JP7062359B2 - Physiological index estimation method and estimation device and health information estimation method and estimation device - Google Patents

Description

The present invention relates to a skin analysis technique.

Judging a person's health condition by the complexion is often done not only during inspection by a doctor but also in daily life.
In traditional Chinese medicine, there is a diagnostic method called "desired diagnosis" (see Non-Patent Document 1). This "desired diagnosis" is a diagnostic method for observing changes in the complexion and morphology of a sick person, observing the internal changes, and determining the nature of the disease and its prognosis. Furthermore, in the diagnostic method, there is a color diagnosis that diagnoses with the skin color called "Nozomi", and the "Nozomi" is when the skin color is biased to one of the five colors. Based on the theory of five elements, it is diagnosed that the viscera related to the color are sick.
Further, Patent Document 1 discloses a method of analyzing the skin condition of the user's face from the face image of the user of the mirror and notifying the analysis result. In this method, a facial image of a user of the mirror is imaged by an imaging means embedded in the mirror, and hemoglobin pigment component information is extracted by applying independent component analysis to the facial image. By comparing and analyzing the amount of hemoglobin in the nose region based on the amount of hemoglobin pigment component in the forehead region, the sympathetic nervous system activity can be obtained as an analysis result.
Non-Patent Document 2 discloses the details of the image pyramid method.

Japanese Unexamined Patent Publication No. 2009-15369

Hayashi Acupuncture, "What is a medical examination?", [Online], "Hayashi Acupuncture", [Search on April 5, 2016], Internet <URL: http://www.lin- shinkyuin.jp/article/13589857.html> D.J.Heeger, J.R.Bergen, COMPUTER GRAPHICS PROCEEDINGS, p229-238 (1995)

The above-mentioned "desire" is a subjective diagnosis by a doctor, and it is difficult to obtain a quantitative result.
On the other hand, the method of Patent Document 1 is to compare the amount of hemoglobin pigment component between the nose where many arteriovenous anastomotic blood vessels are distributed and the forehead where there is almost no change in blood flow due to the influence of the autonomic nervous system. , Judging the sympathetic nervous system activity.
However, this method only looks at the local differences in blood flow in the face and cannot obtain the information that can be obtained by a blood pressure test or a blood test.

The present invention has been made in view of such a problem, and provides a technique for easily obtaining health information obtained by such a test without performing a blood pressure test or a blood test.

The present invention has the following aspects in order to solve the above-mentioned problems.

The first aspect relates to skin analysis methods. The skin analysis method according to the first aspect is the redness acquisition step of acquiring the redness information of the skin of the subject, the statistical information of the redness sample data and the blood sample data acquired in advance from the population, and the redness acquisition step. It comprises an estimation step of estimating health information about the subject, including at least information obtained by a blood test or blood test, using the redness information provided.

The second aspect relates to a skin analyzer. The skin analyzer according to the second aspect is a redness acquisition means for acquiring redness information of the subject's skin, statistical information of redness sample data and blood sample data acquired in advance from the population, and acquisition in the redness acquisition step. It comprises an estimation means for estimating health information about the subject, including at least information obtained by a blood test or a blood test, using the redness information.

The third aspect relates to a method of presenting the effect of a food or drink or a lifestyle-related improvement method including the skin analysis method according to the first aspect. The method according to the third aspect is that the target food or drink estimated by the estimation step is performed by executing the skin analysis method on the subject before and after ingestion of the target food or drink or before and after the implementation of the target lifestyle-related improvement method. A comparison step of comparing each health information before and after ingestion or before and after the implementation of the lifestyle-related improvement method, and a presentation step of presenting effect information of the target food or drink or the target lifestyle-related improvement method based on the comparison result in the comparison step. And further include.

The fourth aspect relates to a method of recommending a food or drink or a lifestyle-related improvement method including the skin analysis method according to the first aspect. The method according to the fourth aspect is a selection step of selecting a specific food or drink or a specific lifestyle-related improvement method based on the health information estimated in the estimation step, and the food or drink selected in the selection step. It further includes a presentation process for presenting recommended information on lifestyle-related improvement methods.

The fifth aspect relates to a method for estimating metabolic syndrome. The method according to the fifth aspect is acquired as physique index information in the first acquisition step of acquiring the skin condition information of the subject, the second acquisition step of acquiring the physique index information of the subject, and the second acquisition step. Including an estimation step of estimating the degree of possibility of metabolic syndrome of the subject based on the skin condition information acquired in the first acquisition step when the anthropometric index value belongs to a predetermined value range indicating obesity. ..

As another aspect of the present invention, it may be a program that causes a computer to execute the methods according to the first, third, fourth, and fifth aspects, or a computer that records such a program. May be a readable storage medium. This recording medium includes a non-temporary tangible medium.

According to each of the above aspects, it is possible to provide a technique for easily acquiring health information obtained by such a test without performing a blood pressure test or a blood test.

It is a flowchart which shows the skin analysis method of 1st Embodiment. It is a figure which conceptually shows the evaluation method (the first method) of the redness density value and the redness unevenness value by visual observation of a hemoglobin component image. It is a figure which conceptually shows the calculation method (third method) of the redness density value and redness unevenness value by image analysis for the skin image of a subject. It is a figure which conceptually shows the hardware composition example of the skin analysis apparatus of 1st Embodiment. It is a figure which conceptually shows the processing composition example of the skin analysis apparatus of 1st Embodiment. It is a flowchart which shows the skin analysis method of 2nd Embodiment. It is a figure which conceptually shows the processing composition example of the skin analysis apparatus of 2nd Embodiment. It is a flowchart which shows the effect presentation method of food and drink. It is a figure which conceptually shows the processing composition example of the skin analysis apparatus which realizes the effect presentation method of food and drink. It is a flowchart which shows the recommended method of food and drink. It is a figure which conceptually shows the processing composition example of the skin analyzer which realizes the recommended method of food and drink. It is a flowchart which shows the metabolic syndrome estimation method which concerns on 3rd Embodiment. It is a figure which conceptually shows the processing composition example of the skin analyzer which realizes the metabolic syndrome estimation method. As a result of "Survey 1", it is a table showing the relationship between the redness concentration value or the redness unevenness value, the BMI, the blood pressure test value, and the blood test value. 15 (a), 15 (b) and 15 (c) show the relationship between the high and low of the redness unevenness value (third method) and the ratio of those who are out of the standard value range of the blood pressure test value or the blood test value. 15 (a) is a graph of a group of subjects having a BMI value of 25 or more, and FIG. 15 (b) is a graph of a group of subjects having a BMI value of 18.5 or more and less than 25. c) is a graph of a group of subjects having a BMI value of less than 18.5. As a result of "Survey 2", it is a table showing the relationship between the redness concentration value or the redness unevenness value and the blood test value. It is a graph which shows the relationship between the redness density value (redness evaluation method D), and the BMI value. It is a figure which compared the investigation index value of the representative subject group with a low redness concentration value of the redness evaluation method D and the representative subject group with a high BMI value in the population in the range of 25 to 28 BMI. It is a figure which shows the change of the investigation index value at the initial time (0M) and after 12 months (12M) in the population with a BMI value of 25 to 28.

Hereinafter, embodiments of the present invention will be described. It should be noted that each of the following embodiments is an example, and the present invention is not limited to the configuration of each of the following embodiments.

First, an outline of each embodiment described later will be described.
The skin analysis method according to each embodiment includes a redness acquisition step and an estimation step.
The redness acquisition step is a step of acquiring redness information of the skin of the subject.
Here, the "skin redness information" is information indicating the color of red visually recognized from a specific portion of the skin of the subject. The "skin redness information" indicates, for example, the density of red or the degree of unevenness of red.
This method is not limited to the method of acquiring skin redness information. For example, a method may be used in which the evaluator directly visually observes the skin of the subject to evaluate the redness of the skin on a predetermined scale. Further, a skin image showing the skin of the subject (may be a face image or a skin image showing only the skin) may be visually observed by the evaluator.
Other specific acquisition methods in the redness acquisition process will be described later.

The estimation step is a step of estimating health information about the subject, including at least information obtained by a blood pressure test or a blood test.
Here, the "information obtained by a blood pressure test or a blood test" may be a blood pressure value or a blood test value (fasting blood glucose level, erythrocyte count, etc.) directly obtained by each test, or of each test. Information indicating the result (good, abnormal, etc.) may be used.
Further, the "health information" may include information related to blood and health other than such information. The "health information" may be blood-related information related to the information obtained by the blood pressure test or the blood test.

