Skin index estimation method

Abstract

To provide a technique capable of estimating an index value of stratum corneum or skin surface characteristics with higher accuracy using infrared absorption spectrum information of stratum corneum.SOLUTION: A skin index estimation method includes the steps for obtaining infrared absorption spectral information about a stratum corneum exfoliated from the skin of an evaluated person by one or more processors and estimating a target index value for the evaluated person by inputting the infrared absorption spectral information into an estimation model obtained using a plurality of data sets of infrared absorption spectral information and known target index values for the stratum corneum exfoliated from the skin of a plurality of sample donors. The infrared absorption spectral information includes a plurality of intensity values in a predetermined wavenumber region. The target index values are index values related to stratum corneum or skin surface characteristics.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a technique for estimating a skin index using infrared absorption spectrum information. [Background technology]

[0002] In the following Patent Document 1, the infrared absorption spectrum of the stratum corneum of the skin shows that ‐1 This method comprises measuring a signal intensity A and a signal intensity B derived from proteins in the wave number region, and measuring the amount of natural moisturizing factor (NMF) in the stratum corneum from the ratio of signal intensity A' of the antisymmetric stretching vibration of carboxylate anion extracted from signal intensity A to signal intensity B. Patent Document 2 listed below discloses a method for evaluating the properties of the stratum corneum of human skin for purposes other than medical treatment, in which an infrared absorption spectrum is measured by infrared spectroscopy, and the amide I absorption band peak derived from the secondary structure of the protein in the infrared absorption spectrum is divided into a superimposed peak of α-helix and random coil and a peak of β-sheet, the areas of the superimposed peak of α-helix and random coil and the peak area of ​​β-sheet are calculated, and the peak area ratio β / α defined as [peak area of ​​β-sheet] / [peak area of ​​superimposed peak of α-helix and random coil] is calculated, and the calculated ratio β / α is used as an index to evaluate the properties of the stratum corneum of skin for purposes other than medical treatment. The following Patent Documents 3 to 5 disclose a method for easily and stably evaluating the properties of the stratum corneum using infrared absorption spectra obtained from the stratum corneum by tape peeling. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2009-210567 A [Patent Document 2] JP 2013-44525 A [Patent Document 3] JP 2018-105783 A [Patent Document 4] JP 2020-193948 A [Patent Document 5] Patent Publication No. 2021-181987 Summary of the Invention [Problem to be solved by the invention]

[0004] The various methods described above evaluate the properties of the stratum corneum based on the signal intensity, peak shape, etc. of a peak in a specific wavenumber region in the infrared absorption spectrum of the stratum corneum. The present invention provides a technique that makes it possible to estimate index values ​​of stratum corneum characteristics or skin surface characteristics with higher accuracy by using infrared absorption spectrum information of the stratum corneum. [Means for solving the problem]

[0005] According to the present invention, a skin index estimation method can be provided in which one or more processors execute an acquisition step of acquiring infrared absorption spectrum information regarding the stratum corneum peeled from the skin of a subject, and an estimation step of estimating a target index value of the subject by inputting the acquired infrared absorption spectrum information into an estimation model obtained using multiple data sets of infrared absorption spectrum information regarding the stratum corneum peeled from the skin of multiple sample providers and known target index values, wherein the infrared absorption spectrum information includes multiple intensity values ​​in a predetermined wavenumber range, and the target index value is an index value regarding the stratum corneum characteristics or skin surface characteristics. Also, a skin index estimation device including at least one processor and a memory and capable of executing the above-mentioned skin index estimation method may be provided. Effect of the Invention

[0006] According to the present invention, it is possible to provide a technique that can estimate index values ​​of stratum corneum characteristics or skin surface characteristics with higher accuracy using infrared absorption spectrum information of the stratum corneum. [Brief description of the drawings]

[0007] [Figure 1]FIG. 1 is a diagram conceptually illustrating an example of the hardware configuration of an information processing device capable of executing a skin index estimation method according to an embodiment of the present invention (the present method). [Diagram 2] 2 is a flowchart of a skin index estimation method (this method) according to the present embodiment. [Diagram 3] 1 is a graph showing an infrared absorption spectrum for the stratum corneum peeled from skin. [Figure 4] 1 is a table showing the estimation accuracy for each target index value related to the stratum corneum delamination rate and the stratum corneum cell shape in the estimation model of Example 1. [Diagram 5] 1 is a table showing the estimation accuracy for each target index value related to stratum corneum intercellular lipids in the estimation model of Example 1. [Figure 6] 1 is a table showing the estimation accuracy for each target index value related to the moisture content of the stratum corneum in the estimation model of Example 1. [Figure 7] 1 is a table showing the estimation accuracy for each target index value regarding skin surface characteristics in the estimation model of Example 1. [Figure 8] 8 is a graph showing weights (regression coefficients) for absorbance of each wave number component (each explanatory variable) in an estimation model (estimation formula) with stratum corneum characteristics as the target index. Fig. 8(a) is a graph related to the estimation model (estimation formula) with stratum corneum moisture content measured using Skicon (manufactured by Yayoi) as the target index, Fig. 8(b) is a graph related to the estimation model (estimation formula) with transepidermal water loss (TEWL) as the target index, Fig. 8(c) is a graph related to the estimation model (estimation formula) with the ratio (NP / NS) between the amount of ceramide NP and the amount of ceramide NS as the target index, and Fig. 8(d) is a graph related to the estimation model (estimation formula) with the stratum corneum delamination rate as the target index. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Hereinafter, preferred embodiments of the present invention (hereinafter, referred to as the present embodiment) will be described. The following embodiments are merely examples, and the present invention is not limited to the configurations of the following embodiments.

[0009] The skin index estimation method according to this embodiment (hereinafter referred to as this method) is executed by one or more processors included in one or more information processing devices. FIG. 1 is a diagram conceptually illustrating an example of the hardware configuration of an information processing device 10 capable of executing the present method. The information processing device 10 is a so-called computer, and includes a CPU 11, a memory 12, an input / output interface (I / F) 13, a communication unit 14, etc. The information processing device 10 may be a stationary PC (Personal Computer), a portable terminal such as a portable PC, a smartphone, or a tablet, or may be a dedicated computer.

