RU2786271C2 - Method and devices for analytical measurement - Google Patents

Abstract

FIELD: measuring equipment.

SUBSTANCE: invention relates to a method for analytical measurement, in particular, to a mobile device and a set for analytical measurement. The method for analytical measurement includes provision of a mobile device with a camera and a test strip made with the possibility of a color-changing analytical reaction flowing on it, when applying a sample to a test field. The test field contains an indicator reagent for detection of analyte in the sample. The camera captures an image of part of the test strip, consisting of a set of pixels. An area of interest is defined on the image, which is correlated with a subset of pixels. Color distribution is assessed within the first subset of pixels, and emissions in the first subset of pixels are eliminated. A subarea of interest is defined within the area of interest, having a smaller area then the area of interest, and is correlated with a subarea of interest of the second subset of pixels. Then, an average value of color distribution of the first subset of pixels is compared with an average value of color distribution of the second subset of pixels with subsequent determination of image homogeneity.

EFFECT: obtainment of a method and a device for analytical measurement.

13 cl, 10 dwg

Description

The technical field to which the invention belongs

The present invention relates to a method for performing an analytical measurement. The invention also relates to a computer program containing software for carrying out the method according to the invention. In addition, the invention relates to a mobile device and a kit for carrying out an analytical measurement. The methods, computer programs, mobile devices and kits according to the invention can be used in medical diagnostics for the qualitative or quantitative determination of one or more analytes in one or more body fluids. However, the present invention can be used in other areas.

State of the art

In the field of medical diagnostics, in many cases it is required to determine one or more analytes in samples of physiological fluid, such as blood, interstitial fluid, urine, saliva, or other kinds of physiological fluid. Examples of such analytes to be determined are glucose, triglycerides, lactate, cholesterol, or other types of analytes commonly found in these physiological fluids. According to the concentration of the analyte and/or its presence, if necessary, the appropriate treatment can be selected.

Devices and methods known to the skilled person typically use test elements containing one or more indicator (analytical) reagents, also called test reagents, which, in the presence of an analyte to be determined, are capable of participating in one or more detectable, for example optically detectable, analytical reactions. For examples of such indicator reagents, reference may be made, for example, to J. Hönes et al.: The Technology Behind Glucose Meters: Test Strips, Diabetes Technology & Therapeutics, Volume 10, Supplement 1, 2008 , pp. 10-26. There are other types of indicator reagents that can also be used in the implementation of the present invention.

Typically, an indicator reagent is observed to analyze one or more optically detectable changes occurring in it, which can be used to judge the concentration of at least one analyte to be determined. As is known, to detect at least one change in the optical properties of the test field, various types of light receivers (detectors) are used. In this case, various types of light sources for illuminating test fields, as well as various types of light radiation receivers, are known. In addition to single receivers such as photodiodes, various types of devices are known using array receivers containing a plurality of photosensitive devices. Thus, WO 2007/115732 A1 discloses a system for determining the concentration of an analyte in a liquid sample. The system contains a receiver for recording the intensities of light emanating from partial areas of the analytical area of the test element. The system also includes an evaluator (data processing device) that determines the frequency distribution for the recorded light intensities. Similarly, EP 1359409 A2 discloses a device for determining the concentration of an analyte in a physiological sample. The device contains at least one light source and a matrix radiation receiver.

In addition, with regard to the use of matrix radiation receivers, methods are known in the art for detecting errors and artifacts in images obtained by matrix radiation receivers. Thus, EP 1 359 409 A2 discloses a means for determining whether sufficient sample material is present in each of several different assay areas, using detected light from those areas for which a sufficient amount of sample has been determined to determine the analyte concentration. Similarly, in WO 2007/115732 A1, an evaluator determines the analyte concentration from a light intensity selected based on a frequency distribution having at least one first maximum relating to non-wetted partial areas of at least one reference area and a second maximum relating to wetted partial areas. As another example, US Pat. No. 6,993,172 B2 discloses a method and system using pixel-by-pixel signal intensity data contained within areas of a scanned image of a molecular matrix and corresponding to detectable features and their backgrounds to determine whether the detectable features and their backgrounds have backgrounds of uneven signal intensities, and therefore are anomalous features and anomalous backgrounds.

For example, US 2015/308961 A1 describes assay pad color quantification and analyte titration, which can be performed under different light conditions. In one embodiment, the illumination conditions under which the digital image is captured are evaluated and these conditions are used to select a set of reference colors from which the quantified color is compared to determine the titer. In yet another embodiment, several comparisons are made under different lighting conditions, with the result having the highest level of confidence being selected to determine the titer.

DE 19630160 A1 discloses an analytical system for evaluating test items, having means for determining whether a sample has been applied evenly and in sufficient quantity to the receiving area of a test item. In the first version of this solution, the analytical system includes at least two light sources illuminating the areas of the receiving area and the test area of the test element, which are separated from each other or at least do not completely overlap. In addition, the analytical system includes a control device capable of actuating at least two light sources separately from each other, at least one sensor capable of detecting light reflected from the study area or transmitted through the study area, and provide output signals , corresponding to the light intensity, and a data processing device.

US 2016/153912 A1 discloses a method for determining at least one analyte in at least one body fluid sample. This uses at least one test element with at least one test field having at least one indicator (analytical) reagent, which is adapted to carry out at least one optically detectable analytical reaction in the presence of an analyte. The method includes obtaining, by means of at least one image receiver, a sequence of test field images. Each image includes many pixels. The method also includes detecting in the images included in the image sequence at least one characteristic feature of the test field. The method also includes correcting a change in the relative position of the image receiver and the test field in the image sequence by using a feature to obtain a corrected image sequence.

Despite the advantages associated with using consumer electronics devices having a camera to evaluate analytical measurements, several technical problems remain. In particular, measurement results obtained on defective or non-ideal areas to be assessed are still usually discarded or limited by the presence of certain defects, for example, in areas with insufficient sample material, methods for determining the analyte concentration are not applied, as is known, for example, from EP 1359409 A2 . The general approach of discarding such measurement results usually creates significant inconvenience for users and/or patients.

Problem being solved

Therefore, it is desired to provide methods and devices that solve the aforementioned technical problems of analytical measurements using mobile devices such as mobile consumer electronics devices, in particular multipurpose mobile devices not specifically designed for analytical measurements, such as smartphones or tablet computers. In particular, it is desired to provide methods and devices that can be widely used with existing mobile devices and are suitable for improving measurement accuracy and user friendliness.

Disclosure of the essence of the invention

This problem is solved in the method and device, characterized by features of independent claims. Preferred embodiments of the invention, which can be implemented individually or in any combination, are indicated in the dependent claims.

In the text of the description and the claims, the terms "has", "comprises", "includes (in itself)" or any of their grammatical varieties are used in a non-exclusive way, leaving the corresponding formulations open. Thus, these terms can be used both in a situation in which the corresponding object in the context of the invention lacks any other features than the feature introduced by these terms, and in a situation in which one or more other features are also present. For example, the expressions "A has B", "A contains B", and "A includes B" can be used both in a situation in which there are no elements other than B in the object A (i.e., in a situation in which A consists of B and only of B), and in a situation in which in object A, in addition to B, there are one or more other elements, for example, element C, elements D and E, or other additional elements.

