with blood glucose levels and/or blood glucose concentrations. Furthermore, the color of the reagent test area may change over time, and therefore the color formation value may change over time. Therefore, the correlation between the color formation value and the analyte concentration can further be time-dependent. Thus, in analytical measurements, the analyte concentration can be determined from the color formation value by further using a hypothetical reaction time value.

As an example, the correlation can be represented by one or more functions, where the analyte concentration can be determined by interpolating a hypothetical reaction time value and a color formation value into the function. Specifically, the hypothetical reaction time value can be interpolated as a numerical value. Alternatively or alternatively, different mathematical correlation functions can be used for different hypothetical reaction time values. Thus, for a first time range of hypothetical reaction time values, a first mathematical correlation function can be used to determine the analyte concentration from the color formation value, and for a second time range of hypothetical reaction time values, a second mathematical correlation function can be used. As an example, the mathematical function "f" can be used for hypothetical reaction time values "between 13 seconds and 45 seconds," where the mathematical function "g" can be used for hypothetical reaction time values "between 45 seconds and 120 seconds." As an example, in the case where the hypothetical reaction time value indicates "longer than 120 seconds," the analytical measurement can even be aborted, for example, by displaying an error message on the display of a mobile device. Further, specifically, the function "g" can be determined from the function "f" corrected by using a predetermined correction function (e.g., applying a correction value). Other forms of functions can be used to represent the correlation between analyte concentration and color formation value, such as lookup tables or interpolation. As an example, suppose the reaction time value is available for selecting a function, such as "f" or "g," to determine the analyte concentration from the color formation value; however, when calculating the analyte concentration itself, i.e., when using and/or applying the mathematical function "f" or "g," it is assumed that the reaction time value may not be used or may even be irrelevant.

As used herein, the term "assessing reasonableness" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term can refer to, but is not limited to, the process of quantitatively and/or qualitatively determining the credibility and/or probability of a component and/or data. As an example, reasonableness can be assessed using one or more characteristic parameters and/or properties of the component and/or data. These one or more characteristic parameters and/or properties can be compared individually or in a predetermined combination with one or more conditions. Thus, as an example, the reasonableness of a hypothetical reaction time value can be assessed using the properties of one or more characteristic parameters and/or desired characteristics, specifically by using a color expectation range, which will be described in further detail below. Specifically, for a hypothetical reaction time value, the corresponding color formation value can be compared with a color expectation range, for example, with one or more comparison values, reference values, or standard values, where the comparison can be qualitative or quantitative and can produce a binary result such as "reasonable" or "unreasonable"/"non-reasonable". However, alternatively or otherwise, the comparison can produce a quantitative result, such as a number indicating the degree of reasonableness.

As used herein, the term "color expectation range" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, a continuous and/or discrete range of a color space within which colors are expected and/or predicted as a range for predefined reaction time values, i.e., a range for predefined reaction time values. Thus, by way of example, a color expectation range may be one or more of a one-dimensional, two-dimensional, or three-dimensional region of a color space including at least one of a comparison value, a reference value, and/or a standard value, for predefined reaction time value ranges. Therefore, a color expectation range may be or may include a continuous region and/or corridor including at least one desired color value. However, additionally or alternatively, a color expectation range may be or may include a discrete collection of desired colors, such as including discrete comparison values, reference values, and/or standard values. Specifically, a color expectation range, particularly a two-dimensional or three-dimensional color expectation range, may have any form and/or shape.

Specifically, in order to derive the desired color range, timely capture time values and allowable delayed capture time values can be used to set and/or predefine a range of reaction time values, and then, in the measurement method, a reasonableness assessment can be based on this range of reaction time values.

As used herein, the term "method for determining at least one color expectation range for evaluating the reasonableness of hypothetical reaction time values used in analytical measurements based on color formation responses," also simply "method for determining," is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, a method for determining a color expectation range as defined above, specifically based on predefined reaction time values, i.e., based on timely capture time values and permissible delayed capture time values. Specifically, the term may refer to a method by which, as a result, at least one range defining a color formation value, particularly for timely capture time values and permissible delayed capture time values, as will be further outlined below.

As used herein, the term "capture time value" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term can refer to, but is not limited to, a numerical indication of the time elapsed between sample application (such as sample application in step b of the determining method) and image capture (such as image capture in step c). Specifically, the capture time value can be specific to a captured image. In particular, the capture time value can refer to the actual time elapsed between sample application and image capture and may therefore differ from the assumed reaction time value used in analytical measurements.

As used herein, the term "timely capture time value" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, capture time values within a predefined time range considered "on time" and "timely." Specifically, all capture time values within a predefined time range that meet a predefined timeliness requirement can be termed "timely capture time values." Specifically, timely capture time values may be or may be included within a predefined time range, such as capture time values within a previously set and/or predefined time range. As an example, the predefined time range and/or predefined timeliness requirement may depend on the characteristics of a color change detection reaction through an optical test strip, i.e., through a reagent test area of the optical test strip. Therefore, as an example, the predefined time range may be between 5 seconds and 300 seconds. Specifically, the predefined time range may be between 5 seconds and 180 seconds. More specifically, the predefined time range may be between 5 seconds and 120 seconds. More specifically, the predefined time range can be between 10 seconds and 60 seconds. More specifically, the predefined time range can be between 13 seconds and 45 seconds. Other predefined time ranges for defining the capture time value as the timely capture time value are possible.

As used herein, the term "delayed capture time value" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, capture time values that include predefined time lags, such as predefined delays. In particular, a delayed capture time value may refer to a capture time value that is delayed relative to a predefined time range considered "on time" and/or "timely." Specifically, all capture time values greater than the upper limit of the predefined range, such as values outside the predefined range in the direction of increasing time, may be referred to as "delayed capture time values." In particular, a delayed capture time value may refer to a numerical indication of the sum of a delay (specifically a preset and/or known delay) and the upper limit of a predefined range and/or predefined on-time requirement for a timely capture time value. Thus, a delayed capture time value may differ from a timely capture time value, except that at least the delay... As an example, throughout the specification, the delay may be referred to as d, where d may be or may include positive or negative values.

As used herein, the term "training set" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, multiple elements having known and/or predetermined differences and/or similarities. In particular, a training set can be used to train a trainable model, such as a model that can be further trained and/or updated based on additional information (e.g., collected from the training set).

Specifically, the term "optical test strip training set" may refer to, but is not limited to, multiple optical test strips as defined above. In particular, the optical test strip training set provided in step a) includes multiple optical test strips, such as optical test strips that are identical in structure and/or design.

As used herein, the term "body fluid sample training set" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, multiple samples having at least one known and/or predetermined analyte concentration (e.g., determined in a laboratory setting). In particular, a body fluid sample training set may include multiple body fluid samples as defined above, wherein for one or more of these samples, quantitative and/or qualitative analytical measurements (such as the concentration of at least one analyte in the sample) are known. Specifically, the number of samples included in the sample training set may differ from the number of optical test strips in the optical test strip training set. However, alternatively, the number of samples in the sample training set may be equal to the number of optical test strips in the optical test strip training set.

As used herein, the term "mobile device" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, mobile electronic devices, and more precisely, mobile communication devices such as cellular phones or smartphones. Additionally or alternatively, a mobile device may also refer to a tablet computer or another type of portable computer having at least one camera. Further, as will be outlined below, a mobile device may optionally include other elements, such as one or more processors.

As used herein, the term "camera" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, a device having at least one imaging element configured to record or capture spatially resolved one-dimensional, two-dimensional, or even 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 refer to data recorded using a camera, such as multiple electronic readings from an imaging device, such as pixels of a camera chip.

Therefore, specifically, the term "image training set" can refer to multiple images, i.e., multiple image data recorded using a camera (e.g., a camera as defined above). Specifically, an image training set can refer to a stack of digital images, such as at least a portion of one or more reagent test areas in an optical test strip training set. Specifically, an image training set includes a first image training subset and a second image training subset. As an example, an image training set may include images of each of the reagent test areas in an optical test strip training set, where, for example, one or more bodily fluid samples may have been applied to the reagent test areas, for example, before the images were captured. Specifically, an image training set can be used to determine a training set of color formation values for the reagent test areas of an optical test strip training set, such as multiple color formation values for the optical test strip training set. One or more of the images in the image training set may be images of more than one reagent test area. Therefore, as an example, the number of images in the image training set may differ from the number of optical test strips in the optical test strip training set. However, it is also possible for the number of images in the image training set to be equal to the number of optical test strips in the optical test strip training set. Specifically, as an example, the image training set may include, for instance, individual images of each of the reagent test areas in the optical test strip training set.

