Calibration method for camera of mobile device for detecting analyte in sample

Abstract

To provide a calibration method (110) for a camera (112) of a mobile device (114) for detecting an analyte in a sample.SOLUTION: A method includes: (a) capturing at least one image of at least one object (116) by the use of a camera (112), a lighting source 120 of a mobile device (114) being turned on during the capturing (118); (b) determining, from the image captured in the step (a), at least one first region (124) in the image which is affected by direct reflection of light generated by the lighting source (120) and reflected by the object (116)(122); and (c) determining at least one second region (128) which does not substantially overlap with the first region (124) in the image and then returning the second region (128) as a target region (130) at a position of a test field (132) of a test piece (134) in a following detection step (126).SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present application relates to a method for calibrating a camera of a mobile device for detecting an analyte in a sample, and a detection method for detecting an analyte in a sample by using the camera of the mobile device. The present invention further relates to a computer program comprising program means for performing the method according to the present invention. Furthermore, the present invention relates to a mobile device. The method, computer program and mobile device according to the present invention can be used in medical diagnosis for qualitatively or quantitatively detecting one or more analytes in one or more body fluids. However, other application fields of the present invention are possible.

Background Art

[0002] In the field of medical diagnosis, it is often necessary to detect one or more analytes from a sample of a body fluid such as blood, interstitial fluid, urine, saliva, or other types of body fluids. Examples of analytes to be detected are glucose, triglyceride, lactate, cholesterol, or other types of analytes normally present in these body fluids. Depending on the concentration and / or presence of the analyte, an appropriate treatment can be selected as needed.

[0003] Generally, devices and methods known to those skilled in the art utilize test elements containing one or more test chemicals 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 these test chemicals, reference can be made, for example, to J. Hoenes et al.: The Technology Behind Glucose Meters: Test Strips, Diabetes Technology & Therapeutics, Volume 10, Supplement 1, 2008, S-10~S-26. Other types of test chemicals are possible and can be used to implement the present invention.

[0004] In analytical measurements, particularly those based on color reactions, one technical challenge lies in the evaluation of color changes resulting from detection reactions. In addition to using dedicated analytical devices such as handheld blood glucose meters, the use of generally available electronic devices such as smartphones and portable computers has become increasingly common in recent years. WO 2012 / 131386 discloses a test device for performing an assay, the test device comprising a container containing a reagent, the reagent reacting to an applied test sample by exhibiting a color or pattern change, and a portable device which is a mobile phone or laptop computer including, for example, a processor and an image capture device, the processor being configured to process data captured by the image capture device and output a test result of the applied test sample.

[0005] WO 2014 / 025415 discloses a method and apparatus for performing a color-based reaction test on biological materials. The method includes capturing and reading digital images of the non-exposed and later exposed devices within an automatically calibrated environment. The device includes some test-specific sequences of a Unique Identification (UID) label, a Reference Color Bar (RCB) providing a standardized color sample for image color calibration, and Chemical Test Pads (CTP). The method further includes identifying the position of the device within the image, extracting the UID, extracting the RCB, and identifying the position of a plurality of CTPs within each image. The method further reduces the image noise of the CTP and automatically calibrates the image according to the illumination measurements performed on the RCB. In this method, the test result is further determined by comparing the color of the CTP image with the color of a Manufacturer Interpretation Color Chart (MICC). The method displays these results in graphical or quantitative mode.

[0006] European Patent Application Publication No. 1801568 discloses a test strip and a method for measuring the concentration of an analyte in a biological fluid sample. This method includes placing a camera on the test strip to detect a color indicator and a reference color area in a picture. A measurement of the relative position between the camera and the test strip is determined and compared with a target value area. While there is a deviation between the measurement and the target value, the camera is moved to reduce the deflection with respect to the test strip. The image area assigned to the indicator is localized in the color image detected by the camera. The concentration of the analyte to be analyzed is determined in the sample by a comparison value.

[0007] European Patent No. 1963828 discloses a method for measuring the concentration of at least one analyte contained in a sample of biological fluid, comprising: a) preparing a test strip having at least one test point, at least one time indicator, and at least one reference color range including white and / or a color scale; b) bringing the fluid sample into contact with the test point and the time indicator; c) disposing a color indicator at the test point as a function of the concentration of the analyte; d) the color of the time indicator changing as a function of the time of contact of the fluid with the test point, independently of the concentration of at least one analyte; e) placing a camera on the test strip; f) determining at least one measurement of the relative position between the camera and the test strip and comparing it with a nominal value range; g) if there is a discrepancy between the measurement and the nominal value range, moving the camera relative to the test strip to reduce the discrepancy, and repeating steps f) and g); h) recording, using the camera, a color image in which at least the color indicator, the time indicator, and the reference color range are imaged; j) localizing in the color image the image areas associated with the color indicator, the time indicator, and the reference color range and determining the color values of these image areas; k) determining the period between the time the fluid sample comes into contact with the test point and the time the color image is recorded, with the aid of a predetermined reference value based on the color value determined for the time indicator; l) determining the concentration of the analyte in the sample using a predetermined comparison value based on the color value determined for the color indicator and the reference color, and on the period.

[0008] The reliability and accuracy of analytical measurements using mobile computing devices generally depend on many technical factors. Specifically, a vast number of mobile devices equipped with cameras are on the market, and they all have different technical and optical characteristics that must be considered for analytical measurements. For example, International Publication No. WO 2007 / 079843 describes a method for measuring the concentration of an analyte contained in a sample of biological fluid. In the method, a test strip is provided that includes at least one test point and at least one reference color section that includes white and / or a color scale. A liquid sample is brought into contact with the test point, and a color indicator is placed at the test point according to the concentration of the analyte. A camera is disposed on the test strip. At least one measurement value is detected for the relative position between the camera and the test strip and compared to a range of set values. When the measurement value is outside the range of the set values, the camera is moved relative to the test strip to reduce the deviation. A color image representing at least the color indicator and the reference color section is detected with the aid of the camera. Image regions are allocated to the color indicator and the color matching section, and the color values of the image regions are determined. The concentration of the analyte in the sample is determined based on the color values using pre-defined comparison values. European Patent Application Publication No. EP 3108244 and International Publication No. WO 2015 / 120819 describe a test strip module that includes a case, a test strip within the case, and a position anchor that extends across a mating surface to a surface of a mobile computing device. The position anchor has a shape that matches a feature of the surface of the mobile computing device.

[0009] International Publication No. 2015 / 038717 describes a system and method for the analysis of fluids. The system includes an opaque container for receiving a liquid sample, a color change indicator disposed on a surface of a cup that is submerged in the fluid sample when the cup contains the fluid sample, a color standard disposed on the surface against which the color of the color change indicator is compared, a camera disposed near the container so as to have a view of the surface and coupled to a processor, an artificial light source for illuminating the surface with standard illumination, and a light diffuser disposed between the artificial light source and the surface. The processor receives an image captured by the camera, extracts a color value from the color change indicator, normalizes the color value against the color standard, and quantitatively associates the color value with a known color value of the color change indicator when exposed to a standardized amount of a known reagent during the test.

[0010] Despite the advantages associated with using a mobile computing device for the purpose of performing analytical measurements, several technical challenges remain. Specifically, it is necessary to improve and ensure the reliability and accuracy of the measurements. The main problem is the presence and influence of gloss. When using an on-board lighting device and an imaging device of a mobile computing device, the light generated from the lighting device first may be at least partially reflected by the test element. Such reflected light may interfere with the evaluation of the color formed in the reagent field of the test element and may not guarantee the reliability and accuracy of the measurement results due to the presence and influence of gloss. Furthermore, the position of the gloss may depend on the relative positions of the lighting device and the camera of the mobile device and may vary depending on the type or model of the mobile device due to the vast number of different mobile devices available in the market. SUMMARY OF THE INVENTION PROBLEMS TO BE SOLVED BY THE INVENTION

[0011] Therefore, it is desirable to provide a method and a device for addressing the above technical problems of analytical measurements using a mobile device such as a mobile device of a household electrical appliance, particularly a general-purpose mobile device that is not dedicated to analytical measurements such as a smartphone or a tablet computer. Specifically, it is necessary to propose a method and an apparatus for ensuring the reliability and accuracy of measurements.