[0010] The CPU 11 is a so-called processor, and may include not only a general CPU (Central Processing Unit), but also an application specific integrated circuit (ASIC), a DSP (Digital Signal Processor), a GPU (Graphics Processing Unit), etc. The memory 12 is a RAM (Random Access Memory), a ROM (Read Only Memory), and an auxiliary storage device (such as a hard disk). The input / output I / F 13 can be connected to user interface devices such as a display device 15 and an input device 16. The display device 15 is a device that displays a screen corresponding to drawing data processed by the CPU 11 or the like, such as an LCD (Liquid Crystal Display) or CRT (Cathode Ray Tube) display. The input device 16 is a device that accepts input of user operations, such as a keyboard, a mouse, etc. The display device 15 and the input device 16 may be integrated and realized as a touch panel. The communication unit 14 communicates with other computers via a communication network and exchanges signals with other devices such as a printer, etc. A portable recording medium, etc. can also be connected to the communication unit 14.

[0011] The hardware configuration of the information processing device 10 is not limited to the example in Fig. 1. The information processing device 10 may include other hardware elements not shown. Furthermore, the number of each hardware element is not limited to the example in Fig. 1. For example, the information processing device 10 may have multiple CPUs 11. Furthermore, the information processing device 10 may be realized by multiple computers consisting of multiple housings.

[0012] The information processing device 10 can execute the present method by the CPU 11 executing a computer program stored in the memory 12. This computer program is installed from a portable recording medium such as a CD (Compact Disc) or a memory card, or from another computer on a network, via the input / output I / F 13 or the communication unit 14, and stored in the memory 12.

[0013] The information processing device 10 (CPU 11) can use the estimation model and can also generate the estimation model. However, the estimation model may be generated by another computer. The estimation model may be stored in the memory 12 in the information processing device 10, or may be stored in the memory of another computer that the information processing device 10 can access by communication. In this way, the information processing device 10 can be described as a skin index estimation device that is capable of using the estimation model and executing the present method. Details of the estimation model will be described later.

[0014] Here, this method will be explained with reference to FIG. FIG. 2 is a flowchart of the skin index estimation method (this method) according to this embodiment. As shown in Fig. 2, this method includes at least an acquisition step (S11) of acquiring infrared absorption spectrum information on the stratum corneum peeled from the skin of the subject, and an estimation step (S13) of estimating the target index value of the subject by inputting (S12) the infrared absorption spectrum information acquired in the acquisition step (S11) into the above-mentioned estimation model. In the example of Fig. 2, this method further includes a step (S14) of outputting the target index value of the subject acquired in the estimation step (S13). This method is executed by an information processing device 10 (CPU 11) as exemplified in Fig. 1. Hereinafter, each step of this method will be described in detail with the CPU 11 acting as the execution subject.

[0015] The infrared absorption spectrum information acquired in the acquisition step (S11) is information on the infrared absorption spectrum (also called the infrared absorption spectrum, the infrared transmission spectrum, etc.) obtained by infrared spectroscopy measurement of a specimen including at least the stratum corneum peeled off from the skin, and includes multiple intensity values ​​in a predetermined wave number region of the infrared absorption spectrum.

[0016] The "stratum corneum peeled off from the skin" includes not only stratum corneum collected or peeled off from the skin using hands, adhesive tape, some kind of tool, etc., but also stratum corneum that has naturally peeled off. The infrared absorption spectrum information may represent only the infrared absorption spectrum obtained for such a stratum corneum, or may represent the infrared absorption spectrum of the stratum corneum plus other components such as tape, moisture, and dust. The "intensity value" is a value indicating the intensity of each wave number in an infrared absorption spectrum, such as absorbance, transmittance, or reflectance.

[0017] Fig. 3 is a graph showing an example of an infrared absorption spectrum for the stratum corneum peeled from the skin, in which the horizontal axis indicates wave number and the vertical axis indicates absorbance (intensity value). The infrared absorption spectrum information acquired in the acquisition step (S11) includes a plurality of intensity values ​​extracted from a group of intensity values ​​in a predetermined wave number region of the infrared absorption spectrum as exemplified in FIG. The "predetermined wavenumber region" of the infrared absorption spectrum is a predetermined wavenumber region, and may be a wavenumber range that is the measurement limit according to the specifications of the device that performs the infrared spectrometry, or may be one or more partial wavenumber regions within the wavenumber range of the measurement limit. For example, as shown in the example of FIG. 3, the predetermined wavenumber region is the 600 cm -1 More than 4000cm -1 The following wave number range may be used:

[0018] However, infrared absorption spectrum information is 600 cm -1 More than 1800cm -1 Several intensity values ​​in the first wavenumber region below 2800 cm -1 More than 3700cm -1 It is preferable to include at least a plurality of intensity values ​​in the following second wavenumber region. As will be described later as an example, the contribution rate (regression coefficient) of the intensity values ​​in the first wavenumber region and the second wavenumber region to the target index value is higher than the intensity values ​​in the other wavenumber regions, and the estimation accuracy of the estimation model can be improved.

[0019] In addition, the infrared absorption spectrum information is -1 More than 1800cm -1 The first wavenumber region below and 2800cm -1 More than 3700cm -1 It is preferable to include at least a plurality of intensity values ​​in the non-peak region of the second wavenumber region as follows: The term "non-peak region" used herein refers to a wavenumber region that is not a peak in an infrared absorption spectrum graph such as that shown in FIG. 3, and specifically refers to a region having a predetermined wavenumber resolution (e.g., 0.5 cm -1 The term "peak region" refers to a wavenumber region that shows a convex shape in the infrared absorption spectrum, and is, for example, a predetermined wavenumber range (e.g., 100 cm) centered on the wavenumber that shows the peak intensity in that wavenumber region. -1 ), or the wavenumber range from the wavenumber showing the peak intensity to the wavenumber showing an intensity that is about 80% to 50% of the peak intensity, with the wavenumber showing the peak intensity at the center. In the example of Figure 3, the non-peak region of the first wavenumber region includes the region from 700 to 800 cm -1 Near 1000 to 1100 cm -1 Near 1400cm -1 The non-peak region of the second wavenumber region is from 3000 to 3100 cm -1 Around 3400 to 3700 cm -1 This applies to the wave number region around The present inventors have found that the estimation accuracy of the estimation model can be improved by using not only the peak intensity value but also a plurality of intensity values ​​in non-peak regions as the infrared absorption spectrum information.

