JP2010025622A - Discrimination method of skin moisture amount distribution, and discrimination device and program therefor - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a discrimination method of a skin moisture amount distribution, further in detail, a technology capable of measuring a skin moisture amount (moisture amount distribution) in a wide range noninvasively, quickly and quantitatively. <P>SOLUTION: The discrimination method of the skin moisture amount distribution includes processes for: acquiring reflection intensity of a plurality points of a near-infrared wave ranges on the skin; acquiring each skin moisture amount on a plurality of points by substituting the reflection intensity acquired in the process for a prediction formula showing a relation between the skin moisture amount prepared beforehand and the reflection intensity of the near-infrared wave range; and discriminating the skin moisture amount distribution from the acquired each skin moisture amount on the plurality of points. A discrimination device for the skin moisture amount distribution and a discrimination program for the skin moisture amount distribution are also provided. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a technique for measuring skin moisture content, and more particularly to a technique for measuring a wide range of skin moisture content, that is, distribution of skin moisture content.

  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 this skin condition varies greatly from person to person, the most important factor for such skin condition is the amount of moisture in the skin. The skin is composed of the epidermis, dermis and subcutaneous tissue, and what is important as the moisture of the skin is the moisture in the epidermis, particularly the amount of moisture in the stratum corneum constituting the epidermis. If the normal stratum corneum cannot be formed due to the environment or pathological factors, the stratum corneum cannot retain appropriate moisture, the skin surface is dry and wrinkled, and is also flexible and elastic. There has been a demand for a highly accurate and simple means for measuring the moisture content of the skin which is likely to cause various troubles such as loss of water.

Such skin moisture measurement methods include in vitro weight method and Karl Fischer method, in vivo ATR spectroscopy, and more simple in vivo measurement method. Some high frequency impedance methods and electrical conductivity methods have been commonly used. However, recently, a skin moisture content measuring method and apparatus using a calibration curve obtained by multivariate analysis of a near-infrared diffuse reflectance spectrum that can be measured with higher accuracy without contact (for example, see Patent Document 1), Methods for measuring the moisture content of hair and nails (see, for example, Patent Document 2, Patent Document 3, and Patent Document 4), methods for distinguishing skin thickness and surface morphology (for example, see Patent Document 5), and types and degrees of hair damage Is disclosed (for example, see Patent Document 6). By such a method, the characteristics of the skin can be distinguished with high accuracy without contact. However, any of the above measurement methods is a measurement of only one point on the skin, and no method for quickly and quantitatively measuring a wide range of skin moisture content (moisture content distribution) has been known.
JP 2002-090298 A JP 2003-270138 A JP 2003-344279 A JP 2003-344278 A JP 2005-034350 A Table 2005-096938

  Under such circumstances, the present inventors measure only one point of skin moisture, which is an important factor, in order to judge skin properties and skin condition and to perform skin counseling, selection of cosmetics, and the like. However, since the accuracy is insufficient by itself, and accurate counseling cannot be performed, a means capable of quickly and quantitatively measuring a certain range of skin moisture content (moisture content distribution) has been studied.

  The present invention has been made under such circumstances, and relates to a technique for distinguishing skin moisture, and more specifically, noninvasively, rapidly and quantitatively measures a wide range of skin moisture (moisture distribution). It is an object to provide the technology to do.

In view of such a situation, the present inventors have sought to use a near-infrared camera that has a possibility of measuring the distribution as a surface in search of a skin moisture content discrimination technique. A near-infrared camera can obtain a reflection intensity in a certain region, but cannot obtain a spectrum. Therefore, it is not possible to use a multivariate analysis technique for a spectrum as reported so far. Therefore, the present inventors pay attention to the spectrum of water existing in the vicinity of 1450 nm, and divide the obtained reflection intensity in the specific wavelength region into the reflection intensity at the short wavelength side and the long wavelength side of the OH band of moisture, and use the prediction formula. It has been found that the moisture content distribution of the skin can be distinguished quickly and quantitatively by producing the present invention, and the present invention has been completed. That is, the present invention is a technique shown below.