Means for Solving the Problems

[0012] This problem is addressed by a method for calibrating a camera of a mobile device for detecting an analyte in a sample, a detection method for detecting an analyte in a sample by using the camera of the mobile device method, a computer program, and a mobile device, which have the features of the independent claims. The dependent claims describe advantageous embodiments that can be implemented alone or in any combination.

[0013] As used hereinafter, the terms "having", "comprising", "including" or any grammatical variations thereof are used in a non-exclusive manner. Therefore, these terms may refer to both a situation where there are no additional features in the entity being described in this context in addition to the features introduced by these terms, and a situation where one or more additional features are present. As an example, the expressions "A has B", "A comprises B" and "A includes B" may all refer to a situation where there are no other elements in A other than B (i.e., a situation where A consists of B alone and exclusively), and a situation where one or more additional elements such as element C, elements C and D, and further additional elements are present in the entity A in addition to B.

[0014] Furthermore, it should be noted that terms such as "at least one", "one or more" indicating that a feature or element can be present one or more times are usually only used once when introducing each feature or element. In the following, in most cases, when referring to each feature or element, the expressions "at least one" or "one or more" are not repeated despite the fact that each feature or element can be present one or more times.

[0015] Furthermore, as used hereinafter, terms such as "preferably", "more preferably", "particularly", "more particularly", "specifically", "more specifically" or similar terms are used in conjunction with any feature without limiting the possibility of alternatives. Thus, the features introduced by these terms are any features and are not intended to limit the scope of the claims in any way. The present invention can be implemented, as will be appreciated by those skilled in the art, by using alternative features. Similarly, features introduced by "in an embodiment of the present invention" or similar expressions are any features without any limitation regarding alternative embodiments of the present invention, without any limitation regarding the scope of the present invention, and without any limitation regarding the possibility of combining features introduced in such a way with any other optional or non-optional features of the present invention.

[0016] In a first aspect, a method for calibrating a camera of a mobile device for analyte detection in a sample is disclosed. This method, by way of example, includes the following steps that can be performed in a given order. However, it should be noted that another order is also possible. Furthermore, it is also possible to perform one or more method steps once or repeatedly. Furthermore, it should be noted that it is also possible to perform two or more method steps simultaneously or overlapping in a timely manner. The present method can include additional method steps not described.

[0017] The present method includes the following steps. a) Capturing at least one image of at least one object by using a camera, wherein during said capturing, the illumination source of the mobile device is turned on. b) Determining, from the image captured in step a), at least one first region within the image that is affected by direct reflection of light generated from the illumination source and reflected by the object. c) Determining at least one second region within the image that does not substantially overlap with the first region and returning the second region as a target region for the position of the test field of the test piece in subsequent detection steps.

[0018] As used herein, the term "mobile device" is a broad term and should be given its ordinary customary meaning to those skilled in the art and should not be limited to a special or customized meaning. This term may specifically, but not exclusively, refer to mobile electronic devices, and more specifically, mobile communication devices such as mobile phones or smartphones. Additionally or alternatively, as further outlined in more detail below, the mobile device may also refer to a tablet computer or another type of portable computer having at least one camera.

[0019] As used herein, the term "test piece" is a broad term and should be given its ordinary and customary meaning to one of ordinary skill in the art and should not be limited to a special or customized meaning. Specifically, without limitation, this term can refer to any element or device configured to perform a color change detection reaction. A test piece can, in particular, have a test field containing at least one test chemical for detecting at least one analyte. By way of example, a test element can include at least one substrate, such as at least one carrier, to which or in which at least one test field is applied. As an example, at least one carrier can be strip-shaped, thereby making the test element a test piece. These test pieces are generally widely used and are available. One test piece can have a single test field or multiple test fields containing the same or different test chemicals. At least one sample may be applied to the test piece.

[0020] As used herein, the term "test field" is a broad term and should be given its ordinary and customary meaning to one of ordinary skill in the art and should not be limited to a special or customized meaning. Specifically, without limitation, this term can refer to a coherent amount of test chemical for, for example, a field of circular, polygonal or rectangular shape having one or more layers of material and having at least one layer of the test field containing the test chemical. Other layers can be present to provide specific optical properties, such as reflective properties, to provide diffusion properties for diffusing the sample, or to provide separation properties, such as separation of the particulate components of the sample, such as cell components.

[0021] As used herein, the term "test chemical substance" is a broad term and should be given its ordinary and customary meaning to those skilled in the art and should not be limited to a special or customized meaning. Specifically, this term may refer to a plurality of compounds such as a compound or a mixture of compounds suitable for performing a detection reaction in the presence of an analyte, and the detection reaction is detectable by specific means such as optically. The detection reaction may specifically be analyte-specific. The test chemical substance may in this case specifically be an optical test chemical substance such as a color-changing test chemical substance whose color changes in the presence of an analyte. The color change may particularly depend on the amount of analyte present in the sample. The test chemical substance may include, for example, at least one enzyme such as glucose oxidase and / or glucose dehydrogenase. Further, other components such as one or more dyes and mediators may be present. Test chemical substances are generally known to those skilled in the art, and reference can be made to J. Hoenes et al.: Diabetes Technology and Therapeutics, Vol. 10, Supplement 1, 2008, pp. 10-26. However, other test chemical substances can also be used.

[0022] As used herein, the term "analyte" is a broad term and should be given its ordinary and customary meaning to those skilled in the art and should not be limited to a special or customized meaning. Specifically, this term may refer to, but is not particularly limited to, one or more specific compounds and / or other parameters to be detected and / or measured. As an example, at least one analyte may be a compound involved in metabolism such as one or more of glucose, cholesterol, or triglyceride. Additionally or alternatively, other types of analytes or parameters such as, for example, the pH value can be determined.

[0023] As used herein, the term "detecting an analyte in a sample" is a broad term and should be given its ordinary and customary meaning to one of ordinary skill in the art and should not be limited to a special or customized meaning. This term may specifically, but not limited to, refer to the quantitative and / or qualitative determination of at least one analyte in any sample. For example, the sample may include a body fluid such as blood, interstitial fluid, urine, saliva or other types of body fluids. As an example, the result of the analytical measurement 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, and thus, the result of the analytical measurement may be, for example, the blood glucose concentration.

[0024] As used herein, the term "calibration" is a broad term and should be given its ordinary and customary meaning to one of ordinary skill in the art and should not be limited to a special or customized meaning. The term calibration may refer to at least one process for ensuring pre-defined or pre-specified image capture conditions and / or for adjusting and / or adapting image capture conditions that depend on the mobile device and / or camera hardware configuration, e.g., the type or model of the mobile device. The calibration method may be configured to ensure that pre-defined and / or pre-specified image capture conditions are met during subsequent determination of the analyte in the sample. This can improve the robustness, reliability, and accuracy of the measurement.

[0025] As used herein, the term "camera" is a broad term and should be given its ordinary and customary meaning to those skilled in the art and should not be limited to a special or customized meaning. Specifically, but not limited to, this term can refer to a device having at least one imaging element configured to record or capture spatially resolved one-dimensional, two-dimensional, or three-dimensional optical information. As an example, a camera can 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. For example, a camera can be a color camera including at least three color pixels, as will be described in detail below. The camera can be a color CMOS camera. For example, a camera can include black and white pixels and color pixels. The color pixels and black and white pixels can be combined inside the camera. A camera can include at least one color camera and at least one black and white camera such as a black and white CMOS. A camera can include at least one black and white CMOS chip. A camera generally can include a one-dimensional or two-dimensional array of image sensors such as pixels. As an example, a camera can include at least 10 pixels in at least one dimension, such as at least 10 pixels in each dimension. However, note that other cameras can also be used. A camera can be a camera of a mobile communication device. The present invention must be applicable to cameras commonly used in mobile applications such as notebook computers, tablets, or specifically mobile phones such as smartphones. Thus, specifically, a camera can be part of a mobile device including one or more data processing devices such as one or more data processors in addition to at least one camera. However, other cameras can also be used. A camera can include additional elements such as one or more optical elements such as one or more lenses in addition to at least one camera chip or imaging chip. As an example, a camera can be a fixed-focus camera having at least one lens fixedly adjusted with respect to the camera.However, alternatively, the camera may also include one or more variable lenses that can be adjusted automatically or manually.