Further, it should be noted that the expressions "at least one", "one or more" or similar expressions indicating that it can be about one or more than one feature or element, below are usually used only once - when introducing the corresponding feature. or element. In most cases, when the corresponding feature or element is subsequently indicated, the expressions "at least one" or "one or more" are not repeated, despite the fact that we can talk about one or more than one corresponding feature or element.

Further, hereinafter, the expressions "preferably", "more preferably", "especially", "mainly", "in particular", "primarily" or similar expressions are used in relation to optional features, without limiting alternative possibilities. Therefore, the features introduced by these expressions are optional, i.e. are optional and are not intended to limit the scope of patent claims in any way. As should be clear to the specialist, the implementation of the invention is possible using alternative features. Likewise, features introduced by the expression "in one embodiment of the invention" or similar expressions are intended to be optional and do not imply any limitations as to alternative embodiments of the invention, as to the scope of the legal protection of the invention, and as to the combination possibilities introduced in this way. features with other optional or mandatory features of the invention.

In a first aspect of the invention, a method for making an analytical measurement is provided. The method includes the following steps, which, for example, can be performed in the order indicated. However, it should be noted that another procedure for performing the corresponding actions is also possible. In addition, it is also possible to perform one or more steps of the method once or more than once. In addition, two or more method steps may be performed simultaneously or overlapping in time. The method may also include other steps not listed.

The method according to the invention for carrying out an analytical measurement generally includes the following steps:

a) providing at least one mobile device having at least one camera;

b) providing at least one test strip configured to undergo a color-changing analytical reaction on it when at least one sample is applied to the test strip, in particular to at least one test field of the test strip, containing at least one indicator reagent for detecting at least one analyte in a sample;

c) capturing by the camera at least one image of at least a portion of the test strip, the image consisting of a plurality of pixels;

d) determining, in particular recognizing, in the image at least one area of interest and correlating with the area of interest of the first subset of pixels;

e) estimating the color distribution within the first pixel subset and eliminating outliers in the first pixel subset;

d) determining, in particular recognizing, within the region of interest, at least one sub-region of interest having a smaller area than the region of interest, and assigning a second subset of pixels to the sub-region of interest; and

g) comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element of image uniformity information.

The method also includes at least one of the following:

- comparing the number of pixels included in the first subset of pixels with at least one threshold value, on the basis of which at least one element of information about the sufficiency of the size of the region of interest is determined, and if at least one element of information about the sufficiency of the size indicates that, that the region of interest is of insufficient size, the execution of the analytical measurement method is interrupted,

- comparison of the number of pixels in the first subset of pixels before the elimination of outliers in step e) with the number of pixels in the first subset of pixels after elimination of outliers in step e), and if the number of pixels in the first subset of pixels after elimination of outliers in step e) is less than a given percentage of the number pixels in the first pixel subset until outliers are eliminated in step e), the analytical measurement method is interrupted.

The term "analytical measurement" is a broad term in this context, to be interpreted in its ordinary meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, this term may refer to, without limitation, the quantitative and/or qualitative determination of at least one analyte in a sample, or sample, of a substance. For example, the sample may include a bodily fluid such as blood, interstitial fluid, urine, saliva, or other types of bodily fluids. The result of an analytical measurement may be, for example, the concentration of an analyte and/or the presence or absence of an analyte to be determined. Specifically, for example, the analytical measurement may be a blood glucose measurement, and thus the result of the analytical measurement may be, for example, a blood glucose concentration.

The term "analyte" is in this context a broad term to be interpreted in its ordinary meaning familiar to the average person, and should not be limited to any private or specialized meaning. In particular, this term may refer, without limitation, to one or more specific chemical compounds and/or other parameters to be determined and/or measured. For example, at least one analyte may be a chemical compound involved in metabolism, in particular, may be one or more of glucose, cholesterol or triglycerides. In addition to or as an alternative to the above, other types of analytes or parameters can be determined, such as pH.

In step a) provide a mobile device having at least one camera. The term "mobile device" in this context is a broad term to be construed in its ordinary meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, the term may refer to, without limitation, a mobile electronic device, namely a mobile communication device such as a cellular phone or smartphone. In addition to or alternatively to a mobile communication device, as discussed in more detail below, a mobile device may also be a tablet computer or other type of portable computer having at least one camera.

The term "camera" in this context is a broad term to be interpreted in its ordinary meaning familiar to the average person, and should not be limited to any private or specialized meaning. In particular, the term may refer to, without limitation, a device capable of capturing spatially resolved optical information, such as capturing one or more images. The camera may generally contain one or more chips (integrated circuits) or imaging devices, such as one or more charge-coupled device (CCD) and/or CMOS chips. A camera may generally comprise a one-dimensional or two-dimensional array of image sensors, such as pixels. For example, a camera may contain at least 10 pixels in at least one dimension, such as at least 10 pixels in each dimension. However, it should be noted that other cameras may be used. The implementation of the invention is particularly possible with respect to cameras commonly used in mobile technology such as portable computers (laptops), tablet computers and especially cellular phones such as smartphones. Thus, in particular, the camera may be part of a mobile device, which, in addition to at least one camera, contains one or more data processing devices, such as one or more data processors. However, other cameras may be used. The camera, in addition to at least one image sensor or an image forming chip, may contain additional elements, for example one or more optical elements, in particular one or more lenses. For example, the camera may be a fixed focus camera having at least one lens fixed to the image sensor. However, as an alternative, the camera may also contain one or more variable lenses, which may be adjusted automatically or manually.

The camera may in particular be a color camera. Thus, the camera can output or generate, for example, per pixel, color information, such as color values for the three colors R, G, B. More color values can also be output, such as four colors per pixel. Color cameras are generally known to those skilled in the art. For example, each camera chip pixel may have three or more different color sensors, such as color-detecting pixels, such as one pixel for red (R), one pixel for yellow (G), and one pixel for blue (B). For each of the pixels, eg R, G, B pixels, the pixels may register values, eg numerical values ranging from 0 to 255, depending on the intensity of the corresponding color. Instead of using three-color systems such as R, G, B, for example, four-color systems such as C, M, Y, K can be used. These methods are generally known to the skilled person.

In step b), at least one test strip is provided. The term "test strip" in this context is a broad term to be construed in its ordinary meaning familiar to the average person, and should not be limited to any private or specialized meaning. In particular, the term may refer to, without limitation, an element or device capable of undergoing a color-changing analytical reaction thereon. The test strip, in particular, may have a test field containing at least one indicator reagent for determining at least one analyte. The test element, for example, may have at least one substrate, in particular at least one carrier, on which at least one test field is applied or embedded. For example, at least one carrier may be in the form of a strip, whereby the test element is in the form of a test strip. Such test strips are widely used and are available to the public. One test strip can carry one test field or multiple test fields containing the same or different indicator reagents.

In this context, the term "test field" is a broad term to be construed in its ordinary meaning familiar to the average person and should not be limited to any particular or specialized meaning. In particular, this term may refer to, without limitation, an amount of indicator reagent in the form of a connected figure, such as a pad, in particular a round, polygonal or rectangular pad, and having one or more layers of material, at least one of which contains an indicator reagent. . Other layers may be provided to provide special optical properties, such as reflective properties, sample spreading properties, or retarding properties, for example to separate particulate components, such as cellular components, from the sample.