Specifically, each image in the image training set can be captured at a timely capture time value and/or a delayed capture time value. Specifically, images in the image training set included in the first image training subset are captured at timely capture time values, wherein the timely capture time values can be different for one or more images in the first image training subset. Specifically, the timely capture time values for one or more images in the first image training subset can be known or even preset. Further, images in the image training set included in the second image training subset are captured at delayed capture time values, wherein the delayed capture time values can be different for one or more images in the second image training subset. Specifically, the delayed capture time values for one or more images in the second image training subset can be known or even preset. Therefore, specifically, each image in the image training set can be assigned and/or concatenated to at least one timely capture time value or a delayed capture time value.

In addition to at least one camera chip or imaging chip, the camera may also include additional elements, such as one or more optical elements, for example, one or more lenses. As an example, the camera may be a fixed-focus camera having at least one lens that is fixedly adjusted relative to the camera. However, alternatively, the camera may also include one or more variable lenses that are automatically or manually adjusted. The invention is particularly applicable to cameras commonly used in mobile applications (e.g., laptops, tablets, or specifically mobile phones, such as smartphones). Therefore, specifically, the camera may be part of a mobile device that, in addition to at least one camera, includes one or more data processing devices such as one or more data processors. However, other cameras are also feasible.

Specifically, the camera can be a color camera. Therefore, color information, such as color values for the three colors R, G, and B, can be provided or generated for each pixel, also known as color channels. A larger number of color values are also possible, such as four color values for each pixel, for example, R, G, G, and B. Color cameras are generally known to those skilled in the art. Thus, as an example, a camera chip can consist of multiple color sensors, each chip containing three or more color sensors, such as color recording pixels, such as one pixel for red (R), one pixel for green (G), and one pixel for blue (B). For each pixel, such as for R, G, and B, individual values, such as digital values in the range of 0 to 255, can be recorded pixel by pixel according to the intensity of the corresponding color. As an example, a quadruple, such as R, G, G, and B, can be used instead of a color triple, such as R, G, and B. The color sensitivity of a pixel can be generated by a color filter or by the appropriate inherent sensitivity of the sensor elements used in the camera pixel. These techniques are well known to those skilled in the art.

As used herein, the term "processor" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, any logical circuit system configured to perform basic operations of a computer or system; and/or, generally, means configured to perform computation or logical operations. In particular, a processor may be configured to process basic instructions that drive a computer or system. As an example, a processor may include at least one arithmetic logic unit (ALU), at least one floating-point unit (FPU) (such as a math coprocessor or numerical coprocessor), multiple registers (specifically registers configured to provide operands to the ALU and store the results of operations), and a memory (such as L1 and L2 caches). In particular, a processor may be a multi-core processor. Specifically, a processor may be or may include a central processing unit (CPU). Additionally or alternatively, a processor may be or may include a microprocessor; therefore, specifically, the elements of a processor may be included in a single integrated circuit (IC) chip. Alternatively or concurrently, the processor may be or may include one or more application-specific integrated circuits (ASICs) and/or one or more field-programmable gate arrays (FPGAs), etc.

The processor, specifically the processor used in step d) of the determining method, can be, for example, a separate processor, such as a standalone processor or a processor integrated into a computer or computer network, independent of the mobile device. Alternatively, however, the processor can be integrated into the mobile device used in step c) to capture the image training set. Therefore, specifically, the processor can be the processor of the mobile device.

Step e) of the determination method may include deriving at least two color expectation ranges. Specifically, the at least two color expectation ranges may be complementary, for example, sharing at least one boundary. Thus, as an example, the determination method may be configured to determine two complementary color expectation ranges.

As an example, for the first in the expected range of complementary colors, the delay, specifically referred to as _d1 , may specifically not exceed a predefined acceptance threshold. Specifically, the acceptance threshold may be referred to as _da throughout the specification. The acceptance threshold _da may be further lower than the expiration threshold _dmax . Therefore, specifically _d1 < _da < _dmax . Further, for the second in the expected range of complementary colors, the delay, specifically referred to as _d2 , may be equal to _da or may lie between the acceptance threshold _da and the expiration threshold _dmax . Therefore, specifically _da ≤ _d2 ≤ _dmax .

Therefore, step e) of the determination method may include deriving at least two complementary color expectation ranges, wherein the first color expectation range may be or may include colors expected for a hypothetical reaction time value range, specifically color formation values, the hypothetical reaction time value range including hypothetical reaction time values that differ from the actual and/or true reaction time values by less than the acceptance threshold _da , specifically by less than an acceptable delay. Specifically, the first color expectation range may be or may include colors derived and/or determined from images captured at timely capture time values and delayed capture time values, specifically color formation values, wherein the delay of the delayed capture time value is less than an acceptable delay. Further, the second color expectation range, for example, derived in step e), may be or may include colors expected for a hypothetical reaction time value range, specifically color formation values, the hypothetical reaction time value range including hypothetical reaction time values that differ from the actual and/or true reaction time values by at least the acceptance threshold _da , specifically by at least the acceptable delay, but not significantly different from the expiration threshold _dmax , specifically not significantly different from the expiration delay. Specifically, the second color expectation range may be or may include colors derived and/or determined from an image captured at a delayed capture time value, specifically color formation values, wherein the delay of the delayed capture time value is greater than or equal to an acceptable delay and less than or equal to a full-time delay. In other words, the first color expectation range may include color formation values expected for a hypothetical reaction time that differs from the actual and/or real reaction time by less than an acceptable delay, while the second color expectation range may include color formation values expected for a hypothetical reaction time that differs from the actual and/or real reaction time by at least an acceptable delay but not more than a full-time delay.

Step d) may further include labeling the color formation values in the color formation value training set with information about the capture time value, i.e., with an immediate capture time value or a delayed capture time value. Specifically, this labeling may be considered in step e). In particular, the information about the capture time value may include information about whether the image was captured at an immediate or delayed capture time value, wherein for delayed capture time values, further information may be included, specifically whether the delay is below or above the at least one predefined expiration threshold and optionally below or above an acceptance threshold.

In step e), the color expectation range may include at least 80% of the color formation values for the color formation of the reagent test area of the optical test strip in the optical test strip training set determined from images captured at one or more of the timely capture time value and the allowable delayed capture time value. Specifically, in step e), the color expectation range may include at least 85% of the color formation values for the color formation of the reagent test area of the optical test strip in the optical test strip training set determined from images captured at one or more of the timely capture time value and the allowable delayed capture time value. More specifically, in step e), the color expectation range may include at least 90% of the color formation values for the color formation of the reagent test area of the optical test strip in the optical test strip training set determined from images captured at one or more of the timely capture time value and the allowable delayed capture time value. More specifically, in step e), the color expectation range may include at least 95% of the color formation values for the color formation of the reagent test area of the optical test strip in the optical test strip training set determined from images captured at one or more of the timely capture time value and the allowable delayed capture time value. More specifically, in step e), the color expectation range may include at least 97% of the color formation values for the color formation of the reagent test area of the optical test strip in the optical test strip training set determined from images captured at one or more of the timely capture time value and the allowable delayed capture time value. More specifically, in step e), the color expectation range may include at least 99% of the color formation values for the color formation of the reagent test area of the optical test strip in the optical test strip training set determined from images captured at one or more of the timely capture time value and the allowable delayed capture time value.

As an example, the color expectation range may be or may include at least one polygon. Specifically, the color expectation range may be or may include a two-dimensional polygon whose edges may correspond to color formation values in a two-dimensional color space (such as a color plane with at least two colors). Alternatively or additionally, the color expectation range may be or may include a three-dimensional polyhedron whose edges may correspond to color formation values in a three-dimensional color space. Furthermore, instead of edges corresponding to color formation values, the edges may be spaced apart from the color formation values such that 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 formation values may be covered by the polygon and/or polyhedron, the color formation values being for the color formation of the reagent test area of the optical test strip of the optical test strip training set determined from an image captured at one or more of the immediate capture time value and the permissible delayed capture time value.

Specifically, the derivation in step e) may include: determining an envelope comprising 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 formation value for the color formation of the reagent test area of the optical test strip in the training set of the optical test strip determined from an image captured at one or more of the timely capture time value and the allowable delayed capture time value; and further extending the envelope by a predetermined safety factor.

As used herein, the term "envelope" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a particular or customary meaning. Specifically, the term may refer to, but is not limited to, elements and/or entities that encompass and/or cover at least one set of data. In particular, the envelope may encompass (i.e., in at least one color plane and/or color space) 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 formation values for the reagent test area of the optical test strip in the training set of the optical test strip, determined with respect to the color formation of the optical test strip at one or more of the immediate capture time value and the permissible delayed capture time value, wherein the envelope may be determined mathematically and/or graphically.

