WO2021256339A1 - Skin wrinkle evaluation method - Google Patents

Abstract

Provided is an invention that makes it possible to more accurately evaluate the skin wrinkles of each individual.　A skin wrinkle evaluation method in which a skin wrinkle index for a given person is estimated on the basis of at least two values consisting of an age value and measured skin brightness value for the person. A wrinkle improvement composition evaluation or searching method including a step for using the wrinkle evaluation method to estimate a wrinkle index for a given person who has had a test substance administered thereto and a step for determining that the test substance is useful for wrinkle improvement if the estimated wrinkle index is lower than a wrinkle index for the given person from before the test substance was administered.

Description

How to evaluate skin wrinkles

The present invention relates to a method for evaluating skin wrinkles and the like.

In general, wrinkles on the skin are more likely to occur on the forehead, between the eyebrows, mouth, and corners of the eyes with aging, but the condition of wrinkles on the skin varies greatly among individuals. Therefore, for the purpose of anti-aging and the like, in the fields of makeup, cosmetology, medicine and the like, techniques for preventing, improving or treating wrinkles on the skin have been proposed for each individual. For this purpose, there is a need for a method for accurately evaluating the state of wrinkles on the skin.

Conventionally, in order to evaluate the state of wrinkles on the skin, a visual evaluation method for evaluating the state of the skin, a device measuring method for measuring the state of the skin, and the like have been used.
For example, in order to evaluate the state of wrinkles, for example, a visual evaluation method by a professional evaluator is known in accordance with the wrinkle grade standard table (0 to 7) of the guideline (Non-Patent Document 1) published by the Japan Cosmetic Industry Association. There is.
For example, as a measuring instrument method for evaluating the state of wrinkles, for example, a two-dimensional image analysis method using oblique illumination with a replica of a wrinkle portion, a three-dimensional measurement method using a replica, and the like are known.

Further, various methods for accurately evaluating the state of wrinkles on the skin have been studied.
For example, in Patent Document 1, a step of performing image processing including cross binarization processing and / or short straight line matching processing on a skin image to obtain a physical amount of skin, and a step of obtaining a physical amount of skin obtained in the above step are described. A method for distinguishing skin texture and / or wrinkles has been proposed, which comprises a step of substituting into a prediction formula prepared in advance and discriminating the obtained evaluation value from the skin texture and / or wrinkle evaluation value.

International Publication No. 2009/142609

Journal of the Japanese Society of Cosmetics, "Report of the Cosmetic Function Evaluation Method Review Committee: Guidelines for Cosmetic Function Evaluation Method", Vol. 30, No. 4, pp.316-332 (2006).

Furthermore, the present inventor can evaluate skin wrinkles more accurately and more easily for each individual, thereby making it more suitable for each individual for prevention, improvement, or treatment of skin wrinkles. I thought it would be easier to propose good skin care technology.
Therefore, it is a main object of the present invention to provide a technique capable of evaluating skin wrinkles more accurately and more easily for each individual.

As a result of diligent studies, the present inventor can estimate the index value of skin wrinkles for each individual based on the accumulation of device evaluation results over a long period of time and the examination results by multivariate analysis, age and skin condition. We were able to find a new optimal combination with and, and we were also able to find a new wrinkle prediction model that fits well. As a result, the present inventor has completed the present invention as follows.

The present invention provides a method for evaluating skin wrinkles, which estimates an index value of skin wrinkles of a subject based on at least two of a subject's age and a measured value of skin brightness.
The method for evaluating skin wrinkles estimates the index value of skin wrinkles of a subject based on the above two and one or two of the measured values of redness of the skin and / or the measured value of the amount of sebum on the skin. You may.
In the method for evaluating skin wrinkles, an index value of skin wrinkles of a subject may be estimated by using two measured values of the subject's age and skin brightness in the wrinkle prediction model.
The method for evaluating skin wrinkles is to use the wrinkle prediction model as two measurement values of the subject's age and skin brightness, and one of the measurement values of skin redness and / or the amount of sebum of the skin. By using one or two, the index value of wrinkles on the skin of the subject may be estimated.
The wrinkle prediction model is obtained by deriving using a linear mixed-effects model in which the wrinkle index value of one individual is used as an objective variable and the measured values of the age and skin brightness of the individual are included in at least the explanatory variables. It may be a model.
In the wrinkle prediction model, the parameters of the linear mixed-effects model may be obtained by using a maximum likelihood method or a limited maximum likelihood method.

In the present invention, the step of estimating the wrinkle index value of the skin of the subject to whom the test substance is administered by using the wrinkle evaluation method, and the estimated wrinkle index value of the skin are the skin of the subject before administration. It is possible to provide a method for evaluating or searching for a wrinkle improving composition, which comprises a step of determining a test substance for wrinkle improving when the wrinkle is improved lower than the wrinkle index value of.

The present invention can provide a technique for evaluating skin wrinkles more accurately and more easily for each individual. The effects described here are not necessarily limited, and may be any of the effects described in the present invention.

It is a flowchart which shows an example of the wrinkle evaluation method of the skin of this invention. It is a flowchart which shows an example of the wrinkle evaluation method of the skin of this invention. It is a flowchart which shows an example of the wrinkle evaluation method of the skin of this invention. It is a hardware block diagram which shows one Embodiment of this invention. It is a schematic diagram which shows an example of the wrinkle evaluation apparatus or system of the skin of this invention. It is a figure which shows an example of the wrinkle evaluation method of the skin of this invention, and the method of providing information for wrinkle improvement. It is a block diagram which shows the processing procedure of the general specialized AI simply.

Hereinafter, suitable embodiments for carrying out the present invention will be described. It should be noted that the embodiments described below show an example of a typical embodiment of the present invention, and the scope of the present invention is not narrowly interpreted by this. Further, in the present specification, the percentage is expressed by mass unless otherwise specified. Further, the upper limit value and the lower limit value of each numerical value range (to) can be arbitrarily combined as desired.

1. 1. Method for evaluating skin wrinkles according to the present invention

The present invention provides a method for evaluating skin wrinkles, which estimates an index value of skin wrinkles of a subject based on at least these two values of a subject's age value and a measured value of skin brightness. It is something to do. As a result, wrinkles on the skin can be evaluated more accurately and more easily for each individual.

Furthermore, the present invention combines the above two values (age value, skin brightness measurement value) with one or two values of skin redness measurement value and / or skin sebum amount measurement value. Therefore, it is preferable to estimate the index value of wrinkles on the skin of the subject based on these values. As a result, wrinkles on the skin can be evaluated more accurately and more easily for each individual.

Further, the present invention uses a wrinkle prediction model, and by using the two values (age value, skin brightness measurement value) of the subject in the wrinkle prediction model, or by using the four values of the subject. It is more preferable to estimate the wrinkle index value of the skin of the subject by using two or more kinds of values selected from the values. The wrinkle prediction model has high model performance, can use device evaluation, and can also provide a wrinkle prediction model that fits well and is suitable for each individual. As a result, wrinkles on the skin can be evaluated more accurately and more easily for each individual.

Further, according to the present invention, the wrinkles on the skin of the subject can be evaluated by comparing the index value of the wrinkles on the skin with the reference value of the skin condition. This makes it possible to propose skin care (particularly wrinkle skin care) that is more convenient, more accurate, and suitable for the subject.
The reference value of the skin condition may be a value that can be obtained by using the wrinkle prediction model, and specifically, a value preset in the wrinkle prediction model (age value, skin brightness). It can be obtained by using (for example, substituting) the value, the value of redness of the skin, the value of the amount of sebum, etc. As a value for obtaining the reference value, it is preferable that the value of age and the value of skin condition (skin brightness, skin redness, amount of sebum, etc.) are associated with each other.
Further, the reference value of the skin condition may be a reference value of a general skin condition (for example, an average value of each skin condition of the age or age corresponding to the age or age of the subject).

Hereinafter, the present invention will be described in more detail.

1-1. Subject The subject is not particularly limited, and humans are preferable, regardless of age or sex, but the gender of the subject is more preferably female from the viewpoint of good wrinkle prediction accuracy.
The race of the subject is not particularly limited, but is preferably a Caucasian race (white), a Mongoloid race (yellow), and preferably a Mongoloid race (preferably Mongoloid A, B, C). The ethnic lineage of the subject is preferably one or more selected from Chinese, Korean, and Japanese, and more preferably Japanese.
In the present specification, the "subject" means a person who receives an estimation of a wrinkle index value by using the evaluation method of the present invention.

The age group of the subject is not particularly limited, but the lower limit is preferably 18 years or older, more preferably 20 years or older, still more preferably 22 years or older, and the upper limit thereof is not particularly limited. For example, it can be 80 years old or younger, 70 years old or younger, 60 years old or younger, and the like. The preferred numerical range is more preferably 18 to 70 years old, still more preferably 22 to 60 years old, from the viewpoint of good wrinkle prediction accuracy.

1-2. Evaluation of subject's age and skin condition In the evaluation method of the present invention, the value of a certain age of the subject and the measured value of the skin condition at that age (measured value of skin brightness, measured value of skin redness, (Measured value of the amount of skin oil, etc.) and is used. The value of a certain age of the subject and the measured value of each skin condition at that age may be interrelated or linked.

1-2-1. Age value The age value is not particularly limited, but is preferably the actual age value of the subject when evaluating the current skin wrinkles.
The "age" in the present specification can be expressed by the full age + "the number of months elapsed from the month of birth" or the full age + "the number of months elapsed from the month of birth / 12 months". For example, if the age is 30 years and 6 months, it can be expressed as 30.5. Further, the "age" may be converted into a "month age" of "the number of months elapsed since the birthday".

1-2-2. Measured value of skin brightness The skin brightness is "brightness L *" when the skin color is expressed by the L * a * b * color system.
In the L * a * b * color system, the lightness is L *, the hue and saturation are indicated by a *, b * (a * and b * are indicated by the color direction, and a * is indicated by the color direction). Red direction, -a * indicates green direction, b * indicates yellow direction, and -b * indicates blue direction).
Further, the measured values of skin color such as skin brightness and redness used in the present invention are not limited to the values by a measuring device capable of measuring the L * a * b * color system, and other color systems can be used. The value converted from the measured value by a measurable measuring device (for example, the value of the XYZ color system, the RGB color system, etc.) to the L * a * b * color system is used as the skin brightness, redness of the skin, etc. It may be used as a measurement value of (for example, Kiyoshi Chaki, "Measurement of Color", Color Material, 57 [10], p558-568, 1984; Hiroshi Kodera, "Development of Color Space", Journal of the Imaging Society of Japan. , Vol. 43, No. 2, p73-81, 2004).

The measured value of the brightness of the skin can be obtained by using a measuring device capable of measuring the L * a * b * color system or the like, or an imaging device. As described above, the "brightness L *" of the value converted from the value of another color system such as the XYZ color system and the RGB color system to the value of the L * a * b * color system is described above. It may be used as a measurement value of skin brightness.
The part of the skin to be measured is not particularly limited, but the skin on the face is preferable, and the cheek (more specifically, the upper part of the cheek) is more preferable.

Further, in the present invention, the operator or the control unit selects a color scheme panel (image, etc.) that is the same as or similar to the skin brightness of the subject, so that the control unit associates with the data of the selected color scheme panel. It may be configured so that the measured value data of the skin brightness of the subject can be selected as the measured value of the skin brightness of the subject. It is preferable to store in advance the measured value data of the skin brightness corresponding to the color tone (value of the color scheme) of each color scheme panel and the color tone (value of the color scheme) of each color scheme panel, and the measurement thereof. It is preferable that the value data is set and stored as the measured value data of the skin brightness associated with the data of the color scheme panel, so that the two can be easily converted to each other.
Note that "associating and storing" includes, but is not limited to, storing specific data and other data in association with each other.

For the measurement of the brightness of the skin, a measuring device capable of measuring the L * a * b * color system (for example, a handy color difference meter compliant with the JIS standard, a spectrocolorimeter, etc.) is generally used. However, the present invention is not limited to these, and an image pickup device (for example, a camera, a video camera, a mobile terminal, etc.) may be used. It is also possible to use a color scheme panel.

The color difference meter is not particularly limited, but it is preferable that the color difference meter complies with the JIS standard. As the spectrophotometer, an integrating sphere type, for example, a spectrophotometer CM-700d (manufactured by Konica Minolta) can be used. It is also possible to use a color scheme panel.

1-2-3. Measured value of skin redness The skin redness is the "chromaticity a *" when the skin color is expressed by the L * a * b * color system.
The "L * a * b * color system", "measuring device capable of measuring the L * a * b * color system", and "imaging device" are described in the above "measured value of skin brightness". Since it overlaps with the above, it is omitted.