For estimating this health information, statistical information of redness sample data and blood sample data acquired in advance from the population, and redness information acquired in the redness acquisition step are used.
The "redness sample data" is data related to skin redness obtained in advance from each person forming the population. The "redness sample data" is preferably data of the same type of information as the redness information acquired in the redness acquisition step in order to improve the estimation accuracy of the health information. For example, when the redness information acquired in the redness acquisition process is the intensity information of redness obtained by visually evaluating the skin of the subject, the "redness sample data" is the same for each person's skin forming the population. It is preferable that the data is the intensity information of redness obtained by visual evaluation. However, the "redness sample data" may be data of information that is different from the redness information acquired in the redness acquisition step and has a correlation with the redness information. For example, when the redness information acquired in the redness acquisition process is the redness intensity information obtained by visually evaluating the subject's skin, the "redness sample data" is an image of the skin image of each person forming the population. It may be redness density information obtained by processing.

"Blood sample data" is blood-related data previously obtained from each person forming a population. The "blood sample data" is preferably data of the same type as the information obtained by the blood pressure test or the blood test estimated in the estimation step in order to improve the estimation accuracy of the health information. For example, when the blood pressure value is estimated in the estimation step, the "blood sample data" is preferably the blood pressure value measured from each person forming the population. However, the "blood sample data" may be data of information that correlates with the information of other types from the information obtained by the blood pressure test or the blood test.

"Statistical information of redness sample data and blood sample data" is obtained by statistically processing redness sample data and blood sample data based on the correlation between redness of skin and information obtained by blood pressure test or blood test. This is the information that was given. The correlation between the redness of the skin and the information obtained by the blood pressure test or the blood test is newly discovered by the present inventors, and for example, a regression equation obtained by regression analysis based on such a correlation. Is given as an example of the statistical information. In this example, the statistical information corresponds to a simple regression equation or a multiple regression equation in which the redness information of the skin is used as an explanatory variable and the information obtained by a blood pressure test or a blood test is used as an objective variable. When the "statistical information of redness sample data and blood sample data" is such a regression equation, the blood pressure test for the subject is performed by substituting the redness information of the skin acquired in the redness acquisition step into the explanatory variable of the regression equation. Alternatively, the information obtained by the blood test (blood pressure value, etc.) can be calculated.
The population from which both sample data are obtained is not particularly limited. The population may be formed only by men or women, may be formed only by a specific age group, or may be formed only by a person having a specific physique.

As described above, according to this method, based on the redness information acquired from the subject, health information including at least the information acquired by the blood pressure test or the blood test regarding the subject is estimated, so that the subject can perform the blood pressure test and the blood. The information obtained by such an inspection can be easily obtained without conducting an inspection.
Further, as an embodiment of the present invention, a skin analysis device that executes the above-mentioned skin analysis method, or a skin analysis program that causes at least one computer to execute the above-mentioned skin analysis method can be realized.
Hereinafter, each embodiment will be described in more detail.

[First Embodiment]
[Skin analysis method]
FIG. 1 is a flowchart showing the skin analysis method of the first embodiment.
The skin analysis method of the first embodiment includes a step (S11) and a step (S12).

The step (S11) corresponds to the above-mentioned redness acquisition step. In the skin analysis method according to the first embodiment, in the step (S11), the skin image of the subject is processed to acquire at least one of the redness index and the unevenness index as redness information.
The skin image of the subject may be an image showing the skin of the subject, an image showing a certain wide range of the skin such as a full face image, or a local part of the skin such as a part of the cheek. It may be an image.
The index value of the red density index is a value indicating the degree of red density, and may be hereinafter referred to as a reddish density value. The redness density value may indicate whether it is dark or light by a binary value, or may indicate a density scale having three or more steps by three or more values. Further, the redness density value may indicate the degree of the average darkness of red, or may indicate the degree of darkness of the darkest portion in the target range.
The index value of the red unevenness index is a value indicating the degree of red unevenness, and may be hereinafter referred to as a reddish unevenness value. Red unevenness means a partial shade of red. The redness unevenness value may indicate whether there is more or less unevenness as a binary value, or may indicate an unevenness scale having three or more stages as three or more values. For example, the redness unevenness value can indicate the degree of dispersion of partial shades of red that can be visually recognized by humans.
That is, in this method, in the step (S11), the redness density value, the redness unevenness value, or the redness density value and the redness unevenness value are acquired as redness information. Hereinafter, a method for acquiring each index value in the step (S11) will be illustrated.

The first method is a method of extracting a hemoglobin component image from a skin image of a subject and visually evaluating the hemoglobin component image by a professional evaluator.
FIG. 2 is a diagram conceptually showing a method (first method) for visually evaluating a redness density value and a redness unevenness value of a hemoglobin component image. In the example of FIG. 2, the hemoglobin component image is extracted by applying the independent component analysis to the color image of the entire face of the subject. As this extraction method, a known method such as the method disclosed in Patent Document 1 described above can be used. On the other hand, hemoglobin component images are extracted in advance from multiple people with different skin redness concentrations and unevenness degrees using the same method, and a photoscale (example at the bottom of Fig. 2) is created with the two axes of hemoglobin component concentration and unevenness. I will do it. By having a professional evaluator evaluate the redness density and the redness unevenness of the hemoglobin component image of the subject using this photoscale, the redness density value and the redness unevenness value of the subject are acquired.

The second method is a method of extracting a hemoglobin component image from the skin image of the subject and calculating the redness density value using the luminance value (pixel value) of the inspection area in the hemoglobin component image. For example, in this method, an SP-polarized image of the entire face of a subject is acquired by projecting S-polarized light on the subject using a polarizing plate and imaging P-polarized light, and independent component analysis is applied to the SP-polarized image. By doing so, the hemoglobin component image is extracted. Since the SP polarized image is an internally reflected light component image, a highly accurate hemoglobin component image can be extracted. The cheek portion of the extracted hemoglobin component image is cut out as an inspection area to a predetermined size (for example, 256 × 256 pixels), the average luminance value of the inspection area is calculated, and the average luminance value with respect to the maximum luminance value (255) is calculated. The redness density value is calculated from the ratio.
Redness density value = log (255 / average brightness value)

The third method is to decompose the inspection area in the hemoglobin component image of the subject into multiple images with different spatial frequency bands by the image pyramid method, and use the brightness value (pixel value) of each decomposed image to obtain the redness density value. And it is a method to calculate the redness unevenness value.
There are various types of image pyramid methods such as Gaussian pyramid, Laplacian pyramid, and steable pyramid, and an appropriate method may be selected according to the distribution characteristics of redness unevenness. Further, the spatial frequency band can be appropriately determined according to the shooting magnification and the like. Details of the image pyramid method are described in Non-Patent Document 2 above.
FIG. 3 is a diagram conceptually showing a method (third method) for calculating a redness density value and a redness unevenness value by image analysis on a skin image of a subject. In the method exemplified in FIG. 3, an inspection region is cut out from the SP polarized image of the entire face of the subject, and an independent component analysis is applied to this inspection region to extract a hemoglobin component image of the inspection region. After grayscale this hemoglobin component image, it is decomposed into five layers of images L1 to L5 having different spatial frequency bands by the image pyramid method, and the standard deviation or average brightness value of the required image brightness in the decomposed image is calculated. do. On the other hand, five layers of images were extracted from the hemoglobin component images of multiple people with different redness density and unevenness of the skin by the same method, and the standard deviation and average brightness value of the brightness of each image were used as explanatory variable candidates. Find a regression equation with each person's redness density value or redness unevenness value as the objective variable. The redness density value and the redness unevenness value of each person are determined by, for example, a visual score. In the present embodiment, a multiple regression equation with the redness density value as the objective variable and a multiple regression equation with the redness unevenness value as the objective variable are calculated. For example, the former is a multiple regression equation having the average luminance value of the image L5 and the standard deviation of the luminance as objective variables, and the latter is a multiple regression equation having the standard deviation of the luminance of the images L4 and L5 as the objective variable. The redness density value and redness unevenness value of the subject are calculated by applying the standard deviation or the average luminance value of the luminance obtained as described above from the image of the subject in the predetermined spatial frequency band to each multiple regression equation.

The fourth method calculates the contribution rate for each of a plurality of predetermined redness main component images by applying the principal component analysis to the skin image of the subject, and the redness density value and the redness unevenness value are calculated based on the calculated contribution rate. It is a method to calculate. In this method, a plurality of redness main component images are derived in advance by principal component analysis on the skin images of a plurality of people having different skin redness densities and unevenness degrees. Then, for example, the order of the reddish principal component having a high correlation with the redness concentration and the order of the reddish principal component having a high correlation with the redness unevenness are specified, and the contribution rate of each specified order is used as an explanatory variable. A regression equation with the redness density value or the redness unevenness value as the objective variable is derived. The redness density value and the redness unevenness value in this case may be determined by other methods as described above. By applying the contribution rate of each order extracted from the subject to this regression equation, the redness density value and the redness unevenness value can be calculated.
In addition, the contribution rate of the order of the specified redness main component of the skin image can be used as the redness index.