[0020] In addition, the intensity value included in the infrared absorption spectrum information may be extracted regardless of whether it is a peak intensity value of the infrared absorption spectrum. For example, the infrared absorption spectrum information may include the 600 cm -1 More than 1800cm -1 Within the first wavenumber range below, at regular wavenumber intervals (first wavenumber intervals) and at 2800cm -1 More than 3700cm -1 The infrared absorption spectrum information may include a plurality of intensity values ​​sampled at a constant wavenumber interval (second wavenumber interval) from within the second wavenumber region below. In this case, the first wavenumber interval and the second wavenumber interval may be the same or different. The infrared absorption spectrum information may include a plurality of intensity values ​​sampled at a constant wavenumber interval (second wavenumber interval) from within the second wavenumber region below. In this case, the first wavenumber interval and the second wavenumber interval may be the same or different. -1 More than 4000cm -1 The signal may include a plurality of intensity values ​​sampled at regular wavenumber intervals from among the signal intensity values ​​(see below) sampled at regular wavenumber intervals. It has been demonstrated in the examples described below that the estimation accuracy of the estimation model can be improved by using multiple intensity values ​​extracted in this manner, regardless of whether they are peak intensity values ​​of the infrared absorption spectrum or not.

[0021] Furthermore, in order to improve the estimation accuracy of the estimation model, the number of intensity values ​​included in the infrared absorption spectrum information is preferably 10 or more, more preferably 25 or more, and even more preferably 50 or more, as described below as an example.

[0022] In the acquisition step (S11), the CPU 11 may acquire the infrared absorption spectrum information from an infrared spectrometer or another computer via communication or a portable recording medium, or may acquire the infrared absorption spectrum information by processing the information acquired from the measurement device or another computer.

[0023] As described above, in this embodiment, various methods can be used to acquire infrared absorption spectrum information. For example, the stratum corneum may be collected from the skin surface using an adhesive tape having a silicone adhesive layer or an adhesive layer of another component, and the infrared absorption spectrum information may be extracted from the results of infrared spectrometry of the adhesive tape to which at least the stratum corneum is attached. In this case, the CPU 11 may acquire information on the results of the infrared spectrometry from an infrared spectrometry device or another computer, and acquire the required infrared absorption spectrum information from the result information. The infrared absorption spectrum information may also be obtained using the techniques disclosed in the above-mentioned Patent Documents 3 to 5. Specifically, a technique may be used in which the stratum corneum is collected from the skin surface using an adhesive tape T1, the collected stratum corneum is transferred from the adhesive tape T1 to a tape T2 having a silicone adhesive layer, the adhesive surface of the tape T2 is subjected to ATR-IR measurement to obtain an infrared absorption spectrum A, and the adhesive surface of an unused tape T3 having a silicone adhesive layer is subjected to ATR-IR measurement to obtain a difference spectrum between the infrared absorption spectrum A and the infrared absorption spectrum B, which is obtained by ATR-IR measurement, to obtain the infrared absorption spectrum information from the difference spectrum. In this technique, the difference spectrum is obtained by extracting the infrared absorption spectrum information from the difference spectrum at 1260 cm, which is the main absorption band derived from the silicone adhesive layer. -1 Absorption bands around 1000~1100cm -1The infrared absorption spectrum A or infrared absorption spectrum B is multiplied by a constant and then subtracted so that the peak intensities derived from the nearby absorption bands or both of them match. Note that in the Examples section, this method is referred to as the disclosed method.

[0024] The estimation model used in step (S12) is a model obtained using multiple data sets relating to multiple sample donors. Each data set is a combination of infrared absorption spectrum information for the stratum corneum peeled from the skin of a sample donor and a known target index value for that sample donor. The infrared absorption spectrum information is used as the value of the explanatory variable that is the input of the estimation model. The infrared absorption spectrum information is as described in step (S11). However, the infrared absorption spectrum information used to construct the estimation model is obtained for the stratum corneum of the sample provider. However, the subject of evaluation may be included in the sample provider.

[0025] The objective index value is an index value related to the stratum corneum characteristics or the skin surface characteristics, and is used as the value of the objective variable that is the output of the estimation model. The known objective index values ​​included in the above-mentioned data set are obtained in advance by performing evaluation, measurement, etc. on each sample provider.

[0026] The index value relating to the stratum corneum characteristics is an index value that indicates the characteristics of the stratum corneum, for example, an index value relating to the delamination rate of the stratum corneum, an index value relating to the cell shape of the stratum corneum, an index value relating to the intercellular lipids of the stratum corneum, an index value relating to the moisture content of the stratum corneum, etc. The index value relating to the skin surface characteristics is an index value obtained by measuring a replica that reproduces the skin surface shape or the skin surface, and includes an index value indicating the morphology of the skin surface. Examples of the index value indicating the morphology of the skin surface include index values ​​of scale, smoothness and wrinkle state of the skin obtained by measuring the surface shape of the skin using a microscope or the like, roughness of the skin surface obtained by measuring the replica, wrinkle depth, number of wrinkles, wrinkle volume, wrinkle area and wrinkle area ratio. In addition, an index value relating to the moisture content of the stratum corneum, such as the transepidermal water loss (TEWL) described below, is also an index value obtained by measuring the skin surface, and therefore can also be considered as an index value relating to skin surface characteristics. However, in this specification, the index value relating to the moisture content of the stratum corneum is considered to be an index value relating to the stratum corneum characteristics, since it is one of the values ​​expressing the physical properties of the "stratum corneum."