The measured value of redness of the skin can be obtained by using a measuring device capable of measuring the L * a * b * color system or the like, or an imaging device. As described in the above "Measured value of skin brightness", the value converted from the value of other color system such as XYZ color system and RGB color system to the value of L * a * b * color system. The "chromaticity a *" of the above may be used as the measured value of the redness of the skin.
The part of the skin to be measured is not particularly limited, but the skin on the face is preferable, and the cheek (more specifically, the upper part of the cheek) is more preferable.

Further, in the present invention, the operator or the control unit selects a color scheme panel (image, etc.) that is the same as or similar to the redness of the skin of the subject, so that the control unit associates with the data of the selected color scheme panel. It may be configured so that the measured value data of the skin redness of the subject can be selected as the measured value of the redness of the skin of the subject. It is preferable that the measured value data of the redness of the skin corresponding to the color tone (value of the color scheme) of each color scheme panel and the color tone (value of the color scheme) of each color scheme panel is stored in advance, and the measured value is concerned. It is preferable that the data is set and stored as the measured value data of the redness of the skin associated with the data of the color scheme panel, which makes it possible to easily convert between the two.

1-2-4. Measured value of the amount of sebum on the skin The amount of sebum on the skin is the amount of sebum secreted on the surface of the skin.
The measured value of the amount of sebum on the skin can be obtained by using a measuring device or an imaging device capable of measuring the amount of sebum. At this time, the part of the skin to be measured is not particularly limited, but the skin on the face is preferable, and more preferably, the forehead (more specifically, the center of the forehead) from the viewpoint that a stable amount of sebum can be collected within a short measurement time. Part) is more preferable.

For the measurement of the amount of sebum on the skin, it is generally preferable to use a measuring device (for example, a Sebumeter) capable of measuring the amount of sebum on the skin surface, but the measurement is not limited to these, and an image pickup device (for example, a camera, etc.) is used. A video camera, mobile terminal, etc.) may be used.

As the sebum amount measuring device, for example, a spectrophotometer Sebumeter SM 815 (manufactured by Course + Khazaka) can be used. In the sebum amount measuring device, the measured value of the sebum amount can be obtained by adhering the sebum secreted on the skin surface to the tape and measuring the light transmission.

In the present invention, as described above, the measured value of the brightness of the skin, the measured value of the redness of the skin, and the measured value of the amount of sebum are measured by a measuring device or a skin condition measuring device such as an imaging device. It can be done and it is not necessary to perform human sensory evaluation. In the case of an image pickup device, each skin condition (for example, skin brightness, skin redness, skin sebum) can be converted into a measured value of each skin condition by using an image pickup data or an image data. It may be converted into a measured value (for example, WO2013 / 0944442, Japanese Patent Application Laid-Open No. 8-308634, etc.). By using the measured values obtained from the skin condition measuring device in this way, it is possible to obtain the measured values of the skin condition more easily, more accurately, and with less variation in the values, as compared with the sensory evaluation by humans.

When carrying out the measurement, the makeup state (presence / absence, etc.) of the subject is not particularly limited, and the subject may be in a state of wearing makeup. More preferably, it is preferable that the subject has a bare skin (more preferably a bare face) from the viewpoint of more accurate evaluation of wrinkles, and more preferably, the subject uses a skin cleanser such as a face wash. It is preferable to perform the measurement after washing the skin (face) to make it in the state of bare skin (bare face). Further, the portion to be measured may be bare skin or skin after washing. The term "bare skin (bare face)" as used herein means "undressed, untouched skin (face)".
More specifically, from the viewpoint of improving the accuracy of wrinkle evaluation, it is preferable to wash the face with a face wash to make it look like a real face, and then perform the measurement after acclimatizing for 20 minutes or more and 60 minutes or less in an indoor environment. .. More specifically, it is preferable to carry out the measurement after washing the face and acclimatizing for 30 minutes in an environment controlled at 20 to 22 ° C. and 50 ± 5%.

1-3. Estimating the index value of skin wrinkles of the subject As described above, the present invention comprises the age value, the measured value of the skin brightness, the measured value of the redness of the skin, and the measured value of the amount of sebum in the subject. Based on two or more values selected from the group, the index value of wrinkles on the skin of the subject can be estimated. Preferably, it contains at least two values, an age value and a skin brightness measurement.
As shown in the following [Example], the above-mentioned "index value of skin wrinkles" is a guideline published by the Japan Cosmetic Industry Association (Journal of the Japan Cosmetic Society, "Report of the Cosmetic Function Evaluation Method Review Committee: Cosmetic Function". "Wrinkle grade standard table (0,1,2,3,4,5,6,7)" according to the evaluation method guideline ", Vol. 30, No. 4, pp.316-332 (2006)." The correlation of is shown. As described above, the "index value of wrinkles on the skin" can correspond to the "wrinkle grade standard table" which has been conventionally used as a standard without any particular conversion. Therefore, it can be said that the index value of skin wrinkles of the present invention has high wrinkle prediction accuracy and high reliability. In addition, the index value of skin wrinkles of the present invention can be regarded as the wrinkle grade in the above-mentioned "wrinkle grade standard table" and used. Further, in the skin wrinkle evaluation method of the present invention, it is easy to utilize information such as documents that employ the "wrinkle grade standard table".

Conventionally, the "wrinkle grade standard table" (wrinkle grade) based on the guidelines announced by the Japan Cosmetic Industry Association is a visual sensory evaluation, so it is an advanced evaluation to become a professional evaluator in order to ensure the accuracy of wrinkle evaluation. It took some proficiency. Further, in the case of sensory evaluation, as the number of subjects increases, the discrimination tends to be blurred, and there is a risk that the accuracy of wrinkle evaluation deteriorates.
However, in the present invention, since the measured value of the skin condition is an instrument evaluation using a device such as a measuring device or an imaging device, the measurer who measures the skin condition is required to have an advanced level in the sensory evaluation. Does not require any proficiency. Further, since the measured value used in the present invention is an instrument evaluation using a measuring device, the variation in the value can be reduced as compared with the variation in the sensory evaluation. Then, in the present invention, by using the measuring device, it is possible to homogenize the ability of the measurer and the homogenization of the measuring method. Therefore, even if a plurality of measurements or long-term measurements are performed, the reliability of the obtained measured value data is high.
As described above, since the device evaluation can be used in the present invention, it is possible to evaluate the wrinkles on the skin of the subject more easily and more accurately.

1-4. Wrinkle prediction model In the skin wrinkle evaluation method of the present invention, it is preferable to use a wrinkle prediction model.
The wrinkle prediction model is a linear mixture in which the wrinkle index value of one individual is used as an objective variable and the age (age value) and skin brightness (measured value of skin brightness) of the one individual are included in at least the explanatory variables. It is preferable that the model is obtained by deriving using an effect model.
Further, the parameters (variables) of the linear mixed-effects model are preferably those obtained by using the maximum likelihood method or the limited maximum likelihood method. The maximum likelihood method is a method of point estimation of the population parameter of the probability distribution to which it follows from given data in statistics. The limited maximum likelihood method is a method for estimating parameters related to the variance of a linear mixed model, and is a maximum likelihood method for a likelihood function limited to "error contrast" rather than the data itself.

As the explanatory variables, in addition to the above-mentioned age value and skin brightness measurement value, one of skin redness (measurement value of redness) and / or skin oil content (measurement value of skin oil content) or It is more preferable to further include two, and it is further preferable that these four explanatory variables are used.

In the skin wrinkle evaluation method of the present invention, it is more preferable to use at least two values (age value and skin brightness measurement value) described above for the wrinkle prediction model. Even more preferably, in the wrinkle prediction model, one or two of the two values of the age value and the measured value of the skin brightness, and the measured value of the redness of the skin and / or the measured value of the amount of sebum of the skin. Use the value. Thereby, wrinkles on the skin can be evaluated more easily and more accurately.

Further, in the wrinkle evaluation method of the present invention, as described above, in the wrinkle prediction model, the subject's "age value", "skin brightness measurement value", "skin redness measurement value", and "skin redness measurement value" are used. By using a value of 2 or more selected from "measured value of the amount of sebum on the skin", the current index value (wrinkle grade) of wrinkles can be estimated. Separately, the values for predicting the future wrinkle condition of the subject (“age”, “skin brightness”, “skin redness”, “skin sebum amount”) are appropriately selected and selected. By using the value for predicting future wrinkles, the future wrinkle reference value can be obtained. As the wrinkle prediction model for obtaining this future wrinkle reference value, the current wrinkle prediction model can be used.
Furthermore, by comparing and examining the current wrinkle reference value and the future wrinkle reference value (prediction), it is possible to propose skin care for the subject.

Using the past age of the subject and the measured values of the past skin condition at this time, the past wrinkle index value can be obtained as the wrinkle reference value in the same manner as described above. As a result, it is possible to propose skin care for the subject by comparing and examining these based on the current wrinkle index value, the past wrinkle index value, the future wrinkle standard value (prediction), and the like. When obtaining the past wrinkle index value, the past wrinkle prediction model may be used, or the current wrinkle prediction model may be used.

1-4-1. Predictor Factors for Wrinkle Prediction Model As the wrinkle prediction model, a wrinkle prediction model composed of specific wrinkle prediction factors is suitable.
The number of the specific wrinkle predictors is not particularly limited, but is preferably 2 to 5 (specifically 2, 3, 4, 5), more preferably 3 to 5, still more preferably 4 to 5, and more. More preferably, it is 5.

Examples of the specific wrinkle predictor include "age", "skin brightness", "skin redness", "skin sebum amount", "interaction term between sebum amount and skin redness" and the like. .. The interaction is preferably a multiplication interaction.

Of these, it is selected from these five wrinkle predictors of "age", "skin brightness", "skin redness", "skin sebum amount", and "interaction term between sebum amount and skin redness". Two or more are preferable.
Of these five wrinkle predictors, at least two wrinkle predictors (specifically, "age" and "skin brightness") have good wrinkle prediction accuracy, and thus the wrinkles of the present invention. It is important in the prediction model. Therefore, in the wrinkle evaluation method of the present invention, a wrinkle prediction model composed of wrinkle predictors containing at least these two is preferable. By using the subject's "age value" and "skin brightness measurement value" for the wrinkle prediction model, the wrinkle index value can be obtained easily and more accurately.

Furthermore, the two wrinkle predictors (specifically, "age" and "skin brightness") are associated with "skin redness", "skin sebum amount", and "skin oil amount and skin redness". A wrinkle prediction model including one or more wrinkle predictors selected from the group consisting of "terms" and composed of these wrinkle predictors is more preferable from the viewpoint of more accurate wrinkle evaluation.
More specifically, two wrinkle predictors of "age" and "skin brightness", and one or two wrinkle predictors of "skin redness" and / or "skin sebum amount". A wrinkle prediction model composed of is more preferable. In the wrinkle prediction model composed of the three or four, the subject's three or four values (specifically, "age value", "skin brightness measurement value", and "skin redness" By using "measured value of" and "measured value of sebum amount of skin"), the wrinkle index value can be obtained easily and more accurately.

Further, in the wrinkle prediction model of the present invention, the above five wrinkle predictors (specifically, "age", "skin brightness", "skin redness", "skin sebum amount", and "sebum amount" A wrinkle prediction model composed of "skin redness interaction term") is even more preferable from the viewpoint of particularly good wrinkle prediction accuracy. The wrinkle prediction model includes the subject's values (subject's "age value", "skin brightness measurement value", "skin redness measurement value", "skin sebum amount measurement value"). By using four, the wrinkle index value can be obtained easily and more accurately.

In the wrinkle prediction model of the present invention, wrinkle predictors other than the above-mentioned five wrinkle predictors (for example, skin water content, transecutaneous water evaporation amount, etc.) are included in the configuration of the wrinkle prediction model of the present invention. However, as described above, from the viewpoint of wrinkle prediction accuracy, the wrinkle prediction model using the above five wrinkle prediction factors is the best model.

Examples of the formula for the wrinkle prediction model of the present invention (hereinafter, also referred to as “wrinkle prediction formula”) include, but are not limited to, wrinkle prediction formulas 1 to 7, which will be described later.
Of the wrinkle prediction formulas 1 to 7, the wrinkle prediction formula 1 and the wrinkle prediction formula 2 are preferable because the wrinkle prediction accuracy is better and can be used as a standard for the target person, and further, the wrinkle prediction formula is suitable. Equation 1 is more suitable because the wrinkle prediction accuracy is better.