As described above, in the first embodiment, the redness information of the subject is acquired by processing the skin image of the subject, but the method of acquiring the index value in the step (S11) is not limited to the above-mentioned example.
For example, when the “image” is not used, a method may be used in which a professional evaluator directly visually observes the skin of the subject to evaluate the darkness or unevenness on a predetermined scale. Further, in this method, a skin image showing the skin of the subject (may be a face image or a local skin image showing only the skin) may be visually observed by a professional evaluator. In this method, the visual score determined by the expert evaluator is regarded as the redness density value or the redness unevenness value.

The step (S12) corresponds to the above-mentioned estimation step. The skin analysis method according to the first embodiment includes statistical information of redness sample data and blood sample data acquired in advance from the population in step (S12), and a red intensity index acquired in step (S11). And at least one of the blood pressure value and the blood test value of the subject is estimated as the above-mentioned health information by using at least one index value of the unevenness index.
Here, the "blood pressure value" is a value indicating blood pressure measured by a blood pressure test, and is a value indicating systolic blood pressure, diastolic blood pressure, or both.
The "blood test value" is a value indicating the test result of one or more test items obtained by a blood test for testing the blood itself.

The present inventors have newly found a correlation between a redness concentration value or a redness unevenness value and a blood pressure value or a blood test value. Based on this new finding, the regression equation as statistical information of redness sample data and blood sample data can be derived as follows. First, the redness concentration value group and the redness unevenness value group are acquired from the population by the above-mentioned method, and further, the blood pressure value group and the blood test value group are acquired by various tests. Then, by statistically analyzing these, a simple regression equation with either the redness concentration value or the redness unevenness value as the explanatory variable and either the blood pressure value or the blood test value as the objective variable, or the redness concentration value and A multiple regression equation can be derived in which both the redness unevenness value are used as explanatory variables and either the blood pressure value or the blood test value is used as the objective variable.
In this method, in the step (S12), at least one of the redness concentration value and the redness unevenness value obtained in the step (S11) is applied to the regression equation derived in this way to obtain the blood pressure value and the blood test value. At least one can be estimated.

However, the estimation method of the step (S12) is not limited to such a method.
The statistical information includes regression lines obtained by statistical analysis of sample data obtained from the population as described above on the two axes of the blood pressure value or blood test value axis and the redness concentration value or redness unevenness value axis. It may be a superimposed graph. Further, the graph may be a graph in which the regression plane obtained by the statistical analysis is superimposed on the three axes of the blood pressure value or the blood test value axis, the redness concentration value axis, and the redness unevenness value axis. In this case, in the step (S12), the blood pressure value and blood test of the subject are performed by comparing at least one of the redness concentration value and the redness unevenness value obtained in the step (S11) with the regression line or the regression plane on the graph. At least one of the values can be estimated.
Furthermore, the blood component of the subject can be estimated from the contribution rate of the order of the specified redness main component of the skin image. In this case, a plurality of reddish principal component images and their contribution ratios are derived in advance by principal component analysis on the skin images of a plurality of people, and then a specific blood among the blood component values measured in advance is specified. Specify the order of the reddish principal component that has a high correlation with the medium component value. For the evaluation subject, the blood component of the subject can be estimated from the contribution rate of the order of the specified redness main component of the skin image.

The skin analysis method of the first embodiment may include a step performed by a person as described above. This method uses the correlation between the redness concentration value or redness unevenness value and the blood pressure value or blood test value, so that the subject's skin is not subjected to time-consuming and labor-intensive tests such as blood pressure test and blood test. It is possible to repeatedly and continuously realize a certain effect that the blood pressure value or the blood test value can be easily obtained from the redness information. Therefore, even if a process carried out by a person is included, this method can be said to be a technical idea utilizing the law of nature as a whole.

[Skin analyzer]
Next, the skin analyzer of the first embodiment will be described with reference to FIGS. 4 and 5.
FIG. 4 is a diagram conceptually showing a hardware configuration example of the skin analyzer 10 of the first embodiment.
The skin analyzer 10 is a so-called computer, and includes, for example, a CPU (Central Processing Unit) 11, a memory 12, an input / output interface (I / F) 13, a communication unit 14, and the like, which are connected to each other by a bus. The number of each hardware element forming the skin analyzer 10 is not limited, and these hardware elements can also be collectively referred to as an information processing circuit. Further, the skin analyzer 10 may include hardware elements (not shown in FIG. 4), and the hardware configuration thereof is not limited.

The CPU 11 may be configured by an integrated circuit (ASIC) for a specific application, a DSP (Digital Signal Processor), a GPU (Graphics Processing Unit), or the like, in addition to a general CPU.
The memory 12 is a RAM (Random Access Memory), a ROM (Read Only Memory), and an auxiliary storage device (hard disk or the like).
The input / output I / F 13 can be connected to a user interface device such as an output device 15 and an input device 16. The output device 15 is at least one of a device such as an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube) display that displays a screen corresponding to drawing data processed by a CPU 11 or the like, a printing device, and the like. The input device 16 is a device that receives input of a user operation such as a keyboard and a mouse. The output device 15 and the input device 16 may be integrated and realized as a touch panel.
The communication unit 14 communicates with another computer via a communication network, exchanges signals with other devices, and the like. A portable recording medium or the like may also be connected to the communication unit 14. Further, a camera (not shown) for photographing the skin of the subject may be connected to the communication unit 14.
Further, the skin analysis device 10 may be a device having a built-in camera.

FIG. 5 is a diagram conceptually showing a processing configuration example of the skin analyzer 10 of the first embodiment.
The skin analyzer 10 has a redness acquisition unit 21, an estimation unit 22, an output processing unit 23, and the like. These processing modules are software elements, and are realized, for example, by executing a program stored in the memory 12 by the CPU 11. This program is installed from an input / output I / F 13 or a communication unit 14 from a portable recording medium such as a CD (Compact Disc), a memory card, or another computer on the network, and is stored in the memory 12. You may.
The skin analysis device 10 realizes the above-mentioned skin analysis method by the operation of the redness acquisition unit 21, the estimation unit 22, and the output processing unit 23. In other words, the skin analysis device 10 can execute the above-mentioned skin analysis method by executing the installed program.

The redness acquisition unit 21 executes the above-mentioned step (S11).
The redness acquisition unit 21 can acquire the redness density value or the redness unevenness value for the subject from an external computer, device, or the like via the input / output I / F 13 or the communication unit 14.
Further, the redness acquisition unit 21 acquires an image obtained by processing the subject's skin image or the skin image (hemoglobin component image, image decomposed by the image pyramid method, etc.) from the outside, and the acquired image. It is also possible to calculate the redness density value or the redness unevenness value for the subject by processing in the same manner as the acquisition method in the step (S11).

The estimation unit 22 executes the above-mentioned step (12).
The estimation unit 22 may hold statistical information of redness sample data and blood sample data previously acquired from the population. Further, the statistical information held by the external computer may be referred to and used by communication.

The output processing unit 23 outputs the health information of the subject estimated by the estimation unit 22. Specifically, the output processing unit 23 outputs at least one of the redness density value and the redness unevenness value estimated for the subject.
The output form by the output processing unit 23 is not limited. For example, the output processing unit 23 may hold the health information as an electronic file so that it can be output, or may transmit the electronic file to another computer via the communication unit 14. Further, the output processing unit 23 may display or print the health information on the output device 15 via the input / output I / F 13.

As described above, in the first embodiment, by processing the skin image of the subject, at least one of the redness density value and the redness unevenness value is acquired as redness information with respect to the subject's skin. Then, based on the correlation between the redness concentration value or the redness unevenness value and the blood pressure value or the blood test value, at least one of the blood pressure value and the blood test value of the subject is healthy from the acquired skin redness information of the subject. Estimated as information.
Therefore, according to the first embodiment, at least one of the blood pressure value and the blood test value of the subject can be easily obtained only by taking an image of the skin of the subject without undergoing a blood test or a blood test. ..

[Second Embodiment]
The second embodiment further uses the subject's body mass index information (for example, BMI (Body Mass Index)) to improve the estimation accuracy of the subject's health information. Hereinafter, the skin analysis method and the skin analysis apparatus according to the second embodiment will be described mainly on the contents different from those of the first embodiment. In the following description, the same contents as those in the first embodiment will be omitted as appropriate.