The term "indicator reagent", also known as an analytical reagent, is in this context a broad term to be construed in its usual meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, this term may refer to, without limitation, a chemical compound or several chemical compounds, for example, a mixture of chemical compounds, capable of participating in an analytical reaction in the presence of an analyte, amenable to detection by certain means, for example, optically detectable. The analytical reaction may in particular be specific for the analyte to be determined. In this case, the indicator reagent may in particular be an optical indicator reagent, for example an indicator reagent that changes color in the presence of an analyte. The color change, in particular, may depend on the amount of analyte present in the sample. The indicator reagent may include, for example, at least one enzyme such as glucose oxidase and/or glucose dehydrogenase. In addition, other components may be present, such as one or more dyes, mediators, and the like. Indicator reagents are generally known to those skilled in the art and reference may be made in this regard to J. Hönes et al.: "Diabetes Technology and Therapeutics", Volume 10, Supplement 1, 2008, pp. 10-26 . However, other indicator reagents may also be used.

In step c), at least one image is captured by the camera. The term "image" is in this context a broad term to be interpreted in its ordinary meaning familiar to the average specialist, and should not be limited to any private or specialized meaning. In particular, the term may refer to, without limitation, data or information recorded by a camera, such as a plurality of electronic values captured from an imager, such as pixels on a camera chip. For example, an image may include a one-dimensional or two-dimensional array of data. Thus, the image itself may include pixels that, for example, correspond to pixels on a camera chip. Therefore, references to "pixels" refer either to units of graphic information generated by the individual pixels of the camera chip, or to the individual pixels of the camera chip themselves.

In step d) within the image, at least one region of interest is determined, in particular recognized. The term "field of interest" is in this context a broad term to be construed in its ordinary meaning familiar to the average person and should not be limited to any particular or specialized meaning. In particular, the term may refer, without limitation, to a subset of data that is within a larger set (set) of data and is recognized for a particular purpose. For example, the term may refer to at least one partial image or area within an image defined for a specific purpose.

In addition, a first subset of pixels is assigned to the region of interest. In this context, the term "subset of pixels" is a broad term to be construed in its ordinary meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, the term may refer, without limitation, to a partial number of picture elements, such as pixels, within an image or picture. In the context of the present invention, a subset of pixels may be, in particular, the number of pixels within the image and participating in the display of the region of interest within the image.

Step e) evaluates the color distribution within the first subset of pixels. In this context, the term "color distribution" is a broad term to be interpreted in its ordinary meaning familiar to the average person, and should not be limited to any private or specialized meaning. In particular, the term may refer to, without limitation, the dispersion of a color in a given set of data, such as an image. The color distribution may be represented in particular in a histogram, for example an image histogram obtained by counting the number of pixels for each color value range from a given set of color value ranges in a color coordinate system. In this context, the term "color coordinate system" is a broad term to be interpreted in its usual meaning familiar to the average person, and should not be limited to any private or specialized meaning. In particular, this term may refer to, without limitation, any coordinate system by which one can characterize, for example mathematically or physically, the color of an object, such as the color of a test field or the color of an image captured by a camera. The person skilled in the art is generally aware of various color coordinate systems, such as the color coordinate systems established by the International Commission on Illumination (CIE). The color coordinates collectively may overlap or define a color space, such as by defining three or four basis vectors.

In addition, outliers are excluded in the first subset of pixels. The term "emissions" in this context is a broad term to be interpreted in its usual meaning familiar to the average specialist, and should not be limited to any particular or specialized meaning. In particular, the term may refer to, without limitation, a statistically unusual (anomalous) data point or value. In particular, an outlier can be a value in a dataset that does not fit a statistical pattern that describes most of the other points in the dataset. For example, to determine which data points are regular (statistically significant) and which are outliers, the percentile method can be used, such as by determining percentile thresholds. In addition to or as an alternative to the determination of percentile thresholds, other means, such as simple threshold procedures, can be used to determine regular data points and outliers.

For example, regular data points may be greater than or equal to the lower percentile threshold and/or less than or equal to the upper percentile threshold. Thus, outliers may be data points below the lower percentile threshold and/or above the upper percentile threshold. In particular, the lower percentile threshold may be, for example, from more than the 0th percentile to the 35th percentile, with the 0th percentile indicating that no data points can be below this percentile threshold; preferably the lower percentile threshold may be from the 5th percentile to the 30th percentile, more preferably from the 15th to the 25th percentile, and even more preferably the lower percentile threshold may be in particular the 25th percentile. Further, in particular, in addition to and/or in combination with the lower percentile threshold, outliers can in particular be data points above the upper percentile threshold. In particular, the upper percentile threshold may be, for example, from the 65th percentile to less than the 100th percentile, with the 100th percentile indicating that all data points are at or below this percentile threshold, preferably the upper percentile threshold. may be from the 70th percentile to the 95th percentile, more preferably from the 75th percentile to the 85th percentile, and even more preferably the upper percentile threshold may be, in particular, the 75th percentile. In particular, as noted above, any combination of the lower percentile thresholds described above and the upper percentile thresholds described above can be used to determine which data points are regular and which are outliers.

Step e) includes determining, in particular recognizing, within the region of interest, at least one sub-region of interest having a smaller area than the region of interest. In particular, a second subset of pixels is assigned to the sub-region of interest.

In step g), at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels are compared. Thereby, at least one element of image uniformity information is determined or obtained. The term "average" is, in this context, a broad term to be construed in its ordinary meaning familiar to the average person and should not be limited to any particular or specialized meaning. In particular, the term may refer to, without limitation, a value or number representing all values in a data set, e.g., may refer to a value or number computed using all values in a data set and representing, for example, the approximate middle of all values in dataset. In particular, the mean may be selected from the group consisting of an arithmetic mean, a geometric mean, or a median. In particular, the average value may be calculated using the sum of the values from the sampled data set divided by the number of values from the sampled data set. For example, in this case, the average value of the color distribution can be calculated, in particular, by summing the colors of the pixels included in a certain set of pixels, and dividing the result by the number of pixels included in this set. Other calculation methods may also be used, such as individual weighting or ranking of all or part of the pixels.

The term "homogeneity information element" is, in this context, a broad term to be construed in its ordinary meaning familiar to the average person and should not be limited to any particular or specialized meaning. In particular, the term may refer to, without limitation, an indication, quantitative description, or information regarding the homogeneity of a particular system. In particular, in this case, this term may refer to an indication or information regarding the uniformity of the image captured by the camera of the mobile device. The uniformity information element may be, for example, logical or numeric information indicating, for example, one or more of the following values: "uniform" or "inhomogeneous", "good" or "unsuitable"/"unsuitable". So, for example, in the case of comparing the average value of the color distribution of the first subset of pixels with the average value of the color distribution of the second subset of pixels and establishing that these average values differ from each other by a value greater than the maximum tolerance acceptable for analytical measurement, the image can be considered unsuitable for analytical measurement. For example, if the average values of the color distributions of the first and second pixel subsets differ by more than the maximum tolerance acceptable for blood glucose measurement, the image may be considered unsuitable for blood glucose measurement, and therefore the uniformity information element may indicate that the image is "unusable". However, as an alternative, homogeneity can also be described or quantified, as already mentioned above.