<Wrinkle prediction formula 1 (Formula 1)>

Wrinkle grade _i = 0.1469 × Age
＋ 0.7540 × Ln (sebum) 
＋ 0.3270 × Skin color a *
＋ 0.1654 × Mean [Skin color L *]
－ 0.1044 × [Ln (sebum) × Skin color a *]
－ 15.90
＋ b _{0, i}
(Equation 1)
b _{0, i} ~ N (0, 0.4847)
Final equation for prediction of wrinkle grade in Japanese women aged 22-60 years

<Wrinkle prediction formula 2 (Formula 2)>

Wrinkle grade _i = 0.1200 ～ 0.2053 × Age
＋ 0.2200 ～ 1.280 × Ln (sebum) 
＋0.050 ～ 0.5710 × Skin color a *
＋ 0.050 ～ 0.4000 × Mean [Skin color L *]
－ 0.030 ～ 0.1800 × [Ln (sebum) × Skin color a *]
－ 25.00-7.600
(Equation 2)

In the method of the present invention, by performing each step of the present invention, the index value of wrinkles on the skin of the subject can be estimated, and this index value is a "wrinkle grade standard table" visually by a professional evaluator. Since it has a high correlation with the sensory evaluation of, it can be used as an evaluation value of skin wrinkles to the same extent as the "wrinkle grade standard table".
Therefore, a subject selects two or more from the group consisting of measured values of age, skin color (brightness, redness), and measured values of sebum amount, and applies them to the wrinkle prediction model or wrinkle prediction formula of the present invention. By doing so, the index value of the skin wrinkles of the subject can be estimated, and further, the skin wrinkles can be evaluated based on the index value.
Therefore, the wrinkle evaluation method of the present invention can easily and accurately provide an index value of wrinkles having a high positive correlation with the wrinkle evaluation derived by a professional evaluator according to the "wrinkle grade standard table". can.

With the method of the present invention, device evaluation by a skin condition measuring device such as a measuring device or an imaging device can be used without relying on sensory evaluation, so that evaluation of skin wrinkles can be performed more easily, more accurately, and more. It can be evaluated objectively. Therefore, it is possible to reduce the decrease in the accuracy of wrinkle evaluation due to the skill level of the measurer and the difference between individuals. Furthermore, by using the wrinkle prediction model of the present invention, the index value of future wrinkles for each individual can be easily and accurately predicted. Furthermore, it will be possible to propose skin care for this future wrinkle.

The method for evaluating skin wrinkles in the present invention may be used for non-therapeutic purposes, or the evaluation results may be finally utilized for therapeutic purposes. The present invention can be applied not to the direct medical practice of a doctor, but to, for example, a method of assisting the diagnosis of wrinkles on the skin. Here, the "non-therapeutic purpose" is a concept that does not include a medical practice, that is, a treatment action on the human body by treatment, and the non-therapeutic purpose includes, for example, a cosmetic purpose, provision of a skin care product, and the like. An advantage of the present invention is that the above-mentioned measurement of age and skin condition can be evaluated or measured by a device such as a measuring device or an imaging device without a doctor performing any of the above-mentioned measurements.
In the present invention, "prevention" means preventing or delaying the onset of a symptom or disease in an application target, or reducing the risk of developing a symptom or disease in an application target. In the present art, "improvement" means improvement or maintenance of a disease, symptom or condition in an application; prevention or delay of exacerbation; reversal, prevention or delay of progression.

1-4-2. Method for Producing Wrinkle Prediction Model The wrinkle prediction model of the present invention can be produced according to the flow described later [Example], and an example thereof is shown below, but the wrinkle prediction model of the present invention is not limited thereto.
The number of participants in creating the wrinkle prediction model is, for example, 40 to 60, but is not limited to this. As the number of tests, participants will be evaluated for skin characteristics at least once a year. The test period is not particularly limited, but is preferably 4 to 6 years. As a test method, participants washed their face with a face wash to make their skin bare, and after acclimatizing for 30 minutes in an environment controlled at 20 to 22 ° C. and 50 ± 5%, the measured values of each skin condition were measured. obtain. A more specific test method can be carried out with reference to the description in [Example] below.
A generalized linear mixed-effects model can be used for statistical analysis for creating a wrinkle prediction model. The stepwise method based on the variable reduction method is used to select the wrinkle predictor, and the model with the minimum AIC (Akaike Information Criterion) is determined as the best model. A sensitivity analysis is performed using the obtained wrinkle predictors. It is preferable to use R ver.3.5.2 statistical software for the analysis, but the analysis is not limited to this as long as the statistical analysis for creating a wrinkle prediction model can be performed.

2. 2. Application example of the skin wrinkle evaluation method according to the present invention The skin wrinkle evaluation method, the skin wrinkle evaluation device, the skin wrinkle evaluation system, etc. according to the present invention can be described with reference to FIGS. 1 to 7. However, the present invention is not limited to these figures.
2-1. Skin wrinkle evaluation device and evaluation system It is also possible to realize the skin wrinkle evaluation method of the present invention by a control unit including a CPU (Central Processing Unit) in a skin wrinkle evaluation device (for example, a computer or the like). (See, for example, FIGS. 4-6). For example, the present invention causes a computer to execute a skin wrinkle evaluation method (wrinkle prediction model, wrinkle evaluation procedure, program, etc.) according to the present invention to perform a computer-based skin wrinkle evaluation method or skin wrinkle evaluation. It may be provided (see, for example, FIGS. 1 to 3, FIG. 7, etc.).
Further, the method of the present invention is stored as a program in a hardware resource including a recording medium (nonvolatile memory (USB memory, etc.), HDD, CD, DVD, Blu-ray (registered trademark) Disc, network server, etc.). It can also be realized by a control unit that discriminates the evaluation of wrinkles on the skin. Alternatively, by providing or using the control unit, it is also possible to provide a skin wrinkle evaluation system, an evaluation or search system for a wrinkle improving composition, or an apparatus thereof. The recording medium is preferably a computer-readable recording medium.

The device or system related to wrinkle evaluation includes an input unit such as a keyboard, a communication unit such as a network, an output unit such as a display, a storage unit such as an HDD, and a measurement unit that measures skin conditions such as the above-mentioned measuring device or imaging device. Can be provided. The device or system preferably includes an input unit, an output unit, and a storage unit, and more preferably includes a communication unit and / or a measurement unit.
The input unit can accept user operations by an operator who uses the wrinkle evaluation method. The input unit may include, for example, a mouse and / or a keyboard. Further, the display surface of the display device may be configured as an input unit that accepts touch operations.
The output unit can output the obtained wrinkle evaluation of the skin and information related thereto (for example, a table, a figure, an explanatory text, etc.). Examples of the output unit include, but are not limited to, a display device for displaying an image, a speaker for outputting sound, a printing device for printing on a printing medium such as paper, and the like.
The storage unit can store data input by the operator and data set in advance for wrinkle evaluation (for example, a wrinkle prediction model). The storage unit may include, for example, a recording medium.

Specific examples of the skin wrinkle evaluation device are not particularly limited as long as they are equipped with a CPU, but for example, a mobile terminal (for example, a notebook computer, a smartphone, a tablet terminal, etc.), a desktop computer, a server, or cloud computing. However, it is not limited to these. The skin wrinkle evaluation device is preferably a device further including a measuring unit, and for example, a mobile terminal equipped with a camera (for example, a Web camera) is preferable.

In addition, the wrinkle evaluation data such as the program related to the skin wrinkle evaluation method of the present invention, the wrinkle prediction model, the wrinkle evaluation result obtained by the wrinkle evaluation method, and the data for executing each step of the present invention can be obtained. It may be stored in a storage unit, a server, or a cloud located inside the device related to the wrinkle evaluation or outside the device.

<Example of hardware configuration of skin wrinkle evaluation device and evaluation system of the present invention>
The skin wrinkle evaluation device and evaluation system of the present invention can be carried out by utilizing a program and hardware. An embodiment of the computer 1 according to the embodiment of the present invention will be described below with reference to FIGS. 4 to 6, but the present invention is not limited thereto. As a component of the computer 1, at least a CPU can be provided, and one or two types selected from a RAM, a storage unit, an output unit, an input unit, a communication unit, a ROM, a measurement unit, and the like can be provided. Of these, it is preferable to include a RAM, a storage unit, an output unit, and an input unit, and further, it is preferable to include at least one communication unit, measurement unit, ROM, and the like. Each component is connected, for example, by a bus as a data transmission path (see FIG. 4).

The CPU is realized by a microcomputer, for example, and controls each component of the computer 1. As the CPU, for example, a control unit capable of performing data acquisition, data processing, determination of evaluation, and the like can be used. These data acquisitions and the like can be realized or executed by, for example, a program, and can function by reading this program by the CPU. The ROM can store control data such as programs and calculation parameters used by the CPU. The RAM can temporarily store, for example, a program executed by the CPU.

The storage unit can store various data, and can store all or part of the data related to the execution of the present invention. The data is not particularly limited, and examples thereof include personal data for each subject, wrinkle evaluation data, product proposal data, calculation parameters, programs, and the like. The storage unit can function as a database existing inside or outside the device. The storage unit can be realized by using, for example, a storage device.

The output unit is an individual for each target person, such as items that identify the target person (for example, name, reference number, etc.), age value of the target person, measured value of the skin condition of the target person, etc. for the operator or the target person. Data; wrinkle index value, wrinkle evaluation result, best wrinkle risk, future wrinkle prediction, wrinkle evaluation data such as charts such as these figures / tables / graphs or images of wrinkle parts;・ Information such as product proposal data such as display columns for single or multiple recommended products (product name, product image, etc.) such as "recommended items from the age" and "recommended items with a wider range" than these. Can be output. The output unit can output, for example, each measurement value input field (numerical value input, color scheme panel selection, etc.), each index value, wrinkle evaluation result, recommended product, etc. to the operator or the target person. The output unit can be realized by, for example, a display unit such as an LCD (Liquid Crystal Display) or an OLED (Organic Light-Emitting Diode).
In addition, the input unit can acquire information such as an item for specifying the target person, an age value of the target person, and a measured value of the skin condition of the target person, which is input by the operator or the target person. The input unit can be realized by, for example, a microphone, a touch sensor, a keyboard, a mouse, a camera, or the like. The input unit can acquire data for evaluating skin wrinkles from, for example, each measurement value input, each color scheme panel image selection, each level selection, each index value selection, and the like.

The communication unit may have a function of communicating via an information communication network by using communication technology such as Wi-Fi, Bluetooth (registered trademark), and LTE (LongTermEvolution). Computer example 1 may include a communication I / F (interface).

The computer 1 may be, for example, a PC (Personal Computer) 1a, a server 1b, a smartphone terminal 1c, a tablet terminal, a mobile phone terminal, a PDA (Personal Digital Assistant), a wearable terminal (HMD: Head Mounted Display, glasses). It may be a type HMD, a band type terminal, etc. (see FIG. 5). These may be standalone or may be connected via a network.

The program that executes the method of the present invention may be stored in a computer device or computer system other than the computer 1. In this case, the computer can use the cloud service that provides the functions of this program (see FIG. 5). Examples of this cloud service include SaaS (Software as a Service), IaaS (Infrastructure as a Service), and PaaS (Platform as a Service).

Furthermore, this program is stored using a recording medium that can be read by various types of computers and can be supplied to the computer. Computer-readable recording media include, for example, magnetic recording media (eg flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (eg magneto-optical disks), CompactDiscReadOnlyMemory (CD-ROM), CD-R. , CD-R / W, including semiconductor memory (eg, mask ROM, Programmable ROM (PROM), Erasable PROM (EPROM), flash ROM, Random Access Memory (RAM)). The program may also be supplied to the computer by various types of computer recording media.

In addition to this, the computer 1 can select the above-mentioned configuration or change it to another configuration as appropriate.

At the input unit of the computer 1, the operator or the subject has at least these two values, that is, the value of the subject's age and the measured value of the skin brightness, and the measured value of the redness of the skin and / or the skin oil. Enter data for one or two values of the quantity measurement. The control unit may select and input such data, and at this time, the control unit may access the storage unit and cause the storage unit to transmit data related to these data to the control unit. When inputting data, in addition to numerical input, select a color panel image from multiple color panel images, select a level from a level bar, etc., and select these images or levels to control based on these images or levels. Can obtain data such as age and each measured value.