[0027] The index values ​​relating to the delamination rate of the stratum corneum and the cell shape of the stratum corneum can be obtained, for example, by analyzing an image of the stratum corneum captured using tape or the like. The stratum corneum layer peeling rate can be obtained by determining the area of ​​the peeled part and the area of ​​the layer peeling part by binarizing the stratum corneum image, and dividing the area of ​​the layer peeling part by the area of ​​the peeled part. The index value for the shape of the stratum corneum cells can be obtained by measuring the shape index values ​​of multiple stratum corneum cells per person and performing statistical processing such as averaging the multiple measured shape index values. For example, multiple stratum corneum cell images are taken per person, multiple stratum corneum cells are identified per stratum corneum cell image, and the shape index value of each identified stratum corneum cell is measured and statistical processing is performed based on the number of stratum corneum cell images, thereby obtaining an index value for the shape of the stratum corneum cells of the subject. Examples of index values ​​for the shape of the stratum corneum cells include the area of ​​the stratum corneum cells, the length of the stratum corneum cells, and the circularity of the stratum corneum cells.

[0028] The index value for intercellular lipids is the amount of a component of the intercellular lipids or the ratio of the amount of each component, for example, the total amount of intercellular lipids, the amount of ceramide, cholesterol or free fatty acid in the intercellular lipids, or the amount of each ceramide molecular species in the intercellular lipids or the ratio of the amount of each ceramide molecular species. The index value of intercellular lipids can be measured, for example, by an analytical method combining liquid chromatography (LC) and mass spectrometry (MS). Examples of index values ​​of intercellular lipids include the total amount of intercellular lipids, the amount of ceramide, the amount of cholesterol, the amount of free fatty acids, the amount of each ceramide molecular species (NDS, NS, NH, NP, ADS, AS, AH, AP, EOS, EOH, EOP, etc.), and the ratio of the amount of each ceramide molecular species (NP / NS, etc.).

[0029] The index value for the moisture content of the stratum corneum is an index value indicating the amount of moisture contained in the stratum corneum (also referred to as stratum corneum moisture content). However, the index value here is not limited to a value strictly indicating the amount of moisture contained only in the stratum corneum, and may be an index value that mainly includes the amount of moisture contained in the stratum corneum, as well as the amount of moisture contained in tissues below the stratum corneum in the epidermis. The moisture content of the stratum corneum can be measured, for example, by a conductance measurement method, a capacitance measurement method, or the like. In addition, in this specification, the transepidermal water loss (TEWL), which is known as an evaluation value indicating the barrier function of the skin and means the amount of water that evaporates through the stratum corneum, is also considered as an index value related to the amount of water in the stratum corneum. The evaluation value here includes an index value indicating not only the barrier function from the inside of the skin to the outside, but also the barrier function from the outside of the skin to the inside. However, as described above, the transepidermal water loss (TEWL) can also be considered as an index value related to the skin surface characteristics.

[0030] The estimation model is constructed using a set of data of such known target index values ​​and infrared absorption spectrum information for multiple sample providers. In this embodiment, an estimation model constructed using multivariate analysis is exemplified. That is, the estimation model in this embodiment is obtained by performing multivariate analysis on multiple data sets related to multiple sample providers. Well-known multivariate analysis techniques include, for example, multiple regression analysis, principal component analysis, partial least squares regression (PLS), and principal component regression analysis (PCR). In this embodiment, the specific technique of multivariate analysis used is not limited as long as it is possible to construct an estimation model in which the infrared absorption spectrum information is an explanatory variable and the objective index value is an objective variable. The estimation model in this embodiment can also be expressed as an estimation formula.

[0031] The estimation model may be composed of a convolutional neural network including a deep neural network, and may be realized by a combination of a computer program and a parameter, a combination of a plurality of functions and parameters, etc. In addition, when the estimation model is constructed by a neural network, and the input layer, the intermediate layer, and the output layer are regarded as a unit of one neural network, the estimation model may refer to one neural network or a combination of multiple neural networks. In addition, the model may be composed of a combination of multiple estimation formulas, or may be composed of one estimation formula. In addition, the estimation model may be composed of a combination of a neural network and another model such as a regression formula or a discriminant formula, and may be a model in which a value obtained as an output of the neural network is input to the other model and the obtained value is output.

[0032] In this embodiment, the estimation model may be one estimation formula with infrared absorption spectrum information including a plurality of intensity values ​​as explanatory variables and one target index value as a target variable, or may be a set of two or more estimation formulas with mutually different target index values ​​as target variables, respectively. In the latter case, two or more target index values ​​are obtained in step (S13). Furthermore, when the estimation model is constructed as an AI model consisting of a neural network, infrared absorption spectrum information including multiple intensity values ​​is input, and one or multiple target index values ​​are output.

[0033] In step (S14), CPU 11 outputs the target index value acquired in step (S13). CPU 11 can display the target index value on display device 15, can output the target index value to a printer device connected via input / output I / F 13 or communication unit 14, and can record or transmit the target index value to a portable recording medium or another computer via input / output I / F 13 or communication unit 14. In this way, the output destination and output method of the target index value are not limited in any way. Furthermore, the CPU 11 may output the target index value acquired in step (S13) as a numerical value as it is, or may output the acquired target index value after normalizing it by digit alignment, etc. This embodiment does not limit the output format of the target index value.

[0034] As described above, in this embodiment, the infrared absorption spectrum information on the stratum corneum peeled from the skin of the subject is 600 cm -1 More than 1800cm -1 The first wavenumber region below and 2800cm -1 More than 3700cm -1 Infrared absorption spectrum information including multiple intensity values ​​in a relatively wide, specific wavenumber range that includes at least the second wavenumber range below is input into the estimation model, and the target index value of the person being evaluated is estimated. The target index value estimated from the infrared absorption spectrum information on the stratum corneum is an index value related to the stratum corneum characteristics or the skin surface characteristics.