(1) Obtaining the reflection intensity in the near-infrared wavelength region at a plurality of points on the skin and the prediction formula indicating the relationship between the skin moisture content and the reflection intensity in the near-infrared wavelength region prepared in advance in the above step A method for differentiating skin moisture distribution, comprising: substituting the reflected intensity for obtaining a plurality of skin moisture amounts; and distinguishing the skin moisture distribution from the obtained plurality of skin moisture amounts.
(2) The method for distinguishing skin moisture distribution according to (1), wherein the near-infrared wavelength region is 1050 to 1650 nm.
(3) In the near-infrared wavelength region, the prediction formula indicates the reflection intensity of the region between the center position of the water absorption wavelength and the position of Hnm from the center position of the water absorption wavelength to the long wavelength side, C, The reflection intensity of the region from the center position of the water absorption wavelength to the position of Hnm on the short wavelength side from the center position of the water absorption wavelength is B, the position of 2 Hnm on the short wavelength side from the center position of the water absorption wavelength and water Y = aX1 + bX2 + c, where A is the reflection intensity in the region from the center position of the absorption wavelength to the Hnm position on the short wavelength side, and Y is the moisture content of the skin.
(However, X1 = B−A, X2 = C−A, and a, b, and c are coefficients.)
The skin water content distribution discrimination method according to any one of (1) and (2), wherein the H is 50 to 150.
(4) The method for distinguishing skin moisture distribution according to (3), wherein the H is 120 to 140.
(5) A device for distinguishing skin moisture distribution, the means for inputting a prediction formula showing the relationship between the skin moisture content prepared in advance and the reflection intensity in the near-infrared wavelength region, and the near-infrared of multiple points on the skin Means for obtaining a reflection intensity in a wavelength range, means for obtaining a plurality of skin moisture contents from the prediction formula and the obtained reflection intensity, and calculating a skin moisture distribution from the obtained plurality of skin moisture contents And a means for displaying the calculated water content distribution.
(6) The computer calculates the skin moisture content at a plurality of points from the prediction formula indicating the relationship between the skin moisture content inputted in advance and the reflection intensity in the near-infrared wavelength region, and the obtained skin reflection intensity at the plurality of points. A skin water content distribution discrimination program that functions as a means and a means for calculating a skin water content distribution from a plurality of obtained skin water content.

  The present invention can provide a technique for quickly and quantitatively distinguishing a wide range of skin moisture content distribution. Therefore, the skin property and skin condition can be determined quickly and accurately by the discrimination method and the discrimination device.

<Difference method of the present invention>
The discrimination method of the present invention is a discrimination method of skin moisture distribution, and is characterized by using a prediction formula for calculating skin moisture with respect to the reflection intensity in the near-infrared specific wavelength region. As described above, if a calibration curve obtained by multivariate analysis of the near-infrared diffuse reflectance spectrum is used, the skin moisture content at one point can be easily measured (see Patent Document 1). In the discrimination method of the present invention, the skin moisture content at a plurality of points, that is, the skin moisture content distribution can be identified. The skin moisture content distribution here refers to measuring and displaying a plurality of points of at least 10 points on the skin at the same time. In the discrimination method of the present invention, an isoline showing a skin moisture distribution easily by using a spline interpolation method or a linear interpolation method, which will be described later, by obtaining a skin moisture amount by simultaneously measuring a plurality of points on the skin. It can be displayed as a diagram.

<The process of obtaining the reflection intensity | strength of the near-infrared wavelength range of multiple points of skin>
In order to simultaneously measure a plurality of points on the skin, a near-infrared camera can be used. When a near-infrared camera is used, the intensity for each wavelength in a specific detection wavelength region cannot be measured, but the reflection intensity in a specific detection wavelength region for a surface in a certain region can be obtained. The distribution of the reflection intensity can be measured. Examples of the near-infrared camera include InGaAs near-infrared camera XEVA (manufactured by Xenix) and infrared vidicon camera C2741-03 (manufactured by Hamamatsu Photonics).

  If the skin moisture content at a plurality of points can be calculated from the reflection intensity of the skin obtained using the near infrared camera, the skin moisture content distribution can be measured and displayed as an isometric diagram or the like. However, only the data of the reflection intensity in a certain wavelength range can be obtained by the near infrared camera. Since the baseline of the reflection intensity varies depending on the region and the subject, estimating the skin moisture amount from the obtained reflection intensity has a large error associated with the variation. In the past, it was impossible to distinguish moisture with high accuracy.

<Prediction formula showing the relationship between the skin moisture content and the reflection intensity in the near-infrared wavelength region of the skin>
The inventors pay attention to the absorption wavelength of water (OH band, 1450 nm) when the reflection intensity obtained from the near-infrared camera is assumed to be an absorption spectrum as shown in FIG. It has been found that a prediction formula is established from a total of three reflection intensities used for correction. By adopting this method, fluctuations in the baseline can be removed, and discrimination with extremely high accuracy can be performed. Hereinafter, an example of the method will be shown.