For example, in the case of skin brightness, by selecting an image that most closely matches or has the same color as the subject's skin brightness from the brightness color scheme panel images, it is linked to the selected image data. The measured value of the existing brightness is used as the measured value data of the brightness of the subject. Similarly, in the case of skin redness, it is associated with the selected image by selecting an image that most closely resembles or has the same color as the subject's skin redness from the redness color scheme panel images. The measured value of redness is used as the data of the measured value of redness of the subject. Further, in the case of the amount of sebum on the skin, by selecting the level with a level bar or the like, the numerical value of the selected level is used as the data of the measured value of the amount of sebum of the subject.

Further, when the computer 1 is provided with one type or two or more types of measurement units, the data of each measured value may be transmitted from the measurement unit to the control unit and input. Further, the measured value data obtained by measuring the target person by the measuring device 2 existing outside the computer 1 may be transmitted to the computer 1 or the control unit thereof via the network and input (see FIG. 5). ).

Thereby, the computer 1 estimates the index value of the skin wrinkle of the subject from these data by using the skin wrinkle evaluation method of the present invention, obtains the wrinkle evaluation result of the subject, and manipulates this evaluation result. It can be provided as wrinkle information to a person or a target person.
Further, the computer 1 can output wrinkle evaluation data, personal data, etc. obtained based on the wrinkle evaluation result of the skin to the output unit. Further, the computer 1 may output a recommended product based on the skin wrinkle evaluation result to the output unit.

The computer 1 can output, for example, the wrinkle risk of the target person as the wrinkle evaluation data of the target person, and can provide this information to the operator or the target person. More specifically, for example, the current wrinkle risk and the best wrinkle risk pattern in the subject (eg, a graph of a linear function), the degree of reduction in the target's risk (eg, the subject's past, present, and future faces). Image) etc. can be output. Further, the computer 1 can output one or more recommended products (for example, cosmetics, external skin preparations, etc.) for the subject as recommended items. As items of "recommended items", "currently recommended items" for presenting products suitable for the current situation, "... switching items from the age of ..." for presenting suitable products in the future, target people "Recommended items with a wider range" can be mentioned to expand the range of product selection, but it is not limited to this, and the items of "Recommended items" output by the operator or the target person can be switched as appropriate. You can choose.

In computer example 1, the data of these results can be stored in the storage unit as personal data of the target person by associating or attaching to the data of the item that identifies the target person. As a result, the control unit can appropriately access the storage unit and use the data of these results in the storage unit for various purposes. The proposal or provision of the recommended product will be described later in "3. Method for evaluating or searching for a composition for improving wrinkles according to the present invention".

2-2. Example of skin wrinkle evaluation according to the present invention The procedure for skin wrinkle evaluation according to the present invention will be described more specifically, but the skin wrinkle evaluation of the present invention is not limited thereto. The description of the procedure for evaluating skin wrinkles can also be used as a description of the operation of the skin wrinkle evaluation method, the skin wrinkle evaluation device, and the evaluation system of the present invention.

In addition, the operator who evaluates wrinkles on the skin has various items such as the age value of the subject, the measured value of the brightness of the skin, and the items for identifying the subject (for example, name, identification number, etc.) at the input unit. You may enter the data of. As a result, these data are transmitted from the input unit to the control unit.
In addition, the data of the item (for example, name, reference number, etc.) that identifies the target person and the measured value of the skin condition of the target person and / or the data of the age are linked in advance in the storage unit by the input of the operator. It may be configured to be attached and stored. The control unit may be configured to control so that the data associated with the input specific item of the target person is transmitted from the storage unit to the control unit.

Further, when the measuring unit measures the skin condition of the subject, the measurement unit may be configured to transmit the measured value data to the control unit. At this time, the control unit may be configured to store these data together with the specific item of the target person in the storage unit.

2-2-1. Embodiments 1 and 2 relating to the evaluation of wrinkles on the skin of the present invention
In the first and second embodiments of the present embodiment, the skin of the subject is based on the four values of the age of the subject, the measured value of the brightness of the skin, the measured value of the redness of the skin, and the measured value of the amount of sebum of the skin. The index value of wrinkles can be estimated (see, for example, FIG. 1).

In step 101, four are transmitted to the control unit: a value of the age of the subject, a measured value of skin brightness, a measured value of skin redness, and a measured value of skin sebum amount.
In step 102, the control unit determines the skin of the subject based on the four values of the age of the subject, the measured value of the brightness of the skin, the measured value of the redness of the skin, and the measured value of the amount of sebum of the skin. Estimate the wrinkle index value. The control unit outputs an index value of wrinkles of the target person.

As the first embodiment 1a, these four values of the subject's age value, skin brightness measurement value, skin redness measurement value, and skin sebum amount measurement value, and a wrinkle prediction model (the following wrinkle prediction formula 1). ), The index value of wrinkles on the skin of the subject can be estimated (see, for example, FIG. 2).
As the present embodiment 2a, the index value of the wrinkles on the skin of the subject can be estimated in the same manner as in the present embodiment 1a except that the wrinkle prediction formula 1 is replaced with the wrinkle prediction formula 2 (for example, FIG. 2).

The wrinkle prediction formula 1 shown in the following formula 1 has five five elements: "age", "skin brightness", "skin redness", "skin sebum amount", and "interaction term between sebum amount and skin redness". It is a wrinkle prediction formula composed of wrinkle predictors.
In step 101a, the control unit uses the wrinkle prediction model (wrinkle prediction formula 1 below) to apply the subject's "age value", "skin brightness measurement value", "skin redness measurement value", and "skin redness measurement value". By substituting these four values of "measured value of the amount of sebum of the skin", the index value (wrinkle grade) of wrinkles can be estimated (see, for example, FIG. 2).
In step 102a, a wrinkle reference value can also be obtained based on a preset value for predicting the future wrinkle state of the subject and the wrinkle prediction formula 1 (see, for example, FIG. 2). The preset value is one, two, or three or more selected from the group consisting of age value, skin brightness value, skin redness value, and skin sebum amount value. Yes, the control unit can obtain the wrinkle reference value by substituting the selected value into the wrinkle prediction formula 1. The operator may appropriately substitute a value for predicting the future wrinkle state of the subject.
In step 103a, by comparing the wrinkle index value with the wrinkle reference value, it is possible to propose skin care for the subject.
Specifically, when the wrinkle index value is less than the wrinkle reference value, the time when the wrinkle reference value is reached is output to the subject as the start time of using the wrinkle improving composition. When the wrinkle index value is equal to or higher than the wrinkle reference value, an output is output to the subject to start using the wrinkle improving composition.
As described above, the operator can also propose skin care based on the wrinkle index value and the wrinkle reference value output from the control unit.

<Wrinkle prediction formula 1 (Formula 1)>

Wrinkle grade _i = 0.1469 × Age
＋ 0.7540 × Ln (sebum) 
＋ 0.3270 × Skin color a *
＋ 0.1654 × Mean [Skin color L *]
－ 0.1044 × [Ln (sebum) × Skin color a *]
－ 15.90
＋ b _{0, i}
(Equation 1)
b _{0, i} ~ N (0, 0.4847)
Final equation for prediction of wrinkle grade in Japanese women aged 22-60 years

<Wrinkle prediction formula 2 (Formula 2)>
The wrinkle prediction formula 2 shown in the following formula 2 has five formulas: "age", "skin brightness", "skin redness", "skin sebum amount", and "interaction term between sebum amount and skin redness". It is a wrinkle prediction formula composed of wrinkle predictors. The points that overlap with those already described in the first and first embodiments of the present embodiment will be omitted as appropriate.
By substituting these four values of "age", "skin brightness", "skin redness", and "skin sebum amount" of the subject into the wrinkle prediction model (wrinkle prediction formula 2), the wrinkles The index value (wrinkle grade) can be estimated (see, for example, FIG. 2). In addition, 4 of the preset values (“age value”, “skin brightness value”, “skin redness value”, “skin sebum amount value”) in the wrinkle prediction formula 2. A wrinkle reference value can also be obtained by substituting two values (see, for example, FIG. 2).
In the present embodiment 2a, similarly to the present embodiment 1a adopting the wrinkle prediction formula 1 described above, the future wrinkle state of the subject can be predicted, and skin care of the subject can also be proposed.

Wrinkle grade _i = 0.1200 ～ 0.2053 × Age
＋ 0.2200 ～ 1.280 × Ln (sebum) 
＋0.050 ～ 0.5710 × Skin color a *
＋ 0.050 ～ 0.4000 × Mean [Skin color L *]
－ 0.030 ～ 0.1800 × [Ln (sebum) × Skin color a *]
－ 25.00-7.600
(Equation 2)

2-2-2. Embodiment 3 relating to the evaluation of wrinkles on the skin of the present invention
As the third embodiment, it is possible to estimate the index value of wrinkles on the skin of the subject based on at least these two, the age of the subject and the measured value of the brightness of the skin (see, for example, FIG. 1). .. Although the figure of the step flow of the embodiment itself is omitted, the flow can be understood by referring to FIGS. 1 and 2.

In step 301, at least two values, an age value of the subject and a measured value of skin brightness, are transmitted to the control unit.
In step 302, the control unit estimates the index value of wrinkles on the skin of the subject based on the value of the age of the subject and the measured value of the brightness of the skin. The control unit outputs an index value of wrinkles of the target person.

As the present embodiment 3a, an index value of wrinkles on the skin of the subject is based on these two values of the age value of the subject and the measured value of the brightness of the skin and a wrinkle prediction model (wrinkle prediction formula 3 below). Can be estimated (see, for example, FIG. 2).
The wrinkle prediction formula 3 shown in the following formula 3 is a wrinkle prediction formula composed of two wrinkle prediction factors, "age" and "skin brightness". It should be noted that the parts that overlap with those already described in the above-described first to second embodiments will be omitted as appropriate.
In step 301a, the control unit substitutes these two values of the subject's "age value" and "skin brightness measurement value" into the wrinkle prediction model (wrinkle prediction formula 3 below). Therefore, the index value (wrinkle grade) of wrinkles can be estimated (see, for example, FIG. 2). Further, the wrinkle reference value can be obtained by substituting the two values of the preset values (“age value” and “skin brightness value”) into the wrinkle prediction formula 3 (“wrinkle reference value”). For example, see FIG. 2).
Similar to the above-described first to second embodiments, the future wrinkle state of the subject can be predicted, and skin care of the subject can be proposed.

<Wrinkle prediction formula 3 (Formula 3)>

Wrinkle grade _i = 0.1484 × Age
＋ 0.1844 × Mean [Skin color L *]
－ 14.80
(Equation 3)

2-2-3. Embodiment 4 relating to the evaluation of wrinkles on the skin of the present invention
As the fourth embodiment, it is possible to estimate the index value of wrinkles on the skin of the subject based on the three values of the age of the subject, the measured value of the brightness of the skin, and the measured value of the amount of sebum of the skin. Yes (see, for example, Figure 1). Although the figure of the step flow of the embodiment itself is omitted, the flow can be understood by referring to FIGS. 1 and 2.

In step 401, at least three values of the age value of the subject, the measured value of the skin brightness, and the measured value of the amount of sebum of the skin are transmitted to the control unit.
In step 402, the control unit estimates the index value of the skin wrinkles of the subject based on the three values of the age value of the subject, the measured value of the skin brightness, and the measured value of the sebum amount of the skin. .. The control unit outputs an index value of wrinkles of the target person.

As the present embodiment 4a, the target is based on these three values of the age value of the subject, the measured value of the skin brightness, the measured value of the sebum amount of the skin, and the wrinkle prediction model (wrinkle prediction formula 4 below). It is possible to estimate the index value of wrinkles on a person's skin (see, for example, FIG. 2).
The wrinkle prediction formula 4 shown in the following formula 4 is a wrinkle prediction formula composed of three wrinkle prediction factors of "age", "skin brightness", and "skin sebum amount". It should be noted that the parts that overlap with those already described in the above-described first to third embodiments will be omitted as appropriate.
In step 401a, the control unit uses the wrinkle prediction model (wrinkle prediction formula 3 below) to indicate the subject's "age value", "skin brightness value", and "skin sebum amount value". By substituting one value, the wrinkle index value (wrinkle grade) can be estimated. Further, by substituting the three values of the preset values (“age value”, “skin brightness value”, and “skin sebum amount value”) into the wrinkle prediction formula 4, the wrinkle prediction formula 4 is substituted. A wrinkle reference value can also be obtained (see, for example, FIG. 2).
Similar to the above-described first to third embodiments, the future wrinkle state of the subject can be predicted, and skin care of the subject can be proposed.