Specifically, step e) may include, in a subsequent step, extending the envelope by a predetermined safety factor. Specifically, the safety factor may be predetermined and/or preset, such as a safety factor taking into account the size and/or volume of the envelope. As an example, the safety factor may be or may include a function dependent on the envelope, i.e., dependent on the size and/or volume of the envelope. As an example, the envelope may be extended such that the size and/or volume of the extended envelope may exceed the size and/or volume of the envelope by a factor of at least 1.1, specifically at least 1.2, more specifically at least 1.5. As an example, the envelope may be extended such that 99% or even 100% of the color formation values determined from images captured at one or more of the timely capture time value and the permissible delayed capture time value are covered. Additionally or alternatively, the safety factor may take into account deviations in the distribution of color formation values, such as the standard deviation σ of the color formation values for the color formation of the reagent test area determined from images captured at one or more of the timely capture time value and the permissible delayed capture time value. Therefore, as an example, the envelope can be extended by a coefficient to cover a range of at least 4σ, preferably at least 5σ, and more preferably at least 6σ.

Specifically, the expansion can be an isometric expansion, such as a uniform and/or consistent expansion of the envelope. As an example, a uniform expansion of the envelope is possible when the color formation values are isometrically distributed within the envelope. However, non-uniform expansion is also possible. Specifically, the envelope can be non-uniformly and/or unevenly expanded, i.e., based on and/or depending on the weighted distribution of the color formation values within the envelope.

Specifically, step e) may include using at least one machine learning algorithm, specifically by training a trainable model via a training set of color-forming values. As used herein, the term "machine learning algorithm" is a broad term and is given a common and conventional meaning to those skilled in the art, and is not limited to a specific or custom-defined meaning. Specifically, the term may refer to, but is not limited to, a mathematical model that can be trained using a training data record (such as including training input data and corresponding training output data). In particular, the training output data of the training data record may be the expected result when the machine learning algorithm is given the same training data record as training input data. As an example, the deviation between the expected result and the actual result produced by the algorithm can be observed and evaluated by a "loss function". The loss function can be used as feedback to adjust the parameters of the internal processing chain of the machine learning algorithm. Machine learning algorithms may include decision trees, Naive Bayes classification, nearest neighbor, 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, a machine learning algorithm can be trained using a training set of color formation values as input data and corresponding information about timely capture time values and/or delayed capture time values as output data. Specifically, the output data may be or may include information about determining the corresponding color formation values of the reagent test area of an optical test strip for an optical test strip training set from images captured at the timely capture time value and the permissible delayed capture time value, or at the end of the capture time (i.e., later than the time required to safely determine an acceptable analyte concentration). Specifically, the machine learning algorithm may be or may include a trainable color expectation range model, i.e., a shape and/or form describing the color expectation range, wherein feedback for adjusting parameters of the model's internal processing chain may be specifically determined quantitatively or qualitatively based on whether the color formation value corresponding to the timely capture time value and/or the permissible delayed capture time value (i.e., the color formation value for an acceptable capture time value) is within the color expectation range. Other forms of feedback are also possible.

Specifically, in step d), color formation values can be determined for at least two color channels, such as for at least two color channels selected from a group consisting of: green channel (G), blue channel (B), and red channel (R). More specifically, in step e), a desired color range can be derived for the at least two color channels for which color formation values were determined in step d).

Further, the method may include step f): attaching at least one optical test strip of the optical test strip training set to a color reference card, the color reference card including a plurality of color reference fields having known reference color values. Specifically, step f) may be performed prior to step c). Furthermore, at least one image of the image set captured in step c) may further display at least a portion of the color reference card, specifically one or more of the color reference fields. As used herein, the term "color reference card" is a broad term and is given a common and customary meaning to those skilled in the art, and is not limited to a specific or customary meaning. Specifically, the term may refer to, but is not limited to, any item having (disposed therein or disposed on, such as on at least one surface) a plurality of color reference fields having known color characteristics or optical characteristics, such as having a plurality of colored fields (which have known reference color values). Furthermore, the color reference card may include a plurality of gray reference fields having known gray levels. As an example, a color reference card may be a planar card comprising at least one substrate having (on at least one surface and/or disposed therein) a plurality of color reference fields having known color values and a plurality of gray reference fields having known gray levels. Specifically, the substrate may have a flat surface on which the color reference fields and gray reference fields are disposed. As an example, the substrate may be or may include one or more of a paper substrate, a cardboard substrate, a plastic substrate, a ceramic substrate, or a metal substrate. Layered substrates are also possible. As an example, the substrate may be sheet-like or flexible. However, it should be noted that the substrate may also be incorporated into articles, such as into the walls of boxes, vials, containers, medical consumables (such as test strips), etc. The color reference card may also be wholly or partially integrated into an optical test strip. At least one image of at least a portion of the reagent testing area of the optical test strip may wholly or partially include an image of at least a portion of the color reference card.

In another aspect of the invention, a measurement method is disclosed for performing analytical measurements based on color formation reactions using a mobile device having a camera and a processor. This measurement method includes the following steps, which, as an example, may be performed in a given order. However, it should be noted that a different order is also possible. Furthermore, one or more method steps may be performed once or repeatedly. Further, two or more method steps may be performed simultaneously or in a timely overlapping manner. This measurement method may include other method steps not listed.

The measurement method includes:

i) Provide at least one optical test strip having at least one reagent test area;

ii) Apply the body fluid sample to the reagent testing area of the optical test strip;

iii) Using the camera, capture at least a portion of the reagent test area to which bodily fluids have been applied.

At least one image;

iv) Determine a hypothetical reaction time value corresponding to the time elapsed between the hypothetical time of applying the sample in step ii) and the time elapsed between capturing the image in step iii); v) Specifically, using the image, determine the test area for the reagent by using a processor.

The color value of at least one color channel formed by the color;

vi) For the at least one color channel, compare the color formation value with at least one color expectation range determined by performing the determination method according to any one of the preceding claims;

vii) If the color formation value is outside the range of at least one color expectation, then the assumption is considered reversed.

The measurement method should be terminated if the time value is deemed unreasonable; and

viii) If the color formation value is within the expected color range, then the assumed reaction time value is considered to be...

It is reasonable to determine the concentration of analytes in body fluid samples by using the color formation value and an optional assumed reaction time value.

For the definition of this measurement method, refer to the description of the determination method above or as will be further described in detail below. Specifically, for this measurement method, optical test strips of the same type as those in the determination method outlined above can be used. Thus, as an example, the optical test strips provided in step i) of this measurement method can be of the same or at least similar type to multiple optical test strips in the optical test strip training set provided in step a) of the determination method as described above or in more detail below. However, the bodily fluid sample can be a bodily fluid sample from the user, whose analyte concentration will be determined and may therefore have been previously unknown.

Specifically, in step vii), it is assumed that the reaction time value may differ from the actual capture time value by more than an acceptable difference. Therefore, in step viii), it is assumed that the reaction time value may differ from the actual capture time value by more than an acceptable difference.

Step vi) may include comparing the color formation value with at least one first color expectation range and with at least one second color expectation range determined by the determination method as described herein. Specifically, in step vii), if the color formation value is outside the first and second color expectation ranges, the assumed capture time may be considered unreasonable and the measurement method may be terminated. Furthermore, in step viii), for color formation values within at least one first color expectation range and within at least one second color expectation range, different algorithms may be used to determine the concentration of the analyte from the color formation value.

Specifically, the measurement method in step viii) may include:

- If the color formation value is within the first color expectation range, then the assumed reaction time is considered to be...

The value is reasonable, and the concentration of the analyte is determined by using the color formation value and the assumed reaction time value; and

- If the color formation value is within the second color expectation range, then the assumed reaction time is considered to be...

The value is reasonable, and the concentration of the analyte is determined by using the color formation value and a predefined delay added to the assumed reaction time value for the second color expectation range.

The measurement method may further include an intensity check, such as checking whether the intensity of the color formation value is higher or lower than at least one intensity threshold. Specifically, the measurement method may be terminated if the color formation value is outside a predefined intensity range, for example, below a lower intensity threshold or above a higher intensity threshold.

The measurement method may further include step ix): capturing at least one image of at least a portion of the reagent test area to which no bodily fluid has been applied using the camera. Specifically, step ix) may be performed prior to step ii). Thus, as an example, the measurement method may include capturing at least one second image, specifically a blank image of the reagent test area to which no bodily fluid sample has been applied.

Further, the measurement method may include step x): attaching an optical test strip to a color reference card, the color reference card comprising a plurality of color reference fields having known reference color values. Specifically, the color reference card may be of the same type as the color reference card optionally used in the determination method described above. Specifically, step x) may be performed before step iii) of the measurement method, and optionally before step ii), wherein specifically, the image captured in step iii) may further display at least a portion of the color reference card, specifically one or more of the color reference fields.

