JP2009297064A - Method of distinguishing visual tenseness - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide technologies for accurately separating and distinguishing the "visual tenseness" of the skin felt when the skin is seen from the "tactile tenseness" felt when the skin is touched according to the physical properties of the skin (the physiological values of the skin). <P>SOLUTION: The method of distinguishing the "visual tenseness" is for separating and distinguishing the "visual tenseness" of the skin felt when the skin is seen from the "tactile tenseness" felt when the skin is touched by using multivariate analysis such as the cluster analysis or regression analysis. The "visual tenseness" is accurately distinguished based on the physical properties of the skin (physiological values of the skin) such as the quantity of moisture transpiration from the epidermis, the quantity of moisture in the horny cell layer and the flexibility of the skin. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a technique for distinguishing skin firmness, and more particularly, to a technique for distinguishing visual firmness.

  Many people want to have beautiful skin as well as women. For this reason, there are many people who want to keep their skin in good condition using cosmetics. Although the skin condition varies greatly depending on the individual, various methods for accurately measuring and evaluating such a skin condition have been studied. There are two types of such methods: sensory evaluation methods and instrumental measurement methods. The sensory evaluation method is a method of measuring a human sense as a measuring instrument, and includes evaluation items such as pushing, pinching, shifting, pulling, sliding, rubbing, evaluation scales, evaluation conditions, and the like. On the other hand, the instrumental measurement method was researched and developed as a substitute for the sensory evaluation method, and the correspondence with the sensory evaluation was an important issue. For this reason, the development of various measurement methods and the relationship with their sensory evaluation methods have been comprehensively studied (Non-Patent Document 1).

  As such equipment development, for example, a skin elasticity / slip measuring instrument has been developed that simulates the action when evaluating sensual skin tension and slippage on the skin surface. It was used for evaluation of skin and cosmetics (see Non-Patent Documents 2 and 3). Thereafter, a scalp tension measuring device (see Patent Document 1), a skin condition evaluation method using a friction coefficient (see Patent Document 2), and a skin beam evaluation device using skin image characteristics and a neural network (see Patent Document 3) ), A physical property measuring apparatus for elastic bodies focusing on the collagen fiber structure of the skin, which is highly related to wrinkles (see Patent Document 4), and a method for evaluating the elasticity of the stratum corneum using oxidized protein in the stratum corneum as an index (Patent Document) 5) etc. are disclosed, and it has become possible to carry out differentiation with an enlarged evaluation target region and accuracy. However, the above method is a method of measuring either physical or tactile elasticity / elasticity, or visual elasticity / elasticity. Was not known at all.

  Under such circumstances, the present inventors have examined means capable of measuring the structural characteristics of “skin elasticity” that is most important by women as an element of ideal skin. It was not known that the skin firmness (hereinafter referred to as “tactile firmness”) that is felt in the skin is completely different from the skin firmness felt when viewing the skin (hereinafter defined as “visual firmness”). In addition, it has not been known at all that such “visual tension” can be accurately distinguished by skin physical properties (skin physiological values).

Japanese Patent Application Laid-Open No. 06-078886 JP 2003-024282 A Japanese Patent Laid-Open No. 2003-024306 Table 01/052724 JP 2006-349372 A FRAGRANCE JOURNAL special issue (5), 376, 1984 J. Soc. Cosmet. Chem. Japan. 15 (1), 32, 1981 J. Soc. Cosmet. Chem. Japan. 18 (2), 121, 1984

  The present invention has been made under such circumstances, and relates to a technique for discriminating “visual elasticity” of the skin, and more specifically, “visual elasticity” felt when the skin is seen, touched the skin. It is an object of the present invention to provide a technique for separating from “tactile tension” at the time and distinguishing with high accuracy by physical properties of the skin (skin physiological values).

  In view of such a situation, the present inventors have made extensive research efforts to find a technique for distinguishing “visual elasticity” of the skin. We have found that it is possible to separate the “visual elasticity” that is felt when looking at the skin by using the skin from the “tactile elasticity” when the skin is touched, and to accurately identify the physical properties of the skin (skin physiological values). I came to let you. That is, the present invention is a technique shown below.

(1) A method for differentiating visual elasticity, wherein multivariate analysis is used.
(2) The method for distinguishing visual tension according to (1), wherein the multivariate analysis is a cluster analysis.
(3) The method for discriminating visual tension according to (1), wherein the multivariate analysis is regression analysis. (4) The regression analysis includes transepidermal water transpiration, stratum corneum moisture, and skin. The method for distinguishing visual tension according to (3), characterized in that the regression formula is obtained by multiple regression analysis of flexibility and an evaluation value of visual tension.