[0035] In the above-mentioned conventional methods, attention was focused on peaks in a specific wavenumber region in the infrared absorption spectrum of the stratum corneum when evaluating the properties of the stratum corneum. However, the present inventor has newly discovered that it is possible to estimate the characteristics of the stratum corneum or the skin surface with higher accuracy by turning attention to a relatively wide, specific wavenumber region in the infrared absorption spectrum of the stratum corneum that includes at least the above-mentioned first and second wavenumber region, and using multiple intensity values ​​extracted from such a wide wavenumber region (intensity values ​​in non-peak regions, multiple intensity values ​​sampled at regular intervals unrelated to peaks, etc.). As a result, according to this embodiment, by using multiple intensity values ​​in the specified wave number region in the infrared absorption spectrum of the stratum corneum, it is possible to estimate an index of the skin surface including the stratum corneum with high accuracy. Furthermore, such skin surface indexes can be easily estimated by simply obtaining infrared absorption spectrum information on the stratum corneum peeled from the skin of the subject, without performing individual processes for obtaining indices of the skin surface including the stratum corneum, such as measuring the skin surface using various measuring devices or taking images, etc. Furthermore, since such infrared absorption spectrum information can be obtained from the stratum corneum in a state where it is peeled from the skin of the subject without contacting the subject, this embodiment enables remote evaluation and is also useful in terms of hygiene.

[0036] Some or all of the above-described embodiments and modifications may be specified as follows: However, the above-described embodiments and modifications are not limited to the following descriptions.

[0037] <1> One or more processors An acquisition step of acquiring infrared absorption spectrum information regarding the stratum corneum peeled from the skin of the subject; an estimation step of estimating the target index value of the subject by inputting the acquired infrared absorption spectrum information into an estimation model obtained by using a plurality of data sets of infrared absorption spectrum information on the stratum corneum peeled from the skin of a plurality of sample donors and known target index values; Run the infrared absorption spectrum information includes a plurality of intensity values ​​in a predetermined wave number region; The target index value is an index value related to a stratum corneum characteristic or a skin surface characteristic. Skin index estimation method.

[0038] <2> The infrared absorption spectrum information is -1 More than 1800cm -1 Several intensity values ​​in the first wavenumber region below 2800 cm -1 More than 3700cm -1 At least a plurality of intensity values ​​in the following second wave number region: <1> The skin index estimation method according to claim 1. <3> The infrared absorption spectrum information includes at least a plurality of intensity values ​​in non-peak regions of the first wave number region and the second wave number region. <2> The skin index estimation method according to claim 1. <4> The infrared absorption spectrum information includes a plurality of intensity values ​​sampled at regular wavenumber intervals from the first wavenumber region and at regular wavenumber intervals from the second wavenumber region, <2> or <3> The skin index estimation method according to claim 1. <5> The target index value is a stratum corneum delamination rate, a stratum corneum cell area, a stratum corneum cell length, or a stratum corneum cell circularity rate. <1> from <4> 2. The skin index estimating method according to claim 1 , <6> The target index value is the total amount of intercellular lipids, the amount of ceramide, the amount of cholesterol, or the amount of free fatty acid, the amount of each ceramide molecular species in the intercellular lipids, or the ratio of the amount of each ceramide molecular species in the intercellular lipids. <1> from <4> 2. The skin index estimating method according to claim 1 , <7> The target index value is the stratum corneum moisture content or the transepidermal water loss. <1> from <4> 2. The skin index estimating method according to claim 1 , <8> The target index value is an index value of the scale state, the smoothness or the wrinkle state of the skin obtained by measuring the surface shape of the skin, or an index value of the roughness of the skin surface, the depth of wrinkles, the number of wrinkles, the volume of wrinkles, the area of ​​wrinkles or the wrinkle area ratio obtained by measuring a replica that reproduces the surface shape of the skin. <1> from <4> 2. The skin index estimating method according to claim 1 ,

[0039] <9> A skin index estimation device including at least one processor and a memory, <1> from <8> 2. A skin index estimation device capable of executing any one of the skin index estimation methods described above.

[0040] The above content will be described in more detail below with reference to several examples, but the description of each example does not impose any limitations on the above content. EXAMPLES

[0041] In Example 1, 390 women aged from their 20s to their 50s served as sample donors, and a data set of infrared absorption spectrum information and target index values ​​for each sample donor was obtained. Infrared absorption spectrum information was obtained by the techniques disclosed above. In addition, the infrared absorption spectrum information is the 600 cm -1 From 4000cm -1 Wavenumber range (wavenumber resolution 0.5 cm -1 ) were used. Regarding the target index value, multiple types of target index values ​​were obtained from each sample provider using an acquisition method corresponding to each target index value. The types of target index values ​​will be described later.

[0042] The collected datasets were divided 7:3, with the former (70%) being used to build an estimation model and the latter (30%) being used to verify the estimation model. The estimation model was constructed by applying partial least squares (PLS) to multiple datasets for constructing the estimation model, and the model (estimation equation) that minimized the predicted residual sum of squares (PRESS) in K-fold cross-validation (K = 5) was selected. The constructed estimation model was then verified using multiple validation data sets. Specifically, the correlation between the target index value (estimated index value) obtained by inputting the infrared absorption spectrum information of the validation data set into the estimation model and the known target index value of the data set was verified.

[0043] 4 to 7 are tables showing the estimation accuracy for each objective index value of the estimation model, and show the correlation coefficient (R value) and P value indicating the estimation accuracy for each objective index value.