The application in step ii) may further include, specifically, user confirmation that a body fluid sample has been applied or has been applied to the reagent testing area of the optical test strip. Therefore, as an example, the application in step ii) may be or may include user confirmation that a body fluid sample has been applied, i.e., by pressing a button and/or other forms of confirmation, such as through interaction with a mobile device. Specifically, step ii) of the measurement method may include prompting the user to perform one or more of the following actions: applying a body fluid sample to the reagent testing area of the optical test strip, and confirming that the body fluid sample has been applied to the reagent testing area of the optical test strip. Specifically, when performing step ii), the user may be prompted to apply a body fluid sample and/or may be prompted to confirm sample application, for example by providing corresponding instructions on the display of the mobile device and/or as voice commands.

In another aspect of the invention, a determination system is disclosed for determining at least one color expectation range for assessing the reasonableness of assumed reaction time values used in analytical measurements based on color formation reactions, the system comprising:

A) At least one mobile device having at least one camera;

B) Optical test strip training set, where each optical test strip has a reagent testing area;

C) A training set of body fluid samples, which includes multiple body fluid samples; and

D) At least one processor configured to:

- Retrieve the image training set, which includes images captured by the camera at the time of capture.

The image training set includes at least a portion of images of at least some of the reagent test areas of the optical test strip training set with applied body fluid samples, captured at an interval time. Specifically, this is the first image training subset captured in step c) of the determination method described above. The capture time value refers to the time elapsed between the application of the sample and the capture of the image. The image training set further includes images of at least some of the reagent test areas of the optical test strip training set with applied body fluid samples, captured by the camera at a delayed capture time value. Specifically, this is the second image captured in step c) of the determination method described above.

Like a training subset;

- Determine a color formation value training set from the images in this image training set, the color formation value training...

The set includes color formation values for at least one color channel, which is used for optical test strip training sets for timely capture time values and delayed capture time values.

Color formation in the reagent test area of the test strip; and

- Derive at least one color period for at least one color channel from the color formation value training set.

The color expectation range defines the expected range of color formation values for timely capture time values and allowable delayed capture time values, wherein for allowable delayed capture time values, the delay d does not exceed at least one predefined expiration threshold _dmax .

Specifically, the delay d can be less than or equal to the expiration threshold _dmax . Therefore, as an example, d ≤ _dmax . Alternatively, the delay d can be less than the expiration threshold _dmax . Therefore, as an alternative, d < _dmax .

The processor of the system can be, for example, a separate processor, such as a standalone processor or a processor integrated into a computer or computer network, independent of the at least one mobile device. Alternatively, the processor can be integrated into the mobile device.

The determining system may further include:

E) At least one color reference card configured to releasably attach an optical test strip to it, the color reference card comprising a plurality of color reference fields having known reference color values, wherein

The images in the training set further show at least a portion of the color reference card, specifically one or more of the color reference fields.

For most definitions of this determining system, reference can be made to the description of the determining method as described above or as will be further described in detail below. Specifically, the determining system can be configured to perform the determining method as described herein. Specifically, the determining system can be configured to perform at least steps d) and e) of the determining method as described herein.

This document further discloses and proposes a computer program including instructions that, when executed by a determining system (specifically, a determining system as described herein), cause the determining system to perform at least steps d) and e) of the determining method as described herein. Therefore, specifically, the computer program may include computer-executable instructions for performing the determining method according to the invention in one or more embodiments covered herein when executed on the determining system, i.e., on at least one processor of the determining system, for example, integrated into a computer or computer network. Specifically, the computer program may be stored on a computer-readable data carrier and/or a computer-readable storage medium.

Therefore, this document further discloses and proposes a computer-readable storage medium including instructions that, when executed by a determining system (specifically, a determining system as described herein), cause the determining system to perform at least steps d) and e) of the determining method as described herein.

As used herein, the terms "computer-readable data carrier" and "computer-readable storage medium" can specifically refer to non-transitory data storage devices, such as hardware storage media having computer-executable instructions stored thereon. Computer-readable data carriers or storage media can specifically be or can include storage media such as random access memory (RAM) and/or read-only memory (ROM).

This document further discloses and proposes a computer program product having program code tools to perform the determination method according to the invention as covered herein, when the program is executed on a determined system, i.e., on at least one processor of the determined system, for example, integrated into a computer or computer network. Specifically, the program code tools may be stored on a computer-readable data carrier and/or a computer-readable storage medium.

This document further discloses and proposes a data carrier having a data structure stored thereon, which, after being loaded into a computer or computer network, such as the working memory or main memory of the computer or computer network, can execute a determination method according to one or more embodiments disclosed herein.

This document further discloses and proposes a computer program product having program code tools stored on a machine-readable medium, so as to perform a determination method according to one or more 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 that is a tradable product. The product can generally exist in any format (such as in paper format) or reside on a computer-readable data carrier and/or a computer-readable storage medium. Specifically, the computer program product can be distributed on a data network.

Furthermore, this invention discloses and proposes a modulated data signal containing instructions readable by a computer system or computer network for performing a determination method according to one or more embodiments disclosed herein.

In another aspect of the invention, a mobile device having at least one camera and at least one processor is disclosed. This mobile device is configured to perform at least steps iv) to viii) of the measurement method as described herein. Therefore, regarding the definitions of terms, refer to the foregoing description of the measurement method as described herein.

This document further discloses and proposes a computer program including instructions that, when executed by a mobile device having a camera and a processor, specifically a mobile device as described herein, cause the mobile device to perform at least steps iv) to viii) of the measurement method. Therefore, specifically, the computer program may include computer-executable instructions for performing the measurement method according to the invention in one or more embodiments covered herein when executed on the processor of the mobile device. Specifically, the computer program may be stored on a computer-readable data carrier and/or a computer-readable storage medium.

Therefore, this document further discloses and proposes a computer-readable storage medium including instructions that, when executed by a mobile device having a camera and a processor, specifically by the mobile device described herein, cause the mobile device to perform at least steps iv) to viii) of the measurement method as described herein.

This document further discloses and proposes a computer program product with program code tools to perform the measurement methods according to the invention as covered herein in one or more embodiments, when the program is executed on a mobile device, i.e., on at least one processor of the mobile device, for example, integrated into a computer or computer network. Specifically, the program code tools may be stored on a computer-readable data carrier and/or a computer-readable storage medium.

This document further discloses and proposes a data carrier having a data structure stored thereon, which, after being loaded into a computer or computer network, such as the working memory or main memory of the computer or computer network, can execute measurement methods according to one or more embodiments disclosed herein.

This document further discloses and proposes a computer program product having program code tools stored on a machine-readable medium, so as to perform measurement methods according to one or more 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 that is a tradable product. The product can generally exist in any format (such as in paper format) or reside on a computer-readable data carrier and/or a computer-readable storage medium. Specifically, the computer program product can be distributed on a data network.

Furthermore, this invention discloses and proposes a modulated data signal containing instructions readable by a computer system or computer network for performing a measurement method according to one or more embodiments disclosed herein.

In another aspect of the invention, a kit is disclosed for determining the concentration of at least one analyte in a bodily fluid sample, specifically a user's bodily fluid sample. The kit includes a mobile device as described above, specifically configured to perform at least steps iv) to viii) of the measurement method as described herein. The kit further includes at least one optical test strip having at least one reagent test area.

The methods and apparatus according to the invention offer numerous advantages over similar methods and apparatus known in the art. Specifically, the methods and apparatus described herein increase measurement safety compared to methods and apparatus known in the art. Specifically, for example, since color formation values must be within the desired color range, particularly when performing this measurement method, measurement safety can be increased by providing effective fail-safe mechanisms to determine analyte concentrations. Therefore, specifically, the provided methods and apparatus can increase measurement safety because not all and all measured color values are converted into analyte concentrations, e.g., into blood glucose levels. Instead, the methods and apparatus of the invention allow for the detection of incorrect user information regarding sample application time.

Furthermore, the proposed method and apparatus improve measurement safety and accuracy compared to known methods and apparatus. Specifically, the method may include preventing the determination of analyte concentration in body fluids if a reasonableness assessment cannot be performed. Therefore, erroneous and/or biased analytical measurements may become less likely.

Furthermore, the proposed method and apparatus enable improved user handling and/or improved user-friendliness for analytical measurements, allowing secure analytical measurements to be performed by capturing only one image instead of at least two. Specifically, the total time required to perform analytical measurements can be reduced compared to known methods and apparatuses.

