Patent Publication Number: US-2022236190-A1

Title: Detection method and detection pad

Description:
TECHNICAL FIELD 
     The present invention relates to a detection method and detection pad. 
     BACKGROUND ART 
     Abnormalities in the body of humans and animals can be detected with high accuracy by detecting the concentration of a substance contained in a body fluid in the living body. An example of detecting a body fluid component is a urine test. When the subject provides urine to a patch containing an indicator, a component in the urine reacts with the indicator such that the color is changed. The changed color is compared with a reference color in a colorimetric table to detect whether the corresponding component is present and/or the concentration of the corresponding component. Another example is a pregnancy test kit which is commonly used. During pregnancy, human chorionic gonadotropin (hCG) is excreted in the urine. Since the pregnancy test kit has a receptor that directly binds to hCG, the receptor binds to hCG such that a predetermined shape and color are displayed. 
     DISCLOSURE 
     Technical Problem 
     A color displayed by a pad that detects a target varies depending on the concentration of the target, and thus a colorimetric table shows various colors depending on the target concentration. However, in many cases, a color obtained by providing a subject&#39;s body fluid to an indicator does not exactly correspond to a color in a colorimetric table, and the color may be misrecognized according to surroundings such that accurate detection may be difficult. Further, the test is conducted only once, and thus it is difficult for the subject to be immediately aware of a history and a current change compared to the past. 
     The present invention is directed to providing a device for detecting whether a target substance is present and/or for detecting the concentration of the target substance. 
     Technical Solution 
     One aspect of the present invention provides a detection method including (a) photographing a first reference color area displayed in a first reference color, a second reference color area displayed in a second reference color, and a detection area of which a color is changed in response to a target, (b) converting a photography result into a single factor, (c) extracting a single factor gradation value from the converted photography result, (d) converting the extracted single factor gradation value into a standard gradation value, and (e) detecting a concentration of the target from the standard gradation value. 
     Another aspect of the present invention provides a detection pad for testing a target in a fluid, the detection pad including a machine-readable code displayed in a first reference color, a second reference color area used to remove an influence of a color change caused by the fluid, and a detection area including a reagent of which a color is changed in response to the target. 
     Advantageous Effects 
     According to the present embodiment, it is possible to quantitatively detect a target in a fluid without using a colorimetric table and also to store a past history and the like by datafying the detected target. 
    
    
     
       DESCRIPTION OF DRAWINGS 
         FIG. 1  illustrates an embodiment of a detection pad according to the present embodiment. 
         FIG. 2  is a flowchart illustrating the overview of a detection method according to the present embodiment. 
         FIG. 3  is a diagram illustrating a state of a portable terminal photographing the detection pad according to the present embodiment. 
         FIG. 4  is a diagram exemplifying a photography result converted into a single color tone. 
         FIG. 5  is a diagram exemplifying a method of detecting a first reagent patch and a fourth reagent patch. 
         FIGS. 6A and 6B  are diagrams schematically illustrating a part of the detection pad to describe a process in which an application obtains a gradation value. 
         FIGS. 7A and 7B  illustrate results obtained by measuring the concentrations (mg/ml) and standard gradation values of protein included in urine and a curve fitting result of the relationship between the concentrations (mg/ml) and standard gradation values of protein included in urine, respectively. 
         FIGS. 8A and 8B  illustrate results obtained by measuring the concentrations (pH) and standard gradation values of hydrogen ions included in urine and a curve fitting result of the relationship between the concentrations (pH) and standard gradation values of hydrogen ions included in urine, respectively. 
         FIGS. 9A and 9B  illustrate results obtained by measuring the concentrations (mg/ml) and standard gradation values of glucose included in urine and a curve fitting result of the relationship between the concentrations (mg/ml) and standard gradation values of glucose included in urine, respectively. 
         FIGS. 10A and 10B  illustrate results obtained by measuring occult blood (red blood cell (RBC)/μl) included in urine and standard gradation values and a curve fitting result of the relationship between the occult blood (RBC/μl) included in urine and standard gradation values, respectively. 
         FIG. 11  is a set of diagrams illustrating differences between the types of portable terminals that take an image. 
     