[Skin analysis method]
FIG. 6 is a flowchart showing the skin analysis method of the second embodiment.
As shown in FIG. 6, the skin analysis method of the second embodiment includes a step of acquiring subject's anthropometric index information (S21), a step of acquiring subject's skin redness information (S22), and subject's health. It includes a step of estimating information (S23). However, in this method, the process (S21) and the process (S22) may be executed in parallel or may be executed in the reverse order.

In the step (S21), this method acquires the anthropometric index information of the subject.
Here, the "physical index information" is information that can indicate the overall physical constitution of a person, and is, for example, weight, height, BMI, body fat percentage, muscle mass, and the like. The subject's physique index information acquired in the step (S21) may be a kind of index value such as BMI only or body fat percentage only, or may be a plurality of index values such as BMI and body fat percentage. good.
The step (S21) may or may not include measuring the anthropometric index of the subject. When this method is executed by a computer, in the step (S21), the physique index information can be acquired according to the input operation of the user. Further, when the body mass index information is BMI, in the step (S21), the BMI value itself input by the user operation may be acquired, or the height data and the weight data input by the user operation may be acquired and they may be acquired. The BMI value may be calculated based on.
As described above, the method for acquiring the anthropometric index information in the step (S21) is not limited.

The step (S22) is the same as the step (S11) of the first embodiment.
In the step (S23), this method includes statistical information of redness sample data and blood sample data acquired in advance from the population, anthropometric index information acquired in the step (S21), and a subject acquired in the step (S22). Estimate the subject's health information using the redness information of. For example, in the step (S23), in addition to the statistical information, at least one of the redness concentration value and the redness unevenness value of the subject acquired in the step (S22) and the BMI value of the subject acquired in the step (S21) are used. It is used to estimate at least one of a subject's blood pressure and blood test values.
There are various ways to use the anthropometric index information in the process (S23).

For example, in step (S23), this method estimates the possibility of abnormality in health information related to one or more indicators as health information based on the combination of the anthropometric index range to which the anthropometric index information belongs and the redness range to which the anthropometric index belongs. do.
Here, the "possibility of abnormality in health information" may indicate whether it is likely to be unhealthy (unhealthy) or not, and the degree of possibility that it is different from the normal state (unhealthy) (unhealthy). The probability of abnormality may be 60%, etc.). Here, the normal state may be, for example, a standard value used in a medical examination or the like.
As described in the section of Examples, the present inventors have a blood pressure value or a blood pressure test value outside the reference value range (abnormality) in a specific combination of the anthropometric index range related to anthropometric index information and the redness range related to redness information. It was found that there is a certain relationship with the proportion of subjects who become (value).
Therefore, in this method, based on this certain relationship, information indicating the possibility of abnormality in health information regarding one or more indicators is provided for each of a specific combination in a plurality of anthropometric index ranges and a plurality of redness ranges. The associated data table is pre-generated. In the step (S23), by referring to this data table, the anthropometric index range to which the anthropometric index information of the subject belongs and the redness range to which the redness information of the skin of the subject belongs are selected and associated with the selected combination. It is possible to identify the possibility of abnormalities in health information related to one or more indicators.

Furthermore, the present inventors have found a high correlation between the redness of the skin and the information obtained by the blood pressure test or the blood test in the specific body shape group including the obese body shape. Therefore, the anthropometric index information may be used as follows.
That is, the present method further includes a step of determining whether or not the subject belongs to a specific physique group including an obese physique based on the physique index information of the subject, and according to the determination result, the step (S23). Decide whether to perform the estimation. Specifically, this method executes the step (S23) when the subject belongs to the specific physique group, and does not execute the step (S23) when the subject does not belong to the specific physique group. When BMI is used as body mass index information, for example, the specific body mass group is preferably specified by a BMI value range of 25 or more, and is specified by a BMI value range of 25 or more and 28 or less from the viewpoint of estimation accuracy. More preferred.
By narrowing down to the subjects belonging to the specific physique group in this way, the estimation accuracy of health information can be improved, and the reliability of this method can be maintained high.
In this case, it is preferable that the step of determining whether or not the body belongs to the specific physique group is executed before the step (S22) in the example of FIG. However, this determination step may be executed at least before the step (S23).

[Skin analyzer]
FIG. 7 is a diagram conceptually showing a processing configuration example of the skin analyzer 10 of the second embodiment. The skin analyzer 10 of the second embodiment further has an anthropometric index acquisition unit 25 in addition to the configuration of the first embodiment. The physique index acquisition unit 25 is also realized in the same manner as other processing modules.

The physique index acquisition unit 25 acquires the physique index information of the subject. That is, the anthropometric index acquisition unit 25 executes the above-mentioned step (S21).
When the physique index measuring device (weight scale, body fat scale, etc.) is connected to the input / output I / F 13 or the communication unit 14, the physique index acquisition unit 25 acquires the physique index information from the measuring device. Can be done. Further, the anthropometric index acquisition unit 25 can also acquire the anthropometric index information from a portable recording medium, another computer, or the like via the communication unit 4. The physique index acquisition unit 25 may acquire the physique index information input according to the user operation using the input device 16 for the physique index information input screen. In addition, the physique index acquisition unit 25 can also acquire weight data and height data to calculate a BMI value as physique index information.

The redness acquisition unit 21 executes the above-mentioned step (S22). The redness acquisition unit 21 may be the same as in the first embodiment.
The estimation unit 22 executes the above-mentioned step (S23).
The estimation unit 22 holds in advance a data table associated with information indicating the possibility of abnormalities in health information regarding one or more indicators for each of a specific combination in a plurality of anthropometric index ranges and a plurality of redness ranges. May be good. Further, when such a data table is stored in another computer, the estimation unit 22 may refer to the data table on the other computer.
Further, as described above, the estimation unit 22 may determine whether or not the subject belongs to the specific physique group including the obese physique, and may switch whether or not to estimate the health information based on the determination result.

The output processing unit 23 outputs the estimated health information of the subject as in the first embodiment. Further, the output processing unit 23 may output that the subject does not make an estimation when it is determined that the subject does not belong to the above-mentioned specific physique group. Further, the output processing unit 23 can also display the input screen of the anthropometric index information on the output device 15.

As described above, according to the second embodiment, the health information of the subject can be estimated with high accuracy by using the anthropometric index information and the redness information of the subject.

[Other embodiments]
The skin analysis method according to the first and second embodiments described above can be applied as an effect presentation method, a recommended method, etc. of foods and drinks and lifestyle-related improvement methods. Hereinafter, the method of presenting the effect of the food or drink or the lifestyle-related improvement method as another embodiment and the recommended method will be described focusing on the contents different from each of the above-described embodiments. In the following description, the same contents as those of the above-described embodiments will be omitted as appropriate.

[Method of presenting the effects of food and drink or lifestyle-related improvement methods]
FIG. 8 is a flowchart showing a method of presenting the effect of a food or drink or a lifestyle-related improvement method.
Hereinafter, the target food and drink for which the effect should be presented will be referred to as the target food and drink, and the target lifestyle-related improvement method will be referred to as the target method. The target foods and drinks are foods, beverages, etc., and the specific varieties and product names thereof are not limited. The target method is a lifestyle menu proposed to the subject in order to improve the lifestyle, for example, a daily meal menu and exercise menu, meal time and number of meals, exercise time, etc., and the specific contents thereof. Is not limited.
This effect presentation method was estimated in the steps (S31 and S32), (S31) and (S32) of carrying out the above-mentioned skin analysis method for the subjects before and after ingestion of the target food and drink or the subjects before and after the implementation of the target method, respectively. It includes a step (S33) of comparing health information and a step (S34) of presenting effect information of a target food or drink or a target method based on the comparison result in (S33).

The skin analysis method carried out in the step (S31) and the step (S32) may be the method according to the above-mentioned first embodiment or the method according to the second embodiment. In addition, it is desirable that the subjects before and after ingestion of the target food and drink or the subjects before and after the implementation of the target method to which the skin analysis method is applied are the same person.
In the step (S33), for example, blood pressure values and blood test values are compared with each other. When the test values of a plurality of types of test items are estimated as blood test values, the test values of the same test item are compared with each other.

The specific content of the effect information presented in the step (S34) is not limited as long as it is information based on the comparison result of the health information. For example, the change tendency (improvement, etc.) of the blood pressure value or the blood test value before and after ingestion of the target food or drink or before and after the implementation of the target method may be used as the effect information, or the difference may be used as the effect information. Further, the effect information may indicate only whether the effect is present or not.
The method of presenting the effect information in the step (S34) is not limited. For example, in the step (S34), the effect information may be displayed on the display device, printed, or read aloud.

