KR102399939B1 - Detection method and detection pad - Google Patents

Abstract

A detection pad according to the present embodiment is a detection pad for inspecting a target in a fluid, and the detection pad includes: a machine readable code displayed in a first reference color; The detection region includes a second reference color region used to remove an effect of discoloration caused by a fluid, and a reagent that changes color by reacting with a target.

Description

Detection method and detection pad

The present technology relates to a detection method and a detection pad.

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 a living body. An example of detecting a body fluid component is a urine test. When the subject provides urine to the patch containing the indicator, the component in the urine reacts with the indicator to change the color. The presence and/or concentration of the component is detected by comparing the changed color with the reference color in the colorimetric table. Another example is a commonly used pregnancy test. During pregnancy, chorionic gonadotropin (hCG, human chorionic gonadotropin) is excreted in the urine, and the pregnancy test has a receptor that directly binds to chorionic gonadotropin. do.

Since the color displayed by the pad detecting the target changes according to the target density, the colorimetric table displays various colors according to the target density. However, in many cases, the color formed by the subject providing the body fluid to the indicator does not accurately correspond to the color of the colorimetric table, and the color may be misunderstood depending on the surrounding environment, which may make accurate detection difficult. Furthermore, it is difficult for the examinee to immediately grasp the past history and changes in the present compared to the past because the examination is performed only once.

One of the problems to be solved in the present embodiments is to provide an apparatus capable of easily detecting the presence and/or concentration of a target material.

A detection pad according to the present embodiment is a detection pad for inspecting a target in a fluid, and the detection pad includes: a machine readable code displayed in a first reference color; The detection region includes a second reference color region used to remove an effect of discoloration caused by a fluid, and a reagent that changes color by reacting with a target.

According to this embodiment, it is possible to quantitatively detect a target in a body fluid without using a colorimetric table, and there is an advantage in that a past history can be stored by converting it into data.

1 is an embodiment of a detection pad according to the present embodiment.
Fig. 2 is a flowchart showing the outline of the detection method according to the present embodiment.
3 is a diagram illustrating a state in which a detection pad according to the present embodiment is photographed by a portable terminal.
4 is a diagram illustrating a photographing result converted to a monochromatic tone.
5 is a diagram illustrating a method for detecting a first reagent patch and a fourth reagent patch.
6A and 6B are diagrams schematically illustrating a part of a detection pad in order to explain a process in which an application obtains a grayscale value.
Figure 7 (a) is the result of measuring the protein concentration (mg / ml) and the standard gray level value contained in urine, Figure 7 (b) is the protein concentration (mg / ml) and the standard gray level value contained in the urine It is a graph of the result of curve fitting for the relationship with
Figure 8 (a) is the result of measuring the concentration (pH) of the hydrogen ion contained in the urine and the standard gray value, Figure 8 (b) is the concentration of the hydrogen ion contained in the urine (pH) and the standard gray value It is a diagram of the result of curve fitting for the relationship.
Figure 9 (a) is the result of measuring the concentration (mg / ml) and standard gray level value of glucose contained in urine, Figure 9 (b) is the concentration of glucose contained in urine (mg / ml) and standard gray level value It is a graph of the result of curve fitting for the relationship with
10(a) is a result of measuring occult blood (RBC/ul) and standard grayscale values in urine, and FIG. 10(b) shows the relationship between occult blood (RBC/ul) in urine and standard grayscale values. It is a diagram of the result of curve fitting.
11 is a diagram illustrating a deviation according to a type of a mobile terminal performing photographing.

Hereinafter, an embodiment of the detection pad according to the present embodiment will be described with reference to the accompanying drawings. 1 is an embodiment of a detection pad 10 according to the present embodiment. Fig. 2 is a flowchart showing the outline of the detection method according to the present embodiment.

In the embodiment illustrated in FIG. 1 , the first reference color region indicated by the first reference color may be any one or more of the QR code 110 indicated by the first reference color and the predetermined region 120 indicated by the first reference color. there is. In one embodiment, the QR code 110 may be displayed in a rectangle. The QR code 110 may include direction markers 112 , 114 , and 116 positioned at three vertices of a rectangle. The QR code 110 may display a classification of the detection pad 10 , a detection target of the detection pad, the number of reagent patches included in the detection area 300 , and the like.