The term "homogeneity" is in this context a broad term to be construed in its ordinary meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, this term may refer, without limitation, to the sameness (uniformity) of characteristics or properties, for example, the similarity of colors, in particular the similarity of pixel colors. Homogeneity, can be described quantitatively, for example, by indicating the width of the distribution of values. For example, uniformity can be expressed in terms of the distance between colors in a color coordinate system.

The method proposed in the first aspect of the present invention, in a private embodiment of its implementation may additionally include the following steps:

h) interrupting the execution of the analytical measurement method if at least one uniformity information element indicates that the image is unsuitable for analytical measurement; and

i) assessing the image and obtaining at least one element of analytical information, in particular at least one element of information about the concentration of at least one analyte in the sample, if at least one element of information about uniformity indicates the suitability of the image for analytical measurement.

In carrying out the method, for example, at least one element of uniformity information may be used, which, for example, may be or may include numerical information or logical information, such as above, for example, "suitable" or "unsuitable", for carrying out an analytical measurement. Depending on this homogeneity information, the method may branch out between steps h) and i), wherein the homogeneity query may be programmed, for example, as an “if…” subroutine, an “if…then…” subroutine, or another similar subroutine. .

The term "element of information about the concentration of at least one analyte" is in this context a broad term to be interpreted in its usual meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, this term may refer to, without limitation, an indication or information about the concentration of at least one analyte in a particular sample. For example, the element of information about the concentration of at least one analyte in the sample may be, in particular, the concentration of glucose in the blood sample.

Further, step g) of the method may include comparing the absolute value (modulo) of the difference between the average value of the color distribution of the first subset of pixels and the average value of the color distribution of the second subset of pixels with at least one threshold value. The term "difference" is in this context a broad term to be interpreted in its ordinary meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, the term may refer to, without limitation, an absolute difference or difference between at least two values or numbers. In particular, a difference between color distribution values, such as a difference between an average color distribution value of a first pixel subset and an average color distribution value of a second pixel subset, may indicate a distance between color distribution values in a color coordinate system. This distance, for example, can be given and/or expressed in "number of intervals", for example in the number of steps in the histogram, in particular, the distance can be indicated by the absolute number of steps (intervals) with a given step size in the color coordinate system.

The term "comparison", without limitation, can refer to the process of determining simply whether the first value is less than, greater than, or equal to the second value, or a similar ratio. In addition or alternatively, the result of the comparison may also be a quantitative expression of the difference between the values. Other means of comparison may also be used, generally generating information about the relationship between values.

The term "threshold" in this context is a broad term to be interpreted in its ordinary meaning familiar to the average person, and should not be limited to any particular or specialized meaning. In particular, the term may refer, without limitation, to an arbitrary value indicating a limit and/or boundary within a system. A threshold, for example, may indicate a value and/or a level below which something may be true and above which something may not be true. In particular, within the scope of the present invention, a threshold value may be a value below which an image may be suitable and above which an image may not be suitable for an analytical measurement. In particular, the threshold value may be used, for example, in determining the uniformity information element. For example, at least one element of uniformity information may indicate the suitability of an image for analytical measurement if the absolute value of said difference, in particular the difference between the average value of the color distribution of the first subset of pixels and the average value of the color distribution of the second subset of pixels, is less than the threshold value, or if the absolute value of the specified difference does not exceed the threshold value.

In particular, the method may include determining a minimum accuracy of the analytical measurement. In particular, the method may also include determining a threshold by converting the minimum accuracy of the analytical measurement to a threshold value by using a definable relationship between the color distribution and the result of the analyte measurement, in particular between the average value of the color distribution of the region of interest and the concentration of the analyte in the sample.

Further, step e) of the method may include a color distribution estimation performed on at least two color coordinates. More preferably, step e) of the method may include a color distribution estimation performed on at least three color coordinates. In particular, the color distribution can be evaluated independently, for example independently of each other for at least two color coordinates, more preferably independently of each other for at least three color coordinates. For example, the color distribution may be evaluated sequentially in time by a first color coordinate indicating, for example, values for red, a second color coordinate indicating, for example, values for yellow, and a third color coordinate indicating, for example, values for blue. colors.

In particular, step g) of the method can be performed independently on all of the at least two color coordinates. For example, the average value of the color distribution of the first subset of pixels and the average value of the color distribution of the second subset of pixels can be compared independently, in particular in an independent manner, for all of the at least two color coordinates. For example, the mean values of the color distribution may be compared sequentially over time for all of the at least two color coordinates.

In particular, at least one uniformity information element may be determined from each of the at least two color coordinates. In particular, image uniformity can be evaluated separately for each color coordinate. In particular, if the uniformity information element determined by the first color coordinate indicates that the image is unsuitable for analytical measurement, the image as a whole may be considered unsuitable for analytical measurement.

For example, the absolute value of the difference between the average value of the color distributions of the first subset of pixels and the average value of the color distributions of the second subset of pixels can be independently compared with at least one threshold value for each of the at least two color coordinates.

In addition, the test strip may contain at least one test field and at least one reference color field. In particular, step c) of the method can be performed such that at least one image includes at least one image or at least one partial image of the test field and at least one image or at least one partial image of the reference color field. . In particular, steps d) to g) of the method can be performed both for the image or partial image of the test field, and for the image or partial image of the reference color field, in particular, can be performed independently.

For example, the reference color field may comprise at least one white color field. In particular, the reference color field may include at least one field having a white color, in particular a predetermined white color or a shade of white color. For example, the reference color field may contain, in particular, the color of the test strip, such as the color of the substrate or carrier of the test strip. Thus, for example, the reference color field may simply be the substrate itself, such as the test strip carrier itself.

In particular, both the region of interest and the subregion of interest may have a shape independently selected from the group consisting of a rectangular shape, a square shape, a round shape, a round shape, as well as subtractions and/or combinations thereof.

Further, step e) of the method may include the exclusion of pixels whose color, in particular the color coordinates of which, is (are) outside the acceptance interval. In particular, pixels whose color is outside the acceptance interval [p ₁ -Δp ₁ , p ₂ +Δp ₂ ], where p ₁ is the lower percentile, p ₂ is the upper percentile, and Δp ₁ , Δp2 are positive tolerance areas, can be excluded. .

In particular, p ₁ may represent a 25% quantile of the color distribution, and p2 may represent a 75% quantile of the color distribution. In particular, the 25% quantile may also be referred to as the "lower quartile", and the 75% quantile may similarly be referred to as the "upper quartile".

For example, the tolerance regions Δp ₁ and Δp ₂ can be described by the following equations, referred to below as equation (1) and equation (2):

where f ₁ , f ₂ are positive tolerance coefficients, in particular satisfying the following expressions: f ₁ , f ₂ ≥1, in particular 1.0≤f ₁ , f ₂ ≤2.0, in particular 1.3≤f ₁ , f ₂ ≤1.7, especially f ₁ , f ₂ =1.5.