    
    
     MODES OF THE INVENTION 
     Hereinafter, embodiments of a detection pad according to the present embodiment will be described with reference to the accompanying drawings.  FIG. 1  illustrates an embodiment of a detection pad  10  according to the present embodiment.  FIG. 2  is a flowchart illustrating the overview of a detection method according to the present embodiment. 
     In the embodiment illustrated in  FIG. 1 , a first reference color area displayed in a first reference color may be any one or more of a quick response (QR) code  110  displayed in the first reference color and a predetermined area  120  displayed in the first reference color. In an embodiment, the QR code  110  may be displayed in a quadrangle. The QR code  110  may include orientation markers  112 ,  114 , and  116  that are located at three vertices of the quadrangle. The QR code  110  may display the classification of the detection pad  10 , a detection target of the detection pad, the number of reagent patches included in a detection area  300 , and the like. 
     The area  120  displayed in the first reference color may be a predetermined area displayed in the first reference color on a substrate sub. According to another embodiment not shown in the drawing, the first reference color area may include letters, numerals, etc. displayed in the first reference color and further include designs and the like. As the embodiment, the first reference color may be black. 
     In the embodiment, the detection pad  10  may be formed on the substrate sub. As an example, the substrate may be a white paper, and the QR code  110  and/or the first reference color area  120  may be printed and formed on the substrate sub. 
     The second reference color area  200  may be used to remove color casts caused by surroundings and lighting during photography and coloration by a fluid including a target as will be described below and may be formed in a second reference color. As the embodiment, when the substrate sub is white, a predetermined area of the substrate sub may be determined as the second reference color area  200 . In another embodiment, as the second reference color area  200 , a white patch, into which the color of a fluid may permeate, may be attached to a predetermined area of the substrate sub. As the embodiment, the second reference color may be white. 
     The detection area  300  may include one or more reagent patches, and the reagent patches include a reagent of which a color is changed in response to the target included in a fluid. As the embodiment, the reagent may react with the target in a fluid such that the degree of coloration may vary depending on the concentration of the target. As an example, the reagent may be a reagent of which a color is changed according to glucose in a fluid, protein in a fluid, hydrogen ions in a fluid, occult blood in a fluid, bilirubin in a fluid, urobilinogen in a fluid, ketone bodies in a fluid, nitrides in a fluid, the specific gravity of a fluid, and white blood cells in a fluid. As an example, the fluid is a body fluid of a human or animal and may be any one of blood, urine, saliva, and sweat. 
     In the embodiment illustrated in  FIG. 1 , the detection area  300  may include four reagent patches  312 ,  314 ,  316 , and  318 , each of which may vary in the degree of color change according to the concentration of glucose in urine, protein in urine, hydrogen ions in urine, or occult blood in urine 
     In an embodiment not shown in the drawing, the detection area may include 10 reagent patches, each of which may vary in the degree of color change according to glucose in urine, protein in urine, hydrogen ions in urine, or occult blood in urine, bilirubin in urine, urobilinogen in urine, ketone bodies in urine, nitrides in urine, the specific gravity of urine, or the concentration of white blood cells in urine. 
     A detection method employing the detection pad  10  according to the present embodiment will be described below.  FIG. 3  is a diagram illustrating a state of a portable terminal photographing the detection pad  10  according to the present embodiment. Referring to  FIG. 3 , a user photographs a first reference area displayed in the first reference color, a second reference color patch, and a detection area of which a color is changed in response to a target (S 100 ). As the embodiment, a portable terminal  20  of the user may be a smartphone including a camera module as shown in  FIG. 3 . In another embodiment not shown in the drawing, the portable terminal may be any one of a portable phone, a tablet, and a laptop. 
     The user may photograph the detection pad  10  using a camera provided in the portable terminal  20  and an application stored in the portable terminal  20 . As an example, in the case of photography, the application may display a frame F corresponding to the quadrangle of the QR code  110  and a guide N that helps the user&#39;s photography. 
     The application converts a photography result into a single factor (S 200 ). As an embodiment, an image captured by the user may be displayed with a red (R) value, a green (G) value, and a blue (B) value in an RGB color space, and the single factor may be any one of the R value, the G value, and the B value in the RGB color space. When the single factor is the R value, the application converts the image captured by the user only into the size of the R value. 
     The single factor may be a linear combination of the R value, the G value, and the B value. For example, when the R value, the G value, and the B value of one pixel included in the image captured by the user are r, g, and b, respectively, a single factor f may be a value represented as f=α×r+β×g+γ×b, and the application converts the image captured by the user into a size of α×r+β×g+γ×b. 
     In another embodiment, the single factor may be a grayscale value. The application may convert the image captured by the user to grayscale and display the converted image. For example, grayscale may be divided into 0 to 255 levels, a total of 256 levels. 
     As another embodiment, the single factor may be any one of a hue value, a saturation value, a value value, and a linear combination of the hue value, the saturation value, and the value value in the hue, saturation and value (HSV) color space. HSV is a color coordinate system that represents a color with hue, saturation, and value. Each pixel of the image captured by the user may be represented with hue, saturation, and value in the HSV color coordinate system, and the application may determine any one of the hue value, the saturation value, the value value, and a linear combination value thereof as the single factor and convert the image captured by the user into the single factor. 