<Wrinkle prediction formula 4 (Formula 4)>

Wrinkle grade _i = 0.1504 × Age
＋ 0.1880 × Mean [Skin color L *]
＋0.044 × Ln (sebum)
－ 15.28
(Equation 4)

2-2-4. Embodiment 5 relating to the evaluation of wrinkles on the skin of the present invention
As the fifth embodiment, wrinkles on the skin of the subject are based on these four values of the age of the subject, the measured value of the brightness of the skin, the measured value of the amount of sebum of the skin, and the measured value of the redness of the skin. The index value of can be estimated (see, for example, FIG. 1). Although the figure of the step flow of the embodiment itself is omitted, the flow can be understood by referring to FIGS. 1 and 2.

In step 501, four transmissions are transmitted to the control unit: the age value of the subject, the measured value of the skin brightness, the measured value of the sebum amount of the skin, and the measured value of the redness of the skin.
In step 502, the control unit determines the skin of the subject based on the four values of the age of the subject, the measured value of the brightness of the skin, the measured value of the amount of sebum of the skin, and the measured value of the redness of the skin. Estimate the wrinkle index value. The control unit outputs an index value of wrinkles of the target person.

As the present embodiment 5a, these four values of the subject's age value, a measured value of skin brightness, a measured value of sebum amount of skin, and a measured value of redness of skin and a wrinkle prediction model (the following wrinkle prediction model). Based on the formula 5), the index value of the wrinkles on the skin of the subject can be estimated (see, for example, FIG. 2).
The wrinkle prediction formula 5 shown in the following formula 5 is a wrinkle prediction formula composed of four wrinkle prediction factors of "age", "skin oil content", "skin redness", and "skin brightness". It should be noted that the parts that overlap with those already described in the above-described first to fourth embodiments will be omitted as appropriate.
In step 501a, the control unit uses the wrinkle prediction model (wrinkle prediction formula 5 below) to indicate the subject's "age value", "skin sebum amount measurement value", "skin redness measurement value", and "skin redness measurement value". By substituting these four values of "measured value of skin brightness", the index value (wrinkle grade) of wrinkles can be estimated (see, for example, FIG. 2).
In addition, 4 of the preset values (“age value”, “skin sebum amount value”, “skin redness value”, “skin brightness value”) in the wrinkle prediction formula 5. A wrinkle reference value can also be obtained by substituting two values (see, for example, FIG. 2).
Similar to the above-described first to fourth embodiments, the future wrinkle state of the subject can be predicted, and skin care of the subject can be proposed.

<Wrinkle prediction formula 5 (Formula 5)>

Wrinkle grade _i = 0.1460 × Age
＋ 0.035 × Ln (sebum) 
＋ 0.013 × Skin color a *
＋ 0.1812 × Mean [Skin color L *]
(Equation 5)

2-2-5. Embodiment 6 relating to the evaluation of wrinkles on the skin of the present invention
As the sixth embodiment, wrinkles on the skin of the subject are based on these four values of the age of the subject, the measured value of the brightness of the skin, the measured value of the amount of sebum of the skin, and the measured value of the redness of the skin. The index value of can be estimated (see, for example, FIGS. 1 to 3). By using the two values of the age value of the subject and the measured value of the skin brightness in the wrinkle prediction model of the sixth embodiment, the index value of the wrinkles of the skin of the subject can be estimated. More specifically, in the sixth embodiment, it is determined whether the skin is light or dark based on the measured value of the skin brightness of the subject, and the state of the brightness of the skin of the subject (bright and dark). By classifying the cases according to the case and determining the evaluation of skin wrinkles in each case, it is possible to propose skin care suitable for the subject more accurately.
Although the parts that overlap with those already described in the first to fifth embodiments are omitted as appropriate, the configurations of the first to fifth embodiments can be appropriately applied.

<Determining whether the skin is light or dark>
In step 601 the control unit determines whether the subject's skin is light or dark based on the measured value of the skin brightness. Specifically, the control unit compares the measured value of the skin brightness of the subject with the reference value of the skin brightness. The reference value of the skin brightness can be appropriately set, for example, even if it is the average value of the skin brightness of a general human (preferably a female, particularly a yellow race (Mongoloid race)). good.
If the subject's skin brightness is equal to or higher than the skin brightness reference value (Yes), it is determined that the subject's skin is bright, and otherwise (that is, if it is less than the predetermined value) (No). ), The subject's skin can be determined to be dark (see, for example, FIG. 3).

<When the skin is light (S602 to S607)>
In step 602, when the control unit determines that the skin of the subject is bright (Yes), the wrinkle prediction formula 6 is selected.
When the subject has light skin, the control unit uses the wrinkle prediction formula 6 to indicate the subject's "age value", "skin redness measurement value", and "skin sebum amount measurement value". By substituting the three values, the wrinkle index value (wrinkle grade) can be estimated.

In step 603, the control unit can obtain a wrinkle reference value for bright skin based on the value for predicting the future wrinkle state and the wrinkle prediction formula 6 separately from step 602. Specifically, the value of each skin condition for predicting the future wrinkle condition of the subject can be selected, and the selected value can be substituted into the wrinkle prediction formula 6. The operator may input each value.

In step 604, apart from step 603, the control unit may obtain a standard skin wrinkle reference value based on the value for predicting the future wrinkle state and the wrinkle prediction formula 1 or wrinkle prediction formula 2. can. Specifically, using the wrinkle prediction formula 1 representing a standard human being, the value for predicting the future wrinkle state and the wrinkle prediction formula 1 in the same manner as in the above-described embodiments 1 and 2. Alternatively, a standard skin wrinkle reference value can be obtained based on 2. The operator may input each value.

If there is step 604, step 603 may be skipped. In this case, the control unit compares the wrinkle index value with the standard skin wrinkle reference value. If there is step 603, step 604 may be skipped. In this case, the control unit compares the wrinkle index value with the wrinkle reference value of bright skin.

In step 605, the control unit compares the bright wrinkle reference value and / or the standard wrinkle reference value with the wrinkle index value. This makes it possible to propose skin care for subjects with bright skin.
Specifically, in step 606, when the wrinkle index value is less than the wrinkle reference value, the time when the wrinkle reference value is reached for the subject is set as the start time of using the wrinkle improving composition. Output.
In step 607, when the wrinkle index value is equal to or higher than the wrinkle reference value, an output is output to the subject to start using the wrinkle improving composition.

From the prediction formulas 6 and 7, when the skin is light, there is a tendency for wrinkles to occur easily. Therefore, by adopting a bright wrinkle reference value, it is easy to prevent or improve wrinkles for a subject with bright skin.
As described above, the operator can also propose skin care based on the wrinkle index value and the wrinkle reference value output from the control unit.

<When the skin is dark (S608-S613)>
In step 608, when the control unit determines that the subject does not have light skin (No) (that is, the subject's skin is dark), the wrinkle prediction formula 7 is selected.
When the subject has dark skin, the control unit uses the wrinkle prediction formula 7 to indicate the subject's "age value", "skin redness measurement value", and "skin sebum amount measurement value". By substituting the three values, the wrinkle index value (wrinkle grade) can be estimated.

In step 609, the control unit can obtain a wrinkle reference value for dark skin based on the value for predicting the future wrinkle state of the subject and the wrinkle prediction formula 7 separately from step 608. Specifically, the value of each skin condition for predicting the future wrinkle condition of the subject can be selected, and the selected value can be substituted into the wrinkle prediction formula 7. The operator may input each value.

In step 610, the control unit can perform the same operation as step 603 described above separately from step 609 to obtain a standard skin wrinkle reference value.

If there is step 609, step 610 may be skipped. In this case, the control unit compares the wrinkle index value with the standard skin wrinkle reference value. If there is step 610, step 609 may be skipped. In this case, the control unit compares the wrinkle index value with the wrinkle reference value of bright skin.

In step 611, the control unit compares the dark wrinkle reference value and / or the standard wrinkle reference value with the wrinkle index value. This makes it possible to propose skin care for subjects with dark skin.
Specifically, in step 612, when the wrinkle index value is less than the wrinkle reference value, the time when the wrinkle reference value is reached for the subject is set as the start time of using the wrinkle improving composition. Output.
In step 613, when the wrinkle index value is equal to or higher than the wrinkle reference value, an output is output to the subject to start using the wrinkle improving composition.

From the prediction formulas 6 and 7, when the skin is light, there is a tendency for wrinkles to occur easily. Therefore, by adopting a standard wrinkle reference value, it is easy to prevent or improve wrinkles for a subject with dark skin.
As described above, the operator can also propose skin care based on the wrinkle index value and the wrinkle reference value output from the control unit.

The wrinkle prediction formula 6 that can be applied to the subject with light skin is the "age", "skin redness", "skin sebum amount", and "interaction term between sebum amount and skin redness". It is desirable to consist of four wrinkle predictors. On the other hand, when the subject has dark skin, it is desirable that the wrinkle prediction formula 7 is composed of three wrinkle predictors of "age", "skin redness", and "skin sebum amount". When using these wrinkle prediction formulas, it is desirable that the subject has a value of "age" and a measured value of "skin lightening", "skin redness", and "skin sebum amount" at that age. ..
Each wrinkle prediction formula is <1-4-2. It can be obtained by the method for producing a wrinkle prediction model>, and can also be obtained by using the data obtained in Test Example 1 described later [Example].

3. 3. Method for evaluating or searching for a wrinkle-improving composition according to the present invention Hereinafter, an embodiment of the method for evaluating or searching for a wrinkle-improving composition of the present invention will be described. In the description of the present embodiment, the description of each configuration, the evaluation method, etc. that overlaps with the above-mentioned "1." and "2." will be omitted as appropriate, but the description of the "1." and "2." It also applies to the form and can be adopted as appropriate. In this embodiment, the above-mentioned skin wrinkle evaluation and wrinkle prediction model (for example, wrinkle prediction formulas 1 to 7) can be appropriately adopted.

The present invention uses the wrinkle evaluation method described in "1." and "2." above to estimate the wrinkle index value of the skin of the subject to whom the test substance is administered, and the estimated subject. A method for evaluating or searching for a wrinkle-improving composition, which comprises a step of determining a test substance for wrinkle-improving when the skin wrinkle index value of the subject is lower than the skin wrinkle index value of a subject before administration. Can be provided.
As a result, the wrinkle index value of the subject can be estimated easily and accurately, so that the wrinkle improving composition suitable for each subject can be evaluated or searched more easily and accurately. In the method for evaluating or searching for a composition for improving wrinkles of the present invention, it is preferable to use the mobile terminal with a camera of the present invention because it is possible to continuously record finely and it is also convenient.

The test substance is not particularly limited, but may be a commercially available product commercially available as a composition for preventing, improving or treating wrinkles. Even if it is a commercially available product, the degree of efficacy varies between individuals. Therefore, according to the present invention, a commercially available product suitable for an individual can be selected. In addition, the test substance may be a new or known substance that can be expected to prevent, improve or treat wrinkles, whereby a more suitable substance for preventing, improving or treating wrinkles can be searched for and selected. can.
The administration may be either oral administration or parenteral administration (for example, injection, application, etc.), but application is preferable.
The administration time can be appropriately selected, and may be administered once a day, divided into multiple times a day, or once every few days or weeks. May be good.

Further, the present invention uses the wrinkle evaluation method described in "1." and "2." above to estimate the wrinkle index value of the skin of the subject, and the estimated wrinkle of the skin of the subject. It is possible to provide a method for providing a wrinkle improving composition, which comprises a step of discriminating a single or a plurality of wrinkle improving compositions based on an index value. Thereby, the wrinkle improving composition corresponding to the wrinkle index value can be discriminated, and the wrinkle improving composition suitable for the subject can be proposed or provided. Further, it is preferable to further include a step of outputting the determined wrinkle improving composition at the output unit. The operator may propose or provide the output wrinkle improving composition to the subject, or the control unit may perform it.

The composition for improving wrinkles may be a composition for preventing wrinkles or treating wrinkles, and may be a commercial product without particular limitation.
In the data of each wrinkle improving composition, the data of the wrinkle index value of the skin corresponding to each wrinkle improving composition may be associated with or attached to the specific data. The corresponding skin wrinkle index value can be obtained based on the known efficacy of the wrinkle improving composition or based on the result of the evaluation or searching method for the wrinkle improving composition of the present invention. For wrinkle improvement corresponding to the wrinkle state (for example, wrinkle index value, wrinkle grade, etc.) of the subject's skin by associating or attaching the data of the wrinkle index value of the skin corresponding to the data of the composition for wrinkle improvement. The composition can be searched more easily and accurately, and the searched information on the wrinkle-improving composition can be provided more easily and accurately to the subject. Thereby, it is possible to propose or provide information on a wrinkle improving composition more suitable for the wrinkle condition of the skin of the subject.