According to this method, it is possible to easily know the effect of the target food or drink or the target method on the subject without having the subject perform a blood test or a blood pressure test.
Thereby, the subject can easily confirm the effect on the target food or drink or the target method, in other words, whether or not the target food or drink or the target method is suitable for the subject in order to obtain the effect. On the other hand, the manufacturer of the target food or drink or the proposer of the target method can easily grasp the overall effect of the food or drink itself or the target method by applying this method to a plurality of subjects.

This effect presentation method may be performed by the skin analyzer 10 described above.
FIG. 9 is a diagram conceptually showing a processing configuration example of the skin analyzer 10 that realizes a method of presenting the effect of a food or drink or a lifestyle-related improvement method. As shown in FIG. 9, the skin analyzer 10 further includes a comparison unit 27 in addition to the configuration of the first embodiment described above. The comparison unit 27 may be realized in the same manner as the other processing modules. Further, although different from the configuration shown in FIG. 9, the skin analyzer 10 may further include a comparison unit 27 similar to that in FIG. 9 in addition to the configuration of the second embodiment described above.
The redness acquisition unit 21 acquires the redness information for each subject before and after ingestion of the target food and drink.
The estimation unit 22 estimates health information about the subjects before and after ingestion of the target food and drink or the subjects before and after the implementation of the target method. That is, the redness acquisition unit 21 and the estimation unit 22 execute the process (S31) and the process (S32).
The comparison unit 27 compares each health information estimated by the estimation unit 22 before and after ingestion of the target food and drink or before and after the implementation of the target method. That is, the comparison unit 27 executes the step (S33).
The output processing unit 23 outputs the effect information of the target food or drink or the target method based on the comparison result by the comparison unit 27. That is, the output processing unit 23 executes the step (S34).

[Recommended method for food and drink or lifestyle-related improvement methods]
FIG. 10 is a flowchart showing a recommended method of eating and drinking or a lifestyle-related improvement method.
The recommended method of food and drink or lifestyle-related improvement method is a specific food or drink or a specific lifestyle based on the health information estimated in the step (S41) and the step (S41) of carrying out the above-mentioned skin analysis method for the subject. It includes a step (S42) of selecting an improvement method, and a step (S43) of presenting recommended information of the food or drink or lifestyle-related improvement method selected in the step (S42).
The skin analysis method carried out in the step (S41) may be the method according to the above-mentioned first embodiment or the method according to the second embodiment.

If a list of foods and drinks or lifestyle-related improvement methods capable of improving the blood condition related to the index is prepared in advance for each index of health information, this list can be used in the step (S42). In this list, for example, foods and drinks or lifestyle improvement methods that can regulate blood pressure with respect to blood pressure indicators are associated, and foods and drinks or lifestyle improvement methods that can regulate glucose metabolism with respect to glucose metabolism indicators (such as fasting blood glucose) are associated. And foods and drinks or lifestyle-improving techniques that can regulate lipid metabolism with respect to lipid metabolism indicators (such as HDLC) are associated.
In the present method, after identifying an index to be improved in the health information of the subject in the step (S42), the food or drink or lifestyle that can improve the blood condition of the specified index is referred to in the above list. Select an improvement method. In the step (S42), one food or drink or a lifestyle-related improvement method may be selected, or a plurality of foods and drinks or a lifestyle-related improvement method may be selected. Further, when the health information of the subject shows an excellent blood condition, the food or drink or the lifestyle-related improvement method may not be selected in the step (S42).
The recommended information presented in the step (S43) may include at least information (name, photo, improvement menu content, etc.) that can identify the food or drink or lifestyle-related improvement method selected in the step (S42). .. In addition to such identification information, the recommended information may further include detailed information on the food or drink such as raw materials, ingestion method, and efficacy, or detailed information on lifestyle-related improvement methods.
The method of presenting the recommended information in the step (S43) is not limited. For example, in the step (S43), the recommended information may be displayed on the display device, printed, or read aloud.

According to this method, a subject can easily obtain information on foods and drinks or lifestyle-related improvement methods capable of improving his / her blood condition without performing a blood test or a blood pressure test.

The recommended method may be performed by the skin analyzer 10 described above.
FIG. 11 is a diagram conceptually showing a processing configuration example of the skin analyzer 10 that realizes a recommended method of eating and drinking or a lifestyle-related improvement method. As shown in FIG. 11, the skin analyzer 10 further includes a selection unit 29 in addition to the configuration of the first embodiment described above. The selection unit 29 may be realized in the same manner as the other processing modules. Further, although different from the configuration shown in FIG. 11, the skin analyzer 10 may further include a selection unit 29 similar to that in FIG. 11 in addition to the configuration of the second embodiment described above.
The redness acquisition unit 21 and the estimation unit 22 execute the step (S41).
The selection unit 29 selects a specific food or drink or a specific lifestyle-related improvement method based on the health information estimated by the estimation unit 22. That is, the selection unit 29 executes the step (S42).
The output processing unit 23 outputs the recommended information of the food or drink or the lifestyle-related improvement method selected by the selection unit 29. That is, the output processing unit 23 executes the step (S43).

[Third Embodiment]
Hereinafter, the metabolic syndrome estimation method according to the third embodiment will be described. In the following description, the same contents as those described above will be omitted as appropriate.
"Metabolic syndrome" means a condition in which a person with visceral obesity who has a large amount of visceral fat easily leads to arteriosclerosis by having hypertension, hyperglycemia, and dyslipidemia. Hereinafter, this "metabolic syndrome" is abbreviated as "metabolic syndrome".
Currently, metabolic syndrome medical examinations are compulsory to prevent lifestyle-related diseases. It is a metabolic syndrome that the waist circumference exceeds the reference value and two or more of systolic blood pressure and / or diastolic blood pressure, fasting blood glucose, HDLC and / or triglyceride (TG) exceed the reference value. It is said to be a diagnostic condition.
However, in order to measure blood pressure, blood glucose and serum lipids, it is necessary to perform a blood pressure test and a blood test, and it takes a certain amount of time to obtain the test results.
Therefore, according to the third embodiment, a technique for estimating the degree of possibility of metabolic syndrome has been realized without performing a blood pressure test or a blood test. Since "estimating the degree of possibility of metabolic syndrome" here is different from medical practice, it can be paraphrased as evaluating the degree of possibility of metabolic syndrome, or estimating or evaluating the state of metabolic syndrome.

FIG. 12 is a flowchart showing a metabolic syndrome estimation method according to the third embodiment.
As shown in FIG. 12, in this method, a step of acquiring subject's skin condition information (S51), a step of acquiring subject's anthropometric index information (S52), and a step of estimating the degree of possibility of metabolic syndrome of the subject. (S53).

The skin condition information acquired in the step (S51) is information indicating the skin condition of the subject. The skin condition includes, for example, the brightness of the skin, the redness of the skin, the yellowness of the skin, the amount of sebum, the amount of exfoliation of the stratum corneum, the amount of water, and the amount of scales. The skin condition information acquired in the step (S51) indicates one or more kinds of skin condition indexes, and may include the above-mentioned redness information.
In the step (S51), skin condition information (sebum amount, water content, stratum corneum peeling amount, etc.) as a measurement result can be acquired from a dedicated skin measuring device. As another method, it is possible to acquire information indicating the redness state of the skin (such as the above-mentioned redness density value or redness unevenness value) and information indicating the yellowness state of the skin from the image data captured by the camera. can.
When this method is executed by a computer, the computer may automatically acquire the skin condition information, or the skin condition information input by the user operation may be acquired.

The step (S52) is the same as the step (S21) shown in FIG.
In the step (S53), this method is based on the skin condition information acquired in the step (S52) when the physique index value acquired as the physique index information in the step (S52) belongs to a predetermined range indicating obesity. To estimate the degree of possibility of metabolic syndrome in the subject.
Here, the "degree of possibility of metabolic syndrome" (also referred to as "possibility of metabolic syndrome") means the degree of conformity to metabolic syndrome or the degree of possibility of conformity.

As a result of conducting experiments focusing on the relationship between changes in the degree of obesity and changes in skin properties, the present inventors have found that the distribution of skin properties varies within a specific range of obesity, and this variation is due to metabolic syndrome. I got the idea that it may be affected by abnormal blood pressure or blood test values related to the possibility. Then, the relationship between the skin condition in the specific obesity range and the blood pressure value or blood test value related to the possibility of metabolic syndrome was investigated, and it was found that there was a mutual correlation.
As a result, in the step (S53), when the anthropometric index value belongs to the predetermined value range, the step (S53) uses statistical information based on the correlation between the specific skin condition and the blood pressure value or the blood test value related to the possibility of metabolic syndrome. The blood pressure value or blood test value related to the possibility of metabolic syndrome is estimated based on the skin condition information acquired in S52), and the degree of possibility of metabolic syndrome is determined using this estimated value.