The region 120 indicated by the first reference color may be a region in a predetermined region indicated by the first reference color on the substrate sub. According to another embodiment not shown, the first reference color region is the first reference color. It may include letters, numbers, etc. indicated by , and may further include a design. In one embodiment, the first reference color may be black.

In one embodiment, the detection pad 10 may be formed on a substrate (sub). For example, the substrate may be white paper, and the QR code 110 and/or the first reference color region 120 may be formed by printing on the substrate sub.

As will be described later, the second reference color region 200 is used to remove color casting caused by the environment, lighting, and coloration caused by a fluid including a target during photographing, and may be formed as a second reference color. there is. As an embodiment, when the substrate sub is white, a predetermined region of the substrate sub may be used as the second reference color region 200 . In another embodiment, the second reference color region 200 may be attached to a predetermined region of the substrate sub as a white patch into which the color of the fluid may permeate. In another embodiment, the second reference color region 200 may be printed on a predetermined region of the substrate sub with white ink that can permeate the color of the fluid. In an embodiment, the second reference color may be white.

The detection region 300 may include one or more reagent patches, and the reagent patches include reagents that change color by reacting with a target contained in a fluid. In one embodiment, the reagent may react with the target in the fluid to change the degree of color development according to the concentration of the target. In one example, the reagent is glucose in fluid, protein in fluid, hydrogen ion in fluid, occult blood in fluid, bilirubin in fluid, urobilinogen in fluid, ketone body in fluid, nitrite in fluid, specific gravity of fluid and white blood cells in fluid. This may be a changing reagent. For example, the fluid is a human or animal body fluid, and may be any one of blood, urine, saliva, and sweat.

In the embodiment illustrated in FIG. 1 detection region 300 may include four reagent patches 312 , 314 , 316 , 318 , each of which is glucose in urine, protein in urine, hydrogen ions in urine or urine. The degree of discoloration can vary depending on the concentration of occult blood in the body.

In an embodiment not shown, the detection region may include ten reagent patches, each of which is glucose in urine, protein in urine, hydrogen ions in urine, occult blood in urine, bilirubin in urine, urobilinogen in urine, and urobilinogen in urine. The degree of discoloration may vary depending on the concentration of ketone bodies, nitrites in urine, specific gravity of urine, or white blood cells in urine.

Hereinafter, a detection method using the detection pad 10 according to the present embodiment will be described. 3 is a diagram illustrating a state in which the detection pad 10 according to the present embodiment is photographed by a mobile terminal. Referring to FIG. 3 , the user uses the mobile terminal 20 to photograph a first reference color region indicated as a first reference color and a detection region in which a color changes in response to a second reference color patch and a target ( S100 ). do. In one embodiment, the user's mobile terminal 20 may be a smart phone as shown in FIG. 3 having a camera module, and in another embodiment not shown, the mobile terminal is any one of a mobile phone, a tablet, and a notebook computer. can be

A 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 . For example, when taking a picture, the application may show a frame F corresponding to a rectangle of the QR code 110 and a guide display N to help the user take a picture.

The application converts the shooting result into a single factor (S200). In one embodiment, the image captured by the user may be displayed as R value, G value, and B value in the RGB color space, and a single element may be any one of R value, G value, and B value in the RGB color space. there is. If a single element is an R value, the application will only convert the image taken by the user to the size of the R value.

A single element can be a linear combination of R values, G values, and B values. For example, if the R value, G value, and B value of a pixel included in the image taken by the user are r, g, and b, respectively, the single element f is f = α×r + β×g + γ×b. It may be a value displayed as a value, and the application converts the image taken by the user into a size of α×r + β×g + γ×b value.

In other embodiments, a single element may be a grayscale value. The application may display the image captured by the user by converting it into grayscale. As an example, the grayscale may be divided into a total of 256 levels of 0-255.

In another embodiment, the single element may be any one of a Hue (hue), Saturation (saturation), Value (brightness) value, and a linear combination of a Hue value, a Satuaration value, and a Value value in the HSV color space. HSV is a color coordinate system that expresses colors in terms of Hue (hue), Saturation (saturation), and Value (brightness). Each pixel of the image taken by the user can be expressed as Hue, Saturation, and Value in the HSV color coordinate system, and the application converts any one of Hue, Saturation, and Value values and linear combinations of these values into a single element. and convert the image taken by the user into a single element.