  According to the present invention, it is possible to distinguish between “visual tension” and “tactile tension” and accurately estimate “visual tension”. As a result, “visual tension” and “tactile tension” are differentiated, and the skin condition can be accurately grasped, and subjects can be selected from the skin condition.

  In the sensory evaluation of the skin, the present invention has been generally described so far with respect to the elasticity and / or elasticity of the skin, that is, a visual element that looks and a tactile element when the skin is touched. This is a technique for distinguishing between elements that are completely different from each other, and a method for accurately distinguishing “visual tension”, which is the visual element that looks, from the physical properties of the skin (skin physiological values). .

  In order to distinguish between the visual element and the tactile element, it is desirable to perform sensory evaluation (scoring) using a sensory evaluation method, and then perform multivariate analysis. For such sensory evaluation, a sensory evaluation table may be created to establish standardized sensory evaluation conditions. Tables 1 and 2 show examples of visual and tactile sensory evaluation methods, respectively. These are the evaluation items narrowed down by factor analysis after collecting a lot of visual and tactile terms for the skin, and the observation sites and points when performing the evaluation. As described above, it is not limited to narrow down sensory evaluation items by factor analysis or the like in advance, but it is a preferable method because accuracy can be improved and time can be shortened. If the evaluation items thus obtained are evaluated by setting 3 to 7 quantitative criteria in the SD method, the state of the skin can be evaluated with high accuracy. At this time, it is desirable to pay sufficient attention to the environmental conditions of the evaluation. Such points to be noted include, for example, the temperature and humidity of the measurement room, the type and position of lighting, the condition of the subject, the positional relationship between the subject and the observer at the time of evaluation, sufficient training of the evaluator, A background situation etc. can be illustrated.

  Next, using the visual and tactile sensory evaluation methods, sensory evaluation is performed on subjects with various skin properties, skin quality, age and sex, and multivariate analysis is performed on the data. At this time, it is desirable that the number of subjects is at least 20 or more, more preferably 40 or more. As the multivariate analysis, principal component analysis, factor analysis, discriminant analysis, quantification theory (class 1 to class 4), cluster analysis, conjoint analysis, and multidimensional scale construction method are preferable. Among such multivariate analyses, cluster analysis and multidimensional scaling method are more preferable. The cluster analysis is an unsupervised data classification method, and automatically classifies given data without external criteria. There are a hierarchical method that is performed hierarchically by data classification and a non-hierarchical method that classifies the data into a specific number of clusters, and typical methods include the Ward's method and the K-average method. An example in which the visual element is distinguished from the tactile element in this way will be described in detail in an example described later, and is shown in FIG. That is, as shown in FIG. 1, “visual tension” and “tactile tension” are classified into different clusters. Multivariate analysis including cluster analysis can be performed using free software or software commercially available from SPSS, SAS Institute, Social Information Service, or the like.

  In order to distinguish “visual tension” with high accuracy, it can be estimated using the correlation with physical properties of the skin (skin physiological values). This is because, in FIG. 1 described above, “visual tension” (noted as tension (visual) in FIG. 1) is very close to “visual moisture feeling” (noted as moist feeling (visual) in FIG. 1). Because of the relationship, it is considered that the skin physical properties (skin physiological values) that are highly correlated with “visual moisture” can be used, such as stratum corneum moisture, transepidermal moisture transpiration, or skin flexibility. Because it is. Therefore, as a multivariate analysis, a regression analysis method that can use “visual tension” as an objective variable and skin physical properties as explanatory variables is preferable. For example, regression analysis (MLR, PLS, PCR, logistic regression), probit analysis , Canonical correlation analysis, path analysis, covariance structure analysis, discriminant analysis, principal component analysis, factor analysis, quantification theory (class 1 to class 3), multidimensional scaling, supervised clustering, neural network, and ensemble learning method Etc. can be illustrated. Of these, multiple regression analysis (MLR), discriminant analysis, and quantification theory are particularly preferable. These are to obtain a regression equation using “visual elasticity” as an objective variable and the skin physical properties of the skin as explanatory variables, and using the regression equation as a prediction equation, it is possible to easily predict “visual elasticity” with high accuracy. This is because it can be done.

  Hereinafter, the present invention will be described in detail with reference to examples and the like, but the scope of the present invention is not limited by these examples.

<Difference between "visual tension" and "tactile tension">
For 42 healthy female subjects aged 22-39 years old, after the face washing 20, five grades were evaluated by three trained evaluators under the following evaluation items and conditions. The obtained data of 42 persons on 11 items were analyzed using cluster analysis (Ward's method) software. The results are shown in FIGS.