  As shown in FIG. 1, the position of Hnm and the position of 2Hnm on the short wavelength side are respectively set on the long wavelength side and the short wavelength side from the center of the absorption wavelength of water, and the reflection intensities (integrated values) of the three regions are set. Let C, B, A. Next, as shown in FIG. 2, X1 = BA and X2 = CA are defined in order to eliminate baseline fluctuations caused by the part or subject. Repeated multiple regression analysis with Hnm in the range of 50-150 nm, with external reference by multiple subjects / parts: Y (measured water content by skin moisture meter) as objective variable and X1 and X2 as explanatory variables The coefficients a, b, and c of Y = aX1 + bX2 + c, which is a prediction formula (calibration curve) of the skin moisture content, are calculated.

  Here, the appropriate value was calculated | required as follows about the value of the said Hnm. FIG. 3 shows the result of calculating the prediction error associated with the change in Hnm in 6 female subjects (cheek part) * 6 locations = 36 samples. Accordingly, since the prediction error is minimum when H = 120 to 140 nm, it can be understood that the skin moisture amount can be estimated most accurately from the near-infrared camera by performing the prediction under this condition.

The skin moisture prediction formula (Y = aX1 + bX2 + c) that can be obtained in this way can be made higher in prediction accuracy by making it for each skin region. Therefore, it is preferable to calculate the coefficients a, b, and c of the skin moisture prediction formula for each region in advance. Furthermore, in order to increase the accuracy of such a skin moisture prediction formula, it is desirable to increase the number of samples for calculating the prediction formula and update the database and the coefficient.
The prediction formula used in the present invention can be created by the above-described method, and can be used without any particular limitation as long as it can remove the fluctuation of the baseline of the reflection intensity due to the subject or the site. it can.

<Difference process>
By substituting the reflection intensity in the specific wavelength region for each part of the skin from the near-infrared camera described above into the skin moisture prediction formula (calibration curve) for each part created in this way, the skin moisture amount is accurate. It can be calculated well.
An example calculated in this way is shown in FIG. FIG. 4, which will be described in detail in Example 1, shows a scatter diagram of the moisture measurement value and the moisture amount calculated by the skin moisture prediction formula and its linear regression equation (correlation coefficient r = 0.860, P <0.01). It can be seen that the skin moisture content is predicted with higher accuracy. By performing the spline interpolation method using a spline curve based on the position coordinates of the skin water amount at each position of the skin thus predicted, the moisture content isometric diagram as shown in FIG. It is possible to determine the moisture content distribution.

  In the discrimination method of the present invention, the near-infrared wavelength region for distinguishing the skin moisture content distribution using the reflection intensity in the near-infrared wavelength region of the skin is near red before and after the absorption wavelength of water existing near 1450 nm. It is preferable that it is 1050-1650 nm from the viewpoint of focusing on the outside wavelength region and the specifications of the near-infrared camera element and imaging tube having a necessary and sufficient sensitivity region. From FIG. 3 described above, it can be measured with the highest accuracy that H = 120 to 140 nm, and since the absorption wavelength of water is 1450 nm, it is more preferable to use 1170 to 1590 nm as the specific wavelength region. From FIG. 3, H = 130 nm is the most desirable, so that the specific wavelength region in that case is more preferably 1190 to 1580 nm.

<Determination device / program for skin moisture content of the present invention>
Another aspect of the present invention is a discrimination apparatus that performs the above-described discrimination process. That is, a means for inputting a prediction formula of skin moisture content and skin reflection intensity in the near-infrared wavelength region prepared in advance, means for obtaining reflection intensities in the near-infrared wavelength region of a plurality of skin points, and the prediction formula And means for obtaining skin moisture content at a plurality of points from the obtained reflection intensity, means for computing skin moisture content distribution from the obtained skin moisture content at a plurality of points, and displaying the calculated moisture content distribution An apparatus for distinguishing skin moisture distribution including means. Furthermore, another aspect of the present invention is a program for performing the above steps. That is, the computer calculates the skin moisture content at multiple points from the prediction formula indicating the relationship between the skin moisture content input in advance and the reflection intensity in the near-infrared wavelength region of the skin and the obtained skin reflection strengths at multiple points. And a means for discriminating a skin water content distribution that functions as a means for calculating the skin water content distribution from the obtained skin water content at a plurality of points. The discrimination program of the present invention can be used by installing it on hardware such as a personal computer.