In particular, the acceptance interval may be [p ₁ -1.5⋅L, p ₂ +1.5⋅L], where L is the region from p ₁ quantile to p ₂ quantile. In the particular case where p ₁ is the 25% quantile and p ₂ is the 75% quantile, the L region may be the interquartile range (IQR), and thus, for example, L=IQR.

Further, method step d) may include determining a region of interest by pattern recognition to recognize at least one element selected from the group consisting of a test field, a test field part, a reference color field, and a reference color field part in the image.

In particular, the center of the region of interest may be located at the center of the test field or at the center of the reference color field within the image. The term "center" is in this context a broad term to be interpreted in its ordinary meaning familiar to the average specialist, and should not be limited to any particular or specialized meaning. In particular, the term may refer to, without limitation, a point or location indicating the middle of a figure or object. In particular, the center may be a point within a circle or sphere that is equidistant from all points on the circle or surface, or a point within a regular polygon that is equidistant from all vertices.

For example, at least one edge of the test field or reference color field may be excluded from the region of interest, preferably all edges of the test field or reference color field. In particular, the edges and vertices of the test field or reference color field may not be contained within the region of interest.

In particular, the center of the subregion of interest may be at the center of the region of interest.

The above threshold may be selected from the group consisting of an absolute threshold and a relative threshold, in particular a relative threshold depending on the number of pixels in the first subset of pixels.

In another aspect of the present invention, a computer-readable storage medium is provided that stores a computer program containing computer-executable instructions for performing at least steps d), e), f) and g) of the method according to the invention according to one of the embodiments described here. In particular, the computer-executable instructions may not only carry out steps d), e), f) and g) of the method, but optionally also one or both steps h)-i). In particular, the program is executed on a computer or computer network, in particular on the processor of a mobile device having at least one camera.

Thus, in general, the invention may be implemented in a computer program containing machine-executable instructions for carrying out the method of the present invention in one or more of the embodiments disclosed herein, when the program is executed on a computer or computer network, such computer program stored in a computer-readable storage medium. Thus, in particular, one step, more than one step, or even all steps of the method as mentioned above can be carried out using a computer or a computer network, preferably by means of a computer program. The computer, in particular, may be fully or partially integrated (embedded) in the mobile device, and computer programs, in particular, may be implemented as a software application. However, as an alternative to using an embedded computer, at least part of the computer may reside outside the mobile device.

In addition, the present application discloses and proposes a data carrier with a data structure stored therein, which, after being loaded into a computer or computer network, for example, into a random access memory or main storage device of a computer or computer network, provides for the implementation of the method in one or more variants of it. implementation disclosed in this description, in particular provides for the implementation of one or more of the steps of the method mentioned above.

In addition, the present application discloses and proposes a computer program product with program code means stored in a computer-readable storage medium for implementing the method in one or more of the embodiments disclosed herein when the program is executed on a computer or computer network. In this context, a computer program product refers to a program as a tradable good. In general, a product may exist in any format, such as a paper format or a computer-readable storage medium. In particular, the computer program product may be distributed over a data network.

Finally, the present application discloses and proposes a modulated information signal containing instructions readable by a computer system or computer network for implementing the method in one or more of the embodiments disclosed herein, in particular one or more of the method steps mentioned above.

In particular, the disclosure of the invention also provides for the possibility of its implementation in the following forms:

- a computer or computer network containing (th) at least one processor, configured to implement the method in one of the embodiments discussed in this description,

- a data structure loaded into a computer, which, when executed in a computer, provides for the implementation of the method in one of the embodiments of its implementation discussed in this description,

- a computer program that, when executed in a computer, provides for the implementation of the method in one of the embodiments of its implementation discussed in this description,

- a computer program containing software for implementing the method in one of its embodiments discussed in this description, when the computer program is executed on a computer or on a computer network,

- a computer program containing the software of the previous embodiment, in which the software is stored in a storage medium accessible to the computer for reading,

- a storage medium in which a data structure is stored, which, after being loaded into the main and / or random access memory of a computer or computer network, provides for the implementation of the method in one of the embodiments of its implementation discussed in this description, and

- a computer program product having program code means that can be stored or stored in a storage medium and, when executed on a computer or on a computer network, provides for the implementation of the method in one of the embodiments of its implementation discussed in this description.

In yet another aspect of the present invention, a mobile device for performing an analytical measurement is provided. The mobile device has at least one camera. The mobile device is configured to take at least one analytical measurement through the following steps:

A) capturing by the camera at least one image of at least a portion of the test strip, the image being comprised of a plurality of pixels;

B) determining, in particular recognizing, in the image at least one area of interest and correlating with the area of interest of the first subset of pixels;

B) estimating the color distribution within the first pixel subset and eliminating outliers in the first pixel subset;

D) determining, in particular recognizing, within the region of interest, at least one sub-region of interest having a smaller area than the region of interest, and correlating with the sub-region of interest of the second subset of pixels; and

E) comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element of image uniformity information.

For most of the terms used here and possible definitions, reference may be made to the description of the methods discussed above.

The mobile device may include at least one processor. In particular, the processor can be programmed to perform steps B)-E).

For possible definitions or embodiments of the invention, reference may be made to the above description of the method. Thus, in particular, a mobile device, in particular through the use of its processor, can be configured to carry out the method of performing an analytical measurement according to one of the embodiments described above or discussed in more detail below.

In yet another aspect of the present invention, a kit is provided for performing an analytical measurement. The set contains:

- at least one mobile device; and

at least one test strip capable of undergoing a color-changing analytical reaction on it, in particular an optical one, i.e. analyzed by optical methods, a test strip, primarily a test strip having at least one test field containing at least one indicator reagent for determining at least one analyte in the sample.

For possible definitions of terms and possible embodiments of the invention, reference may again be made to the description above or below.

Proposed in the present invention, the methods and devices can provide many advantages over known methods and devices for analytical measurements. Thus, in particular, the proposed in the present invention, the process of carrying out an analytical measurement can be characterized by less time compared to other processes known from the prior art. In particular, the present invention may allow the use of slightly defective images or images containing defective or non-ideal evaluation areas, such as a test field or a reference color field, for analytical measurement. The present invention may allow the use of images that would otherwise have to be discarded, thus providing a means for less time consuming and more practical analytical measurement than known methods and devices.

In addition, the present invention can improve the reliability of the analytical measurement process and its user-friendliness compared to prior art processes. In particular, the present invention can improve the reliability and usability of an application program, such as an application containing computer-executable instructions for performing an analytical measurement, compared to known applications or computer programs. In particular, the present invention can enable active enhancement (correction) of defective images or images containing defective or non-ideal evaluation areas, thereby allowing such images to be used. For example, by actively enhancing an image captured for an analytical measurement, the present invention can improve the reliability and ease of implementation of the analytical measurement process.