<Evaluation items and conditions>
1) Visual evaluation: moist feeling, glossiness, firmness, skin color, smoothness, wrinkle feeling, color unevenness, brightness (See Table 1 for observation sites and points)
2) Tactile evaluation: elasticity, moist feeling, firmness (see Table 2 for observation sites and points)
3) Environmental conditions: Temperature 20 ± 1 ° C, humidity 50 ± 5%, Lighting VITA-LITE (registered trademark) manufactured by LS
4) Analysis method: SPSS hierarchical cluster analysis (Ward's method)

  As shown in FIG. 1, four clusters were extracted, and the firmness (sight) and the firmness (tactile sensation) were classified into different clusters, indicating that the firmness (sight) and the moist feeling (sight) were very close. From this, it can be seen that “visual tension” and “tactile tension” are separated and distinguished. Moreover, since the mutual relationship according to the similarity between female subjects can be understood from the dendrogram of FIG. 2, it can be used for selecting subjects, for example, in a cosmetic use test or creation of a skin condition reference photograph.

<Estimation of “visual elasticity”>
In Example 1, the following physical properties of the skin (skin physiological values) were further measured, and a correlation analysis was performed on all data, and a multiple regression analysis was performed using “visual tension” as an objective variable and the skin physical properties of the skin as an explanatory variable. It was.

<Evaluation items and conditions>
1) Sensory evaluation and environmental conditions: the same as in Example 1 2) Measurement items (skin physical properties)
・ Corn layer moisture content: SKICON200-EX manufactured by IBS, AS-M1 manufactured by Asahi Biomed
・ Transepidermal water transpiration (TEWL): C + K Tevameter TM 210, Asahi Biomed AS-TW2
・ Skin flexibility: Venustron manufactured by Axim,
・ Skin gloss: MULTIL LOSS268 manufactured by Konica Minolta
-Sebum amount: Sebetter made by C + K
・ Stratum corneum: TA (Thick Abration), regularity of stratum corneum cells, PK (presence of nucleated cells), by APEX skin check manufactured by Polar Chemical Industries
-Skin surface condition: Silicon replica ASB-01-ww manufactured by Asahi Biomed
3) Analysis method: Correlation analysis and multiple regression analysis are multivariate analysis software manufactured by SPSS.

A significant correlation was found between “visual tension” and stratum corneum moisture, transepidermal moisture transpiration, or skin softness (P <0.05). Further, it was found that the “visual tension” can be accurately estimated by the following multiple regression equation (Equation 1) including the items of transepidermal moisture transpiration, stratum corneum moisture, and skin softness.
"Visual elasticity" = -4.6E-02 * (transepidermal water transpiration) + 7.6E-04 * (horny layer water)-2.3E-03 * (skin softness) + 3.3・ ・ (Formula 1)
(Speman correlation coefficient: R = 0.673)

<Improvement of "visual elasticity">
Cosmetics with a high moisturizing function were used continuously for 3 months for 33 healthy female subjects aged 22 to 39 years. Sensory evaluation before and after the use test and physical properties of the skin were measured to evaluate the relevance. As a result, before and after the use test, moist feeling (visual), firmness (visual), and a significant increase in stratum corneum water content were observed (P <0.01). From this, it can be seen that, as in Examples 1 and 2, “visual tension” is strongly related to moisture (sight) and stratum corneum moisture content.

<Evaluation items and conditions>
1) Sensory evaluation and environmental conditions: the same as in Example 1 2) Measurement items (skin physical properties)
・ Corn layer moisture content: SKICON200-EX manufactured by IBS
-Transepidermal water transpiration (TEWL): Cemometer TM 210 manufactured by C + K

<Prescription> Mass%
Squalane 8
Vaseline 2
Trioctanoin 3
Candelilla wax 1
Tween 60 1.5
Span60 1.5
Ceramide 2 0.5
Pure water remaining

  According to the present invention, it is possible to quickly and accurately grasp the skin state and classify the skin. Using the results, skin counseling and cosmetic selection advice can be accurately performed at the sales site.

It is a figure which shows the result of a cluster analysis. It is a figure which shows the dendrogram obtained by cluster analysis.

Claims (4)

A method for distinguishing visual elasticity, characterized by using multivariate analysis. The method for distinguishing visual tension according to claim 1, wherein the multivariate analysis is cluster analysis. The method for distinguishing visual tension according to claim 1, wherein the multivariate analysis is regression analysis. The regression analysis is a regression equation obtained by a multiple regression analysis of transepidermal moisture transpiration, stratum corneum moisture and skin flexibility, and an evaluation value of visual elasticity. The method of distinguishing the described visual elasticity.

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