Further, the data of each wrinkle improving composition may be grouped by a predetermined range based on the wrinkle index value data of the skin that can be dealt with by each wrinkle improving composition. The control unit may group based on the data of the corresponding wrinkle index values attached to the data of each wrinkle improving composition. Grouping by predetermined range can be performed according to the division of the wrinkle grade standard table, for example, wrinkle grades 3 to 4: wrinkle improving compositions A, B, C, etc., wrinkle grades 4 to 5: wrinkle composition. Wrinkle grades 5 to 6: wrinkle improving compositions G, H, i, J and the like, wrinkle grades 6 to 7: wrinkle improving compositions O and P, etc., and data of each composition. May be attached with data of a wrinkle index value (for example, 4.5 or 6.7) that can be dealt with. The interval for each predetermined range is not particularly limited, and may be an interval of 1 or 0.5, for example, in 8 steps of 0, 1, 2, 3, 4, 5, 6, and 7. There may be. By grouping, it is possible to propose or provide information on a single group or a plurality of groups including a composition for improving wrinkles corresponding to the wrinkle state of the skin of the subject to the operator or the subject more easily and accurately. ..
Various data related to the wrinkle improving composition such as wrinkle improving composition data, compatible wrinkle index value data, and group data may be stored in the storage unit.

Further, the wrinkle improving composition proposed or provided to the operator or the target person may be a wrinkle improving composition corresponding to the current or future wrinkle grade of the target person. For example, the control unit may use a single or multiple wrinkle-improving compositions or groups equal to or higher than this (more preferably equivalent or one step higher) based on the wrinkle index value of the subject's skin. And can output, propose or provide to the operator or subject the information of the identified single or multiple wrinkle-relieving compositions or groups. The control unit can propose or provide the information of the identified wrinkle improving composition or group as the "currently recommended item" of the subject.

In addition, the control unit obtains the future skin wrinkle index value of the subject based on the skin wrinkle index value and the wrinkle prediction model of the subject, and in the same manner as before, the future skin wrinkle index value of the subject. Based on, the information of the wrinkle improving composition or group equal to or higher than this future wrinkle index value (more preferably equal to or one step higher) is used as the future wrinkle improving composition. It can be output, proposed or provided to the operator or the target person. The control unit can use the identified wrinkle-improving composition or group as a "future recommended item" such as a "... switching item from the age of" of the subject. In addition, the control unit further raises the stage from one step above to one step below for "equal to or higher than the wrinkle index value of the skin of the subject (more preferably equivalent or one step higher than that)". By expanding the range of stages, the range of information on the wrinkle-reducing composition proposed or provided can be expanded, and the number of products can be increased. As a "recommended item", it can be proposed or provided to the operator or the target person.

Hereinafter, a method for providing a composition for preventing, improving or treating wrinkles using the wrinkle prediction model of the present invention is shown as Example 1 and Example 2. As the wrinkle prediction model, the wrinkle prediction model or the wrinkle prediction formula of the above "1." and "2." can be appropriately used.

<Example 1>
In step 701, the control unit inputs four values of the subject's skin, a measured value of brightness, a measured value of redness, and a measured value of sebum amount, into the wrinkle prediction model. As a result, the wrinkle prediction formula a for one individual subject can be set.
In step 702, the control unit inputs a value of the age of the target person into the wrinkle prediction formula a, so that the index value of the current wrinkle of the target person is output. This allows the operator or the target person to understand the current wrinkle risk (wrinkle grade) of the target person.
In step 703, the control unit can output the wrinkle reference value and the age at this time by inputting the wrinkle grades 3 to 5 as the best wrinkle risk value in the wrinkle prediction formula a. The lower the wrinkle grade setting, the better the wrinkle risk.
The output is not particularly limited to screen display, audio display, and the like. Further, the operator of the wrinkle prediction model is not particularly limited to a product salesperson, a counselor, an operator, a target person, and the like.

If there is a numerical input field on the input screen, the operator will be responsible for the data of the measured values of each skin condition of the subject (measured value of brightness, measured value of redness, measured value of sebum amount). It may be obtained by inputting a measured value in a numerical value input field. In addition, if the input screen has an input field for selecting the image of the color scheme panel or the level, the operator or the target person has the same or similar to the skin condition of the target person from the images or levels of the multiple color scheme panels. By selecting the color scheme panel or level to be used, each measured value data associated with or attached to each of these data is selected by the control unit, whereby the control unit may obtain the measured value data. When selecting the color scheme panel, the operator may select a color scheme panel or the like that is the same as or similar to the skin condition of the subject by visual comparison with the skin condition or the captured image data, or the control unit captures the image. A color scheme panel that is the same as or most similar to the color tone of the image data of the subject's skin may be selected.

In step 704, when the index value of the current wrinkle of the subject is equal to or higher than the wrinkle reference value (Yes), the control unit compares it with the efficacy of the wrinkle improving composition currently used by the subject. However, one or more of the recommended wrinkle improving compositions having stronger efficacy are output.
In step 705, when the current wrinkle index value of the subject is not greater than or equal to the wrinkle reference value (No) (that is, less than the wrinkle reference value), the control unit is best based on the wrinkle prediction model a. Outputs the expected age when reaching the wrinkle grade (3 to 5) set as the wrinkle risk value of. Output one or more wrinkle-reducing compositions recommended for use after this expected age.

<Example 2>
In step 801 the control unit inputs three values, a measured value of the skin brightness of the subject, a measured value of the redness of the skin, and a measured value of the amount of sebum of the skin, into the wrinkle prediction model. This makes it possible to set the wrinkle prediction formula b for one individual subject.
In step 802, the control unit outputs one or more wrinkle improving compositions capable of dealing with the current wrinkle grade, in addition to the wrinkle improving agent currently used, while outputting the current wrinkle index value. Output.

<Example 3>
From the image (image, video, etc.) on which the operator selects the color scheme panel or level of each skin condition (measured value of brightness, measured value of redness, measured value of sebum amount) of the subject on the input screen. Select a color scheme panel or level that is the same as or similar to the subject (see Figure 6). Further, the control unit may obtain measured value data of each skin condition of the subject based on personal data such as image data of the subject. The age value of the target person may be directly input by the operator or may be read by the control unit from personal data. Based on the selected color scheme panel or level (for example, the measured value data associated with the data of the color scheme panel), the control unit can obtain the data of each measured value corresponding to these.

In step 901, the control unit can input four values of the subject's skin, a measured value of brightness, a measured value of redness, and a measured value of sebum amount, into the wrinkle prediction model. As a result, the wrinkle prediction formula a for one individual subject can be set.

In step 902, the control unit inputs the age value of the target person into the wrinkle prediction formula a, so that the index value of the current wrinkle of the target person is output. As a result, the control unit can output or provide the current wrinkle risk (wrinkle grade) of the target person to the operator or the target person.

In step 903, the control unit can output the wrinkle reference value and the age at this time in the same manner as in step 703 of the above <Example 1>. Further, as shown in FIG. 6, the wrinkle risk of the subject can be output as the wrinkle evaluation data of the subject. For example, the output of the current wrinkle risk and the best wrinkle risk pattern in the subject, and the present and future facial images of the subject showing the degree of reduction of the risk aimed at by the subject.

In step 904, the control unit attaches or attaches a wrinkle index value equal to or higher than the wrinkle index value equal to or higher than the current wrinkle index value of the subject to a single or a plurality of wrinkle improvement compositions. The determined and identified wrinkle improving composition or group can be output to the output unit to the operator or the target person as a recommended item to be proposed or provided. The control unit can allow the operator or the target person to select one or more wrinkle-improving compositions from the recommended items output to the input unit, whereby the control unit can select the selected wrinkle-improving composition. The composition can be provided to the target person as a product by selling or shipping.

Example 3 of the present invention can also provide the following configurations.
The present invention estimates a subject's skin wrinkle index value based on the subject's age value, skin brightness measurement value, skin redness measurement value, and sebum amount measurement value. , The process of estimating the wrinkle index value of the subject's skin, and
Provided is a method for providing information on a wrinkle improving composition suitable for a subject, including a step of determining a wrinkle improving composition suitable for the subject based on the estimated wrinkle index value of the skin of the subject. can do.

It is preferable that the data of the wrinkle improving composition is associated with or attached to the data of the wrinkle index value of the corresponding skin, and the data of the wrinkle index value of the corresponding skin is selected. As a result, the control unit can determine the wrinkle improving composition or the group suitable for the subject.
Further, it is preferable that the output unit further outputs, proposes, or provides information on the identified single or a plurality of wrinkle improving compositions or the group thereof.

Prior to the estimation step, a color scheme panel that is the same as or similar to the skin brightness of the subject is selected, so that the measured value data of the skin brightness associated with the data of the color scheme panel is selected. By using the selected measurement value data as the measurement value of the skin brightness and / or selecting a color arrangement panel that is the same as or similar to the redness of the subject's skin, it is linked to the data of the color arrangement panel. It is more preferable that the attached skin redness measurement value data is selected, and the selected measurement value data is used as the skin redness measurement value.

4. Evaluation System for Wrinkle Prediction An embodiment of the evaluation system for wrinkle prediction of the present invention will be described below. In the description of the present embodiment, the description of each configuration, the evaluation method, etc. that overlaps with the above-mentioned "1." to "3." will be omitted as appropriate, but the description of the "1." to "3." It also applies to the form and can be adopted as appropriate.

In the skin wrinkle evaluation system of the present invention, the wrinkle prediction model of the subject can be derived by applying the measured values of the age and skin condition of the subject to the wrinkle prediction model.
Further, the control unit can estimate the wrinkle index value of the skin of the subject based on the actual age of the subject.
On the other hand, by setting the future age of the subject, the control unit estimates this future wrinkle index value. The future age may be the age desired by the subject, or may be the actual age of the subject + α-year or the like and a future age preset in the memory unit or the like. This makes it possible to predict the wrinkle condition of the subject in the future.

Further, in the same wrinkle prediction model, the control unit can determine when to start using the composition for improving wrinkles by comparing the wrinkle index value with the set wrinkle reference value.

Further, the control unit preferably compares the wrinkle index value with the wrinkle grade "3 to 5" of the set wrinkle reference value, whereby the control unit uses the composition for improving wrinkles. The start time can be determined.

The wrinkle reference value to be set may be stored in advance in a storage unit or the like and set.
The control unit can estimate the wrinkle index value from the actual age of the subject using the wrinkle prediction model. On the other hand, the control unit can estimate the age of the subject when the set wrinkle reference value, for example, "3 to 5", is estimated by using the same wrinkle prediction model, and is estimated from this reference value. Determine the age as the time to start using the wrinkle improving composition.

Further, when the wrinkle index value estimated by the wrinkle prediction model reaches a preset wrinkle reference value, the control unit determines the age at which the wrinkle index value is reached as the start time of use of the wrinkle improving composition. be able to.

It is preferable that the measured value is a measured value by a measuring device or a measuring device for a skin condition such as an imaging device (for example, a digital camera, a video camera, a moving image, a still image). As a result, it is possible to reduce the variation in the measured value caused by the measurer.

The wrinkle evaluation system of the present invention is
Determining that the wrinkle index value estimated by the prediction model has reached the preset wrinkle reference value,
It is preferable to include determining the age at which this is reached as the time to start using the composition for improving wrinkles.
More preferably, the preset wrinkle reference value is a standard wrinkle reference value of the same age of the subject + 5 years old.

5. Evaluation Program for Wrinkle Prediction Hereinafter, embodiments of the evaluation system for wrinkle prediction of the present invention will be described. In the description of the present embodiment, the description of each configuration, the evaluation method, etc. that overlaps with the above-mentioned "1." to "4." will be omitted as appropriate, but the description of the "1." to "4." It also applies to the form and can be adopted as appropriate.
A function to input the age value of the subject and the measured value of the skin condition,
A skin wrinkle evaluation program that realizes a function of estimating an index value of skin wrinkles of a subject by using the age value and the measured value of the skin condition in a wrinkle prediction model, and a computer.

A function to input the age value of the subject and the measured value of the skin condition,
The function of estimating the index value of wrinkles on the skin of the subject by using the value of the age and the measured value of the skin condition in the wrinkle prediction model, and
By comparing the estimated wrinkle index value with the preset wrinkle reference value,
When the estimated wrinkle evaluation value reaches a preset wrinkle reference value, the function of determining the age at which the estimated wrinkle evaluation value is reached as the start time of use of the wrinkle improving composition, and
A skin wrinkle evaluation program that makes a computer realize.