The statistical information may be a simple regression equation generated using sample data of the population, with a specific skin condition as an explanatory variable and either a blood pressure value or a blood test value as an objective variable. , The graph may be a graph in which a regression line obtained from sample data of the population is superimposed on two axes of a specific skin condition axis and a blood pressure value or a blood test value axis.
In addition, as blood pressure values or blood test values related to the possibility of metabolic syndrome, systolic blood pressure, diastolic blood pressure, fasting blood pressure, HDLC (good cholesterol), triglyceride (TG), abdominal circumference, Non-HDLC, γ-GT. There are (γ-GTP), high-sensitivity CRP, and the like. Of these, systolic blood pressure, diastolic blood pressure, fasting blood glucose, HDLC, triglyceride, and abdominal circumference are used as diagnostic conditions for metabolic syndrome, so if these diagnostic conditions are met, the degree of possibility is set to 1. You may decide. In this case, depending on the severity of the disease that can be caused by the progression of metabolic syndrome, if the metabolic syndrome diagnostic conditions are met and Non-HDLC or γ-GT exceeds the reference value, the degree of possibility is reduced to 2. If it is determined and the high-sensitivity CRP exceeds the reference value, the degree of possibility may be determined to be the maximum value of 3. In addition, the degree of possibility may be determined to be the highest value when the metabolic syndrome diagnostic conditions are met. In this case, the blood pressure value or blood test value included in the metabolic syndrome diagnostic conditions exceeds the standard value. Depending on the number, the degree of possibility may be determined to be 2 or 1.

Further, in the step (S53), when the BMI value is 25 or more and 28 or less, the blood pressure value or the blood test value is estimated based on the redness information of the skin acquired in the step (S52), and this estimated value. The degree of possibility of metabolic syndrome is determined by comparison with the reference value.
The degree of possibility of metabolic syndrome may be indicated, for example, whether or not it is compatible with metabolic syndrome, or the degree of compatibility with metabolic syndrome may be indicated in two or more stages.
The estimation of the degree of possibility of metabolic syndrome in the step (S53) may be automatically performed by a computer or may be partially performed by a person. In the latter case, for example, a computer outputs a blood pressure value or a blood test value estimated based on skin condition information side by side with a reference value, and based on this output, a person has a blood pressure value or a blood test exceeding the reference value. You may confirm the existence of the value and finally estimate the degree of possibility of metabo.

As described above, in the third embodiment, the skin condition information and the anthropometric index information of the subject are acquired, and the degree of the possibility of the metabolic syndrome of the subject is estimated based on these. Therefore, according to the third embodiment, the subject can easily obtain the degree of possibility of his / her metabolic syndrome without performing a blood pressure test or a blood test.

The above-mentioned metabolic syndrome estimation method may be performed by the skin analyzer 30 shown in FIG. The skin analyzer 30 may have the same hardware configuration as the skin analyzer 10 shown in FIG.
FIG. 13 is a diagram conceptually showing a processing configuration example of the skin analyzer 30 that realizes the metabolic syndrome estimation method. As shown in FIG. 13, the skin analysis device 30 includes a skin condition acquisition unit 31, a physique index acquisition unit 32, an estimation unit 33, an output processing unit 34, and the like. Each of these processing modules is realized in the same manner as the processing modules of each of the above-described embodiments.

The skin condition acquisition unit 31 acquires the skin condition information of the subject. That is, the skin condition acquisition unit 31 executes the above-mentioned step (S51). The skin condition acquisition unit 31 can acquire the skin condition information of the subject from an external computer, device (skin measuring device, etc.), a portable recording medium, or the like via the input / output I / F 13 or the communication unit 14.
Further, the skin condition acquisition unit 31 can also calculate the redness concentration value or the redness unevenness value for the subject as the skin condition information by the same processing as the redness acquisition unit 21 described above. The skin condition acquisition unit 31 may acquire the skin condition information input according to the user operation using the input device 16 for the skin condition information input screen.

The physique index acquisition unit 32 acquires the physique index information of the subject. That is, the anthropometric index acquisition unit 32 executes the above-mentioned step (S52). The physique index acquisition unit 32 may acquire physique index information in the same manner as the physique index acquisition unit 25 described above.
The estimation unit 33 estimates the degree of possibility of metabolic syndrome of the subject by using the skin condition information acquired by the skin condition acquisition unit 31 and the anthropometric index information acquired by the anthropometric index acquisition unit 32. That is, the estimation unit 33 executes the above-mentioned step (S53). The estimation unit 33 may hold in advance statistical information based on the correlation between a specific skin condition and a blood pressure value or a blood test value related to the possibility of metabolic syndrome when the anthropometric index value belongs to a predetermined range. The statistical information held by an external computer may be referred to and used by communication.
The output processing unit 34 outputs the degree of possibility of metabolic syndrome estimated by the estimation unit 33. The output form by the output processing unit 34 is not limited. For example, the output mode by the output processing unit 34 is the same as the output processing unit 23 in each of the above-described embodiments.

Examples will be given below, and the above contents will be described in more detail. The present invention is not limited to the description of the following examples.

The present inventors investigated the relationship between redness of skin and information obtained by blood pressure test and blood test in women in their 30s to 40s.
As the information indicating the redness of the skin, the redness concentration value or the redness unevenness value obtained by the first method (see FIG. 2), the second and the third methods in the first embodiment is used, and each person in the population. Redness concentration value, BMI, blood pressure test value, and blood test value were obtained from. In the following description, such blood pressure test values, blood test values, and BMI may be referred to as survey index values.
14, FIG. 15 (a), FIG. 15 (b), and FIG. 15 (c) show the above-mentioned investigation results.

FIG. 14 shows the relationship between the redness concentration value and the redness unevenness value (first, second and third methods) and the BMI, blood pressure test value, and blood test value in the population of 362 women as Survey 1. It is a table showing.
In this survey, multiple types of skin redness information were obtained by the following multiple methods.
The "redness evaluation method A" is a redness concentration value obtained by the above-mentioned first method (see FIG. 2).
The "redness evaluation method B" is the redness unevenness value acquired by the above-mentioned first method (see FIG. 2).
The "redness evaluation method C" is a redness density value obtained by the above-mentioned second method.
The "redness evaluation method D" is a redness concentration value obtained by the above-mentioned third method (see FIG. 3).
The "redness evaluation method E" is a redness unevenness value acquired by the above-mentioned third method (see FIG. 3).
The systolic blood pressure and the diastolic blood pressure are shown as blood pressure test values, and the remaining index values such as fasting blood glucose, fasting insulin, and HOMA-R are shown as blood test values.
The numerical values in the table are correlation coefficients between the redness information of each type of skin and each survey index value, and a pattern is attached to the background of the 5% significance level and the 10% significance level.
As shown in FIG. 14, the redness concentration value or redness unevenness value correlates with physiological indicators such as blood pressure, glucose metabolism, lipid metabolism, blood in general, and uric acid, and in particular, BMI, systolic blood pressure, and diastolic blood pressure. , Fasting blood glucose, fasting insulin, HOMA-R, LDLC, HDLC, non-HDLC, TG, uric acid, leukocyte count, erythrocyte count, hemoglobin, hematocrit value were confirmed to be correlated at a 5% significance level. .. By using this correlation, as described in the above-described embodiment, the blood pressure test value or blood test value of the subject can be estimated based on the redness concentration value or the redness unevenness value of the skin of the subject.

15 (a), 15 (b) and 15 (c) are graphs of different BMI value ranges, and FIG. 15 (a) is a graph of a group of subjects having a BMI value of 25 or more. 15 (b) is a graph of a group of subjects having a BMI value of 18.5 or more and less than 25, and FIG. 15 (c) is a graph of a group of subjects having a BMI value of less than 18.5.
Each of these figures shows the relationship between the high and low of the redness unevenness value (redness evaluation method E) and the ratio of those who are out of the standard value range of the blood pressure test value or the blood test value. In each figure, the median redness unevenness is divided into a high group and a low group.
As shown in the figure, the difference in the proportion of blood pressure test values or blood test values outside the reference value range between the high and low redness unevenness values is larger in the group with high BMI than in the group with low BMI. In particular, in the BMI group of 25 or more, the difference in the ratio of those who are out of the reference value range of the blood pressure test value or the blood test value is remarkable depending on the level of the redness unevenness value. A BMI of less than 18.5 is defined as underweight, a BMI of 18.5 or more and less than 25.0 is defined as standard weight, and a BMI of 25.0 or more is defined as obesity.
According to FIGS. 15 (a), 15 (b) and 15 (c), subjects having a BMI value (25.0 or more) indicating an obese physique are compared with those having a lower BMI value. It is confirmed that the information obtained by the blood pressure test or the blood test can be estimated with high accuracy from the redness information of the skin.