In another embodiment, the single element may be any one of a linear combination of a Cyan (cyan) value, a Magenta (magenta) value, a Yelllow (yellow) value, and a Key value in a CMYK color space. The resulting image taken by the user can be displayed as a cyan value, a magenta value, a Yelllow value, and a key value, and the application converts the image taken by the user into a cyan value, a magenta value, a Yelllow value, a key value, and a linear combination of these values. Any one of them can be used as a single element, and the image taken by the user can be converted into a single element.

In another embodiment, a single element may be a linear combination of L* values, a* values and b* values and L* values, a* values, b* values in the CIE Lab color space. The CIE Lab color space has L* values ranging from black (0) to white (100), a* values ranging from green (-), red to (+) values, and blue (-) values to yellow. It is a color coordinate system that displays colors with b* values having a (+) value. The application uses any one of the L* value, a* value and b* value, and the linear combination of L* value, a* value, and b* value as a single element for the image taken by the user, can be expressed as the size of a single element.

In the above-described embodiment, when a single element is calculated by a linear combination of each element, the constants α, β, and γ may be appropriately adjusted according to the ranges of the values of the elements to be calculated. As an example, when the value of a single element has a value of 0 to 255 and all r, g, and b values have a value of 0 to 255, the constants α, β, and γ may all have values of 0 to 1.

The embodiment illustrated in FIG. 4 is a diagram illustrating a photographing result converted into a single element. However, FIG. 4 is merely a diagram exemplifying grayscale as a single element for explanation, and the state 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 region 300 are also converted into a single element.

A single element gradation value is extracted from the photographing result converted into a single element (S300). As an embodiment, the application may detect the position of the detection area 300 before extracting a single element grayscale value. Referring to Figure 5, the application forms a center point (O) between the two direction markers (112, 116) located in the diagonal direction of the QR code (110) square. Then, a reference point P is formed at a distance of a predetermined ratio r with respect to the length between the center point O and the direction marker. The position (a) of the first reagent patch 312 included in the detection area 300 may be determined by rotating the reference point by a predetermined first angle θ1 based on the central point O.

Then, the position (b) of the fourth reagent patch 318 included in the detection area 300 may be determined by rotating the reference point P by a predetermined second angle θ2 based on the central point O. In addition, the application divides the distance between the position (a) of the first reagent patch 312 and the position (b) of the fourth reagent patch 318 into thirds so that the position of the second reagent patch 314 and the position of the third reagent patch ( 316) can be identified.

In one embodiment, the application forms a second reference point at a distance of a predetermined ratio with respect to the length between the center point O and the direction marker, and rotates the second reference point based on the center point O by a second predetermined angle The position of the second reference color patch included in the detection area 300 may be determined.

In one embodiment, the application calculates the gradation value of a single element at 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 316 . can be extracted. The application extracts a single element grayscale value for a plurality of points in the second reference color region 200 , the first reference color region, and the first to fourth reagent patches 312 , 314 , 316 , and 318 . 6(A) and 6(B) show an application of a single element in the second reference color region 200, the first reference color region and the first to fourth reagent patches 312, 314, 316, 318. A diagram schematically illustrating a part of a detection pad in order to explain a process of obtaining a grayscale value. In the embodiment shown in FIG. 6(A) , the application includes a QR code 110 marked with a first reference color, first to fourth reagent patches 312 , 314 , 316 , 318 , and a second reference color region ( 200), the grayscale value of a single element may be obtained from a plurality of different points, and the grayscale value of the single element may be extracted by obtaining an average value for them. In the embodiment shown in FIG. 6(B) , the application includes a QR code 110 marked with a first reference color, first to fourth reagent patches 312 , 314 , 316 , 318 , and a second reference color region ( 200), the grayscale value of a single element is obtained from a plurality of different points, and the average value is obtained by excluding the maximum value and the minimum value among them, and the grayscale value of the single element can be extracted.

The application corrects the extracted single element grayscale value as a standard grayscale value (S400). When the detection area 300 is photographed, light reflected from the floor, ceiling, and wall may be color-cast to the first to fourth reagent patches 312 , 314 , 316 , and 318 , and fluorescent lighting, incandescent lighting, etc. There may be color casting by artificial lighting such as

Also, when a fluid including a target is applied to the detection region 300 , the reagent patches may be discolored 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 the grayscale value of the single element extracted by photographing the second reference color area to 255, and sets the grayscale value of the single element extracted by photographing the first reference color area to 0. The grayscale value of the single element photographed in the first to fourth reagent patches 312 , 314 , 316 and 318 is converted into a standard grayscale value by scaling the extracted grayscale values of the single element in a total of 2 ⁿ steps do. As an embodiment, the application may perform standard grayscale value conversion using Equation 1, where n is 8, 2 ⁿ ??1 is 255, and the standard grayscale value has a total of 256 steps of 0-255.