6. Trained model according to the present invention Hereinafter, embodiments of the trained model according to the present invention will be described. In the description of the present embodiment, the description of each configuration, the evaluation method, etc. that overlaps with the above-mentioned "1." to "5." will be omitted as appropriate, but the description of the "1." to "5." It also applies to the form and can be adopted as appropriate. Further, in the present embodiment, the above-mentioned skin wrinkle evaluation and wrinkle prediction model (for example, wrinkle prediction formulas 1 to 7) can be appropriately adopted.
The wrinkle prediction model used in the present invention may be a wrinkle prediction model generated by a method for generating a trained model, and the above-mentioned explanation of "1-4-2. Method for producing a wrinkle prediction model" is adopted. It is preferable to do so.

To briefly show an example of the processing procedure of the specialized AI used as the trained model in the present invention, "(1) training data-> (2) algorithm-> (3) trained model""(4) input data-> (3) Trained model → (5) Result product ”, but is not limited to this (see, for example, FIG. 7). The specialized AI is a large framework in which the result is obtained by applying arbitrary input data to a trained model constructed by incorporating training data (teacher data) into an algorithm that functions as a learning program. It is a mechanism that can be obtained.

In the present invention, the subject in the learning data (teacher data) can include the participants in the above-mentioned "1-4-2. Method for producing a wrinkle prediction model".
The control unit acquires at least two values, a value of the age of the subject and a measured value of the brightness of the skin, as learning data (teacher data) for a plurality of people as data. It is preferable that at least two values, an age value of the same subject and a measured value of skin brightness, are set as one data set. As the teacher data, for example, the above "1-4-1. Predictor factor of wrinkle prediction model" can be adopted, and age, skin brightness, skin redness, skin sebum amount, sebum amount and skin. Two or three or more selected from the redness interaction term and the like are preferable.
It is more preferable that the control unit further acquires the two values and one or two values of the measured value of redness of the skin and / or the measured value of the amount of sebum of the skin as data. The control unit can read out the teacher data selected from these two or more from the storage unit. In addition, the storage unit stores the age value and the measured value acquired from a plurality of subjects as data in advance.

Next, the control unit can construct a wrinkle prediction model (learned model) by incorporating the learning data read from the storage unit into a preset algorithm. As a result, the control unit has a configuration having a wrinkle prediction model. As explained in "1-4. Wrinkle prediction model", a trained model (wrinkle prediction model) can be obtained by using "statistical analysis".

The above-mentioned algorithm can function as, for example, a machine learning algorithm. The type of machine learning algorithm is not particularly limited, and is an algorithm using a neural network such as RNN (Recurrent Neural Network), CNN (Convolutional Neural Network) or MLP (Multilayer Perceptron). It may be any algorithm.

Next, the control unit relates to the wrinkle evaluation for outputting from the display by inputting the input data from the operator ((4) input data (input layer) into the constructed wrinkle prediction model (trained model)). Data ((5) result (output layer)) can be generated.
The trained model may be, for example, a trained model generated by deep learning. For example, the trained model may be a multi-layer neural network, for example, a deep neural network (DNN), and more specifically, a convolutional neural network (CNN). You may. A multi-layer neural network may be used as the trained model, and the multi-layer neural network includes an input layer for inputting an age value and a measured value by the subject, an output layer for outputting the wrinkle evaluation result of the subject, and the like. It may have at least one intermediate layer provided between the input layer and the output layer.

The control unit can realize the following method of generating a trained model, a method of evaluating skin wrinkles for a subject using the trained model, or a method of providing an evaluation of skin wrinkles.
(A) Acquiring a plurality of teacher data including at least these two values of the age value of the subject and the measured value of the skin brightness, and (b) each subject using the teacher data. Enter at least these two values, the age value of the person and the measured value of the skin brightness, and (c) the wrinkle prediction for estimating the index value of the skin wrinkles of the subject from these input data. A trained model generation method, including generating a trained model that outputs a model.

(D) Obtaining at least these two values of the subject's age value and the measured value of the skin brightness as data, and (e) measuring the subject's age value and the skin brightness. At least these two values of the age value of the subject and the measured value of the skin brightness with respect to the trained model generated by the trained model generation method using at least these two values. By applying the above, an index value of skin wrinkles estimated by the subject is generated, and (f) a method of using the generated index value as an evaluation of skin wrinkles or a method of providing the index value as an evaluation of skin wrinkles. ..
A program for causing a computer to execute the method for evaluating skin wrinkles or the method for evaluating skin wrinkles, or a recording medium for storing the program. A skin wrinkle evaluation device or a skin wrinkle evaluation system including the program or the recording medium.

The present technology can also adopt the following configurations.
[1] A skin wrinkle evaluation method or a skin wrinkle evaluation method for estimating an index value of skin wrinkles of a subject based on at least these two values of a subject's age value and a measured value of skin brightness. A method of providing an assessment of wrinkles on the skin.
The method described in [1] above is selected from the operator, the provider of the evaluation result to a third party, the target person, the end user, the product purchaser, the person in the business (counselor, operator, product salesperson, etc.). It is preferable to use one kind or two or more kinds. The method according to [1] may be a method for assisting the evaluation of wrinkles on the skin, which comprises presenting, displaying or providing the estimation result of the index value of the wrinkles. The method described in [1] above may be a method of causing a computer to execute the method.

[2] Estimate the index value of skin wrinkles of the subject based on the above two values and one or two values of the measured value of redness of the skin and / or the measured value of the amount of sebum of the skin. , The evaluation method or the evaluation providing method according to the above [1].
[3] The index value of wrinkles on the skin of the subject is estimated by using two values, the age value of the subject and the measured value of the skin brightness, in the wrinkle prediction model. The evaluation method described or the method of providing the evaluation.
[4] In the wrinkle prediction model, two values of the subject's age and skin brightness, and one or two of the skin redness measurement and / or the skin oil content measurement. The evaluation method or the method for providing an evaluation according to the above [2], which estimates an index value of wrinkles on the skin of a subject by using the two values.
[5] The wrinkle prediction model shall be derived using a linear mixed effect model in which the wrinkle index value of one individual is used as the objective variable and the measured values of the age and skin brightness of the individual are included in at least the explanatory variables. The evaluation method or the method for providing the evaluation according to the above [3] or [4], which is the model obtained by the above.
[6] The method for providing the evaluation method or evaluation according to the above [5], wherein the parameters of the linear mixed-effects model are obtained by using the maximum likelihood method or the limited maximum likelihood method.
[7] A step of estimating the wrinkle index value of the skin of a subject to whom the test substance is administered by using the wrinkle evaluation method according to any one of the above [1] to [6], and the estimation thereof. A method for evaluating or searching for a composition for improving wrinkles, which comprises a step of determining a test substance for wrinkle improvement when the wrinkle index value of the skin is lower than the wrinkle index value of the skin of a subject before administration. , Or a method of providing evaluation or search results.
[8] The wrinkle index value of the skin of the subject, which estimates the index value of the wrinkle of the skin of the subject based on at least these two values of the age value of the subject and the measured value of the brightness of the skin. A method for providing information on a wrinkle-improving composition suitable for a subject, which comprises a step of estimating the wrinkle and a step of determining a wrinkle-improving composition based on the estimated wrinkle index value of the skin of the subject. The estimation step may be estimated using the wrinkle evaluation method according to any one of the above [1] to [6].

[9] A skin wrinkle evaluation device that causes a computer to execute the method for evaluating skin wrinkles or the method for providing skin wrinkle evaluation according to any one of the above [1] to [6]. The wrinkle evaluation device is configured to perform any one of the above methods [1] to [6], (a) a skin wrinkle evaluation program, and / or (b) a recording of the program. Alternatively, it is preferable to have a stored recording medium. It is preferable that the wrinkle evaluation device accesses the program or the medium existing outside the device to execute the method according to any one of the above [1] to [6]. The recording medium may be a computer recording medium having instructions that can be executed by a computer.

[10] (a) Have a computer create a wrinkle prediction model using a trained model, and (b) use the obtained wrinkle prediction model to measure the age value of the subject and the brightness of the skin. A method for evaluating skin wrinkles or a method for providing skin wrinkle evaluation, which estimates an index value of skin wrinkles of a subject based on at least these two values. As the wrinkle prediction model, any one of the above [3] to [6] is suitable.
[11] Obtaining a plurality of teacher data including at least these two values, that is, the age value of the subject and the measured value of the skin brightness, are obtained.
A wrinkle prediction model that estimates the index value of wrinkles on the skin of a subject by inputting at least these two values, an age value of each subject and a measured value of skin brightness, using the teacher data. A trained model generation method that generates a trained model that outputs. It is preferable that the data further includes one or two values of the measured value of redness of the skin and / or the measured value of the amount of sebum of the skin.
-[12] Obtain at least these two values, the age value of the subject and the measured value of the skin brightness, as data.
Using teacher data, input at least these two values, the age value of each subject and the measured value of skin brightness, and output a wrinkle prediction model that estimates the index value of wrinkles on the skin of the subject. To the learning model trained by
A skin wrinkle evaluation method or a skin wrinkle evaluation method for estimating an index value of skin wrinkles of a subject based on at least these two values of a subject's age value and a measured value of skin brightness. How to provide a rating for. It is preferable that the data further includes one or two values of the measured value of redness of the skin and / or the measured value of the amount of sebum of the skin.
[13] A program for causing a computer to execute the method for evaluating skin wrinkles or the method for providing evaluation of skin wrinkles according to the above [11], or a recording medium for storing the program. A skin wrinkle evaluation device or a skin wrinkle evaluation system including the program and the recording medium.

Hereinafter, the present invention will be described in more detail based on test examples and the like. It should be noted that the test examples and the like described below show an example of a representative test example and the like of the present invention, and the scope of the present invention is not narrowly interpreted by this.

<Test Example 1: Wrinkle prediction model>
Test Example 1-1. Participants in the study A total of 48 Japanese females who participated in the wrinkle and skin condition evaluation study conducted from 2011 to 2013 at Kose Research Institute Co., Ltd. were selected as participants in this study. All subjects signed a written consent prepared by the Kose Laboratory under the Helsinki Convention.
This study was a repetitive study over time, and wrinkles and skin characteristics of participants were evaluated annually from 2011 to 2017. The age of participants (female) ranged from 22 to 60 years throughout the survey period. The age composition at the end of 2017 was 20s: 6 people, 30s: 15 people, 40s: 13 people, 50s: 13 people, 60s 1 person. Participants participated in the test up to 6 times, at least 3 times, and most of the subjects participated in the survey 5 times.

Test Example 1-2. Evaluation of wrinkles and evaluation of each device of skin condition Participants washed their face with the same facial cleanser, and after acclimatizing for 30 minutes in an environment controlled at 20 to 22 ° C and 50 ± 5%, the following All evaluations (wrinkles, cleansing water content, transepidermal water evaporation amount, sebum amount, skin color, etc.) were performed. Each evaluation other than the wrinkle evaluation was measured with a general measuring device and measuring site as described below.

The wrinkle condition of the participants is the guideline published by the Japan Cosmetic Industry Association (Journal of Japanese Cosmetic Science Society), "Cosmetic Function Evaluation Method Review Committee Report: Cosmetic Function Evaluation Method Guideline", According to Vol. 30, No. 4, pp.316-332 (2006).), A visual evaluation was carried out by a trained expert. According to the wrinkle grade standard table, the wrinkle condition of the right outer corner of the eye was evaluated as the wrinkle grade for every 0.25 points up to "0,1,2,3,4,5,6,7". In the wrinkle grade standard table, for example, in the case of grade 0, "no wrinkles" and in the case of grade 7, "significantly deep wrinkles are observed".
Participant's stratum corneum water content was indexed by the stratum corneum capacitance measured by using SKICON-200EX (manufactured by IBS) on the upper right cheek of the participant.
The transepidermal water loss was measured on the right cheek in the same manner using a Vapometer (manufactured by Delfin technologies).
The amount of sebum of the participants was measured using a Sebumeter (Courage + manufactured by Khazaka electronic GmbH) at the center of the forehead.
For the skin color of the participants, Spectrophotometer CM-700d (manufactured by KONICA MINOLTA) was used, and the L * value (index of brightness), a * value (index of redness), and b * value (index of redness) on the right cheek of the participants. The index of yellowness) was measured.

Test Example 1-3. Statistical analysis for wrinkle prediction model development The following wrinkle prediction models (Equations 1 to 7) were obtained using the data obtained in "Test Examples 1-1." And "Test Examples 1-2.".