[0026] The camera can specifically be a color camera. Thus, for each pixel etc., color information such as color values of three colors R, G, B can be provided or generated. More color values, such as four colors, can also be used for each pixel. Color cameras are generally known to those skilled in the art. Thus, by way of example, each pixel of a camera chip can have color recording pixels such as three or more different color sensors, for example, one pixel for red (R), one pixel for green (G), and one pixel for blue (B). For each pixel such as R, G, B, depending on the intensity of each color, the value can be recorded by a pixel such as a digital value in the range from 0 to 255. By way of example, instead of using a triple of colors such as R, G, B, a quadruple such as C, M, Y, K or RGGB, BGGR, RGBG, GRGB, RGGB can be used. The color sensitivity of the pixel can be generated by a color filter such as a color filter array, for example, by at least one Bayer filter, or by the appropriate inherent sensitivity of the sensor element used in the camera pixel. These techniques are generally known to those skilled in the art.

[0027] As used herein, without limitation, the term "image" may relate, in particular, to data recorded using a camera, such as multiple electronic readings from an imaging device such as the pixels of a camera chip. Thus, the image itself may include pixels, and the pixels of the image correlate to the pixels of the camera chip. Thus, when referring to "pixel", either the unit of image information generated by a single pixel of the camera chip or a single pixel of the camera chip is directly referenced. An image may include raw pixel data. For example, an image may include data within the RGGB space, monochromatic data from one of the R, G, or B pixels, a Bayer pattern image, etc. An image may include evaluated pixel data such as a full-color image or an RGB image. The raw pixel data can be evaluated, for example, by using a demosaicing algorithm and / or a filtering algorithm. These techniques are generally known to those skilled in the art. The term "capturing at least one image" refers to one or more of imaging, image recording, image acquisition, image capture. The term "capturing at least one image" may include capturing a single image and / or multiple images such as a series of images. For example, capturing an image may include continuously recording a series of images such as a video or a movie. The capture in step a) can be performed within a time frame of less than 1 second, preferably less than 0.5 second, more preferably less than 0.1 second. However, longer time frames are possible.

[0028] The capture of at least one image may be initiated by a user action or automatically when the presence of at least one object within the field of view of the camera and / or within a predetermined sector of the field of view is automatically detected. These automatic image acquisition techniques are known, for example, in the field of automatic barcode readers such as automatic barcode reading applications.

[0029] For example, in step a), a plurality of images can be captured. The plurality of images may include at least one sequence of images. In step b), at least one image that meets at least one predefined and / or pre-specified selection criterion among the plurality of images can be selected and used. The predefined and / or pre-specified selection criteria can be provided in a look-up table and / or determined empirically or semi-empirically. The selection criteria can, as an example, be further stored in a storage device included in the mobile device. Specifically, the selection criteria can be stored in the storage device by software, more specifically by an application. The predefined or pre-specified selection criteria can be selected from the group consisting of at least one sharpness criterion, at least one spatial criterion, and the state of ambient light. The sharpness criterion can include at least one sharpness threshold such that if exceeded, the image is considered "in focus" or "sharp". The image can be captured such that the object fills and / or covers the largest area of the image. In step b), among the plurality of images, an image in which the object fills and / or covers the largest area of the image can be selected and used. The spatial criterion can include at least one angle threshold that, for example, refers to an acceptable deviation from a plane-parallel position of the mobile device with respect to any plane of the object. The spatial criterion may depend on the distance between the camera and the object. For example, an angular deviation from the plane-parallel position of the mobile device may be considered acceptable if it is less than 25°, preferably less than 20°, and most preferably less than 15°. Step b) can include selecting the best image from the sequence of images, for example, the image that best meets the predefined or pre-specified selection criteria. The sequence of images can be captured continuously during at least one time interval. Step b), for example, the selection of the image, and / or step c) can be performed online, that is, while the image sequence is being captured. The capture can be repeated, for example, until at least one image that meets the selection criteria is determined.

[0030] When capturing an image, a visual display such as visual guidance can be provided to the user. The visual display can be provided to the user before capturing the image. The visual display can include at least one instruction such as a text message and / or a graphic instruction. For example, the visual display can include a visualization of an object, or a part of the object such as the contour and / or the outer shape of the object. The visual display can include a contour of the object or a reference area on the object, for example, a frame corresponding to the shape of the object superimposed on the display of the mobile device, and provides visual guidance for positioning the camera with respect to the object. When it is determined that sharpness criteria and / or spatial criteria are met, in particular when it is determined that the contour of the object of the visual display overlaps the object, the capture of at least one image can be automatically started. The visual display may depend on the object used in step a). For example, the visual display such as the contour and / or the outer shape of the object can be determined empirically and / or can be stored in at least one look-up table and / or at least one data storage of the mobile device by software, specifically by at least one app downloaded from an app store or the like. Additionally or alternatively, audio guidance or other types of guidance can be provided.

[0031] As used herein, the term "object" refers to any object having pre-defined surface characteristics, particularly planar surface characteristics and / or pre-defined reflection characteristics. The object used in step a) can be selected from the group consisting of at least one flat surface, a reference card, at least one test piece for detecting an analyte in a sample, the test piece having at least one test field containing at least one test chemical for performing an optical detection reaction in the presence of the analyte, at least one test piece container, and at least one, particularly the packaging of the test piece. The packaging can be a packaging selected from the group consisting of a packaging for a single test piece, a packaging for a plurality of test pieces such as two or more test pieces, and a test piece container. Thus, one or more test piece containers, a packaging for receiving at least one test element, or the object itself such as a test piece or a part thereof can function as an object. In step a), the distance between the camera and the object can be 0.03 m to 0.3 m, preferably 0.03 to 0.15 m, and most preferably 0.03 to 0.1 m. For example, shorter distances may be possible depending on the type of mobile device, the angle between the object and the camera, and the depth of the object.

[0032] The mobile device and the object can be arranged such that the camera of the mobile device and the object, particularly at least one surface of the object, are essentially parallel to each other. As used herein, the term "essential parallel" refers to the condition that the object and the camera are parallel to each other with a tolerance, for example, of ±20° or less, preferably ±10° or less, more preferably ±5° or less. The object may include at least one position marker. The relative position and / or orientation between the object and the camera can be determined by using the position marker. For example, the position marker may include at least one OpenCV ArUco marker. Techniques for determining the position using OpenCV ArUco markers are generally known to those skilled in the art. Further, the mobile device may comprise at least one position sensor adapted to determine a spatial position, particularly an angular position and / or at least one orientation in space. For example, the object may be a flat surface such as a table and / or a wall, and the mobile device can be arranged parallel to the flat surface, for example, on top, by the user. For example, the object may be at least one package having at least one flat surface, such as a cubic package. The mobile device and / or the package can be arranged parallel to each other in a plane. For example, the object may be placed on a table, and the mobile device can be placed by the user relative to the object. To ensure a parallel orientation, a visual display may be provided to the user when arranging the object and the mobile device relative to each other. Specifically, the mobile device may comprise a display. The mobile device can be adapted to provide a visual display on the display. For example, the visual display may include at least one prompt and / or at least one instruction to the user regarding how to adapt and / or change and / or arrange the mobile device relative to the object and / or how to adapt and / or change and / or arrange the object relative to the mobile device.The visual representation may include at least one text message and / or at least one graphic instruction. In particular, when capturing an image of an object, a visual representation can be provided to the user. When it is determined that the relative position and / or orientation is satisfied, the capture of at least one image can be automatically started. This enables hands-free operation, particularly the calibration and / or measurement of the object to be analyzed.

[0033] As used herein, the term "lighting source of a mobile device" refers to any light source of a mobile device. The term "lighting source" refers to at least one device adapted to generate light for illuminating an object. As used herein, the term "light" generally refers to one or more electromagnetic radiations in the visible spectrum range, ultraviolet spectrum range, and infrared spectrum range. The term "visible spectrum range" generally refers to the spectrum range of 380 nm to 780 nm. Preferably, the light used within the present invention is light in the visible spectrum range. The lighting source may include at least one light-emitting diode integrated into the mobile device. The lighting source may have two states, namely, an on state in which at least one light beam is generated to illuminate the object and an off state in which the lighting source is off. As used herein, the term "turned on" refers to the lighting source being on to illuminate the object or being in an on state in which it generates a light ray for illuminating the object. The mobile device may include a further lighting device such as at least one lighting source adapted to illuminate the display, and / or the display may be designed as a further lighting source itself.