In summary, and without excluding other possible embodiments, the following embodiments are conceivable:

Example 1: A method for determining at least one color expectation range for evaluating the reasonableness of assumed reaction time values used in analytical measurements based on color-forming reactions, the method comprising:

a) Provide an optical test strip training set, where each optical test strip has a reagent testing area;

b) Provide a training set of body fluid samples and apply at least one of the body fluid samples to the reagent test area of each optical test strip in the optical test strip training set;

c) Capture an image training set using at least one mobile device having at least one camera, the images

The training set includes

- A first image training subset, comprising at least a portion of images of at least some of the reagent test areas of the optical test strip training set to which a body fluid sample has been applied, captured at an in-time capture time value, the capture time value referring to the time elapsed between the application of the sample and the capture image in step b).

- At least one second image training subset, the at least one second image training subset comprising at least some of at least a portion of images of at least some of the reagent test areas of the optical test strip training set to which a body fluid sample has been applied, captured at a delayed capture time value;

d) Specifically, by using at least one processor, more specifically, the processor of the mobile device, a color formation value training set is determined from the images of the image training set, the color formation value training set including color formation values of at least one color channel, the color channel being used for color formation of the reagent test area of the optical test strip training set for timely capture time values and delayed capture time values; and

e) Derive from the color formation value training set at least one color expectation range for at least one color channel, the color expectation range defining the expected range of color formation values for timely capture time values and permissible delayed capture time values, wherein for permissible delayed capture time values, the delay d does not exceed at least one predefined expiration threshold _dmax .

Example 2: The determination method according to the foregoing examples, wherein step e) includes deriving at least two complementary color expectation ranges.

Example 3: According to the determination method described in the foregoing examples, for the first complementary color in the expected range, the delay _d1 does not exceed a predefined acceptance threshold _da that is lower than the expiration threshold _dmax , specifically _d1 < _da < _dmax , and for the second complementary color in the expected range, the delay _d2 is equal to _da or lies between the acceptance threshold _da and the expiration threshold _dmax , specifically _da ≤ _d2 ≤ _dmax .

Example 4: The determination method according to any one of the foregoing embodiments, wherein step d) further includes labeling the color formation values of the color formation value training set with information about the capture time value, i.e., labeling with an immediate capture time value or a delayed capture time value, wherein the labeling is specifically considered in step e), and the information about the capture time value may include information about whether the image was captured at an immediate capture time value or a delayed capture time value, wherein for a delayed capture time value, it includes further information about whether the delay is lower than or higher than the at least one predefined expiration threshold and optionally lower than or higher than the acceptance threshold.

Example 5: The determination method according to any one of the foregoing embodiments, wherein 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%, more specifically at least 99% of color formation values, which are for the color formation of the reagent test area of the optical test strip of the optical test strip training set determined from an image captured at one or more of an immediate capture time value and an allowable delayed capture time value.

Example 6: The determination method according to any one of the foregoing embodiments, wherein the derivation in step e) includes: determining an envelope comprising 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 formation value, the color formation value being for the color formation of the reagent test area of the optical test strip of the optical test strip training set determined from an image captured at one or more of the timely capture time value and the allowable delayed capture time value; and further expanding the envelope by a predetermined safety factor.

Example 7: The determination method according to any one of the foregoing embodiments, wherein step e) includes using at least one machine learning algorithm, specifically by training a trainable model via a training set of color forming values.

Example 8: The determination method according to any one of the foregoing embodiments, wherein in step d), a color formation value is determined for at least two color channels, specifically for at least two color channels selected from the group consisting of: green channel, blue channel and red channel.

Example 9: The determination method according to any one of the foregoing embodiments, wherein in step e), a color expectation range is derived for at least two color channels for which color formation values are determined in step d).

Example 10: The determination method according to any one of the foregoing embodiments, wherein the method further includes step f): attaching at least one optical test strip of the optical test strip training set to a color reference card, the color reference card including a plurality of color reference fields having known reference color values, wherein step f) is performed prior to step c), wherein at least one image of the image training set captured in step c) further displays at least a portion of the color reference card, specifically one or more of the color reference fields.

Example 11: A measurement method for performing analysis and measurement based on color formation response using a mobile device with a camera and a processor, the method comprising:

i) Provide at least one optical test strip having at least one reagent test area;

ii) Apply the body fluid sample to the reagent testing area of the optical test strip;

iii) Using the camera, capture at least a portion of the reagent test area to which bodily fluids have been applied.

At least one image;

iv) Determine a hypothetical reaction time value corresponding to the time elapsed between the hypothetical time of applying the sample in step ii) and the time elapsed between capturing the image in step iii); v) Specifically, using the image, determine the test area for the reagent by using a processor.

The color value of at least one color channel formed by the color;

vi) For the at least one color channel, compare the color formation value with at least one color expectation range determined by performing the determination method according to any one of the foregoing embodiments;

vii) If the color formation value is outside the range of at least one color expectation, then the assumption is considered reversed.

The measurement method should be terminated if the time value is deemed unreasonable; and

viii) If the color formation value is within the expected color range, then the assumed reaction time value is considered to be...

It is reasonable to determine the concentration of analytes in body fluid samples by using the color formation value and an optional assumed reaction time value.

Example 12: The measurement method according to the foregoing embodiments, wherein step vi) includes comparing the color formation value with at least one first color expectation range and at least one second color expectation range determined by the determination method according to any one of Examples 2 to 10, and wherein in step vii), if the color formation value is outside both the first color expectation range and the second color expectation range, the assumed capture time is considered unreasonable and the measurement method is terminated, and wherein in step viii), for the color formation value within the at least one first color expectation range and the at least one second color expectation range, the concentration of the analyte is determined from the color formation value using different algorithms.

Example 13: According to the measurement method described in the foregoing examples, in step viii):

- If the color formation value is within the first color expectation range, then the assumed reaction time is considered to be...

The value is reasonable, and the concentration of the analyte is determined by using the color formation value and the assumed reaction time value; and

- If the color formation value is within the second color expectation range, then the assumed reaction time is considered to be...

The value is reasonable, and the concentration of the analyte is determined by using the color formation value and a predefined delay added to the assumed reaction time value for the second color expectation range.

Example 14: A measurement method according to any one of the preceding two examples, wherein the method further includes step ix): capturing at least one image of at least a portion of a reagent test area to which no bodily fluid has been applied by using the camera, wherein step ix) is performed prior to step ii).

Example 15: A measurement method according to any one of the preceding two embodiments, wherein the method further includes step x): attaching the optical test strip to a color reference card, the color reference card including a plurality of color reference fields having known reference color values, wherein step x) is performed before step iii) and optionally before step ii), wherein the image captured in step iii) further shows at least a portion of the color reference card, specifically one or more of the color reference fields.

Example 16: The measurement method according to any one of the preceding five examples, wherein step ii) includes prompting the user to perform one or more of the following actions: applying a body fluid sample to the reagent test area of the optical test strip, and confirming that the body fluid sample has been applied to the reagent test area of the optical test strip.

Example 17: A determination system for determining at least one color expectation range for assessing the reasonableness of assumed reaction time values used in analytical measurements based on color-forming reactions, the determination system comprising:

A) At least one mobile device having at least one camera;

B) Optical test strip training set, where each optical test strip has a reagent testing area;

C) A training set of body fluid samples, which includes multiple body fluid samples;

D) At least one processor configured to:

- Retrieve the image training set, which includes images captured by the camera at the time of capture.

The image training set includes at least a portion of images of at least some of the reagent test areas of the optical test strip training set of the optical test strip training set with the applied body fluid sample, captured at an interval time. Specifically, it includes a first image training subset captured in step c) of the determination method according to any of the determination methods mentioned in the foregoing embodiments, where the capture time value refers to the time elapsed between the application of the sample and the capture of the image. The image training set further includes images captured by the camera at a delayed capture time value, specifically images of at least some of the reagent test areas of the optical test strip training set of the optical test strip training set with the applied body fluid sample.

The second image training subset captured in step c) of the determination method;

- Determine a color formation value training set from the images in this image training set, the color formation value training...

The set includes color formation values for at least one color channel, which is used for optical test strip training sets for timely capture time values and delayed capture time values.

Color formation in the reagent test area of the test strip; and

- Derive at least one color period for at least one color channel from the color formation value training set.

The color expectation range defines the expected range of color formation values for timely capture time values and allowable delayed capture time values, wherein for allowable delayed capture time values, the delay d does not exceed at least one predefined expiration threshold _dmax .

Example 18: The determination system according to the foregoing embodiments, wherein the determination system further includes:

E) At least one color reference card configured to releasably attach an optical test strip to it, the color reference card comprising a plurality of color reference fields having known reference color values, wherein

The images in the training set further show at least a portion of the color reference card, specifically one or more of the color reference fields.