In order to verify the model that predicts the wrinkle state due to aging, which is the main purpose of this study, we confirmed the distribution of the acquired wrinkle grades and the relationship between age and wrinkle grades.
Next, as candidates for wrinkle predictors, in addition to the skin condition measurements at all time points obtained by age and device evaluation, the average of all measurement points for each evaluation device is an important characteristic that indicates the individual's skin condition. Considering that it will be a value, we decided to add it to the wrinkle predictor.
In the prediction, we decided to avoid dividing into verification data and test data because the number of data is not large, and to use all the data. Furthermore, we decided to use a generalized linear mixed-effects model that can express unpredictable differences between individuals in time-repeated data as a variable effect.

The stepwise method based on the variable reduction method (algorithm) was used to select the wrinkle predictor, and the model with the smallest AIC (Akaike Information Criterion) was determined to be the best model. (Algorithm: Mallows (1973) Technometrics 15, 661-675 .; Steyerberg (2009) Statistics in Medicine 19 (8), 1059-1079 .; Akaike (1973) In 2nd International Symposium on Information Theory and an Extension of the Maximum Likelihood Principle, BN Petrov, and F. Csaki (eds), 267-281.). In the selection of this wrinkle predictor, the full model using all the wrinkle predictors was examined in order.
Finally, a sensitivity analysis was performed using the obtained wrinkle predictors. All analyzes were performed using R ver.3.5.2 statistical software (R Foundation for Statistical Computing, Vienna, Austria).

Test Example 1-4. Results and discussion [Test Example 1-4.1 Participants]
The average age of participants during the study period ranged from 38.64 years (95% CI: 35.47-41.81) at the start of the study to 44.24 years (95% CI: 41.47-47.34) at the end of the study. ).
Next, regarding the change over time in the wrinkle grade for each individual, a strong linear relationship such that the wrinkle grade increased with increasing age and a large individual difference in the average wrinkle value for each individual were observed. For this reason, we selected a linear mixed-effects model that introduces a variable effect into the intercept as the wrinkle prediction model in this study.

[Test Example 1-4.2 Development of wrinkle prediction model]
Five wrinkle predictors (1) "age", 2) "sebum amount (skin sebum amount)", 3) "a * value (skin redness)", 4) "for each individual" as the final wrinkle prediction model It was estimated that the average L * value (skin brightness) for all measurement years) and 5) “interaction term between sebum amount and a * value”) were included (Table 1).
In order to verify the accuracy of the wrinkle prediction model of the present invention, ^{the result of calculating R 2} (%) indicating the prediction accuracy of the wrinkle grade explained by the wrinkle predictor and RMSE showing the difference between the predicted value and the observed value (R ^2). = 84.75, RMSE = 0.685), and from this result, the wrinkle prediction model showed good prediction accuracy.

[Test Example 1-4.3 Wrinkle prediction model (Equation 1)]
Further, the following wrinkle prediction model (Equation 1) using the five wrinkle predictors derived above and the linear mixed-effects model is shown.

Wrinkle grade _i = 0.1469 × Age
＋ 0.7540 × Ln (sebum) 
＋ 0.3270 × Skin color a *
＋ 0.1654 × Mean [Skin color L *]
－ 0.1044 × [Ln (sebum) × Skin color a *]
－ 15.90
＋ b _{0, i}
(Equation 1)
b _{0, i} ~ N (0, 0.4847)
Final equation for prediction of wrinkle grade in Japanese women aged 22-60 years

Considering Test Example 1 described above and Test Examples 2 to 5 described later, at least two of the five wrinkle predictors, the measured values of age and skin brightness, are important in the wrinkle prediction model of the present invention. Met. Therefore, it is considered that the subject who wants to evaluate the wrinkles of the skin can estimate the index value of the wrinkles of the subject with good prediction accuracy based on these two.

Generally, the wrinkle grade increases with age, but it is said that moisturizing is good to prevent this wrinkle. For this reason, conventionally, age and measured values related to moisturization (for example, skin water content, transepidermal water evaporation amount) are considered to be the most important values. However, in the wrinkle prediction model of this study, it is not necessary to have measured values of skin water content and transepidermal water evaporation, and age and skin brightness were the most important values in the present invention. It was completely unexpected to the person. By accumulating data indicating age and skin condition (skin evaluation and measurement values, etc.) for each individual over a long period of time and using multivariate analysis (especially linear mixed-effects model), it has never been seen before. Succeeded in deriving results and ideas.

Furthermore, the wrinkle prediction model, which consists of five wrinkle predictors of age, skin brightness, skin redness, skin sebum amount, and the interaction term between sebum amount and skin redness, has particularly good prediction accuracy. I was also able to confirm that it would be.
For example, in the subject (female), the "age value" is 35 years old, the "skin brightness measurement value" is 68, the skin redness measurement value is 8.3, and the skin oil content measurement value is 6. If it is 0, these are "age value" in "Age" of the above (Equation 1), "measured value of skin brightness" in "Skin color L *", and "skin" in "Skin color a *". When "measured value of the amount of sebum of the skin" is substituted for "measured value of redness" and "sebum", the result is as follows, and the wrinkle grade of the skin is 3.0.

Furthermore, by this study, it was possible to obtain equation 1 of the wrinkle prediction model and equations 2 to 7 described later. Conventionally, wrinkle evaluation (wrinkle grade) relies on human visual inspection, so it is necessary to rely on experienced specialists, which has not been convenient. However, with this technology, wrinkle grade can be quantified more easily and objectively. Moreover, the measured value of the skin condition used in this study can be more easily obtained by a skin condition measuring device such as a measuring device. Therefore, according to the present invention, even if the expert is not an experienced expert, the wrinkle grade numerical value can be obtained more easily and more accurately. Further, according to the present invention, the wrinkle grade can be quantified by using the camera function and the video function of a smartphone or a personal computer with a Web camera, so that the present invention is a simpler operation regardless of time and place. Instead, wrinkles can be evaluated objectively and more accurately.
Then, by executing the wrinkle prediction model of the present invention on a computer including a CPU, it is possible to easily use wrinkle evaluation with better prediction accuracy for each individual on a mobile terminal or the like. Is.
Therefore, the present invention can provide a technique for evaluating skin wrinkles more accurately and more easily for each individual.

<Test Example 2: Wrinkle prediction model (Equation 2)>
Using the data obtained in Test Example 1, when each section in the wrinkle prediction model (Equation 1) was in the following range, the wrinkle prediction accuracy at the individual level was as good as 60% or more. .. Therefore, it was confirmed that the following equation 2 can be used as a wrinkle prediction model (formula 2).
Therefore, in the present invention, by using the wrinkle prediction formula 1 or the wrinkle prediction formula 2, four values of age value, skin brightness measurement value, skin redness measurement value, and skin sebum amount measurement value are used. Based on the above, the index value of wrinkles on the skin of the subject can be estimated more accurately and more easily.

Wrinkle grade _i = 0.1200 ～ 0.2053 × Age
＋ 0.2200 ～ 1.280 × Ln (sebum) 
＋0.050 ～ 0.5710 × Skin color a *
＋ 0.050 ～ 0.4000 × Mean [Skin color L *]
－ 0.030 ～ 0.1800 × [Ln (sebum) × Skin color a *]
－ 25.00-7.600
(Equation 2)

<Test Example 3: Number of wrinkle predictors>
Using the data obtained in Test Example 1, the device evaluation of the skin condition was performed in addition to the values (age, sebum amount, skin redness, skin brightness) adopted for the above wrinkle predictors. For example, device evaluations such as skin water content, transepidermal water evaporation, and skin yellowing were performed. However, as a result of comparing the wrinkle grade predicted using all the measured values as predictors with the best model, the prediction accuracy was as large as about 60%, or the RMSE value was as large as about 1.5, so good prediction accuracy was obtained. Not shown. Therefore, in addition to the above five wrinkle predictors (age, sebum amount, skin redness, skin brightness, interaction term between sebum amount and a * value), other wrinkle predictors (for example, skin water content). , Transepidermal water loss amount, etc.) is considered to reduce the prediction accuracy. From this, it is considered that the wrinkle prediction model using the above five wrinkle prediction factors is the best model.

<Test Example 4: In the case of the above two wrinkle predictors (age and skin brightness)>
"Age" and "skin brightness" are selected from the above five wrinkle predictors, and a wrinkle prediction model (Equation 3) using these two wrinkle predictors is shown below. The wrinkle prediction accuracy at the individual level was as good as 80% or more. The wrinkles prediction model and wrinkles prediction accuracy, use the R ² mentioned above, "Development of Test Example 1-4.2 wrinkles predictive model""Test Example 1-3. Statistical analysis for wrinkles predictive model development" and board.
Therefore, in the present invention, by using the wrinkle prediction formula 3, the index value of the wrinkles on the skin of the subject can be accurately and easily determined based on the two values of the age value and the measured value of the skin brightness. It can also be estimated.

Wrinkle grade _i = 0.1484 × Age
＋ 0.1844 × Mean [Skin color L *]
－ 14.80
(Equation 3)

<Test Example 5: In the case of the above two wrinkle predictors + wrinkle predictors (sebum amount)>
Using the data obtained in Test Example 1, among the above five wrinkle predictors, "age" and "skin brightness" were selected, and then "sebum amount" was selected, and these three wrinkle predictors were selected. The wrinkle prediction model (Equation 4) using the above is shown below. The wrinkle prediction accuracy at the individual level was as good as 80% or more. The wrinkles prediction model and wrinkles prediction accuracy, use the R ² mentioned above, "Development of Test Example 1-4.2 wrinkles predictive model""Test Example 1-3. Statistical analysis for wrinkles predictive model development" and board.
Therefore, in the present invention, by using the wrinkle prediction formula 4, the index value of the wrinkles on the skin of the subject is determined based on the three values of the age value, the measured value of the skin brightness, and the measured value of the amount of sebum. It can be estimated more accurately and more easily.

Wrinkle grade _i = 0.1504 × Age
＋ 0.1880 × Mean [Skin color L *]
＋0.044 × Ln (sebum)
－ 15.28
(Equation 4)

<Test Example 6: In the case of the above two wrinkle predictors + wrinkle predictors (redness, sebum amount)>
Using the data obtained in Test Example 1, among the above five wrinkle predictors, "age" and "skin brightness" were selected, and then "redness" and "sebum amount" were selected, and these 4 A wrinkle prediction model (Equation 5) using two wrinkle predictors is shown below. The wrinkle prediction accuracy at the individual level was as good as 80% or more. The wrinkles prediction model and wrinkles prediction accuracy, use the R ² mentioned above, "Development of Test Example 1-4.2 wrinkles predictive model""Test Example 1-3. Statistical analysis for wrinkles predictive model development" and board.
Therefore, in the present invention, by using the wrinkle prediction formula 5, the index of wrinkles on the skin of the subject is based on the four values of age value, skin brightness measurement value, and redness and sebum amount measurement value. The value could be estimated more accurately and more easily.

Wrinkle grade _i = 0.1460 × Age
＋ 0.035 × Ln (sebum) 
＋ 0.013 × Skin color a *
＋ 0.1812 × Mean [Skin color L *]
(Equation 5)

Claims (7)

A skin wrinkle evaluation method that estimates the index value of skin wrinkles of a subject based on at least these two values, the age value of the subject and the measured value of skin brightness. Claim 1 for estimating an index value of skin wrinkles of a subject based on the above two values and one or two values of a measured value of redness of the skin and / or a measured value of the amount of sebum of the skin. The method for evaluating skin wrinkles described in 1. The skin wrinkle according to claim 1, wherein the index value of the skin wrinkle of the subject is estimated by using two values, the age value of the subject and the measured value of the skin brightness, in the wrinkle prediction model. Evaluation method. In the wrinkle prediction model, two values of the subject's age and skin brightness measurement value and one or two values of the skin redness measurement value and / or the skin oil content measurement value are used. The method for evaluating skin wrinkles according to claim 2, wherein an index value of skin wrinkles of a subject is estimated by using the method. The wrinkle prediction model is
By deriving using a linear mixed-effects model that includes at least the measured values of the age and skin brightness of the individual as the objective variable, with the wrinkle index value of the individual as the objective variable.
The method for evaluating skin wrinkles according to claim 3 or 4, which is the obtained model. The method for evaluating skin wrinkles according to claim 5, wherein the parameters of the linear mixed-effects model are obtained by using the maximum likelihood method or the limited maximum likelihood method. A step of estimating the skin wrinkle index value of a subject to whom the test substance is administered by using the skin wrinkle evaluation method according to any one of claims 1 to 6, and the estimated skin wrinkle index. A method for evaluating or searching for a wrinkle-improving composition, which comprises a step of determining a test substance for wrinkle-improving when the value is lower than the wrinkle index value of the skin of a subject before administration.

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