  The aspect of the discrimination device will be described with reference to FIG. The identification device of the present invention may be a general-purpose computer such as a personal computer or a dedicated computer for identification. The input unit 1 is an input unit for the prediction formula, and inputs a prediction formula used in the discrimination method of the present invention in advance. The input unit 1 can use, for example, an input device such as a keyboard. The data acquisition unit 2 is means for obtaining reflection intensities in the near infrared wavelength region at a plurality of points on the skin, and a commercially available near infrared camera as described above can be used. A CPU 3 (Central Processing Unit) is means for calculating a plurality of skin moisture distributions from a prediction formula inputted in advance and the obtained reflection intensity. Further, means for obtaining an equivalent diagram of the moisture amount as shown in FIG. 5 by performing a spline interpolation method using a spline curve on the identified skin moisture amount at each position of the skin based on the respective position coordinates. It can also be. By installing the above-described discrimination program on a general-purpose computer such as a personal computer, it functions as such means. A RAM 4 (Random Access Memory) is storage means for storing temporary data. The display unit 5 is means for outputting the skin moisture distribution calculated by the CPU 3 and its equivalence diagram, and can be, for example, a display device such as a liquid crystal display or an output device such as a printer.

  More specifically, the data acquisition unit 2 includes a near-infrared camera, a light source, an optical filter, an optical filter switching device, and the like. Three optical filters may be prepared, and only transmit light in the wavelength regions of (1450-2H) to (1450-H) nm, (1450-H) to 1450 nm, and 1450 to (1450 + H) nm, It is preferable to use one that does not transmit other light.

  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.

<Preparation of prediction formula>
After face washing for 6 T-zones (frontal and nose) and 6 U-zones (cheeks and chins) of 6 female subjects in their 20s and 40s (total of 36 for each zone) After 15 minutes, the diffuse reflectance spectrum was measured using a near infrared spectroscopic analyzer, and the skin moisture content was measured using a skin moisture meter.
Next, the center of the absorption wavelength of water = 1450 nm and H = 130 nm were set according to the calculation method of the prediction formula shown in FIGS. That is, the A region in FIG. 1 is 1190 to 1320 nm, the B region is 1320 to 1450 nm, and the C region is 1450 to 1580 nm. Repeated multiple regression analysis using skin moisture content (Y) as an objective variable and X1 and X2 obtained from the reflection intensity based on the measured diffuse reflectance spectrum as explanatory variables. The coefficients a, b, and c of Y = aX1 + bX2 + c, which are prediction formulas (calibration curves), were calculated. In the T zone, FIG. 4 shows a scatter diagram in which the moisture content and the measured moisture value according to the skin moisture prediction formula thus calculated are plotted and its linear regression equation (correlation coefficient r = 0.860, P < 0.01). It can be seen that the skin moisture content is predicted with higher accuracy. Further, from the calculation results shown below, it is understood that the values of a, b, and c differ depending on the zone, and it can be understood that the accuracy is further improved by calculating a, b, and c for each part.
T zone: a = -13.328, b = 9.978, c = 68.883
U zone: a = −17.821, b = 12.076, c = 88.309

<Measurement equipment and conditions>
The measurement apparatus and measurement conditions used in this example are shown below.
Near infrared spectrometer: Near infrared spectrometer HN200 (Spectrontech)
Skin moisture meter: Corneometer (registered trademark) CM825 (manufactured by CK)
Measurement conditions: temperature 20 ± 1 ° C, humidity 50 ± 5%

<Differential identification of skin moisture content distribution>
After 15 minutes of face washing, the face (T zone and U zone) of a 42 year old female subject was measured using a near infrared camera (InGaAs near infrared camera XEVA, Xenix) equipped with an optical filter. Reflection intensities in the wavelength regions of ˜1320 nm (A region), 1320 to 1450 nm (B region), and 1450 to 1580 nm (C region) were obtained at a plurality of points (about 80,000 points) on the skin. For each point where the reflection intensity is obtained, X1 and X2 are obtained from the reflection intensities in the A, B, and C regions, and are substituted into the zone-specific skin moisture amount prediction formula created in advance in Example 1 into the prediction formula. Substituting X1 and X2 that are necessary for the calculation, two-dimensional map data of the skin moisture content was calculated. FIG. 5 shows an isometric diagram of the moisture distribution produced from the two-dimensional map data by the spline interpolation method. From this, it can be seen that there is a bias in the distribution of moisture in the cheek, and it is important to know the distribution of skin moisture.