Furthermore, the present inventors investigated the relationship between the change in the survey index value and the change in the skin condition for the same subject. As Survey 2, 33 women with a BMI in the range of 23.7 to 32.9 in their 50s were set as the initial (0M) population, and the redness concentration value or redness unevenness value and the redness unevenness value from each person in this population, and The survey index value was acquired. Subsequently, each expert provided guidance on nutrition and exercise to 33 people in the initial population four times during the four months from the initial (0M) to 4M. Then, at 12M, 12 months after the initial time, 25 of the 33 people were set as the final population, and the redness concentration value or the redness unevenness value and the survey index value were obtained from each person in this final population.
The results of this investigation are shown in FIGS. 16, 17, 18, and 19.

FIG. 16 is a table showing the relationship between the redness concentration value and the redness unevenness value (first, second and third methods) of Survey 2 and the blood test value. As shown in FIG. 16, it was confirmed that the redness concentration value or the redness unevenness value was correlated with the high-sensitivity CRP and HMW-Ad at the 10% significance level. By using this correlation, in a subject with a relatively obese physique, the state of the blood index (blood test value) of the subject can also be estimated based on the redness concentration value or the unevenness value of the skin.
FIG. 17 is a graph showing the relationship between the redness density value (redness evaluation method D) and the BMI value. The population in FIG. 17 is a group of 33 subjects at the initial stage (0M). In this figure, the range of BMI values 25 to 28 is shown by the dashed line.
By observing such a graph, the present inventors have found that the redness information and the skin condition information of the skin having a BMI value in the range of 25 to 28 are different from those in the other ranges. I got the idea that this variation may be affected by abnormalities in blood pressure or blood test values related to the possibility of metabolic syndrome. Then, the relationship between the redness concentration value and the blood pressure value or blood test value related to the possibility of metabolic syndrome was investigated by narrowing down the subjects having a BMI value in the range of 25 to 28. The findings are shown in FIGS. 18 and 19.

FIG. 18 is a diagram comparing the survey index values of the representative subject group having a low redness concentration value and the representative subject group having a high redness concentration value of the redness evaluation method D in the population having a BMI value in the range of 25 to 28.
In the representative subject group with a low redness concentration value, the BMI value exceeds the standard range, but the blood pressure test value and the blood test value are almost within the standard values except for non-HDLC. On the other hand, in the representative subject group having a high redness concentration value, the BMI value exceeded the standard range, and most of the blood pressure test value and the blood test value exceeded the standard value, and the metabolic syndrome was in an advanced state.

FIG. 19 is a diagram showing changes in survey index values between the initial time (0M) and 12 months (12M) in a population having a BMI value in the range of 25 to 28. As mentioned above, the population receives guidance from experts from the initial stage to 12 months later.
As the redness concentration value improved, most of the blood pressure test values and blood test values improved. From these, as in the third embodiment described above, the blood pressure test value or the blood test value related to the metabolic syndrome possibility can be estimated from the skin condition such as the redness concentration value, and based on this, the metabolic syndrome possibility can be estimated. It was confirmed that the degree of can be estimated.

In the plurality of flowcharts used in the above description, a plurality of steps (processes) are described in order, but the execution order of the steps executed in each embodiment is not limited to the order of description. In each embodiment, the order of the illustrated steps can be changed within a range that does not hinder the contents. In addition, the above-mentioned embodiments can be combined as long as the contents do not conflict with each other.

Part or all of the above content may also be specified as follows: However, the above contents are not limited to the following descriptions.

<1> The redness acquisition process for acquiring the redness information of the subject's skin,
Health including at least information obtained by a blood pressure test or a blood test for the subject using the redness sample data and blood sample data statistical information acquired in advance from the population and the redness information acquired in the redness acquisition step. The estimation process for estimating information and the estimation process
Skin analysis methods including.

<2> In the redness acquisition step, by processing the skin image of the subject, at least one of the redness index and the unevenness index is acquired as the redness information.
The skin analysis method according to <1>.
<3> In the estimation step, at least one of the blood pressure value and the blood test value of the subject is estimated as the health information.
The skin analysis method according to <1> or <2>.
<4> A physique acquisition process for acquiring the subject's physique index information,
Further prepare
In the estimation step, the health information of the subject is estimated by further using the physique index information acquired in the physique acquisition step.
The skin analysis method according to any one of <1> to <3><5> In the estimation step, based on the combination of the physique index range to which the physique index information belongs and the redness range to which the redness information belongs, Estimate the possibility of abnormalities in health information related to one or more indicators as the health information,
The skin analysis method according to <4>.
<6> A step of determining whether or not the subject belongs to a specific physique group including an obese physique based on the acquired physique index information.
Further prepare
In the estimation step, when the subject belongs to the specific physique group, statistical information of redness sample data and blood sample data acquired in advance from the population of the specific physique group, and redness acquired in the redness acquisition step. Using the information, the health information of the subject is estimated.
The skin analysis method according to <4> or <5>.
<7> The skin analysis method according to any one of <1> to <6> is included.
By executing the skin analysis method for the subject before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method, before and after ingestion of the target food and drink or the lifestyle-related improvement method estimated by the estimation step. A comparison process that compares each health information before and after the implementation,
A presentation step of presenting effect information of the target food or drink or the target lifestyle-related improvement method based on the comparison result in the comparison step, and
A method of presenting the effects of foods and drinks or lifestyle-related improvement methods including.
<8> The skin analysis method according to any one of <1> to <6> is included.
A selection process for selecting a specific food or drink or a specific lifestyle-related improvement method based on the health information estimated in the estimation process.
A presentation process that presents recommended information on food and drink or lifestyle-related improvement methods selected in the selection process, and
A method of recommending foods and drinks or lifestyle-related improvement methods including.
<9> The first acquisition process for acquiring the skin condition information of the subject,
The second acquisition step of acquiring the anthropometric index information of the subject, and
When the anthropometric index value acquired as the anthropometric index information in the second acquisition step belongs to a predetermined range indicating obesity, the metabolic syndrome of the subject is possible based on the skin condition information acquired in the first acquisition step. An estimation process that estimates the degree of sex, and
Metabolic syndrome estimation method including.
<10> The skin condition information is skin redness information.
The physique index value is a BMI value.
The method according to <9>.
<11> Redness acquisition means for acquiring the redness information of the subject's skin,
Health including at least information obtained by a blood pressure test or a blood test for the subject using the redness sample data and blood sample data statistical information previously acquired from the population and the redness information acquired by the redness acquisition means. An estimation method for estimating information and
A skin analyzer equipped with.
<12> The redness acquisition means acquires at least one of the redness index and the unevenness index as the redness information by processing the skin image of the subject.
The skin analyzer according to <11>.
<13> The estimation means estimates at least one of the blood pressure value and the blood test value of the subject as the health information.
The skin analyzer according to <11> or <12>.
<14> Anthropometric index acquisition means for acquiring the anthropometric index information of the subject,
Further prepare
The estimation means estimates the health information of the subject by further using the physique index information acquired by the physique index acquisition means.
The skin analyzer according to any one of <11> to <13>.
<15> The estimation means estimates the possibility of abnormality in health information related to one or more indicators as the health information based on the combination of the anthropometric index range to which the anthropometric index information belongs and the redness range to which the redness information belongs. ,
The skin analyzer according to <14>.
<16> The estimation means determines whether or not the subject belongs to a specific physique group including an obese physique based on the physique index information acquired by the physique index acquisition means, and the subject belongs to the specific physique group. In the case of belonging to, the health information of the subject is obtained by using the statistical information of the redness sample data and the blood sample data acquired in advance from the population of the specific physique group and the redness information acquired in the redness acquisition step. presume,
The skin analyzer according to <14> or <15>.
<17>
The redness acquisition means acquires the redness information for the subject before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method, respectively.
The estimation means estimates the health information of the subject before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method.
A comparison means for comparing each health information estimated by the estimation means before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method.
An output processing means that outputs effect information of the target food or drink or the target lifestyle-related improvement method based on the comparison result by the comparison means, and
The skin analyzer according to <11>.
<18> A selection means for selecting a specific food or drink or a specific lifestyle-related improvement method based on the health information estimated by the estimation means.
An output processing means that outputs recommended information of foods and drinks or lifestyle-related improvement methods selected by the selection means, and
The skin analyzer according to <11> or <17>.
<19> Skin condition acquisition means for acquiring subject's skin condition information,
Anthropometric index acquisition means for acquiring the anthropometric index information of the subject, and
When the anthropometric index value acquired as the anthropometric index information by the anthropometric index acquisition means belongs to a predetermined range indicating obesity, the metabolic syndrome of the subject is possible based on the skin condition information acquired by the skin condition acquisition means. An estimation method for estimating the degree of sex, and
A metabolic syndrome estimator equipped with.
<20> The skin condition information is skin redness information.
The physique index value is a BMI value.
The metabolic syndrome estimation device according to <19>.