Example 19: A determination system according to any one of the preceding two embodiments, wherein the determination system is configured to perform at least step d) and step e) of the determination method according to any one of the determination methods mentioned in the foregoing embodiments.

Example 20: A computer program including instructions that, when executed by a determining system, specifically a determining system according to any of the determining systems mentioned in the foregoing embodiments, cause the determining system to perform at least step d) and step e) of the determining method according to any of the foregoing embodiments relating to the determining method.

Example 21: A computer-readable storage medium including instructions that, when executed by a determining system, specifically by a system according to any of the determining systems mentioned in the foregoing embodiments, cause the determining system to perform at least steps d) and e) of the determining method according to any of the foregoing embodiments relating to the determining method.

Example 22: A mobile device having at least one camera and at least one processor, the mobile device being configured to perform at least steps iv) to viii) of a measurement method according to any of the foregoing embodiments relating to a measurement method.

Example 23: A computer program including instructions that, when executed by a mobile device having a camera and a processor, specifically by a mobile device according to the foregoing embodiments, cause the mobile device to perform at least steps iv) to viii) of the measurement method according to any one of the foregoing embodiments relating to the measurement method.

Example 24: A computer-readable storage medium including instructions that, when executed by a mobile device having a camera and a processor, specifically by a mobile device according to any of the preceding embodiments relating to a mobile device, cause the mobile device to perform at least steps iv) to viii) of the measurement method according to any of the preceding embodiments relating to a measurement method.

Example 25: A kit for determining the concentration of at least one analyte in a body fluid sample, the kit comprising the mobile device according to Example 21, the kit further comprising at least one optical test strip having at least one reagent test area.

Attached Figure Description

Preferably, in conjunction with the dependent claims, other optional features and embodiments will be disclosed in more detail in the following description of embodiments. These optional features, as will be recognized by those skilled in the art, can be implemented individually and in any feasible combination. The scope of the invention is not limited to the preferred embodiments. Embodiments are schematically depicted in the accompanying drawings. In these drawings, the same reference numerals refer to the same or functionally equivalent elements.

In the attached diagram:

Figure 1 shows an embodiment of the determination system and an embodiment of the kit;

Figure 2 shows an illustration of an embodiment of the determination method;

Figures 3 and 4 show an embodiment of the desired color range;

Figures 5 and 6 show illustrations of different embodiments of the measurement method;

Figure 7 shows a diagram illustrating the relationship between actual blood glucose values and blood glucose values determined using both conventional methods and systems and the methods and systems of the present invention for determining blood glucose concentration.

Detailed Implementation

Figure 1 illustrates an embodiment of the determination system 110. The determination system 110 includes at least one mobile device 112 having at least one camera 114. Further, the determination system 110 includes an optical test strip training set 116. The optical test strip training set 116 includes a plurality of optical test strips 118, each optical test strip 118 having a reagent testing area 120. Further, the determination system 110 includes a body fluid sample training set 122, which includes a plurality of body fluid samples 124. Specifically, for each of the body fluid samples 124 and the body fluid sample training set 122, the analyte concentration, such as glucose concentration, may be known. Furthermore, the determination system 110 includes at least one processor 126. The processor 126 of the determination system 110 may, for example, be a separate processor 126. However, alternatively, and as shown in Figure 1, the processor 126 may be integrated into the mobile device 112, such that the processor 126 may be the processor 126 of the mobile device 112.

In the determination system 110, the processor 126 is configured to retrieve an image training set comprising images captured by the camera 114 of the mobile device 112. Specifically, the image training set includes a first image training subset and a second image training subset, wherein the images of the first image training subset are captured at a timely capture time value, and wherein the images of the second image training subset are captured at a delayed capture time value. Therefore, the processor 126 is configured to retrieve both the first and second image training subsets, specifically from the camera 114. Further, in the determination system 110, the processor 126 is configured to determine a color formation value training set from the images in the image training set. This color formation value training set includes color formation values for at least one color channel, which is used for color formation of the reagent test area 120 of each optical test strip 118 in the optical test strip training set 116 for both timely and delayed capture time values. Furthermore, in the determination system 110, the processor 126 is configured to derive the at least one color expectation range 128 for the at least one color channel from the color formation value training set, wherein the color expectation range 128 defines the expected range of color formation values for timely capture time values and allowable delayed capture time values, wherein for allowable delayed capture time values, the delay d does not exceed at least one predefined expiration threshold _dmax .

Figure 1 illustrates an embodiment of a kit 130 configured to determine the concentration of at least one analyte in a bodily fluid sample 124. Specifically, the bodily fluid sample 124 may include a user's bodily fluids, such as samples with unknown analyte concentrations. In Figure 1, such samples are exemplarily shown on the far right of the figure. The kit 130 includes at least one optical test strip 118 having at least one reagent test area 120. In Figure 1, this optical test strip 118, i.e., a single optical test strip 118, is exemplarily shown on the far right of the figure. Further, the kit 130 includes a moving device 112 having at least one camera 114 and at least one processor 126. As an example, the moving device 112 of the kit 130 may be the same moving device 112 of the determination system 110. However, alternatively, the kit 130 and the determination system 110 each include their own moving device 114, i.e., different and independent moving devices 112.

Specifically, the determination system 110 can be configured to at least partially perform the determination method 132. An exemplary embodiment of the determination method 132 is shown in FIG2. The determination method 132 is configured to determine at least one color expectation range 128 for assessing the reasonableness of assumed reaction time values used in analytical measurements based on color formation reactions. The determination method 132 includes the following steps:

a) (represented by reference numeral 134) provides an optical test strip training set 116, each optical test strip 118 having a reagent test area 120;

b) (referred to as reference numeral 136) provides a training set 122 of bodily fluid samples and applies at least one of the bodily fluid samples 124 to each optical test strip in the optical test strip training set 116.

The reagent testing area is 120 (118).

c) (denoted by reference numeral 138) by at least one movement having at least one camera 114

Device 112 captures an image training set, which includes:

- A first image training subset, which includes at least a portion of images of at least some of the reagent test areas 120 of the optical test strip training set 116 captured at a timely capture time value, on which a bodily fluid sample 124 has been applied, the capture time value referring to the time elapsed between the application of the sample 124 and the capture image in step b).

- At least one second image training subset, the at least one second image training subset comprising at least some of the images of at least a portion of the reagent test area 120 of the optical test strip training set 116 captured at a delayed capture time value, on which the body fluid sample 124 has been applied;

d) (denoted by reference numeral 140) Specifically, by using at least one processor 126, more specifically, the processor 126 of the mobile device 112, a color formation value training set is determined from the images of the image training set, the color formation value training set including color formation values of at least one color channel, the color channel being used for reagent test areas of optical test strips 118 of the optical test strip training set 116 for timely capture time values and for delayed capture time values.

Color formation of 120; and

e) (represented by reference numeral 142) derive from the color formation value training set the at least one color expectation range 128 for the at least one color channel, the color expectation range 128 defining the expected range of color formation values for timely capture time values and allowable delayed capture time values, wherein for the allowable delayed capture time value, the delay d does not exceed at least one predefined expiration threshold _dmax .

In Figures 3 and 4, exemplary embodiments of the color expectation range 128 are shown. As shown in Figure 3, the color expectation range 128 may be, for example, a polygon, such as a two-dimensional polygon in a color plane. For example, on the horizontal axis, the color plane may display color values in the red channel 144, while on the vertical axis, the color plane may display color values in the green channel 146. Further, in Figure 3, color formation values of an exemplary color formation value training set are shown. As an example, the color expectation range 128 may include at least 80% of the color formation values for the color formation of the reagent test area of an optical test strip training set determined from images captured at one or more of a timely capture time value and an allowable delayed capture time value, i.e., at least 80% of these color formation values may be covered by the polygonal shape of the color expectation range 128.

Specifically, as exemplarily illustrated in Figure 3, at least two complementary color expectation ranges 128 can be determined, namely a first color expectation range 148 and a second color expectation range 150. The first color expectation range 148 may be or may include the color expected for a hypothetical reaction time value, specifically a color formation value, the difference between the hypothetical reaction time value and the actual and/or true reaction time value not exceeding an acceptable delay, wherein the acceptable delay may correspond to a predefined and/or predetermined acceptance threshold d_{_a} . The second color expectation range 150 may be or may include the color expected for a hypothetical reaction time value, specifically a color formation value, the difference between the hypothetical reaction time value and the actual and/or true reaction time value exceeding an acceptable delay but not exceeding a maturity delay, wherein the maturity delay may correspond to a predefined and/or predetermined maturity threshold d_{_max} . Specifically, in Figure 3, the first color expectation range 148 may also be represented by “I”, and the second color expectation range 150 may also be represented by “II”, wherein the region outside both the first color expectation range 148 and the second color expectation range 150 may be represented by “III”.