[0044] Figure 4 is a table showing the estimation accuracy for each objective index value related to the stratum corneum delamination rate and stratum corneum cell shape. In Figure 4, the objective index values ​​related to the stratum corneum cell shape include the stratum corneum cell area, stratum corneum cell length, and stratum corneum cell circularity. The stratum corneum cell length indicates the maximum length of a single stratum corneum cell, and the stratum corneum cell circularity is a value that approaches 1 for a perfect circle, and approaches 1 as the shape approaches a perfect circle. In this embodiment, four images of the stratum corneum were taken per person, and approximately 10 to 15 stratum corneum cells were identified in each stratum corneum image. The shape index value of each identified stratum corneum cell was then measured and the average of the four stratum corneum images was taken to obtain the actual measured values ​​of each target index in Figure 4. As shown in Figure 4, the P values ​​for the estimation accuracy of the target index values ​​of the stratum corneum delamination rate, stratum corneum cell area, stratum corneum cell length, and stratum corneum cell circularity rate were sufficiently small (at a significance level of 1%), and the correlation coefficients were 0.25 or higher.

[0045] Figure 5 is a table showing the estimation accuracy for each objective index value related to stratum corneum intercellular lipids. The objective index values ​​shown in Figure 5 are the amounts of ceramide NDS, ceramide NS, ceramide NH, ceramide NP, ceramide ADS, ceramide AS, ceramide AH, ceramide AP, ceramide EOS, ceramide EOH, and ceramide EOP, the total amount of ceramide, the total amount of free fatty acid, the amount of cholesterol, the amount of cholesterol sulfate, the total amount of stratum corneum intercellular lipids, and the ratio of the amount of ceramide NP to the amount of ceramide NS (NP / NS). As shown in Figure 5, with regard to the estimation accuracy of the target indicator values ​​related to stratum corneum intercellular lipids, except for ceramide NS amount and ceramide AS amount, the P value was sufficiently small (at the 1% significance level) and the correlation coefficient was 0.25 or more. With regard to the estimation accuracy of ceramide AS amount, the correlation coefficient was 0.201 at the 5% significance level, and with regard to the estimation accuracy of ceramide NS amount, the correlation coefficient was 0.180 at the 10% significance level.

[0046] Figure 6 is a table showing the estimation accuracy for each objective index value related to the moisture content of the stratum corneum. The objective index values ​​shown in Figure 6 are transepidermal water loss (TEWL), the moisture content of the stratum corneum obtained by the capacitance measurement method, and the moisture content of the stratum corneum obtained by the conductance measurement method. As shown in FIG. 6, the actual values ​​of transepidermal water loss (TEWL) were measured using a Tewameter (MPA580, Courage+Khazaka, Germany), the actual values ​​of the items labeled "Corneometer-Capacitance" were measured using a Corneometer (MPA580, Courage+Khazaka, Germany) as a capacitance measurement method, and the actual values ​​of the items labeled "Skicon-Conductance" were measured using Skicon (Yayoi) as a conductance measurement method. As shown in FIG. 6, with regard to the estimation accuracy of the objective index value related to the stratum corneum moisture content, the P value was sufficiently small (at the 1% significance level) and the correlation coefficient was 0.45 or higher.

[0047] Fig. 7 is a table showing the estimation accuracy for each objective index value related to skin surface characteristics. The objective index values ​​shown in Fig. 7 are index values ​​showing the scale condition (SESC), skin smoothness (SESM), and wrinkle condition (SEW) obtained by surface morphology measurement of the cheek skin, and the arithmetic mean roughness (Ra), root mean square roughness (Rq), total mean wrinkle depth, ten-point mean roughness (Rz), number of wrinkles, total wrinkle volume, total wrinkle area, and wrinkle area ratio obtained by surface morphology measurement of a replica of the corner of the eye.

[0048] The actual measured values ​​of the items marked "Visioscan" in Fig. 7 were measured from the skin of the cheek using a Visioscan (Courage+Khazaka, Germany). The actual measured values ​​of the items marked "replica" in Fig. 7 were obtained by applying a silicone agent for skin replicas (SILFLO, FLEXICO) to the corners of the eyes, hardening it, and then peeling it off to create a concave-convex replica that reproduced the surface shape of the skin, and then analyzing the replica with a three-dimensional skin analysis system, PRIMOS (Canfield Scientific). The arithmetic mean roughness (Ra) is the average value obtained by adding up the absolute values ​​of the distance from the mean line to the measurement curve, the root mean square roughness (Rq) is the root mean square over the reference length, the total mean wrinkle depth is the average depth of wrinkles extracted from the three-dimensional shape shape-corrected for the replica's surface shape, the ten-point mean roughness (Rz) is the sum (distance) between the average of the five highest peaks and the average depth of the five lowest valleys, the number of wrinkles is the total number of wrinkles extracted from the three-dimensional shape shape-corrected for the replica's surface shape, the total wrinkle volume is the sum of the volumes of each wrinkle extracted from the three-dimensional shape shape-corrected for the replica's surface shape, the total wrinkle area is the sum of the areas of each wrinkle extracted from the three-dimensional shape shape-corrected for the replica's surface shape, and the wrinkle area ratio is the ratio of the total wrinkle area to the area of ​​the region from which wrinkles are extracted.

[0049] As shown in Figure 7, the estimation accuracy of the target index value related to the skin surface characteristics shows a correlation coefficient of 0.2 or more at the 5% or 1% significance level, except for "Visioscan-SESM", "Replica - total wrinkle area", and "Replica - wrinkle area ratio". The estimation accuracy of "Replica - wrinkle area ratio" shows a correlation coefficient of 0.185 at the 5% significance level, and the estimation accuracy of "Visioscan-SESM" and "Replica - total wrinkle area" shows an estimation accuracy of 0.16 or more at the 10% significance level.

[0050] Thus, according to Example 1, the 600 cm -1 From 4000cm -1 A fixed interval in the wavenumber range (wavenumber resolution 0.5 cm -1 It has been demonstrated that by using the absorbance values ​​of a large number (6,950) of these samples, it is possible to estimate index values ​​for the characteristics of the stratum corneum and skin surface with high accuracy.