     As still another embodiment, the single factor may be any one of linear combinations of a cyan value, a magenta value, a yellow value, and a key value in the cyan, magenta, yellow, and key (CMYK) color space. The result image captured by the user may be displayed with a cyan value, a magenta value, a yellow value, and a key value, and the application may determine any one of the cyan value, the magenta value, the yellow value, the key value, and a linear combination value thereof as the single factor and convert the image captured by the user into the single factor. 
     As yet another embodiment, the single factor may be an L* value, an a* value, and a b* value, and a linear combination of the L* value, the a* value, and the b* value in the CIELAB color space. The CIELAB color space is a color coordinate system that represents a color with L* having a value of black (0) to white ( 100 ), a* having a negative (−) value for green to a positive (+) value for red, and b* having a negative (−) value for blue to a positive (+) value for yellow. The application may determine any one of the L* value, the a* value, and the b* value, and the linear combination value thereof as the single factor and convert the image captured by the user with the size of the single factor. 
     In the above-described embodiments, when the single factor is calculated as a linear combination of factors, the constants α, β, and γ may be appropriately adjusted according to the range of calculated values of the factors. For example, when the single factor has a value of 0 to 255 and all of r, g, and b have a value of 0 to 255, all of the constants α, β, and γ may have a value of 0 to 1. 
     An embodiment illustrated in  FIG. 4  exemplifies a photography result converted into a single factor. However,  FIG. 4  is a diagram exemplifying grayscale as the single factor, and a state in which the photography result is converted to grayscale may not be displayed to the user. As illustrated in  FIG. 2 , images of the first to fourth reagent patches  312 ,  314 ,  316 , and  318  included in the detection area  300  may also be converted into the single factor. 
     A single factor gradation value is extracted from the photography result converted into the single factor (S 300 ). As the embodiment, the application may detect the location of the detection area  300  before extracting the single factor gradation value. Referring to  FIG. 5 , the application forms a center point O between the two orientation markers  112  and  116  diagonally located in the quadrangle of the QR code  110 . Subsequently, a reference point P is formed at a distance corresponding to a predetermined ratio r of the length between the orientation markers from the center point O. A location a of the first reagent patch  312  included in the detection area  300  may be detected by rotating the reference point by a first angle θ 1  with respect to the center point O. 
     Subsequently, a location b of the fourth reagent patch  318  included in the detection area  300  may be detected by rotating the reference point by a second angle θ 2  with respect to the center point O. Also, the application may detect a location of the second reagent path  314  and a location of the third reagent patch  316  by trisecting the distance between the location a of the first reagent patch  312  and the location b of the fourth reagent patch  318 . 
     In the embodiment, the application may form a second reference point at a distance corresponding to a predetermined ratio of the length between the center point O and the orientation marker and rotate the second reference point by a predetermined second angle with respect to the center point O to detect a location of the second reagent patch included in the detection area  300 . 
     In the embodiment, the application may extract grayscale values of the single factor from a plurality of different points in the first reagent patch  312 , the second reagent patch  314 , the third reagent patch  316 , and the fourth reagent patch  318 . The application extracts grayscale values of the single factor from a plurality of points in the second reference color area  200 , the first reference color area, and the first to fourth reagent patches  312  to  318 . 
       FIGS. 6A and 6B  are diagrams schematically illustrating a part of the detection pad to describe a process in which the application obtains gradation values of the single factor from the second reference color area  200 , the first reference color area, and the first to fourth reagent patches  312  to  318 . In the embodiment shown in  FIG. 6A , the application may obtain grayscale values of the single factor from a plurality of different points in the QR code  110  displayed in the first reference color, the first to fourth reagent patches  312  to  318 , and the second reference color area  200  and average the grayscale values to extract a grayscale value of the single factor. In the embodiment shown in  FIG. 6B , the application may obtain grayscale values of the single factor from a plurality of different points in the QR code  110  displayed in the first reference color, the first to fourth reagent patches  312  to  318 , and the second reference color area  200  and average the grayscale values other than the maximum and the minimum to extract a grayscale value of the single factor. 
     The application corrects the extracted single factor grayscale value with standard grayscale values (S 400 ). In the case of photographing the detection area  300 , light reflected from the floor, the ceiling, and the wall may make a color cast on the first to fourth reagent patches  312  to  318 , and artificial lighting, such as a fluorescent lamp light and incandescent lamp light, may make a color cast. 
     Also, when a fluid including the target is applied to the detection area  300 , the colors of the reagent patches may be changed by the color of the fluid. For example, when the fluid is urine, the reagent patches may be colored yellow, and when the fluid is blood, the reagent patches may be colored red. 
     The application sets a grayscale value of the single factor extracted by photographing the second reference color area to 255 and sets a grayscale value of the single factor extracted by photographing the first reference color area to 0. The gradation values of the single factor captured in the first to fourth reagent patches  312  to  318  are converted into standard gradation values by scaling the extracted grayscale values of the single factor to a total of 2 11  levels. As the embodiment, the application may perform a standard gradation value conversion using Equation 1. When n equals 8, 2 n −1 equals 255, and standard gradation values have 0 to 255 levels, a total of 256 levels. 
     