Furthermore, in Figure 3, color formation values are shown for timely capture time values and delayed capture time values. Specifically, color formation values corresponding to timely capture time values, such as d = 0 minutes, are denoted by reference numeral 152. Similarly, color formation values corresponding to delayed capture time values of d = 1 minute are denoted by reference numeral 154. Further, 156 corresponds to d = 2 minutes, 158 corresponds to d = 3 minutes, 160 corresponds to d = 4 minutes, 162 corresponds to d = 5 minutes, 164 corresponds to d = 7.5 minutes, and 166 corresponds to d = 10 minutes.

As an example, using the color expectation ranges of 148 and 150 shown, the acceptable delay can be considered as a 2-minute delay, i.e., d_{_a} = 2 minutes, and the expiration delay can be considered as a 6-minute delay, i.e., d_{_max} = 6 minutes. Other options for the acceptable delay and/or expiration delay are possible.

Alternatively or alternatively, and as exemplarily illustrated in Figure 4, the color expectation range 128 may be or may include a three-dimensional form, such as a polyhedron. As an example, the color expectation range 128 may be formed by polygons in a two-dimensional color space, such as polygons in the color planes of the red channel 144 and green channel 146, which have been extended into a third dimension, for example, referring to the blue channel 170, or alternatively, referring to intensity values, i.e., values in the intensity dimension, such as the absolute intensity values of the green channel 146. Specifically, the color expectation range 128 may be constrained in the direction of the blue channel 170 by an upper plane 172 and by a lower plane 174. Other forms and/or geometries of the color expectation range 128 are possible.

Specifically, at least one color expectation range 128 can be used to assess the reasonableness of assumed reaction time values used in analytical measurements based on color formation reactions. Such analytical measurements can be performed by measurement method 176. Exemplary embodiments of measurement method 176 are shown in Figures 5 and 6. Measurement method 176 includes the following steps:

i) (represented by reference numeral 178) provides at least one reagent test area 120.

One optical test strip 118;

ii) (represented by reference numeral 180) Applying body fluid sample 124 to the optical test strip 118

Agent testing area 120;

iii) (represented by reference numeral 182) The test sample with applied bodily fluid 124 is captured by using camera 114.

At least one image of at least a portion of the reagent test area 120;

(iv) (represented by reference number 184) Determine the hypothetical reaction time value, which corresponds to the time elapsed between the hypothetical time of sample application in step ii) and the time elapsed between image capture in step iii);

v) (denoted by reference numeral 186) Specifically, by using processor 126, at least one color channel is determined for the color formation of the reagent test area 120 using the image.

Color formation value;

vi) (represented by reference numeral 188) For at least one color channel, the color forming value is compared with at least one color expectation range determined by determination method 132;

vii) (represented by reference number 190) If the color formation value is outside the expected range of at least one color 128, the assumed reaction time value is considered unreasonable and the measurement method is terminated 176.

and

viii) (represented by reference number 192) If the color formation value is within the desired color range of 128

If the assumed reaction time value is considered reasonable, the concentration of the analyte in body fluid sample 124 is determined by using the color formation value and the optional assumed reaction time value.

Another embodiment of measurement method 176 is shown in Figure 6. The starting point can be indicated by the solid circle at the top of the figure. As an example, measurement method 176 may further include an intensity check 196, such as a step of checking whether the intensity of the color formation value is higher or lower than at least one intensity threshold. Specifically, the measurement method can be terminated if the color formation value is outside a predefined intensity range, for example, below a lower intensity threshold or above a higher intensity threshold. Specifically, if the color formation value fails the intensity check, the color formation value can be considered unreasonable, and therefore measurement method 176 can be terminated.

It is important to note that the color expectation range 128 can be a variable color expectation range, such as the base points of the polygonal shape and/or parameters defining the plane. For example, these base points and/or parameters can be provided to the application (on the user's mobile device) in the form of metadata associated with a color card, which allows the application to change the base points and/or parameters at a later point in time if needed. Changes to the color expectation range can be implemented in optional method steps before the implementation of measurement method 176.

As an example, where the first color expectation range 148 corresponds to the first color expectation range 148 shown in FIG. 4, specifically, step vi) 188 of measurement method 176 may include a separate step for comparing the color formation value with the first color expectation range 148. As an example, as shown by reference numeral 198, it may be checked whether the color formation value is above the lower plane 174. Further, as shown by reference numeral 200, it may be checked whether the color formation value is below the upper plane 172. Additionally, as shown by reference numeral 202, it may be checked whether the color formation value is within the first polygonal shape "I" in the color plane defined by the red channel 144 and the green channel 146. If the color formation value fails any of checks 198 to 202, according to step vii) 190, the color formation value may be considered unreasonable and the method may be terminated. Further, optionally, after terminating the method, measurement method 176 may include displaying an error message 204. The same check may be performed on the second color expectation range 150. This step is shown in FIG. 6 by reference numeral 206. For each of the first color expectation range 148 and the second color expectation range 150, different post-processing code functions can be used to determine the concentration of the analyte. Thus, as indicated by reference numerals 208 and 210, a flag is set such that if the color formation value is included in the first color expectation range 148, the flag is set to "I" 208, or if it is included in the second color expectation range 150, the flag is set to "II" 210. As an example, for the first color expectation range 148, i.e., "I", a first mathematical correlation function, such as the mathematical function "f", can be used to determine the analyte concentration from the color formation value, and for the second color expectation range 150, i.e., "II", a second mathematical correlation function, the mathematical function "g", can be used.

Figure 7 shows a graphical illustration of the relationship between actual blood glucose values and blood glucose values determined using both conventional methods and systems and the methods and systems of the present invention for determining blood glucose concentration. Specifically, the graph shown in Figure 7 indicates the relationship between actual blood glucose value 212, expressed in mg/dl, and measured blood glucose value 214, expressed in mg/dl. Specifically, values indicated by crosses show the relationship for normal measurements (i.e., measurements performed without provocation, specifically without erroneous and/or inappropriate procedures), while values indicated by circles show the relationship for provocational measurements performed using the methods and apparatus of the present invention, i.e., measurements performed with erroneous and/or inappropriate user procedures. As can be seen, for provocational measurements, only valid results with small errors can be achieved.

Furthermore, Figure 7 shows regions A through E of the error grid analysis (specifically, regions A through E of the Parkes error grid), which quantifies the clinical accuracy of a determined blood glucose concentration compared to the actual blood glucose concentration. For example, blood glucose values fall within the following regions:

- Zone A includes values within 20% of the reference sensor's values;

- Zone B includes values outside the 20% threshold that will not lead to inappropriate treatment;

- Zone C includes values that lead to unnecessary treatment;

Zone D includes values indicating the potential danger of failing to detect hypoglycemia or hyperglycemia.

and

- Zone E includes values that could lead to the misuse of treatment for hypoglycemia for hyperglycemia, and vice versa.

For more information on error grid analysis, please 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.

The measurements shown in Figure 7 are based on the same sample and assumed reaction time. Specifically, the same sample and assumed reaction time were used to determine the blood glucose values for both measurements.

Table 1 shows the number of blood glucose values determined by a set of induced measurements performed using known methods and apparatus, as well as by the same measurements performed using the methods and apparatus of the present invention. The set of induced measurements, for reference and/or control purposes, further includes a total of 15 “normal” measurements performed without induction, specifically without erroneous and/or inappropriate procedures, and used as reference measurements.

legend A B C D E Number of blood glucose values determined using known methods and apparatus 89 14 2 2 0 The number of blood glucose values determined using the method and apparatus of the present invention 19 0 0 0 0

Table 1: Number of blood glucose values determined using known methods and apparatus as well as using the methods and apparatus of the present invention

Specifically, as can be seen in Table 1, the values from measurements performed using known methods and apparatus provide blood glucose values for almost all measurements, except in the measurements according to the invention, where no blood glucose values are provided for hypothetical time intervals considered unreasonable. In particular, when using the methods and apparatus of the invention, blood glucose values for all 15 normal measurements were determined, which were used as references within the induced measurement set.