As a summary, the following are proposed embodiments of the present invention, not excluding other possibilities:

Option 1: Analytical measurement method, including the following steps:

a) providing at least one mobile device having at least one camera;

b) providing at least one test strip configured to undergo a color-changing analytical reaction on it when at least one sample is applied to the test strip, in particular to at least one test field of the test strip, containing at least one indicator reagent for detecting at least one analyte in a sample;

c) capturing by the camera at least one image of at least a portion of the test strip, the image consisting of a plurality of pixels;

d) determining, in particular recognizing, in the image at least one area of interest and correlating with the area of interest of the first subset of pixels;

e) estimating the color distribution within the first pixel subset and eliminating outliers in the first pixel subset;

d) determining, specifically recognizing, within the region of interest, at least one sub-region of interest having a smaller area than the region of interest, and assigning a second subset of pixels to the sub-region of interest; and

g) comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element of image uniformity information.

Option 2: The method of the previous option, also including:

h) interrupting the execution of the analytical measurement method if at least one uniformity information element indicates that the image is unsuitable for analytical measurement; and

i) assessing the image and obtaining at least one element of analytical information, in particular at least one element of information about the concentration of at least one analyte in the sample, if at least one element of information about uniformity indicates the suitability of the image for analytical measurement.

Option 3: The method according to one of the previous options, in which step g) includes comparing the absolute value of the difference between the average value of the color distribution of the first subset of pixels and the average value of the color distribution of the second subset of pixels with at least one threshold value

Option 4: The method of the previous option, wherein at least one element of uniformity information indicates the suitability of the image for analytical measurement if the absolute value of said difference is less than a threshold value or if the absolute value of said difference is less than a threshold value.

Option 5: The method according to one of the two previous options, including determining the minimum accuracy of the analytical measurement and including determining the threshold by converting the minimum accuracy of the analytical measurement to a threshold value by using a definable relationship between the color distribution and the result of the measurement of the analyte, in particular between the mean the value of the color distribution of the region of interest and the concentration of the analyte in the sample.

Option 6: The method according to one of the previous options, in which step e) includes a color distribution evaluation performed on at least two color coordinates, preferably on at least three color coordinates, in particular performed independently.

Option 7: The method according to the previous option, wherein step g) is performed independently on all of the at least two color coordinates.

Option 8: The method of the previous option, wherein at least one uniformity information element is determined from each of at least two color coordinates.

Option 9: The method according to one of the previous options, in which the test strip contains at least one test field and at least one reference color field, and step c) is performed so that at least one image includes at least one image or at least one partial image of the test field and at least one image or at least one partial image of the reference color field, and steps d)-g) are performed both for the image or partial image of the test field, and for the image or the partial image of the reference color field is in particular performed independently.

Option 10: The method according to the previous option, in which the reference color field contains at least one field of white color.

Embodiment 11: The method of one of the previous embodiments, wherein both the region of interest and the subregion of interest have a shape independently selected from the group consisting of a rectangular shape, a square shape, a round shape, a round shape, and a subtraction and/or combination thereof.

Option 12: The method according to one of the previous options, in which step e) is performed such that the exclusion of outliers in the first subset of pixels is performed using histogram analysis and/or percentile analysis of color distribution.

Option 13: The method according to one of the previous options, in which step e) includes the exclusion of pixels, color, in particular color coordinates, which are (are) outside the acceptance interval [p ₁ -Δp ₁ , p ₂ +Δp ₂ ], where p ₁ is the lower percentile, p ₂ is the upper percentile, and Δp ₁ , Δp ₂ are positive tolerance areas.

Embodiment 14: The method of the previous embodiment, wherein p ₁ is the 25% quantile of the color distribution and p ₂ is the 75% quantile of the color distribution.

Option 15: The method according to one of the two previous options, in which the tolerant regions are described by the expressions:

Δp ₁ \u003d f ₁ ⋅ (p ₂ -p ₁ ),

and Δp ₂ \u003d f ₂ ⋅ (p ₂ -p ₁ ),

where f ₁ , f ₂ are positive tolerance coefficients, in particular satisfying the following expressions: f ₁ , f ₂ ≥1, in particular 1.0≤f ₁ , f ₂ ≤2.0, in particular 1.3≤f ₁ , f ₂ ≤1.7, especially f ₁ , f ₂ =1.5.

Option 16: The method of the previous option, in which p ₁ is a 25% quantile of the color distribution, and p ₂ is a 75% quantile of the color distribution, and the acceptance interval is [p ₁ -1.5⋅L, p ₂ +1.5⋅L], where L is the area from p ₁ quantile to p ₂ quantile.

Option 17: The method according to one of the previous options, in which step d) includes determining the region of interest by the pattern recognition method for recognizing in the image at least one element selected from the group consisting of a test field, a part of the test field, a reference color field , parts of the reference color field.

Option 18: The method of the previous option, wherein the center of the region of interest is at the center of the test field or at the center of the reference color field within the image.

Option 19: The method according to one of the two previous options, in which at least one edge of the test field or reference color field is excluded from the region of interest, preferably all edges of the test field or reference color field.

Option 20: The method according to one of the two previous options, in which the center of the subregion of interest is in the center of the region of interest.

Option 21: The method according to one of the previous options, also including comparing the number of pixels included in the first subset of pixels with at least one threshold value, on the basis of which at least one element of information about the adequacy of the size of the area of interest is determined, and if at least one element of sufficient size information indicates that the region of interest is of insufficient size, the analytical measurement method is interrupted.

Embodiment 22: The method of the previous embodiment, wherein the threshold is selected from the group consisting of an absolute threshold and a relative threshold, in particular a relative threshold dependent on the number of pixels in the first subset of pixels.

Embodiment 23: The method of one of the preceding embodiments, further comprising comparing the number of pixels in the first pixel subset before outlier elimination in step e) with the number of pixels in the first pixel subset after outlier elimination in step e).

Option 24: The method according to the previous option, in which if the number of pixels in the first subset of pixels after the elimination of outliers in step e) is less than a predetermined percentage of the number of pixels in the first subset of pixels before the elimination of outliers in step e), the analytical measurement method is interrupted.

Option 25: Computer program containing computer-executable instructions for implementing the method according to one of the previous options, in particular steps d), e), f) and g) of the method, and, if necessary, one or both steps h) - i), when performing programs in a computer or computer network, in particular in the processor of a mobile device having at least one camera.

Option 26: A mobile device for taking an analytical measurement, having at least one camera and capable of taking at least one analytical measurement through the following steps:

A) capturing the camera at least one image of at least part of the test strip, and the image consists of a plurality of pixels;

B) determining, in particular recognizing, in the image at least one area of interest and correlating with the area of interest of the first subset of pixels;

B) estimating the color distribution within the first pixel subset and eliminating outliers in the first pixel subset;

D) determining, in particular recognizing, within the region of interest, at least one sub-region of interest having a smaller area than the region of interest, and correlating with the sub-region of interest of the second subset of pixels; and

E) comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element of image uniformity information.

Option 27: The mobile device according to the previous option, containing at least one processor programmed to perform steps B)-E).

Option 28: A mobile device according to one of the previous options related to a mobile device, made in particular by a processor, with the possibility of implementing the method according to one of the options of the latter.

Option 29: Analytical measurement kit comprising:

- at least one mobile device according to one of the previous options related to a mobile device; and

- at least one test strip configured to undergo a color-changing analytical reaction on it, in particular an optical test strip, in particular a test strip having at least one test field containing at least one indicator reagent for determining in a sample of at least one analyte.