[0034] The calibration method may further include evaluating whether the illumination source is configured to provide an illumination intensity sufficient to perform the detection method. Evaluating whether the illumination source is configured to provide sufficient illumination can use at least one threshold method. The sufficiency of the illuminance may depend on the surface characteristics of the object and / or the state of the ambient light. In particular, for bright objects with high reflection characteristics, it may be sufficient with a lower light intensity compared to dark objects with low reflection characteristics. Further, for example, in the case of bright ambient light conditions due to sunlight, a higher intensity may be required compared to shielded ambient light conditions.

[0035] As outlined above, from the image captured in step a), at least one first region within the image that is affected by the direct reflection of light generated by the illumination source and reflected by the object is determined. The term "first region" refers to a region of any shape within the image. In particular, the first region can be one or more of at least one stripe, at least one quadrant, at least one rectangular region, at least one circle. For example, the first region can correspond to a circle having the radius of the light spot generated by the direct reflection within the image. The illumination source of the mobile device can illuminate the object. However, in a mobile device, the illumination source and the camera are arranged such that the light rays generated by the illumination source, particularly the flash light, are at least partially reflected by the object. The term "affected by the direct reflection of the light generated by the illumination source" refers to the light spot within the image generated by the direct reflection of the light beam generated by the illumination source. The light spot within the image can be a region brighter than the surrounding image regions.

[0036] Histogram analysis of the image can be used to determine the first region in step b). Histogram analysis can include determining the position of the first region within the image. Histogram analysis can include determining the maximum intensity within the image and the position of the maximum intensity within the image. The first region can be determined by using at least one intensity threshold in the histogram analysis. The histogram analysis can include at least one two-dimensional Gaussian fit. For example, an image region where the intensity exceeds 1σ can be regarded as the first region. Using histogram analysis, it can be determined whether the light source functions properly, that is, whether an appropriate amount of light is generated to illuminate the object.

[0037] In step c), at least one second region that does not essentially overlap with the first region is determined within the image, and the second region is returned as the target region for the position of the test field of the test piece in subsequent detection steps. The detection step can be carried out, in particular, after the calibration method. Thus, the detection step may not be part of the calibration method. The term "second region" refers to a region or zone of the image that is different from the first region, and a small overlap between the first region and the second region is possible. The second region can be a continuous region of the image. As used herein, the term "target region" refers to a region where the test field of the test piece can be placed in subsequent detection steps. The target region can be a predetermined or pre-specified region where it is assumed that the test field of the test piece is placed while capturing the image. The second region can be determined such that the influence by the direct reflection of light from the light source is prevented and / or minimized and / or at least significantly reduced. The target region can be determined to be a zone affected by the direct light reflection from the light source, particularly away from the first region. Further, the target region can be determined such that the analyte can be determined, for example, the test field is sufficiently illuminated and within the field of view of the camera. The second region can be determined to be a region of the image with essentially uniform illumination. The term "essentially uniform illumination" refers to the condition of uniform illumination with an allowable error of 10% or less, preferably 5% or less, and most preferably 1% or less. The second region can be determined to be a region where the illumination intensity is below at least one intensity threshold. The second region can be selected such that the illumination generated by the light spot from the direct reflection is minimized.

[0038] As outlined below, the detection method includes at least one step in which a visual display is provided to the user to arrange the test piece relative to the camera such that the test field is at least partially located in the target region. The target region may have the same shape as the shape of the test piece or a part of the shape. The target region can be configured as the outer shape or overlap of the test piece. The visual display may be an overlay of the live image of the camera on the display of the mobile device and the target region, for example, the contour of the test piece. Thus, when the test piece is placed within the field of view of the camera, the visual display shows the overlap between the target region and the test piece, enabling the user to easily position the target region and the test piece.

[0039] As used herein, the term "essentially non-overlapping" refers to the first region and the second region being spatially separated regions. However, there may be an overlapping region that does not affect the measurement of the analyte. For example, the regions of the first region and the second region may overlap by less than 10%, preferably less than 5%, and most preferably less than 1%. For example, a captured image may be segmented into at least four segments, for example, in quadrants. The first region may be assigned to at least one first segment of the image. The second region may be assigned to at least one second segment of the image that is different from the first segment. For example, the first region may be determined to be in the lower left quadrant. The second region may be assigned to the upper left quadrant and / or the upper right quadrant and / or the lower right quadrant.

[0040] The term "return the second region as the target region" refers to generating at least one piece of information about the location of the target region. The information about the location of the target region may be provided as a prompt to the computing means of the mobile device, for example, to external computing means or the computing means such as a processor. The computing means can adapt and / or generate a visual display for arranging the test piece and the mobile device relative to each other based on the information about the location of the target region.

[0041] In a further aspect of the present invention, a detection method for detecting an analyte in a sample by using a camera of a mobile device is disclosed. This method includes, by way of example, the following steps that can be performed in a given order. However, it should be noted that another order is also possible. Furthermore, it is also possible to perform one or more method steps once or repeatedly. It should also be noted that it is possible to perform two or more method steps simultaneously or in a timely overlapping manner. The method can include additional method steps not described. The method includes the following steps. i) Calibrating the camera by using the calibration method according to the present invention. ii) Providing at least one test piece for detecting an analyte in a sample, the test piece having at least one test field containing at least one test chemical for performing an optical detection reaction in the presence of the analyte. iii) Applying at least one sample to the test field of the test piece. iv) Providing a visual indication to the user for positioning the test piece with respect to the camera such that the test field is at least partially disposed in a target area. v) Capturing at least one image of the test field by using the camera, wherein during the capturing, the illumination source of the mobile device is turned on. vi) Determining the analyte concentration in the sample from the image captured in step v).

[0042] Regarding the embodiments and the definition of the detection method, reference is made to the description of the calibration method above and will be further described in more detail below. In particular, with respect to method step i), reference can be made to the description of the calibration method above.

[0043] As used herein, the term "visual display" refers to visual guidance for a user regarding how to position a mobile device and a test piece relative to each other. The mobile device may comprise a display adapted to display a visual display. The visual display may include a text message, at least one instruction for the user such as a prompt, and / or at least one graphical instruction. For example, the visual display may include visualization of a portion of the test piece such as the test piece or the contour and / or outer shape of the test piece. The visual display may specifically be visual guidance, overlaid on the display of the mobile device, providing visual guidance for positioning a camera relative to the test piece, which may be, for example, the contour of the shape of the test piece or may include it. The visual display may include relative visualization of both the mobile device and the test piece. The visual display may include position information such as direction and / or distance prompts, such as at least one arrow and / or at least one text message. The term "at least partially located in the target area" refers to the test piece and / or the mobile device being positioned such that the test piece covers the target area with a tolerance of 20% or less, preferably 10% or less, most preferably 5% or less, and / or matches exactly.

[0044] Determination of analyte concentration may include optical detection. As used herein, the term "optical detection" refers to the detection of a reaction using an optical test chemical such as a color-changing test chemical whose color changes in the presence of an analyte. The color change may depend in particular on the amount of analyte present in the sample. Step vi) may include analyzing the color of a spot on the test field of the test strip, said spot comprising at least partially the sample. Techniques for determining an analyte by optical detection, in particular for analyzing the color of a spot on a test field, are generally known to those skilled in the art. Several algorithms generally known to those skilled in the field of analysis, such as in the field of blood glucose monitoring, can be used to evaluate at least one image and derive at least one analysis information therefrom. Thus, by way of example, the color of a test element such as the color of at least one test field having at least one test chemical can be evaluated. By way of example, when evaluating an image, the region of interest can be defined within the image of the test element, such as the region of interest within the test field of the test element, and the color analysis can be performed, such as a statistical analysis. By way of example, a rectangular, square, polygonal, elliptical, or circular region of interest can be defined within the portion of the image recognized as an image of the test field. Subsequently, a statistical analysis of the color of the pixels within the region of interest can be performed. By way of example, one or more color coordinates can be derived for the pixels, and a statistical analysis of the color coordinates can be performed over the region of interest. By way of example, the center of the distribution of at least one color coordinate can be determined. The term "insertion plane" as used herein is a broad term and should be given its ordinary customary meaning by those skilled in the art and should not be limited to a special or customized meaning. Specifically, this term can refer to, but is not limited to, the coordinates of any color coordinate system used to describe color using coordinates. Several color coordinate systems are generally known to those skilled in the art and can also be used in the context of the present invention. Thus, by way of example, a colorimetric coordinate system or coordinate system based on human perception, such as the CIE 1964 color space, the Munsell color system, or other coordinate systems such as R, G, B, L, a, b, can be used.