List of reference numerals

110 Determine System

112 Mobile devices

114 Camera

116 Optical Test Strip Training Set

118 Optical Test Strips

120 Reagent Testing Area

122 Body Fluid Sample Training Set

124 Body fluid samples

126 Processor

128 Color Expectation Range

130 Reagent Kit

132 Determination Method

134 Step a)

136 Step b)

138 Step c)

140 Step d)

142 Step e)

144 Red Channel

146 Green Channel

148 First color expected range

150 Second color expected range

152 Color formation value corresponding to the timely capture time value (d = 0 minutes)

154 d = 1 minute

156 d = 2 minutes

158 d = 3 minutes

160 d = 4 minutes

162 d = 5 minutes

164 d = 7.5 minutes

166 d = 10 minutes

170 Blue Channel

172 Upper plane

174 Lower plane

176 Measurement Methods

178 Step i)

180 Step ii)

182 Step iii)

184 Step iv)

186 Step v)

188 Step vi)

190 Step vii)

192 Step viii)

196 Strength Check

198. Check if the color formation value is higher than the lower plane.

200 Check if the color formation value is lower than that of the upper plane.

202 Check if the color formation value is within the polygon.

204 Error Message

206. Check if the color formation value is within the second color expectation range.

208 Setting the flag "I"

210 Setting the marker "II"

212 Actual blood glucose levels are expressed in mg/dl.

214. Blood glucose levels are measured in mg/dl.

Claims (17)

1. A method for determining at least one color expectation range (128) for evaluating the reasonableness of assumed reaction time values used in analytical measurements based on color-forming reactions, the method comprising: a) Provide an optical test strip training set (116), each optical test strip (118) having a reagent test area (120); b) Provide a training set of body fluid samples (122) and apply at least one of the body fluid samples (124) to the reagent test area of each optical test strip (118) in the training set of optical test strips (116); c) Capturing an image training set by at least one mobile device (112) having at least one camera (114), the image training set comprising - A first image training subset, comprising at least a portion of images of at least some of the reagent test areas (120) of the optical test strip training set (116) with the body fluid sample applied, captured at a timely capture time value, wherein the capture time value refers to the time elapsed between the application of the sample and the capture of the image in step b). - At least one second image training subset, said at least one second image training subset comprising at least a portion of images of at least some of the reagent test areas (120) of the optical test strip training set (116) to which the body fluid sample is applied, captured at a delayed capture time value; d) Determine a color formation value training set from the images in the image training set, the color formation value training set including color formation values for at least one color channel, the at least one color channel being used for color formation of the reagent test area (120) of the optical test strip (118) in the optical test strip training set (120) for both timely capture time values and delayed capture time values; and e) Derive the at least one color expectation range (128) for the at least one color channel from the color formation value training set, the color expectation range defining the expected range of color formation values for timely capture time values and allowable delayed capture time values, wherein for the allowable delayed capture time value, the delay d does not exceed at least one predefined expiration threshold _dmax . 2. The determination method according to the preceding claim, wherein step e) includes deriving at least two complementary color expectation ranges (148, 150). 3. The determination method according to the preceding claim, wherein for the first of the complementary color expectation ranges (148), the delay _d1 does not exceed a predefined acceptance threshold _da below the expiration threshold _dmax , specifically _d1 < _da < _dmax , and for the second of the complementary color expectation ranges (150), the delay _d2 is equal to _da or lies between the acceptance threshold _da and the expiration threshold _dmax , specifically _da ≤ _d2 ≤ _dmax . 4. The determination method according to any one of the preceding claims, wherein step d) further comprises labeling the color formation values in the color formation value training set with information about the capture time values. 5. The determination method according to any one of the preceding claims, wherein in step e), the color expectation range (128) includes 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 formation value, the color formation value being for the color formation of the reagent test area of the optical test strip in the optical test strip training set determined from an image captured at one or more of the timely capture time value and the permissible delayed capture time value. 6. The determination method according to any one of the preceding claims, wherein the derivation in step e) comprises: determining an envelope comprising at least 80% of the color formation values for the color formation of the reagent test region (120) of the optical test strip (118) in the optical test strip training set (116) determined from an image captured at one or more of the timely capture time value and the permissible delayed capture time value; and further extending the envelope by a predetermined safety factor. 7. The determination method according to any one of the preceding claims, wherein step e) comprises using at least one machine learning algorithm. 8. A measurement method for performing analytical measurements based on color formation response using a mobile device (112) having a camera (114) and a processor (126), the method comprising: i) Provide at least one optical test strip (118) having at least one reagent test area (120); ii) Apply the body fluid sample (124) to the reagent test area (120) of the optical test strip (118); iii) Capturing at least one image of at least a portion of the reagent test area (120) to which bodily fluid has been applied by using the camera (114); iv) Determine a hypothetical reaction time value, which corresponds to the time elapsed between the hypothetical time of applying the sample in step ii) and the time elapsed between capturing the image in step iii); v) Determine the color formation value of at least one color channel for the color formation of the reagent test area (120) using the image; vi) For the at least one color channel, the color formation value is compared with at least one color expectation range (128) determined by performing the determination method according to any one of the preceding claims; vii) If the color formation value is outside the at least one color expectation range (128), the assumed reaction time value is considered unreasonable and the measurement method is terminated; and viii) If the color formation value is within the color expectation range (128), the assumed reaction time value is considered reasonable and the concentration of the analyte in the body fluid sample is determined by using the color formation value. 9. The measurement method according to the preceding claims, wherein step vi) comprises: comparing the color formation value with at least one first color expectation range (148) determined by the determination method according to any one of claims 2 to 7 and with at least one second color expectation range (150), and wherein in step vii), if the color formation value is outside both the first color expectation range and the second color expectation range, the assumed capture time is considered unreasonable and the measurement method is terminated, wherein in step viii), different algorithms are used to determine the concentration of the analyte from the color formation value for the color formation value in the at least one first color expectation range and the at least one second color expectation range. 10. The measurement method according to the preceding claim, wherein in step viii): - If the color formation value is within the first color expectation range (148), then the assumed reaction time value is considered reasonable and the concentration of the analyte is determined by using the color formation value and the assumed reaction time value; and - If the color formation value is within the second color expectation range (150), the assumed reaction time value is considered reasonable and the concentration of the analyte is determined by using the color formation value and a predefined delay for the second color expectation range added to the assumed reaction time value. 11. The measurement method according to any one of the preceding two claims, wherein the method further comprises step ix): capturing 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), wherein step ix) is performed prior to step ii). 12. The measurement method according to any one of the preceding two claims, wherein the method further comprises step x): attaching the optical test strip (118) to a color reference card, the color reference card comprising a plurality of color reference fields having known reference color values, wherein step x) is performed prior to step iii, and wherein the image captured in step iii) further shows at least a portion of the color reference card. 13. A determination system (110) for determining at least one color expectation range (128) for evaluating the reasonableness of assumed reaction time values used in analytical measurements based on color-forming reactions, said determination system comprising: A) At least one mobile device (112) having at least one camera (114); B) Optical test strip training set (116), each optical test strip (118) has a reagent test area (120); C) A training set of body fluid samples (126), which includes multiple body fluid samples (128); and D) At least one processor (126), said processor (126) being configured to: - Retrieve an image training set, the image training set comprising at least a portion of at least some of the reagent test areas (120) of the optical test strip training set (116) with the body fluid sample (124) applied, captured by the camera (114) at a timely capture time value, the capture time value being the time elapsed between the application of the sample and the capture of the image, the image training set further comprising at least a portion of at least some of the reagent test areas (120) of the optical test strip training set (116) with the body fluid sample (124) applied, captured by the camera (114) at a delayed capture time value; - Determine a color formation value training set from the images in the image training set, the color formation value training set including color formation values for at least one color channel, the at least one color channel being used for color formation of the reagent test area (120) of the optical test strip (118) in the optical test strip training set (116) for both timely capture time values and delayed capture time values; and - Derive the at least one color expectation range (128) for the at least one color channel from the color formation value training set, the color expectation range (128) defining the expected range of color formation values for timely capture time values and allowable delayed capture time values, wherein for the allowable delayed capture time value, the delay d does not exceed at least one predefined expiration threshold _dmax . 14. The determining system (110) according to the preceding claim, wherein the determining system further comprises: E) At least one color reference card configured to releasably attach the optical test strip thereto, the color reference card comprising a plurality of color reference fields having known reference color values, wherein the images in the image training set further display at least a portion of the color reference card, specifically one or more of the color reference fields. 15. A determining system (110) according to any one of the preceding two claims, wherein the determining system is configured to perform at least step d) and step e) of a determining method according to any one of the preceding claims relating to a determining method. 16. A mobile device (112) having at least one camera (114) and at least one processor (126), the mobile device (112) being configured to perform at least steps iv) to viii) of the measurement method according to any of the preceding claims relating to the measurement method. 17. A kit (130) for determining the concentration of at least one analyte in a body fluid sample (124), the kit (130) comprising a mobile device (112) according to the preceding claim, the kit (130) further comprising at least one optical test strip (118) having at least one reagent test area (120).