For 10 females (20 to 59 years old) with various skin properties, the measurement of the U-zone skin moisture distribution by the method of Example 2 and the moisture content measurement at one location of the cheek by a skin moisture meter were performed. Separately, 30 minutes after washing the face, the amount of sebum on the cheek was measured (Sebmeter SM810 (registered trademark), manufactured by CK), and skin classification was performed with reference to the amount of water and the amount of sebum. Table 1 shows the results (number distribution) of the skin classification using the moisture classification that can measure only the moisture content at one point of the skin classification and the skin classification using the skin moisture content distribution method according to the present invention.

  From Table 1, when comparing the skin classification using the discrimination method of the present invention and the skin classification using a moisture meter, the skin classification using the moisture meter is oily skin with the skin classification using the discrimination method of the present invention. Two out of the three identified were classified as oily dry skin with less moisture, and one out of three identified as normal skin was classified as dry with less moisture. Such a deviation in the determination is considered to be caused by the fact that a moisture meter capable of measuring only one moisture content of the skin cannot obtain a correct measurement value due to irregularities on the skin surface unique to oily skin or the like. In the present invention, since the distribution of a wide range of skin moisture content can be measured, it is considered that this is a differentiation method in which the influence of measurement error is less likely to occur compared to the case where only one moisture content of skin is measured.

  According to the present invention, it is possible to quickly and accurately determine skin properties and skin conditions, and as a result, it is possible to quickly and accurately select skin properties and skin condition advice and cosmetics at a sales site or the like. Can provide.

It is a figure explaining the prediction method in the distribution map of the reflection intensity when it displays as an absorption spectrum. It is a figure which shows the removal method of a baseline in FIG. It is a figure which shows the relationship between the change of Hnm, and a prediction error in discrimination of the skin moisture content by a near-infrared camera. It is a figure which shows the correlation with a water | moisture content measured value and the water | moisture content predicted value by a prediction formula. It is a figure (isoline map) which shows the skin moisture content distribution of the cheek part measured with the near-infrared camera of Example 2. FIG. It is a figure which shows the structural example of a discrimination apparatus.

Claims (6)

  Reflection intensity obtained in the above step in the process of obtaining the reflection intensity in the near-infrared wavelength region at a plurality of points on the skin and the prediction formula showing the relationship between the skin moisture content prepared in advance and the reflection intensity in the near-infrared wavelength region A method for differentiating skin moisture distribution, comprising the step of substituting and obtaining a skin moisture content at a plurality of points, and a step of distinguishing the skin moisture content distribution from the obtained plurality of skin moisture content.   2. The method for distinguishing skin moisture distribution according to claim 1, wherein the near-infrared wavelength region is 1050 to 1650 nm. In the near-infrared wavelength region, the prediction formula is C, the reflection intensity in the region between the center position of the water absorption wavelength and the position of Hnm from the center position of the water absorption wavelength to the long wavelength side, and water absorption. The reflection intensity of the region from the center position of the wavelength and the center position of the absorption wavelength of water to the position of Hnm to the short wavelength side is B, the position of 2 Hnm from the center position of the absorption wavelength of water to the short wavelength side and the absorption wavelength of water When the reflection intensity of the region from the center position to the position of Hnm on the short wavelength side is A and the moisture content of the skin is Y,
Y = aX1 + bX2 + c
(However, X1 = B−A, X2 = C−A, and a, b, and c are coefficients.)
Represented by
3. The method for distinguishing skin moisture distribution according to claim 1, wherein the H is 50 to 150.   The said H is 120-140, The differentiation method of the skin moisture content distribution of Claim 3 characterized by the above-mentioned.   A device for distinguishing skin moisture distribution, comprising means for inputting a prediction formula indicating a relationship between a skin moisture content prepared in advance and a reflection intensity in the near infrared wavelength region, and a plurality of near infrared wavelength region skin points. Means for obtaining a reflection intensity; means for obtaining a plurality of skin moisture amounts from the prediction formula and the obtained reflection intensity; and a means for calculating a skin moisture distribution from the obtained plurality of skin moisture amounts And a means for displaying the calculated water content distribution, and a device for discriminating the skin water content distribution.   Means for calculating a plurality of skin moisture amounts from a prediction formula indicating a relationship between the skin moisture amount inputted in advance and the reflection intensity in the near-infrared wavelength region, and the obtained skin reflection intensity at the plurality of points; and A discrimination program for skin moisture content distribution that functions as a means for calculating skin moisture content distribution from a plurality of obtained skin moisture content.

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