[0045] Thus, in order to derive analysis information from an image, as an example, a predetermined or determinable relationship between at least one color coordinate of a test element such as a test field can be monitored. As outlined above, the statistical analysis can be performed on a test element or a part thereof, such as over a test field containing at least one test chemical and / or over a region of interest within a test field containing at least one test chemical. Thus, as an example, at least one test field within an image of the test element can preferably be automatically recognized, for example, by pattern recognition and / or other algorithms as described in the following examples. Also in this case, one or more regions of interest can be defined within a partial image of the test field. Also here, by using one or more histograms, it is possible to determine a region of interest, color coordinates, for example: also in this case, the color coordinates of blue and / or the coordinates of other colors. The statistical analysis can include placing one or more fitting curves as described above on at least one histogram, thereby, for example, determining the center of a peak. Thus, a color-forming reaction can be monitored by using one or more images, and for one or more images, the center of a peak can be determined by using statistical analysis, thereby determining a color shift within at least one coordinate. As is generally known to those skilled in the art, when a color development reaction ends or reaches a predetermined or determinable endpoint, a shift in at least one color coordinate or the color coordinate of the endpoint can be determined from blood glucose monitoring, and can be converted, for example, into the concentration of an analyte in a sample by using a predetermined or determinable correlation between the color coordinate and the concentration. As an example, the correlation as a conversion function, conversion table, or look-up table can be determined empirically and can be stored, as an example, in at least one data storage device of a mobile device by an app downloaded from software, especially an app store, etc.

[0046] As will be outlined in more detail below, the calibration method and the detection method can be implemented, fully or partially, on a computer of a mobile device, particularly a processor of a mobile device, such as a mobile device. Thus, specifically, the method may include at least one processor and software instructions for performing one or more of at least method steps b) and c) of the calibration method and / or method steps i), iv), and vi) of the detection method. Specifically, these methods may be implemented fully or partially as so-called apps for Android or iOS, for example, and may be downloadable from an app store. The software instructions, particularly the apps, may further provide user instructions by one or more of a display, voice commands, or other commands to support the method steps of the calibration method and / or the detection method. Among them, as shown above, method steps a), b), and c) may also be implemented, fully or partially, by a computer by automatically taking at least one image of at least one object by using a camera when the object enters the field of view of the camera and / or within a specific range within the field of view. The processor for performing the calibration method and / or the detection method may specifically be part of a mobile device.

[0047] As outlined above, the mobile device may specifically be a mobile computer and / or a mobile communication device. Thus, specifically, the mobile device may be selected from the group consisting of a mobile communication device, specifically a smartphone, a portable computer, particularly a notebook, a tablet computer.

[0048] As shown above, further method steps can be implemented on a computer or assisted by a computer, particularly by a processor of a mobile device. Thus, by way of example, visual guidance for a user to position a mobile device relative to an object and / or a specimen can be computer-implemented or computer-assisted. Additionally or alternatively, audio guidance or other types of guidance can be provided.

[0049] In a further aspect of the invention, a computer program is disclosed that includes computer-executable instructions for performing a calibration method according to any one of the embodiments described herein. Specifically, the computer-executable instructions may be suitable for performing one or more of method steps a), b) and c). In particular, the program is executed on a computer or a computer network, specifically on a processor of a mobile device having at least one camera.

[0050] Thus, generally speaking, when the program is executed on a computer or a computer network, a computer program including computer-executable instructions for performing the method according to the present disclosure is further disclosed and proposed in one or more embodiments included herein. Specifically, the computer program can be stored on a computer-readable data carrier. Thus, specifically, one, two or more, or all of the method steps disclosed herein can be performed using a computer or a computer network or any suitable data processing means, preferably using a computer program. The computer can be specifically integrated completely or partially into a mobile device, and the computer program can be specifically embodied as a software application. However, alternatively, at least a part of the computer may be located outside the mobile device.

[0051] A data carrier storing a data structure is further disclosed and proposed, which can execute the method according to one or more embodiments disclosed herein after being loaded into a computer or a computer network, such as the working memory or main memory of a computer or a computer network.

[0052] When the program is executed on a computer or a computer network, a computer program product having program code stored on a machine-readable carrier is further disclosed and proposed to execute the calibration method according to one or more embodiments included herein. As used herein, a computer program product refers to a program as a tradable product. The product generally exists in any format, such as a paper format, or on a computer-readable data carrier. Specifically, the computer program product may be distributed via a data network.

[0053] Finally, what is disclosed and proposed herein is a modulated data signal including instructions readable by a computer system or a computer network for executing a calibration method according to one or more embodiments disclosed herein, specifically one or more steps of the calibration method as described above.

[0054] Specifically, the following is further disclosed herein. - A computer or a computer network comprising at least one processor, wherein the processor is adapted to execute the method according to one of the embodiments described in this description. - A computer-loadable data structure adapted to execute the calibration method according to one of the embodiments described herein while the data structure is being executed on a computer. - A computer program adapted to execute a calibration method according to one of the embodiments described in this description while the program is being executed on a computer. - A computer program including program means for executing a calibration method according to one of the embodiments described in this description while the computer program is being executed on a computer or on a computer network. - A computer program including the program means according to the previous embodiment, wherein the program means is stored on a computer-readable storage medium. - A storage medium in which a data structure is stored, and after the data structure is loaded into the main storage unit and / or the working storage unit of a computer or a computer network, the storage medium is adapted to execute a method according to one of the embodiments described herein. - A computer program product having program code means that can store the program code means or can be stored on a storage medium to execute a calibration method according to one of the embodiments described in this description when the program code means is executed on a computer or a computer network.

[0055] In a further aspect of the present invention, a computer program including computer-executable instructions for executing a detection method according to any one of the embodiments described herein is disclosed. Specifically, the computer-executable instructions may be suitable for executing one or more of method steps i) to vi). In particular, the program is executed on a computer or a computer network, specifically on a processor of a mobile device having at least one camera.

[0056] Thus, generally speaking, when a program is executed on a computer or a computer network, in one or more embodiments included herein, a computer program including computer-executable instructions for executing the detection method according to the present disclosure is further disclosed and proposed. Specifically, the computer program can be stored in a computer-readable data carrier. Thus, specifically, one, two or more, or all of the method steps disclosed herein can be executed using a computer or a computer network or any suitable data processing device, preferably using a computer program. The computer can specifically be fully or partially integrated into a mobile device, and the computer program can specifically be embodied as a software application. However, alternatively, at least a part of the computer may be disposed outside the mobile device.

[0057] A data carrier storing a data structure is further disclosed and proposed, which can execute the calibration method according to one or more embodiments disclosed herein after being loaded into a computer or a computer network, such as the working memory or main memory of the computer or computer network.

[0058] When the program is executed on a computer or a computer network, a computer program product having program code stored in a machine-readable carrier is further disclosed and proposed for executing the detection method according to one or more embodiments included herein. As used herein, a computer program product refers to a program as a tradable product. The product generally exists in any format, such as in a paper format, or on a computer-readable data carrier. Specifically, the computer program product may be distributed via a data network.

[0059] Finally, what is disclosed and proposed in this specification is a detection method according to one or more embodiments disclosed in this specification, specifically, a modulated data signal including instructions readable by a computer system or a computer network for executing one or more steps of the detection method as described above.

[0060] Specifically, the following is further disclosed in this specification. - A computer or computer network comprising at least one processor, wherein the processor is adapted to execute a method according to one of the embodiments described in this description. - A computer loadable data structure adapted to execute a detection method according to one of the embodiments described in this specification while the data structure is being executed on a computer. - A computer program adapted to execute a detection method according to one of the embodiments described in this description while the program is being executed on a computer. - A computer program including program means for executing a detection method according to one of the embodiments described in this description while the computer program is being executed on a computer or a computer network. - A computer program including the program means according to the previous embodiment, wherein the program means is stored on a computer-readable storage medium. - A storage medium on which a data structure is stored, and after the data structure is loaded into the main storage and / or working storage of a computer or a computer network, the storage medium is adapted to execute a method according to one of the embodiments described in this specification. - A computer program product having program code means that can store, or can be stored on a storage medium, the program code means for performing the detection method according to one of the embodiments described in this description when the program code means is executed on a computer or a computer network.