       
         
           
             Ical 
             = 
             
               
                 ( 
                 
                   
                     2 
                     n 
                   
                   - 
                   1 
                 
                 ) 
               
               ⁢ 
               
                 
                   
                     I 
                     i 
                   
                   - 
                   
                     G 
                     ⁢ 
                     1 
                   
                 
                 
                   
                     G 
                     ⁢ 
                     2 
                   
                   - 
                   
                     G 
                     ⁢ 
                     1 
                   
                 
               
             
           
         
       
     
     (L cal : a calculated standard gradation value, I i : a gradation value of the single factor extracted in the previous step, G 1 : a gradation value of the single factor extracted from the first reference color area, G 2 : a gradation value of the single factor extracted from the second reference color area, n: a natural number) 
     Table 1 illustrates an example of converting gradation values I1, I2, I3, and I4 of the single factor extracted from the first to fourth reagent patches  312  to  318  and gradation values G1 and G2 of the single factor extracted from the first reference color area and the second reference color area into standard gradation values Ical1, Ical1, Ical1, Ical1, Gcal1, and Gcal2 when the gradation value G1 of the single factor extracted from the first reference color area is 15 and the gradation value G2 of the single factor extracted from the second reference color area is 231. As illustrated in Table 1, extracted gradation values of the single factor are converted into standard gradation values of 0 to 255 levels, a total of 256 levels. 
     