(I _cal : calculated standard gradation value, I _i: gradation value of a single element extracted in the previous step, G ₁ : gradation value of a single element extracted from the first target color area, G ₂ : from the second target color area The grayscale value of the extracted single element, n: a natural number)

Table 2 shows that when the grayscale value (G1) of the single element extracted from the first reference color region is 15 and the grayscale value (G2) of the single element extracted from the second reference color region is 231, the first to fourth reagent patches Single element grayscale values I1, I2, I3, and I4 extracted from 312, 314, 316, and 318 and single element grayscale values G1, An example in which G2) is converted into standard grayscale values (Ical1, Ical1, Ical1, Ical1, Gcal1, Gcal2) is exemplified. As exemplified in Table 2, it can be seen that the grayscale values of the extracted single elements are converted into standard grayscale values of 0 to 255 in a total of 256 steps.

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 an example for displaying a standard grayscale value as 8-bit digital data. A standard grayscale value divided into a total of 1024 steps of from 1023 to 1023 can be obtained. Alternatively, as in Equation (2) of Equation 2 below, a standard gradation value obtained by dividing the extracted gradation value into a total of 64 steps of 0 to 63 by multiplying n by 6 in Equation 1 may be obtained. If the standard grayscale value divided into higher levels is used, a standard grayscale value having high resolution can be obtained, and when the standard grayscale value divided into lower steps is used, the calculation speed can be improved.

By scaling the gradation value of a single photographed element to a standard gradation value, it is possible to remove the effect of the gradation value change due to color casting caused by the environment and the light source during the shooting process and the effect of discoloration due to the color of the fluid. A difference due to a difference between a mobile terminal and a camera module performing photographing may be similarly eliminated.

The application detects the target density from the standard grayscale value (S500). In an embodiment, the application detects the target density by calculating a density formula for a standard grayscale value.

There may be a measurement deviation with respect to the standard gradation according to a camera module included in the portable terminal performing photographing and/or an image processing algorithm of the portable terminal. As a method for reducing the measurement deviation of such a mobile terminal, there is a method of deriving an expression for the concentration of a target for a standard concentration measurement value for each terminal, and measuring the concentration using the expression derived for each terminal. can As another method, by using a result of collecting data for several types of portable terminals and averaging the collected data, it is possible to reduce the measurement deviation for each type.

Equations 3 to 6 described below are results obtained using a result of collecting data with a mobile terminal type of a plurality of domestic and foreign mobile terminals and averaging the collected data. Figure 7 (a) is the result of measuring the protein concentration (mg / ml) and the standard gray level value contained in urine, Figure 7 (b) is the protein concentration (mg / ml) and the standard gray level value contained in the urine It is a graph of the result of curve fitting for the relationship with In FIG. 7 , the horizontal axis represents the standard gradation scaled in 256 steps, and the vertical axis represents the concentration (mg/ml) of protein contained in urine. Through the curve fitting process, the relationship between the target concentration and the standard gray level value obtained through the experiment can be obtained, and the relationship between the protein concentration (mg/ml) in urine and the standard gray level value can be obtained through curve fitting (curve fitting) The resulting expression is as Equation 3 below.

(protein: protein concentration, Ical: standard gradation value, A, B: constant determined by experiment)

Figure 8 (a) is the result of measuring the concentration (pH) of the hydrogen ion contained in the urine and the standard gray value, Figure 8 (b) is the concentration of the hydrogen ion contained in the urine (pH) and the standard gray value It is a diagram of the result of curve fitting for the relationship. In FIG. 8 , the abscissa axis represents standard gradations expressed in 256 steps, and the ordinate axis represents the hydrogen ion concentration (pH). Through the curve fitting process, the relationship between the target concentration and the standard gray value obtained through the experiment can be obtained, and the result of a linear fitting of the relationship between the concentration (pH) of hydrogen ions in urine and the standard gray value is obtained. The formula is the same as Equation 4 below.