[0061] In a further aspect of the present invention, a mobile device for performing analytical measurements is disclosed. The mobile device - includes at least one camera, - includes at least one light source, - and includes at least one processor including program means for performing a calibration method according to one of the preceding embodiments.

[0062] For most of the terms and possible definitions used in this specification, reference can be made to the description of the above method.

[0063] The processor may further include program means for performing the detection method according to any one of the foregoing embodiments. The mobile device may be a mobile communication device.

[0064] The apparatus and method according to the present invention provide many advantages over known apparatuses and methods of the same kind. The present invention can improve the reliability and usability of the process of performing analytical measurements as compared to processes known in the art. Specifically, the present invention can improve the reliability and usability of an application, for example, an application including computer-executable instructions for performing analytical measurements, as compared to a known application or computer program. In particular, the present invention can enable robust, especially invariant, image capture conditions for camera hardware configurations such as different positions of the LED flash with respect to different mobile devices and / or cameras for each particular mobile device. Specifically, this is ensured by dynamically placing the contour of the test piece, such as the frame of the test piece for test piece recognition, on the display of the mobile device outside the zone affected by the direct light reflection of the light generated from the light source and reflected by the test piece. The present invention can provide improved reliability and accuracy of an application or computer program that uses mobile camera images because the influence of gloss is essentially avoided or at least significantly reduced.

[0065] In summary, the following embodiments can be envisioned without excluding further possible embodiments.

[0066] [Embodiment 1] A calibration method for a camera of a mobile device for detecting an analyte in a sample, the calibration method comprising the following. a) Capturing at least one image of at least one object by using the camera, wherein the illumination source of the mobile device is turned on during the capturing. b) Determining at least one first region within the image affected by the direct reflection of the light generated from the illumination source and reflected by the object from the image captured in step a). c) determining at least one second region in the image that does not substantially overlap with the first region and returning the second region as a target region for the position of the test field of the test piece in subsequent detection steps.

[0067] [Embodiment 2] The calibration method according to the preceding embodiment, wherein histogram analysis of the image is used to determine the first region in step b).

[0068] [Embodiment 3] The calibration method according to the preceding embodiment, wherein the first region is determined by using at least one threshold of intensity in histogram analysis.

[0069] [Embodiment 4] The calibration method according to any one of the preceding two embodiments, wherein the histogram analysis includes at least one two-dimensional Gaussian fit.

[0070] [Embodiment 5] The captured image is segmented into at least four segments, the first region is assigned to at least one first segment of the image, and the second region is assigned to at least one second segment of the image different from the first segment. The calibration method according to any one of the preceding embodiments.

[0071] [Embodiment 6] The calibration method according to any one of the preceding embodiments, further including evaluating whether the illumination source is configured to provide sufficient illumination intensity to execute the detection method.

[0072] [Embodiment 7] The calibration method according to the preceding embodiment, evaluating whether an illumination source configured to provide sufficient illumination uses at least one threshold method.

[0073] [Embodiment 8] The calibration method according to any one of the preceding embodiments, wherein the calibration method further takes into account the distance and / or angle between the camera and the object.

[0074] [Embodiment 9] The calibration method according to the preceding embodiments, wherein the object includes at least one position marker, and the relative position and / or orientation between the object and the camera is determined by using the position marker.

[0075] [Embodiment 10] The calibration method according to any one of the preceding embodiments, wherein in step a), a plurality of images are captured, the plurality of images includes at least one image sequence, and in step b), at least one image among the plurality of images that satisfies at least one predefined selection criterion is selected and used.

[0076] [Embodiment 11] The calibration method according to the preceding embodiments, wherein the image sequence is continuously captured during at least one time interval, and steps b) and / or c) are performed during the capture of the image sequence.

[0077] [Embodiment 12] The calibration method according to any one of the preceding embodiments, wherein the camera is a camera of a mobile communication device.

[0078] [Embodiment 13] The calibration method according to any one of the preceding embodiments, wherein in step a), the distance between the camera and the object is 0.03 m to 0.3 m, preferably 0.03 to 0.15 m, and most preferably 0.03 to 0.1 m.

[0079] [Embodiment 14] The object used in step a) is at least one flat surface, a reference card, a test piece having at least one test field for detecting an analyte in a sample and including at least one test chemical substance for performing an optical detection reaction in the presence of the analyte, at least one test piece container, at least one, in particular the packaging of the test piece, and is selected from the group consisting of. The calibration method according to any one of the preceding embodiments.

[0080] [Embodiment 15] The calibration method according to the preceding embodiments, wherein at least one sample is applied to the test piece.

[0081] [Embodiment 16] The calibration method according to any one of the preceding embodiments, wherein the illumination source of the mobile device includes at least one light-emitting diode integrated into the mobile device.

[0082] [Embodiment 17] The calibration method according to any one of the preceding embodiments, wherein the capture in step a) is performed within a time frame of less than 1 second, preferably less than 0.5 second, more preferably less than 0.1 second.

[0083] [Embodiment 18] A detection method for detecting an analyte in a sample by using a camera of a mobile device, the method comprising the following. i) Calibrating the camera by using the calibration method according to any one of the preceding embodiments. ii) Providing at least one test strip for detecting an analyte in a sample, the test strip having at least one test field containing at least one test chemical for performing an optical detection reaction in the presence of the analyte. iii) Applying at least one sample to the test field of the test strip. iv) Providing a visual indication to the user for positioning the test strip relative to the camera such that the test field is at least partially disposed within a target area. v) Capturing at least one image of the test field by using the camera, wherein the illumination source of the mobile device is turned on during the capture. vi) Determining the analyte concentration in the sample from the image captured in step v).

[0084] [Embodiment 19] The detection method according to the preceding embodiment, wherein step vi) includes analyzing the color of a spot on the test field of the test strip, the spot at least partially containing the sample.

[0085] [Embodiment 20] A computer program including program means for executing a calibration method according to one of the foregoing embodiments with reference to the calibration method while the computer program is being executed on a computer or on a computer network, particularly on a processor of a mobile device.

[0086] [Embodiment 21] The computer program according to the preceding embodiment, the computer program including program means for executing the following steps. Determining at least one first region of an image that is affected by direct reflection of light generated from an illumination source and reflected by an object from the image captured in step a). Determining at least one second region in the image that does not substantially overlap with the first region and returning the second region as a target region for the position of the test field of the test piece in subsequent detection steps.

[0087] [Embodiment 23] A computer program including program means for executing a detection method according to one of the foregoing embodiments with reference to the detection method while the computer program is being executed on a computer or on a computer network, particularly on a processor of a mobile device.

[0088] [Embodiment 24] The computer program according to the preceding embodiment, the computer program including program means for executing the following steps. - i) Calibrating the camera by using a calibration method according to any one of the foregoing embodiments. - iv) Providing a visual indication to the user for placing the test piece with respect to the camera such that the test field is at least partially disposed in the target region. - vi) Determining the analyte concentration in the sample from the image captured in step v).

[0089] [Embodiment 25] A mobile device, at least one camera, and At least one light source, At least one processor comprising program means for executing a calibration method according to one of the foregoing embodiments referring to the calibration method, a mobile device.

[0090] [Embodiment 26] The mobile device according to the preceding embodiment, wherein the processor further comprises program means for executing a detection method according to any one of the foregoing embodiments referring to the detection method.

[0091] [Embodiment 27] The mobile device according to any one of the preceding two embodiments, wherein the mobile device is a mobile communication device.

[0092] Any further optional features and embodiments are preferably disclosed in more detail in the subsequent description of the embodiments in conjunction with the dependent claims. Among them, each optional feature can be realized independently and in any feasible combination, as will be understood by those skilled in the art. The scope of the present invention is not limited by the preferred embodiments. The embodiments are schematically shown in the figures. Among them, the same reference signs in these figures refer to the same or functionally comparable elements.