Brief description of the drawings

Other optional features of the invention and the possibility of its implementation are disclosed in more detail in the following description of the preferred embodiments of the invention, preferably in conjunction with dependent claims. In this case, the corresponding optional features can be implemented, as it is clear to the specialist, separately, as well as in any arbitrary combination. The scope of protection of the invention is not limited to the preferred embodiments. Embodiments of the invention are shown schematically in the drawings. In the drawings, like reference numerals refer to like or functionally comparable elements. The drawings show:

in fig. 1 and 2 are block diagrams of a method for carrying out an analytical measurement;

in fig. 3 is a perspective view of one embodiment of a kit and a mobile device for performing an analytical measurement;

in fig. 4 is a variant of an image captured by a mobile device;

in fig. 5A and 6A show variants of images captured by a mobile device and a region of interest defined thereon;

in fig. 5B and 6B are variants of the histograms corresponding to FIG. 5A and 6A; and

in fig. 7 and 8 show variants of images captured by the mobile device and the region of interest defined thereon, as well as the defined subregion of interest.

Detailed description of embodiments of the invention

In FIG. 1 is a flow diagram of a method for performing an analytical measurement in one embodiment. The method includes step a) (step 110 in the flowchart) of providing at least one mobile device 112 having at least one camera 114. For example, a mobile device 112 having at least one camera 114 can be provided as shown in FIG. 3. The method also includes step b) (step 116 in the flowchart) of providing at least one test strip 118 configured to undergo a color-changing analytical reaction on it when at least one sample is applied to the test strip 118 . The sample can be applied, in particular, to at least one test field 120 containing at least one indicator reagent for determining at least one analyte in the sample. In particular, the test strip 118 and test field 120 shown in FIG. 3. Additionally, the test strip 118 may also contain a reference color field 121.

The method also includes step c) (step 122 in the flowchart) of camera 114 capturing at least one image 124 of at least a portion of test strip 118. In particular, image 124, as shown in FIG. 4. Image 124 is composed of a plurality of pixels. In addition, the method includes step d) (step 126 in the flowchart) determining (finding), in particular recognizing, in the image 124 at least one area of interest 128 and correlating with this area of interest 128 of the first subset of pixels. In particular, a region of interest 128 can be determined, as shown, for example, in FIG. 5A.

The method also includes step e) (step 130 in the flowchart) of estimating the color distribution within the first subset of pixels and eliminating outliers in the first subset of pixels. In addition, the method includes step e) (step 132 in the flowchart) determining (finding), in particular recognizing, within the region of interest 128 at least one sub-region of interest 134 having a smaller area than the region of interest 128, and correlation with the subregion of interest 134 of the second subset of pixels. The method also includes step g) (step 136 in the flowchart) comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element image homogeneity information 124.

As shown in FIG. 2, the implementation flow of the analytical measurement method in this embodiment may also include a branch 138. Branch 138 may indicate a condition request, such as deciding between the first branch 140 and the second branch 142. For example, when requesting a condition, an information element about homogeneity. The uniformity information element may include logical image uniformity information 124 such as "good" ("yes") or "unsuitable" ("no"). The first branch 140 indicates that the image 124 is unsuitable for performing an analytical measurement, and therefore the first branch 140 leads to step h) (step 144 in the flowchart), namely, to aborting the analytical measurement method if at least one piece of information homogeneity indicates that the image 124 is unsuitable for analytical measurement. In particular, if the uniformity information element indicates that the image 124 is "unsuitable" for measuring blood glucose, the blood glucose measurement may not be taken.

The second branch 142 indicates the suitability of the image 124 for an analytical measurement. Therefore, the second branch leads to step i) (step 146 in the flowchart), namely to evaluate the image 124 and obtain at least one element of analytical information, in particular at least one element of information about the concentration of at least one analyte in sample, if at least one element of uniformity information indicates the suitability of the image 124 for analytical measurement. In particular, if the uniformity information element indicates that the image 124 is suitable for taking a blood glucose measurement, a blood glucose measurement may be performed. In particular, at least one element of information about the concentration of at least one analyte in the sample can be obtained from image 124.

In FIG. 3 is a perspective view of a kit 148 and a mobile device for performing an analytical measurement in one embodiment of the invention. Kit 148 includes at least one mobile device 112 and at least one test strip 118 configured to undergo a color-changing assay reaction thereon. The mobile device 112 having the camera 114 may also include a processor 149. The mobile device 112 may be configured, in particular by the processor 149, to perform the method shown in FIG. 1 and 2. The test strip 118 may in particular be optical, i. analyzed by optical methods, a test strip. In particular, as described above, the test strip 118 may have at least one test field 120 containing at least one indicator (analytical) reagent for determining at least one analyte in a sample.

Mobile device 112, as shown in FIG. 3 may capture with camera 114 at least one image 124 of at least a portion of test strip 118. A variation of image 124 captured by mobile device 112 is shown in FIG. 4. In particular, the image 124 is composed of a plurality of pixels. As shown in FIG. 4, the image 124 of at least a portion of the test strip 118 may have various defective or non-ideal evaluation areas, such as damage 150 of the test strip 118 and/or soiled or dirty areas 152 within the test field 120 or reference color field 121. .

In addition, as shown in FIG. 5A, at least one region of interest 128 can be defined within image 124, and a first subset of pixels can be associated with region of interest 128. Region of interest 128 may be in the form of subtracting a circular shape from a rectangular shape, as shown by broken lines, for example. For example, within the region of interest 128 within the reference color field 121, there may be dirty or dirty areas 152. The dirty or dirty area 152 shown in FIG. 5A may in particular be a red stain of blood. In FIG. 5B is a histogram corresponding to that shown in FIG. 5A of region of interest 128. This histogram may be based on a single color coordinate, such as color coordinates indicating values for red. In particular, the histogram may represent the distribution of the number of pixels (vertical axis) over the red values of those pixels (horizontal axis). As can be seen, some pixels may have a darker shade of red, such as pixels having values of 120-170 units on the horizontal axis, than most pixels having values around 180 units on the horizontal axis. Thus, compared to that shown in FIG. 5A region of interest, pixels having a darker shade of red can be clearly associated with soiled or dirty areas 152, in particular with a red-colored blood stain located within region of interest 128.

After evaluating the color distribution within the first subset of pixels and eliminating outliers in the first subset of pixels, dirty or dirty areas 152, in particular a red-colored blood spot located within the reference color field 121, will no longer be within the region of interest 128, as shown in FIG. 6A. In FIG. 6B is a histogram corresponding to that shown in FIG. 6A of region of interest 128. This histogram, as shown in FIG. 6B is based on color coordinates indicative of values for red and represents the distribution of the number of pixels (vertical axis) over the red values of pixels (horizontal axis) within the region of interest 128 shown in FIG. 6A. As can be seen, the area of interest 128 no longer contains pixels having a darker shade of red, such as pixels having values of 120-170 units on the horizontal axis.

Within region of interest 128, a subregion of interest 134 can be defined. Subregion of interest 134, in particular, has a smaller area than region of interest 128, as shown in FIG. 7 and 8. In particular, as shown in FIG. 7, subregion of interest 134 may have a different shape than region of interest 128, for example.