[0051] Fig. 8 is a graph showing weights (regression coefficients) for absorbance of each wave number component (each explanatory variable) in an estimation model (estimation formula) with stratum corneum characteristics as the target index value. Fig. 8(a) is a graph related to the estimation model (estimation formula) with stratum corneum moisture content measured using Skicon (manufactured by Yayoi) as the target index value, Fig. 8(b) is a graph related to the estimation model (estimation formula) with transepidermal water loss (TEWL) as the target index value, Fig. 8(c) is a graph related to the estimation model (estimation formula) with the ratio (NP / NS) between the amount of ceramide NP and the amount of ceramide NS as the target index value, and Fig. 8(d) is a graph related to the estimation model (estimation formula) with the stratum corneum delamination rate as the target index value. In FIG. 8, a wave number component having a large absolute value on the vertical axis of the graph indicates a high contribution rate to the target index value.

[0052] According to Figure 8, 600 cm -1 More than 1800cm -1 The first wavenumber region below and 2800cm -1 More than 3700cm -1 Since there are multiple peaks in the second wavenumber region described below, it can be seen that the contribution rate of the intensity values ​​in the first wavenumber region and the second wavenumber region to the target index value is higher than the intensity values ​​in other wavenumber regions. Therefore, as in this embodiment, 600 cm -1 More than 1800cm -1 Several intensity values ​​in the first wavenumber region below 2800 cm -1 More than 3700cm -1 It has been demonstrated that the accuracy of estimating the target index value using the estimation model can be improved by using infrared absorption spectrum information that includes at least a plurality of intensity values ​​in the second wave number region described below. EXAMPLES

[0053] In the above-mentioned Example 1, an example was shown in which infrared absorption spectrum information was obtained by the above-mentioned disclosed method, i.e., a method in which the stratum corneum is transferred from an adhesive tape T1 to a tape T2 having a silicone adhesive layer, the adhesive surface of the tape T2 is subjected to ATR-IR measurement to obtain an infrared absorption spectrum A, and the adhesive surface of an unused tape T3 having a silicone adhesive layer is subjected to ATR-IR measurement to obtain an infrared absorption spectrum B, and the infrared absorption spectrum information is extracted from the difference spectrum.

[0054] In Example 2, infrared absorption spectrum information was obtained by a method different from the disclosed method employed in Example 1. That is, in Example 2, infrared absorption spectrum information was obtained by collecting stratum corneum from the skin surface with adhesive tape T1, transferring the collected stratum corneum from the adhesive tape T1 to tape T2 having a silicone adhesive layer, and measuring the adhesive surface of tape T2 with an infrared spectrometer. Therefore, it can be said that the infrared absorption spectrum information in Example 2 includes at least spectrum information related to the components of adhesive tape T2, stratum corneum components, and moisture.

[0055] In Example 2, an estimation model was constructed in the same manner as in Example 1, and the correlation between the target index value (estimated index value) obtained by inputting the infrared absorption spectrum information of the validation data set (30% of the data set) into the estimation model and the known target index value of the data set was verified. Then, the correlation verified in Example 1 was compared with the correlation verified in Example 2.

[0056] As a result, for the estimated model (estimation equation) with stratum corneum moisture content (Skicon-conductance) as the target index value, the correlation coefficient obtained in Example 1 was 0.491 and the P value was 2.49E-08 (see Figure 6), while the correlation coefficient obtained in Example 2 was 0.520 and the P value was 2.68E-09. Regarding the estimation model (estimation equation) with the stratum corneum moisture content (Corneometer-capacitance) as the target index value, the correlation coefficient obtained in Example 1 was 0.577 and the P value was 2.15E-11 (see Figure 6), while the correlation coefficient obtained in Example 2 was 0.606 and the P value was 1.14E-12. Regarding the estimation model (estimation equation) with transepidermal water loss (TEWL) as the target index value, the correlation coefficient obtained in Example 1 was 0.460 and the P value was 2.91E-07 (see FIG. 6 ), and the correlation coefficient obtained in Example 2 was 0.530 and the P value was 1.53E-09. Regarding the estimated model (estimation formula) in which the ratio between the amount of ceramide NP and the amount of ceramide NS (NP / NS) was used as the target index value, the correlation coefficient obtained in Example 1 was 0.607 and the P value was 1.00E-12 (see Figure 5), while the correlation coefficient obtained in Example 2 was 0.573 and the P value was 3.17E-11. Regarding the estimated model (estimation formula) with the stratum corneum delamination rate as the target index value, the correlation coefficient obtained in Example 1 was 0.453 and the P value was 3.25E-07 (see Figure 4), while the correlation coefficient obtained in Example 2 was 0.507 and the P value was 6.50E-09. Therefore, even when infrared absorption spectrum information obtained by a method different from that of Example 1 is used as in Example 2, it was found that the estimation accuracy of the estimation model can be maintained almost similarly to Example 1. EXAMPLES

[0057] In Example 1, the infrared absorption spectrum information is the 600 cm -1 From 4000cm -1 Wavenumber range (wavenumber resolution 0.5 cm -1 In other words, the absorbances included in the infrared absorption spectrum information used in Example 1 are at a constant wavenumber interval (wavenumber resolution 0.5 cm -1 ) intensity value. In Example 3, the wave number interval is constant, but the wave number interval is larger than that in Example 1, and the wave number interval is 600 cm -1 From 4000cm -1 In other words, the number of absorbances in the infrared absorption spectrum information used in Example 3 was 1 / 278 of that in Example 1.

[0058] In Example 3, an estimation model was constructed in the same manner as in Examples 1 and 2, and the correlation between the target index value (estimated index value) obtained by inputting infrared absorption spectrum information of a data set for verification (30% of the data set) into the estimation model and the known target index value of the data set was verified. Then, the correlation verified in Example 1 was compared with the correlation verified in Example 3.