Brief Description of the Drawings

[0093]

Figure 1

Figure 2

Figure 3

Figure 4

Mode for Carrying Out the Invention

[0094] FIG. 1 shows a flowchart of a calibration method 110 for calibrating a camera 112 of a mobile device 114 for detecting an analyte in a sample, and a flowchart of a method for detecting the analyte 115. The calibration method 110 includes the following steps: a) Capturing at least one image of at least one object 116 by using the camera 112 (indicated by reference numeral 118), wherein during the capturing, the illumination source 120 of the mobile device 114 is turned on. b) Determining, from the image captured in step a), at least one first region 124 in the image that is affected by the direct reflection of light generated from the illumination source 120 and reflected by the object 116 (indicated by reference numeral 122). c) Determining at least one second region 128 in the image that does not substantially overlap with the first region 124, and returning the second region 128 as a target region 130 for the position of the test field 132 of the test strip 134 in subsequent detection steps (indicated by reference numeral 126).

[0095] FIG. 2 shows a perspective view of a mobile device 114 for performing the calibration method 110. Further, at least one object 116 is shown. The object 116 can be selected from the group consisting of at least one flat surface, a reference card, at least one test strip 134 for detecting an analyte in a sample, the at least one test strip having at least one test field 132 containing at least one test chemical for performing an optical detection reaction in the presence of the analyte, at least one test strip container, and at least one, in particular the packaging 136 of the test strip 134. In the embodiment shown in FIG. 2, the object 116 can be the packaging 136. In step a) 118, the distance between the camera 112 and the object 116 can be 0.03 m to 0.3 m, preferably 0.03 to 0.15 m, and most preferably 0.03 to 0.1 m.

[0096] The mobile device 114 and the object 116 can be arranged such that the camera 112 of the mobile device 114 and the object 116, particularly at least one surface of the object 116, are essentially parallel to each other. The object 116 can include at least one position marker 138, for example, at least one OpenCV ArUco marker. The relative position and / or orientation between the object 116 and the camera 112 can be determined by using the position marker 138, particularly the OpenCV ArUco marker. As shown in FIG. 2, the object 116 can be at least one package 136 having at least one flat surface including at least one position marker 138. For example, the package 136 can be a cubic package. The mobile device 114 and / or the package 136 can be arranged parallel to each other in a plane. For example, the object 116 can be placed on a table, and the mobile device 114 can be placed by the user relative to the object 116. When arranging the object 116 and the mobile device 114 relative to each other, a visual display can be provided to the user. Specifically, the mobile device 114 can include a display 140, and the visual display can be provided on the display 140. The mobile device 114 can include at least one processor 142. The processor 142 can be adapted to generate a visual display. For example, the visual display can include at least one prompt and / or at least one instruction to the user on how to adapt and / or change and / or arrange the mobile device 114 relative to the object 116 and / or how to adapt and / or change and / or arrange the object 116 relative to the mobile device 114. The visual display can include at least one text message and / or at least one graphic instruction. In particular, a visual display can be provided to the user when capturing an image of the object 116. If it is determined that the relative position and / or orientation can be satisfied, the capture of at least one image can be automatically started. This enables hands-free operation, particularly the calibration and / or measurement of the object to be analyzed.

[0097] The illumination source 120 may include at least one light-emitting diode integrated into the mobile device 114. The illumination source 120 may have two states, namely, an on state in which light rays for illuminating the object 116 are generated and an off state in which the illumination source 120 is off. The mobile device 114 may include additional illumination devices such as at least one illumination source for illuminating the display 140, and / or the display 140 may be designed as an additional illumination source itself. The calibration method 110 may further include evaluating whether the illumination source 120 is configured to provide an illumination intensity sufficient to perform the detection method. Evaluating whether the illumination source 120 is configured to provide sufficient illumination can use at least one threshold method. The sufficiency of the illumination intensity may depend on the surface characteristics of the object 116 and / or the ambient light conditions. In particular, in the case of a bright object 116 having high reflection characteristics, it may be sufficient with a lower light intensity compared to a dark object 116 having low reflection characteristics. Further, for example, in the case of bright ambient light conditions such as sunlight, a higher intensity may be required compared to shielded ambient light conditions. In step a) 118, a single image of the object 116 may be captured, and / or a plurality of images of the object 116 such as a series of images may be captured. For example, capturing an image may include continuously recording a series of images such as a video or a movie. The capture in step a) 118 can be performed within a time frame of less than 1 second, preferably within a time frame of less than 0.5 second, more preferably within a time frame of less than 0.1 second. The capture of at least one image of the object may be initiated by a user action or may be automatically initiated when the presence of at least one object 116 within the field of view of the camera 112 and / or within a predetermined sector of the field of view is automatically detected. These automatic image acquisition techniques are known, for example, in the field of automatic barcode readers such as automatic barcode reading applications.

[0098] For example, in step a) 118, a plurality of images can be captured. The plurality of images may include at least one sequence of images. In step b) 122, at least one image among the plurality of images that meets at least one predefined and / or pre-specified selection criterion can be selected and used. The predefined and / or pre-specified selection criterion can be provided in a look-up table and / or can be determined empirically or semi-empirically. The selection criterion can, for example, be further stored in a storage device configured by the mobile device 114. Specifically, the selection criterion can be stored in the storage device by software, more specifically by an app. The predefined or pre-specified selection criterion can be selected from the group consisting of at least one sharpness criterion, at least one spatial criterion, and the state of ambient light. The sharpness criterion can include at least one sharpness threshold such that if exceeded, the image is considered "in focus" or "sharp". The spatial criterion can include, for example, at least one angular threshold that refers to an acceptable deviation from the plane-parallel position of the mobile device 114 with respect to any plane of the object 116. Step b) 122 can include selecting the best image from the sequence of images, for example, the image that best meets the predefined or pre-specified selection criterion. The sequence of images can be captured continuously during at least one time interval. Step b) 122, for example, the selection of the image, and / or step c) 126 can be performed online, that is, while the image sequence is being captured. The capture can be repeated, for example, until at least one image that meets the selection criterion is determined. As outlined above, a visual display such as visual guidance can be provided to the user when capturing an image of the object 116. For example, the visual display can include a visualization of the object 116 or a part of the object 116 such as the contour and / or outline of the object 116.The visual representation may include a contour of the object 116 or a reference region on the object 116, for example, a frame corresponding to the shape of the object 116 superimposed on the display 140 of the mobile device 114, and provides visual guidance for positioning the camera 112 with respect to the object 116. The capture of at least one image of the object 116 may be automatically initiated when it is determined that sharpness criteria and / or spatial criteria are met, particularly when it is determined that the contour of the object 116 in the visual representation overlaps the object 116. Additionally or alternatively, audio guidance or other types of guidance may be provided.

[0099] Figures 3A and 3B show embodiments of an image captured by mobile device 114. From the image captured at step a) 118, at least one first region 124 within the image that is affected by direct reflection of light generated by illumination source 120 and reflected by object 116 is determined. As shown in FIGS. 3A and 3B, light spot 144 within the image is generated by direct reflection of light beam 146 generated by illumination source 120. Light spot 144 within the image can be a region that is brighter than the surrounding image regions. Histogram analysis of the image can be used to determine first region 124 of step b) 122. Histogram analysis can include determining the position of first region 124 within the image. Histogram analysis can include determining the maximum intensity within the image and determining the position of the maximum intensity within the image. First region 124 can be determined by using at least one threshold of intensity in the histogram analysis. Histogram analysis can include at least one two-dimensional Gaussian fit. For example, an image region having an intensity exceeding 1σ can be considered as first region 124. The images shown in FIGS. 3A and 3B can be divided into at least four segments, for example in quadrants. First region 124 can be assigned to at least one first segment of the image. For example, in the image shown in FIG. 3A, first region 124 can be determined to be located in the two upper segments of the quadrant. For example, in the image shown in FIG. 3B, first region 124 can be determined to be located in the two lower segments.