(C, D, E, F, G, H: constant determined by experiment)

Figure 9 (a) is the result of measuring the concentration (mg / ml) and standard gray level value of glucose contained in urine, Figure 9 (b) is the concentration of glucose contained in urine (mg / ml) and standard gray level value It is a graph of the result of curve fitting for the relationship with In FIG. 9 , the abscissa axis represents standard gradations expressed in 256 steps, and the ordinate axis represents the concentration of glucose (mg/ml). Through the curve fitting process, the relationship between the target concentration obtained through the experiment and the standard gray level value can be obtained, and curve fitting for the relationship between the concentration of glucose in urine (mg/ml) and the standard gray level value The resulting expression is as Equation 5 below.

(I, J: constant determined by experiment)

10(a) is a result of measuring occult blood (RBC/ul) and standard grayscale values in urine, and FIG. 10(b) shows the relationship between occult blood (RBC/ul) in urine and standard grayscale values. It is a diagram of the result of curve fitting. In FIG. 10 , the horizontal axis represents the standard gradation scaled in 256 steps, and the vertical axis represents occult blood (RBC/ul). Through the curve fitting process, the relationship between the target concentration and the standard gray level values obtained through the experiment can be obtained. Equation 6 below.

In another embodiment of detecting the concentration of the target, the application may store the concentration value of the target with respect to standard grayscale values. The application may detect the concentration value of the target stored as the calculated standard grayscale value. As an embodiment, the application may perform an operation by interpolating or extrapolating the concentration value of the target stored as the standard grayscale value, and may use the result of the operation as the concentration value of the target.

Although it has been described with reference to the embodiment shown in the drawings in order to help the understanding of the present invention, this is an embodiment for implementation, it is merely an example, and various modifications and equivalents from those of ordinary skill in the art It will be appreciated that other embodiments are possible. Accordingly, the true technical protection scope of the present invention should be defined by the appended claims.

10: detection pad sub: substrate
20: mobile terminal 110: QR code
112, 114, 116: direction marker 120: area indicated by the first target color
200: second target color area 300: detection area
312, 314, 316, 318: first, second, third, fourth reagent patches
N: Guidance display F: Frame
S100~S500: Each step of the detection method

Claims (8)

A detection pad for inspecting a target in a fluid, the detection pad comprising:
a code displayed as a first reference color and readable by a machine (machine readable code);
a second reference color region used to remove the effect of discoloration due to the fluid; and
and a detection region in which a reagent whose color changes in reaction with the target is located;
The machine-readable code indicated by the first reference color is a rectangular QR code with direction markers marked at three vertices,
A virtual reference point is formed at a distance between a virtual center point located between the two direction markers located in diagonal directions of the rectangle, and a distance between the virtual center point and the length of the two direction markers in a predetermined ratio,
A detection pad in which the detection area is located in an area in which the reference point is rotated by a predetermined first angle based on the virtual center point, and the location of the detection area is determined by an application of a user's mobile terminal. According to claim 1,
The first reference color is black, and the second reference color is white. According to claim 1,
The machine-readable code is:
A detection pad on which information on the number of reagent pads included in the detection pad and information on the classification of the detection pads are displayed. According to claim 1,
wherein the fluid is a bodily fluid of any one of a human and an animal. According to claim 1,
wherein the detection area includes a plurality of reagent patches. According to claim 1,
A plurality of the reagent patches are located in the detection area,
Each of the plurality of reagent patches includes glucose in the fluid, proteins in the fluid, hydrogen ions in the fluid, occult blood in the fluid, bilirubin in the fluid, urobilinogen in the fluid, ketone bodies in the fluid, nitrite in the fluid , a detection pad containing a reagent whose color changes depending on the specific gravity of the fluid and leukocytes in the fluid. According to claim 1,
wherein the detection region includes a first reagent patch, a second reagent patch, a third reagent patch, and a fourth reagent patch. 8. The method of claim 7,
The first reagent patch, the second reagent patch, the third reagent patch, and the fourth reagent patch are each a glucose in the fluid, a protein in the fluid, hydrogen ions in the fluid, occult blood in the fluid, bilirubin in the fluid , urobilinogen in the fluid, ketone bodies in the fluid, nitrite in the fluid, a specific gravity of the fluid, and a reagent that changes color according to white blood cells in the fluid.

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