[0059] As a result, for the estimated model (estimation equation) with stratum corneum moisture content (Skicon-conductance) as the target index value, the correlation coefficient obtained in Example 1 was 0.491 and the P value was 2.49E-08 (see Figure 6), while the correlation coefficient obtained in Example 3 was 0.522 and the P value was 2.26E-09. Regarding the estimation model (estimation equation) with the stratum corneum moisture content (Corneometer-capacitance) as the target index value, the correlation coefficient obtained in Example 1 was 0.577 and the P value was 2.15E-11 (see Figure 6), while the correlation coefficient obtained in Example 3 was 0.574 and the P value was 3.12E-11. Regarding the estimation model (estimation equation) with transepidermal water loss (TEWL) as the target index value, the correlation coefficient obtained in Example 1 was 0.460 and the P value was 2.91E-07 (see FIG. 6), while the correlation coefficient obtained in Example 3 was 0.417 and the P value was 4.35E-06. Regarding the estimated model (estimation formula) in which the ratio between the amount of ceramide NP and the amount of ceramide NS (NP / NS) was used as the target index value, the correlation coefficient obtained in Example 1 was 0.607 and the P value was 1.00E-12 (see Figure 5), while the correlation coefficient obtained in Example 3 was 0.545 and the P value was 4.38E-10. Regarding the estimation model (estimation formula) with the stratum corneum delamination rate as the target index value, the correlation coefficient obtained in Example 1 was 0.453 and the P value was 3.25E-07 (see Figure 4), while the correlation coefficient obtained in Example 3 was 0.542 and the P value was 3.37E-10. Therefore, even when infrared absorption spectrum information formed from absorbances at wavenumber intervals and numbers different from those in Example 1 is used as in Example 3, it was found that the estimation accuracy of the estimation model can be maintained almost similarly to Example 1.

[0060] [Comparative Example] Finally, the method disclosed in the above Patent Document 2 will be presented as a comparative example, and the results of comparing the estimation accuracy between this comparative example and Example 1 will be described. As described above, the comparative example is a method in which the peak area ratio β / α is calculated and the calculated ratio β / α is used as an index to evaluate the properties of the stratum corneum of the skin for purposes other than medical treatment. The method of this comparative example estimated transepidermal water loss (TEWL), and the estimation accuracy was calculated by comparing the obtained estimated value with the actual measured value measured as described above. As a result, the estimation accuracy of the comparative example was 0.274 in correlation coefficient (R value) and 3.30E-03 in P value, whereas the estimation accuracy of the method of Example 1 was 0.460 in correlation coefficient (R value) and 2.91E-07 in P value, as shown in FIG. Therefore, Example 1 enables estimation of stratum corneum characteristics with higher accuracy than the Comparative Example, demonstrating the superiority of Example 1. [Explanation of symbols]

[0061] 10 Information processing device (skin index estimation device) 11 CPU 12. Memory 13 Input / Output Interface 14 Communication unit 15 Display device 16 Input Devices

Claims

1. One or more processors An acquisition step of acquiring infrared absorption spectrum information regarding the stratum corneum peeled from the skin of the subject; an estimation step of estimating the target index value of the subject by inputting the acquired infrared absorption spectrum information into an estimation model obtained by using a plurality of data sets of infrared absorption spectrum information on the stratum corneum peeled from the skin of a plurality of sample donors and known target index values; Run the infrared absorption spectrum information includes at least a plurality of intensity values ​​in a first wavenumber region of 600 cm −1 or more and 1800 cm −1 or less and a plurality of intensity values ​​in a second wavenumber region of 2800 cm −1 or more and 3700 cm −1 or less; The target index value is an index value related to a stratum corneum characteristic or a skin surface characteristic. Skin index estimation method.

2. One or more processors An acquisition step of acquiring infrared absorption spectrum information regarding the stratum corneum peeled from the skin of the subject; an estimation step of estimating the target index value of the subject by inputting the acquired infrared absorption spectrum information into an estimation model obtained by using a plurality of data sets of infrared absorption spectrum information on the stratum corneum peeled from the skin of a plurality of sample donors and known target index values; Run the infrared absorption spectrum information includes at least a plurality of intensity values ​​in a peak region and a non-peak region of a first wavenumber region of 600 cm -1 or more and 1800 cm -1 or less, and a plurality of intensity values ​​in a peak region and a non-peak region of a second wavenumber region of 2800 cm -1 or more and 3700 cm -1 or less; The target index value is an index value related to a stratum corneum characteristic or a skin surface characteristic. Skin index estimation method.

3. One or more processors An acquisition step of acquiring infrared absorption spectrum information regarding the stratum corneum peeled from the skin of the subject; an estimation step of estimating the target index value of the subject by inputting the acquired infrared absorption spectrum information into an estimation model obtained by using a plurality of data sets of infrared absorption spectrum information on the stratum corneum peeled from the skin of a plurality of sample donors and known target index values; Run the infrared absorption spectrum information includes at least a plurality of intensity values ​​sampled at regular wavenumber intervals from a first wavenumber region of 600 cm −1 to 1800 cm −1 and at regular wavenumber intervals from a second wavenumber region of 2800 cm −1 to 3700 cm −1 , The target index value is an index value related to a stratum corneum characteristic or a skin surface characteristic. Skin index estimation method.

4. The target index value is a stratum corneum delamination rate, a stratum corneum cell area, a stratum corneum cell length, or a stratum corneum cell circularity rate. The skin index estimation method according to claim 1 .

5. The target index value is the total amount of intercellular lipids, the amount of ceramide, the amount of cholesterol, or the amount of free fatty acid, the amount of each ceramide molecular species in the intercellular lipids, or the ratio of the amount of each ceramide molecular species in the intercellular lipids. The skin index estimation method according to claim 1 .

6. The target index value is the stratum corneum moisture content or the transepidermal water loss. The skin index estimation method according to claim 1 .

7. The target index value is an index value of the scale state, the smoothness or the wrinkle state of the skin obtained by measuring the surface shape of the skin, or an index value of the roughness of the skin surface, the depth of wrinkles, the number of wrinkles, the volume of wrinkles, the area of ​​wrinkles or the wrinkle area ratio obtained by measuring a replica that reproduces the surface shape of the skin. The skin index estimation method according to claim 1 .

8. A skin index estimation device comprising at least the one or more processors and a memory, The estimation model is available, The memory stores a computer program; The skin index estimation device is capable of executing the skin index estimation method according to claim 1 by the one or more processors executing the computer program.

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