       
         
           
               
               
               
               
               
             
               
                   
                 TABLE 1 
               
               
                   
                   
               
               
                   
                 Extracted gradation value 
                   
                 Standard gradation value 
               
               
                   
                   
               
             
            
               
                   
               
            
           
           
               
               
               
               
               
            
               
                   
                 G1 
                 15 
                 Gcal1 
                 0 
               
               
                   
                 G2 
                 231 
                 Gcal2 
                 255 
               
               
                   
                 I1 
                 175 
                 Ical1 
                 183 
               
               
                   
                 I2 
                 195 
                 Ical2 
                 212 
               
               
                   
                 I3 
                 134 
                 Ical3 
                 152 
               
               
                   
                 I4 
                 125 
                 Ical4 
                 135 
               
               
                   
                   
               
            
           
         
       
     
     The above example is for displaying a standard gradation value as 8-bit digital data, and as shown in (1) of Equation 2, standard gradation values may be obtained by dividing gradation values of the single factor, which are extracted by setting n to 10 in Equation 1, into 0 to 1023 levels, a total of 1024 levels. Alternatively, as shown in (2) of Equation 2, standard gradation values may be obtained by dividing gradation values, which are extracted by setting n to 6 in Equation 1, into 0 to 63 levels, a total of 64 levels. When standard gradation values divided into higher levels are used, standard gradation values having a higher resolution may be obtained, and when standard gradation values divided into lower levels are used, the calculation speed may be increased. 
     
       
         
           
             
               
                 
                   Ical 
                   = 
                   
                     1023 
                     ⁢ 
                     
                       
                         
                           I 
                           i 
                         
                         - 
                         
                           G 
                           ⁢ 
                           1 
                         
                       
                       
                         G2 
                         - 
                         
                           G 
                           ⁢ 
                           1 
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   1 
                   ) 
                 
               
             
           
         
       
       
         
           
             
               
                 
                   
                     
                       I 
                     
                     ⁢ 
                     
                         
                     
                     ca 
                     ⁢ 
                     l 
                   
                   = 
                   
                     63 
                     ⁢ 
                     
                       
                         
                           l 
                           i 
                         
                         - 
                         
                           G 
                           ⁢ 
                           1 
                         
                       
                       
                         
                           G 
                           ⁢ 
                           2 
                         
                         - 
                         
                           G 
                           ⁢ 
                           1 
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   2 
                   ) 
                 
               
             
           
         
       
     
     A change in gradation value caused by color casts made by surroundings and a light source and influence of a color change caused by the color of a fluid may be removed. Likewise, a difference caused by the difference between a portable terminal and a camera module that take an image may be removed. 
     The application may detect a target concentration from the standard gradation value (S 500 ). As the embodiment, the application detects the target concentration by calculating the concentration equation of a standard gradation value. 
     There may be a measurement difference in standard gradation according to a camera module included in a portable terminal that takes an image and/or an image processing algorithm of the portable terminal. As a method of reducing such a measurement difference, there is a method of deriving an equation regarding the concentration of a target for a standard concentration measurement value according to each terminal and measuring the concentration using the equation derived for each terminal. As another method, pieces of data may be collected from several types of portable terminals, and a type-specific measurement difference may be reduced using a result obtained by averaging the collected pieces of data. 
     Equations 3 to 6 described below are results obtained by collecting pieces of data according to types of a plurality of domestic and foreign portable terminals and using a result obtained by averaging the collected pieces of data.  FIGS. 7A and 7B  illustrate results obtained by measuring the concentrations (mg/ml) and standard gradation values of protein included in urine and a curve fitting result of the relationship between the concentrations (mg/ml) and standard gradation values of protein included in urine, respectively. In  FIGS. 7A and 7B , the horizontal axis represents standard gradation of 256 levels, and the vertical axis represents the concentration (mg/mi) of protein included in urine. The relationship between a target concentration obtained through an experiment and a standard gradation value may be obtained through a curve fitting process, and a curve fitting result equation for the relationship between the concentration (mg/mi) of protein included in urine and a standard gradation value is given below as Equation 3. 
     