10, 30 skin analyzer 11 CPU
12 Memory 13 I / O I / F
14 Communication unit 15 Output device 16 Input device 21 Redness acquisition unit 22 Estimating unit 23 Output processing unit 25 Physical index acquisition unit 27 Comparison unit 29 Selection unit 31 Skin condition acquisition unit 32 Physical index acquisition unit 33 Estimating unit 34 Output processing unit

Claims (12)

A method of estimating physiological indicators performed by a computer that includes at least a processor and memory.
The computer
The redness acquisition process for acquiring the redness information of the subject's skin,
Using the statistical information of redness sample data and blood sample data acquired in advance from the population and the redness information acquired in the redness acquisition step, sugar metabolism, lipid metabolism, and blood in general obtained by a blood test for the subject. Or the estimation process for estimating the physiological index information of uric acid,
And run
The population is a set of a plurality of people.
The redness sample data is data of skin redness information of each person forming the population.
The blood sample data is data of the physiological index information obtained by a blood test for each person forming the population.
The statistical information is a regression equation obtained by regression analysis of the redness sample data and the blood sample data based on the correlation between the redness of the skin and the physiological index information obtained by the blood test, and is a regression equation of the skin. It is a regression equation using the redness information as an explanatory variable and the physiological index information obtained by a blood test as an objective variable.
Method of estimating physiological indicators . In the redness acquisition step, by processing the skin image of the subject, one or both of the red density index and the red unevenness index are acquired as the redness information.
The redness sample data is index value data of one or both of the red color intensity index and the red unevenness index of each person forming the population.
The method for estimating a physiological index according to claim 1. The population is a group of a plurality of men or women only, a group of a plurality of persons of a specific age group, or a group of a plurality of persons having a specific physique.
The method for estimating a physiological index according to claim 1 or 2. A method of estimating health information performed by a computer, including at least a processor and memory.
The computer
The redness acquisition process for acquiring the redness information of the subject's skin,
Using the statistical information of redness sample data and blood sample data acquired in advance from the population and the redness information acquired in the redness acquisition step, the systolic blood pressure or diastolic blood pressure obtained by the blood pressure test for the subject is determined. An estimation step for estimating health information including at least blood pressure information or physiological index information of glucose metabolism, lipid metabolism, blood in general or uric acid obtained by blood test, and
The physique acquisition process for acquiring the subject's physique index information and
And run
The population is a set of a plurality of people.
The redness sample data is data of skin redness information of each person forming the population.
The blood sample data is the data of the blood pressure information obtained by the blood pressure test for each person forming the population or the data of the physiological index information obtained by the blood test.
The statistical information is obtained by regression analysis of the redness sample data and the blood sample data based on the correlation between the redness of the skin and the blood pressure information obtained by the blood test or the physiological index information obtained by the blood test. It is a regression equation with skin redness information as an explanatory variable and the blood pressure information obtained by a blood test or the physiological index information obtained by a blood test as an objective variable.
In the estimation step, the health information of the subject is estimated by further using the physique index information acquired in the physique acquisition step.
How to estimate health information . In the estimation step, the systolic blood pressure, the diastolic blood pressure, the glucose metabolism, or the lipid metabolism is based on the combination of the anthropometric index range to which the anthropometric index information belongs and the redness range to which the redness information belongs. Estimate the possibility of abnormalities in health information related to one or more indicators as the above-mentioned health information.
The method for estimating health information according to claim 4. The computer
A step of determining whether or not the subject belongs to a specific physique group including an obese physique based on the acquired physique index information.
Further execute,
The population is a set of a plurality of people belonging to the specific physique group.
In the estimation step, when the subject belongs to the specific physique group, statistical information of redness sample data and blood sample data acquired in advance from the population of the specific physique group, and acquired in the redness acquisition step. Using the redness information, the health information of the subject is estimated.
The method for estimating health information according to claim 4 or 5. The method for estimating a physiological index according to any one of claims 1 to 3 or the method for estimating health information according to any one of claims 4 to 6 is included.
The computer
By executing the estimation method of the physiological index for the subject before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method, the pre- and post-ingestion of the target food and drink or the lifestyle-related improvement estimated by the estimation step. Estimated by the estimation step by comparing each physiological index information before and after the implementation of the method , or by executing the health information estimation method for the subject before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method. A comparison process that compares each health information before and after ingestion of the target food and drink or before and after the implementation of the lifestyle-related improvement method .
A presentation step of presenting effect information of the target food or drink or the target lifestyle-related improvement method based on the comparison result in the comparison step, and
A method of presenting the effects of food and drink or lifestyle-related improvement methods that further implement. The method for estimating a physiological index according to any one of claims 1 to 3 or the method for estimating health information according to any one of claims 4 to 6 is included.
The computer
A selection process for selecting a specific food or drink or a specific lifestyle-related improvement method based on the physiological index information or health information estimated in the estimation process.
A presentation process that presents recommended information on food and drink or lifestyle-related improvement methods selected in the selection process, and
How to recommend food and drink or lifestyle-related improvement methods to further implement. The redness acquisition method for acquiring the redness information of the subject's skin,
Using the statistical information of redness sample data and blood sample data acquired in advance from the population and the redness information acquired by the redness acquisition means, sugar metabolism, lipid metabolism, and blood in general obtained by a blood test for the subject. Or an estimation means for estimating the physiological index information of uric acid,
Equipped with
The population is a set of a plurality of people.
The redness sample data is data of skin redness information of each person forming the population.
The blood sample data is data of the physiological index information obtained by a blood test for each person forming the population.
The statistical information is a regression equation obtained by regression analysis of the redness sample data and the blood sample data based on the correlation between the redness of the skin and the physiological index information obtained by the blood test, and is a regression equation of the skin. It is a regression equation using the redness information as an explanatory variable and the physiological index information obtained by a blood test as an objective variable.
Physiological index estimator . The redness acquisition method for acquiring the redness information of the subject's skin,
Using the statistical information of redness sample data and blood sample data acquired in advance from the population and the redness information acquired by the redness acquisition means, the systolic blood pressure or diastolic blood pressure obtained by the blood pressure test for the subject is determined. An estimation means for estimating health information including at least blood pressure information or physiological index information of glucose metabolism, lipid metabolism, blood in general or uric acid obtained by blood test, and
The physique acquisition means for acquiring the physique index information of the subject, and
Equipped with
The population is a set of a plurality of people.
The redness sample data is data of skin redness information of each person forming the population.
The blood sample data is the data of the blood pressure information obtained by the blood pressure test for each person forming the population or the data of the physiological index information obtained by the blood test.
The statistical information is obtained by regression analysis of the redness sample data and the blood sample data based on the correlation between the redness of the skin and the blood pressure information obtained by the blood test or the physiological index information obtained by the blood test. It is a regression equation with skin redness information as an explanatory variable and the blood pressure information obtained by a blood test or the physiological index information obtained by a blood test as an objective variable.
The estimation means estimates the health information of the subject by further using the physique index information acquired by the physique acquisition means.
Health information estimation device. The redness acquisition means acquires the redness information for the subject before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method, respectively.
The estimation means estimates the health information of the subject before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method.
A comparison means for comparing each health information estimated by the estimation means before and after ingestion of the target food and drink or before and after the implementation of the target lifestyle-related improvement method.
An output processing means that outputs effect information of the target food or drink or the target lifestyle-related improvement method based on the comparison result by the comparison means, and
10. The health information estimation device according to claim 10. A selection means for selecting a specific food or drink or a specific lifestyle-related improvement method based on the health information estimated by the estimation means, and
An output processing means that outputs recommended information of foods and drinks or lifestyle-related improvement methods selected by the selection means, and
10. The health information estimation device according to claim 10.

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