List of reference symbols

110 - step a): providing at least one mobile device having at least one camera

112 - mobile device

114 - camera

116 - step b): providing at least one test strip configured to undergo a color-changing analytical reaction on it when at least one sample is applied to the test strip

118 - test strip

120 - test field

121 - reference color field

122 - step c): camera capture of at least one image of at least part of the test strip

124 - image

126 - step d): determination of at least one region of interest in the image 128 region of interest

130 - step e): evaluation of the color distribution within the first subset of pixels and elimination of outliers in the first subset of pixels

132 - step e): determining, within the region of interest, at least one subregion of interest having a smaller area than the region of interest, and assigning a second subset of pixels to the subregion of interest

134 - subregion of interest

136 - step g): comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element of image uniformity information

138 - branching

140 - first branch

142 - second branch

144 - step h): interrupting the execution of the analytical measurement method if at least one element of uniformity information indicates that the image is unsuitable for analytical measurement,

146 - step i): evaluating the image and obtaining at least one element of analytical information, in particular at least one element of information about the concentration of at least one analyte in the sample, if at least one element of information about uniformity indicates the suitability of the image for carrying out an analytical measurement

148 - set

149 - processor

150 - damage

152 - dirty areas.

Claims (38)

1. A method for conducting an analytical measurement, including the following steps: a) providing at least one mobile device (112) having at least one camera (114); b) providing at least one test strip (118) configured to undergo a color-changing analytical reaction on it when at least one sample is applied to at least one test field (120) of the test strip (118) containing at least one indicator reagent for detecting at least one analyte in a sample; c) camera (114) capturing at least one image (124) of at least a portion of the test strip (118), wherein the image (124) consists of a plurality of pixels; d) determining in the image (124) at least one area of interest (128) and correlating with the area of interest (128) of the first subset of pixels; e) estimating the color distribution within the first pixel subset and eliminating outliers in the first pixel subset; e) determining within the region of interest (128) at least one sub-region of interest (134) having a smaller area than the region of interest (128), and correlating with the sub-region of interest (134) a second subset of pixels; and g) comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element of image uniformity information (124), wherein the method also includes at least one of the following: - comparing the number of pixels included in the first subset of pixels with at least one threshold value, on the basis of which at least one element of information about the sufficiency of the size of the region of interest (128) is determined, and if at least one element of information about the sufficiency of the size indicates the fact that the area of interest (128) is of insufficient size, the method of conducting an analytical measurement is interrupted, - comparison of the number of pixels in the first subset of pixels before the elimination of outliers in step e) with the number of pixels in the first subset of pixels after the elimination of outliers in step e), and if the number of pixels in the first subset of pixels after elimination of outliers in step e) is less than a given percentage of the number pixels in the first pixel subset until outliers are eliminated in step e), the analytical measurement method is interrupted. 2. The method according to the previous paragraph, also including: h) interrupting the execution of the analytical measurement method if at least one uniformity information element indicates that the image (124) is unsuitable for analytical measurement; and i) evaluating the image (124) and obtaining at least one element of analytical information, if at least one element of information about uniformity indicates the suitability of the image (124) for performing an analytical measurement. 3. The method according to one of the preceding claims, wherein step g) includes comparing the absolute value of the difference between the average value of the color distribution of the first subset of pixels and the average value of the color distribution of the second subset of pixels with at least one threshold value. 4. The method according to the previous paragraph, in which at least one element of information about uniformity indicates the suitability of the image (124) for analytical measurement if the absolute value of the specified difference is less than the threshold value or if the absolute value of the specified difference does not exceed the threshold value. 5. The method according to one of the previous claims, in which step e) includes a color distribution evaluation performed on at least two color coordinates, and step g) is performed independently on all of at least two color coordinates, and at least one element of uniformity information is determined for each of the at least two color coordinates. 6. The method according to one of the preceding paragraphs, in which the test strip contains at least one test field (120) and at least one reference color field, and step c) is performed so that at least one image (124) includes including at least one image (124) or at least one partial image (124) of the test field (120) and at least one image or at least one partial image of the reference color field (121), wherein steps d)- g) is performed both for the image (124) or partial image of the test field (120), and for the image (124) or partial image (124) of the reference color field (121), moreover, the reference color field (121) includes at least at least one white field. 7. The method according to one of the previous claims, in which step e) is performed such that the exclusion of outliers in the first subset of pixels is performed using a histogram analysis and/or a percentile analysis of the color distribution. 8. The method according to one of the previous claims, in which step e) includes the exclusion of pixels whose color is outside the acceptance interval [p ₁ -Δp ₁ , p ₂ +Δp ₂ ], where p ₁ is the lower percentile, p ₂ - upper percentile, and Δp ₁ , Δp ₂ - positive tolerant areas. 9. The method according to one of the two previous paragraphs, in which the tolerant areas are described by the expressions: Δp ₁ \u003d f ₁ ⋅ (p ₂ -p ₁ ), and Δp ₂ \u003d f ₂ ⋅ (p ₂ -p ₁ ), where f ₁ , f ₂ - positive coefficients of tolerance. 10. The method according to one of the previous paragraphs, in which step d) includes determining the region of interest (128) by a pattern recognition method to recognize in the image (124) at least one element selected from the group consisting of a test field (120) , parts of the test field (120), reference color field (121), part of the reference color field (121). 11. A computer-readable storage medium that stores a computer program containing computer-executable instructions for performing at least steps d), e), f) and g) of the method according to one of the previous paragraphs when the program is executed on a computer or computer network. 12. A mobile device (112) for performing an analytical measurement, having at least one camera (114) and configured to perform at least one analytical measurement through the following steps: A) camera (114) capturing at least one image (124) of at least a portion of the test strip (118), wherein the image (124) consists of a plurality of pixels; B) determining on the image (124) at least one area of interest (128) and correlating with the area of interest (128) of the first subset of pixels; B) estimating the color distribution within the first pixel subset and eliminating outliers in the first pixel subset; D) determining within the region of interest (128) at least one sub-region of interest (134) having a smaller area than the region of interest (128), and correlating with the sub-region of interest (134) of the second subset of pixels; and E) comparing at least one average value of the color distribution of the first subset of pixels and at least one average value of the color distribution of the second subset of pixels and determining by this comparison at least one element of image uniformity information (124), wherein at least one of the following is implemented: - comparing the number of pixels included in the first subset of pixels with at least one threshold value, on the basis of which at least one element of information about the sufficiency of the size of the region of interest (128) is determined, and if at least one element of information about the sufficiency of the size indicates the fact that the region of interest (128) is of insufficient size, the analytical measurement is interrupted, - comparison of the number of pixels in the first subset of pixels before the elimination of outliers in step e) with the number of pixels in the first subset of pixels after the elimination of outliers in step e), and if the number of pixels in the first subset of pixels after elimination of outliers in step e) is less than a given percentage of the number pixels in the first pixel subset until outliers are eliminated in step e), the analytical measurement is interrupted. 13. Set (148) for analytical measurement, containing: - at least one mobile device (112) according to the previous paragraph; and - at least one test strip (118) configured to undergo a color-changing analytical reaction on it and having at least one test field (120) containing at least one indicator reagent for determining at least one analyte in the sample .

Images