       
         
           
             
               ln 
               ⁡ 
               ( 
               protein 
               ) 
             
             = 
             
               A 
               - 
               
                 B 
                 · 
                 Ical 
               
             
           
         
       
     
     (protein: the concentration of protein, Ical: a standard gradation value, A and B: constants determined through an experiment) 
       FIGS. 8A and 8B  illustrate results obtained by measuring the concentrations (pH) and standard gradation values of hydrogen ions included in urine and a curve fitting result of the relationship between the concentrations (pH) and standard gradation values of hydrogen ions included in urine, respectively. In  FIG. 8 , the horizontal axis represents standard gradation of 256 levels, and the vertical axis represents the concentration (pH) of hydrogen ions. The relationship between a target concentration obtained through an experiment and a standard gradation value may be obtained through a curve fitting process, and a linear fitting result equation for the relationship between the concentration (pH) of hydrogen ions included in urine and a standard gradation value is given below as Equation 4. 
     
       
         
           
             
               ln 
               ⁡ 
               ( 
               pH 
               ) 
             
             = 
             
               C 
               + 
               
                 D 
                 · 
                 Ical 
               
               - 
               
                 
                   E 
                   ⁡ 
                   ( 
                   
                     Ical 
                     - 
                     F 
                   
                   ) 
                 
                 2 
               
               - 
               
                 
                   G 
                   ⁡ 
                   ( 
                   
                     Ical 
                     - 
                     H 
                   
                   ) 
                 
                 3 
               
             
           
         
       
     
     (C, D, E, F, G, and H: constants determined through an experiment) 
       FIGS. 9A and 9B  illustrate results obtained by measuring the concentrations (mg/ml) and standard gradation values of glucose included in urine and a curve fitting result of the relationship between the concentrations (mg/ml) and standard gradation values of glucose included in urine, respectively. In  FIG. 9 , the horizontal axis represents standard gradation of 256 levels, and the vertical axis represents the concentration (mg/ml) of glucose. The relationship between a target concentration obtained through an experiment and a standard gradation value may be obtained through a curve fitting process, and a curve fitting result equation for the relationship between the concentration (mg/mi) of glucose included in urine and a standard gradation value is given below as Equation 5. 
     
       
         
           
             
               ln 
               ⁡ 
               ( 
               Glucose 
               ) 
             
             = 
             
               I 
               - 
               
                 J 
                 · 
                 Ical 
               
             
           
         
       
     
     (I and J: constants determined through an experiment) 
       FIGS. 10A and 10B  illustrate results obtained by measuring occult blood (red blood cell (RBC)/μl) included in urine and standard gradation values and a curve fitting result of the relationship between the occult blood (RBC/μl) included in urine and standard gradation values, respectively. In  FIG. 10 , the horizontal axis represents standard gradation of 256 levels, and the vertical axis represents the occult blood (RBC/μl). The relationship between a target concentration obtained through an experiment and a standard gradation value may be obtained through a curve fitting process, and a linear fitting result equation for the relationship between occult blood (RBC/μl) included in urine and a standard gradation value is given below as Equation 6. 
     
       
         
           
             
               ln 
               ⁡ 
               ( 
               Blood 
               ) 
             
             = 
             
               K 
               - 
               
                 L 
                 · 
                 Ical 
               
             
           
         
       
     
     (K and L: constants determined through an experiment) 
     In another embodiment of detecting the concentration of a target, the application may store concentration values of the target with respect to standard gradation values. The application may detect the stored concentration of the target with a calculated standard gradation value. As the embodiment, the application may calculate the stored concentration value of the target with a standard gradation value through interpolation or extrapolation and determine the calculation result as the concentration of the target. 
     Although the present invention has been described with reference to embodiments illustrated in the drawings to aid in understanding, the embodiments are for implementation and merely illustrative. Those of ordinary skill in the art should appreciate that various modifications and equivalents can be can be made from the embodiments. Therefore, the technical scope of the present invention should be determined by the appended claims.