[0100] In step c) 126, at least one second region 128 that does not essentially overlap with the first region 124 is determined in the image, and the second region 128 is returned as the target region 130 for the position of the test field 132 of the test piece 134 in subsequent detection steps. The second region 128 can be determined such that it is prevented from being affected by the direct reflection of light from the illumination source 120 and / or at least significantly reduced. The target region 130 can be determined to be outside the zone, specifically, outside the first region 124 that is affected by the direct light reflection from the illumination source 120. Further, the target region 130 can be determined such that the analyte can be determined, for example, such that the test field 132 is sufficiently illuminated and within the field of view of the camera 112. The second region 128 can be determined to be a region of the image with essentially uniform illumination. The second region 128 can be determined to be a region where the illumination intensity is below at least one intensity threshold. The second region can be selected such that the illumination generated by the light spot from the direct reflection is minimized. Thus, the second region 128 can be determined to be located in at least one other segment of the image that is different from the first segment in which the first region 124 is determined. Further, the second region 128 can be determined to be sufficiently separated from the image edge to enable sufficient illumination by the light source and prevent boundary effects due to the image edge. FIGS. 3A and 3B show the determined second region 128 and the respective target regions 130. In FIG. 3A, when the first region 124 is determined to be located in two upper segments, the second region 128 can be determined to be located in one or both of the two lower segments of the quadrant. In FIG. 3B, when the first region 124 is determined to be located in two lower segments, the second region 128 can be determined to be located in the two upper segments.

[0101] The information on the position of the target area 130 can be provided, for example, as a prompt, to computing means such as external computing means or the computing means of the mobile device 114 such as the processor 142. Based on the information on the position of the target area 130, the processor 142 can adapt and / or generate a visual display for arranging the test piece 134 and the mobile device 114 relative to each other.

[0102] The detection method 115 includes a step 146 of providing at least one test piece 134 for detecting an analyte in a sample. FIG. 2 shows an embodiment of a test piece 134 having at least one test field 132 containing at least one test chemical for performing an optical detection reaction in the presence of an analyte. The detection method 115 includes a step 148 of applying at least one sample to the test field 132 of the test piece 134.

[0103] The detection method 115 includes a step 152 of providing a visual display 150 for the user to place the test piece 134 with respect to the camera 112 such that the test field 132 is at least partially disposed in the target area 130. The target area 130 may have the same shape as the shape of the test piece 134 or a part of the shape. The target area 130 may be configured as the contour or overlap of the test piece 134. The visual display 150 may be an overlay of the live image of the camera on the display 140 of the mobile device 114 and the target area 130, such as the contour of the test piece 134. Thus, when the test piece 134 is placed within the field of view of the camera 112, the visual display 150 indicates the overlap between the target area 130 and the test piece 134, enabling the user to easily place the test piece 134 in alignment with the target area 130. The visual display 150 may include a text message, such as at least one instruction for the user, such as a prompt, and / or at least one graphical instruction. For example, the visual display may include a visualization of the test piece 134 or a part of the test piece 134, such as the contour and / or outline of the test piece 134. The visual display 150 may specifically be visual guidance, for example, an outline that is overlaid on the display 140 of the mobile device 114 and that has the shape of the test piece 134, providing visual guidance for placing the camera with respect to the test piece 134, or may include such an outline. The visual display 150 may include a visualization of the mobile device 114 and the test piece 114 with respect to each other. The visual display 150 may include positioning information such as direction and / or distance prompts, such as at least one arrow and / or at least one text message. FIGS. 4A and 4B show embodiments of the visual display 150 on the display 140 of the mobile device 114. In FIG. 4A, the visual display 150 may include an overlap 154 corresponding to the test piece 134 used in the detection method 115. The overlap 154 may be determined empirically and / or stored in at least one look-up table by software, specifically by at least one app downloaded from an app store or the like, and / or in at least one data storage of the mobile device.Furthermore, on the display 140, a live image of the camera of the test piece 134 can be shown so that the user can be adapted to coincide with the overlap 154 and the test piece 134. Figure 4B shows a further visual display 150. In particular, the visual display 150 may include a text message and a graphic display that request the user to change the side of the test piece.

[0104] The detection method 115 includes a step 156 of capturing at least one image of the test field 132 by using the camera 112, and during the capture, the illumination source 120 of the mobile device 114 is turned on. The detection method 115 includes a step 158 of determining the analyte concentration in the sample from the image captured in the previous step 156.

Description of the reference numerals

[0105] 110 Calibration method 112 Camera 114 Mobile device 115 Method for detecting an analyte 116 Object 118 Step a) 120 Illumination source 122 Step b) 124 First region 126 Step c) 128 Second region 130 Target region 132 Test field 134 Test piece 136 Packaging 138 Position marker 140 Display 142 Processor 144 Light spot 146 Light beam 148 Method step 150 Visual display 152 Method step 154 Overlap 156 Method step 158 Method step

Claims

1. A method (110) for calibrating a camera (112) of a mobile device (114) for detecting an analyte in a sample, comprising: a) capturing (118) at least one image of at least one object (116) by using the camera (112), wherein during the capturing, an illumination source (120) of the mobile device (114) is turned on; b) (122) determining from the image captured in step a) at least one first region (124) in the image that is affected by direct reflection of light originating from the illumination source (120) and reflected by the object (116); c) (126) determining at least one second region (128) in said image that is substantially non-overlapping with said first region (124) and returning said second region (128) as a target region (130) for a location of a test field (132) of a test strip (134) in a subsequent detection step; A calibration method (110) comprising:

2. The calibration method (110) of claim 1, wherein a histogram analysis of the image is used to determine the first region (124) in step b) (122).

3. 3. The method of calibration (110) of claim 2, wherein the first region (124) is determined by using at least one intensity threshold in the histogram analysis.

4. The calibration method (110) of any one of claims 1 to 3, wherein the calibration method (110) further takes into account the perspective and / or angle between the camera (112) and the object (116).

5. 5. The calibration method (110) of any one of claims 1 to 4, wherein in step a) (118) a plurality of images are captured, said plurality of images comprising at least one image sequence, and in step b) (122) at least one image of said plurality of images that satisfies at least one predefined selection criterion is selected for use.

6. The calibration method (110) according to any one of claims 1 to 5, wherein in step a) (118), the distance between the camera (112) and the object (116) is between 0.03 m and 0.3 m, preferably between 0.03 and 0.15 m, most preferably between 0.03 and 0.1 m.

7. 7. The calibration method (110) of any one of claims 1 to 6, wherein the object (116) used in step a) (118) is selected from the group consisting of at least one flat surface, a reference card, at least one test strip (134) for detecting the analyte in the sample, at least one test strip container, and at least one package (136).

8. The calibration method (110) of any one of claims 1 to 7, wherein the illumination source (110) of the mobile device (114) comprises at least one light emitting diode integrated in the mobile device (114).

9. Calibration method (110) according to any one of claims 1 to 8, wherein the capturing in step a) (118) is performed in a time frame of less than 1 second, preferably in a time frame of less than 0.5 seconds, more preferably in a time frame of less than 0.1 seconds.

10. A detection method (115) for detecting an analyte in a sample by using a camera (112) of a mobile device (114), comprising: i) calibrating said camera (112) by using a calibration method according to any one of claims 1 to 9; ii) providing at least one test strip (134) for detecting the analyte in the sample, the test strip (134) having at least one test field (132) containing at least one test chemical for performing an optical detection reaction in the presence of the analyte; iii) applying at least one sample to the test field (132) of the test strip (134); iv) providing a visual indication (150) to a user for positioning the test strip (134) relative to the camera (112) such that the test field (132) is at least partially located within the target area (130); v) capturing at least one image of the test field (134) by using the camera (112), wherein during the capturing, the illumination source (120) of the mobile device (114) is turned on; vi) determining an analyte concentration in the sample from the image captured in step v); A detection method (115) comprising:

11. 11. The method of claim 10, wherein step vi) comprises analyzing the color of a spot on the test field of the test strip, the spot at least partially containing the sample.

12. A computer program comprising program means for executing one or more of the method steps a), b) and c) of the calibration method according to claim 1 while the computer program is running on a computer or a computer network, in particular on a processor of said mobile device (114).

13. 12. A computer program comprising program means for executing one or more of the method steps i), iv) and vi) of the detection method (115) according to claim 10 or 11 while the computer program is running on a computer or a computer network, in particular on a processor of said mobile device (114).

14. A mobile device (114), at least one camera (112), at least one illumination source (120); - at least one processor (142) including program means for executing the calibration method (110) according to any one of claims 1 to 9 referring to said calibration method.

15. The mobile device (114) according to claim 14, wherein the processor (142) further comprises program means for executing the detection method (115) according to claim 10 or 11 referring to the detection method.

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