Tactile classification methods

Abstract

One embodiment of the present invention relates to a method comprising: a step of determining the state of a user's bare skin; and a step of inferring the feel of the cosmetic on the user's skin after applying the cosmetic from the determined state of the bare skin based on a correspondence between the state of the bare skin and the tactile feel of the cosmetic on skin after applying the cosmetic. Thus, the tactile feel of the cosmetic on skin after applying the cosmetic is evaluated considering the state of the skin.

Description

Technical Field

[0001] This invention relates to a method for classifying tactile sensations. Background Technology

[0002] Previously, as part of the evaluation of cosmetics such as skin care lotions (toners), there has been an evaluation of the user experience of the cosmetics (e.g., Patent Document 1). Specifically, this evaluation assesses the tactile sensation felt by a person who has applied the cosmetic when touching their own skin that has been coated with the cosmetic.

[0003] Existing technical documents

[0004] Patent Document 1: Japanese Patent Application Publication No. 2008-64722 Summary of the Invention

[0005] The problem that the invention aims to solve

[0006] However, previous evaluations of the feel of cosmetics did not take into account the nature of the skin on which the cosmetics were applied.

[0007] Therefore, the object of the present invention is to evaluate the feel of cosmetics on skin after applying them, taking into account the condition of the skin.

[0008] Technical solutions for solving the problem

[0009] One embodiment of the present invention relates to a method comprising: a step of determining the state of a user's bare skin (natural skin, skin without makeup); and a step of inferring the feel of the cosmetic on the user's skin after applying the cosmetic from the determined state of the bare skin based on a correspondence between the state of the bare skin and the tactile feel of the cosmetic on skin after applying the cosmetic.

[0010] Invention Effects

[0011] According to the present invention, the tactile feel of cosmetics on skin after application can be evaluated taking into account the condition of the skin. Attached Figure Description

[0012] Figure 1 This diagram is used to illustrate the skincare water used in the experiment.

[0013] Figure 2 It is a diagram used to illustrate friction.

[0014] Figure 3 It is a diagram used to illustrate vibration.

[0015] Figure 4 It is a chart showing the changes in friction after applying various cosmetics.

[0016] Figure 5It is a chart showing the changes in vibration after applying various cosmetics.

[0017] Figure 6 It is a graph showing the changes in friction between different clusters.

[0018] Figure 7 It is a graph showing the changes in vibration in each cluster.

[0019] Figure 8 It is a diagram used to illustrate the bare skin state of each cluster.

[0020] Figure 9 It is a diagram used to illustrate the bare skin state of each cluster.

[0021] Figure 10 This is a graph used to illustrate the results of sensory evaluations for each cluster.

[0022] Figure 11 This is a flowchart of a process for predicting the tactile sensation after application, according to one embodiment of the present invention.

[0023] Figure 12 This is a flowchart of a process for predicting the state of bare skin according to one embodiment of the present invention.

[0024] Figure 13 This is an overall configuration diagram related to one embodiment of the present invention.

[0025] Figure 14 This is a functional block diagram of an evaluation device according to one embodiment of the present invention.

[0026] Figure 15 This is a block diagram illustrating an example of the hardware configuration of an evaluation device according to one embodiment of the present invention. Detailed Implementation

[0027] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings.

[0028] Furthermore, this specification describes an embodiment in which values ​​representing tactile sensation are obtained by measuring at least one of friction and vibration generated on skin with cosmetics applied or on bare skin; however, the values ​​representing tactile sensation are not limited to this. For example, values ​​representing tactile sensation may also be used, such as temperature (°C) measured using a temperature sensor, and surface shape (μm) measured using a laser displacement meter, a confocal laser microscope, a white light interferometer, or a contact roughness measuring instrument.

[0029] First, refer to Figures 1-10 This study explains the relationship between the state of a subject's bare skin and the tactile sensation of cosmetics on the skin of a subject who had applied cosmetics.

[0030] <Experimental Procedure>

[0031] (1) First, the condition of the bare skin on the subject's face was measured.

[0032] (2) Next, apply various cosmetics (skin care lotion A, skin care lotion B, skin care lotion C, and skin care lotion D) to the subject's face.

[0033] (3) Next, the tactile sensation of the cosmetics on the skin of the subjects who applied each cosmetic was measured (hereinafter (A)) and the sensory evaluation of the subjects was carried out (hereinafter (B)).

[0034] (A) The tactile sensation of the cosmetics on the skin of the subjects after applying each cosmetic was measured. Specifically, the measurements were taken immediately after application of each cosmetic (0 seconds), 30 seconds, 60 seconds, 90 seconds, 120 seconds, 180 seconds, and 240 seconds later.

[0035] (B) Subjects answered a questionnaire about the feel of their skin when they touched it with various cosmetics applied (specifically, the degree of moisturization).

[0036] <Subject>

[0037] The subjects of the experiment were 40 healthy Japanese women aged 21 to 68.

[0038] <Cosmetics used in the experiment>

[0039] Figure 1 This diagram is used to illustrate the skincare water used in the experiment. Figure 1 This indicates the viscosity and sensory evaluation results (specifically, the degree of moisturizing (hydration)) of skin care lotion A, skin care lotion B, skin care lotion C, and skin care lotion D.

[0040] <Measurement of bare skin condition>

[0041] The following items were measured on the subject's bare skin. Additionally, the equipment used in the measurement is indicated in parentheses.

[0042] • Water content of the stratum corneum (Corneometer CM 825 (registered trademark))

[0043] • Skin Visiom II

[0044] • Skin elasticity (Cutometer CT580 (registered trademark))

[0045] • Softness sensor of the stratum corneum

[0046] • Transdermal water loss (VapoMeter (registered trademark))

[0047] • Sebum (Sebumeter SM 815 (registered trademark))

[0048] <Measurement of tactile sensation>

[0049] In one embodiment of the invention, at least one of friction and vibration generated on skin with cosmetic applied is measured, and the measured value is used as a value representing the tactile feel of the cosmetic on the skin with cosmetic applied.

[0050] In one embodiment of the invention, a sensor capable of measuring friction and vibration while a probe touches the skin is rotating on a rotating motor is used. Furthermore, the probe of this sensor is made of metal with a surface that mimics a fingerprint. Additionally, in this sensor, friction is measured by a 6-axis force sensor, and vibration is measured by a 3-axis accelerometer.

[0051] Figure 2 This is a diagram used to illustrate friction. For example... Figure 2 As shown, the coefficient of friction was measured at various times. The coefficient of friction (the average of Fx (frictional force) / Fz (perpendicular force)) is used as the value representing friction. Alternatively, frictional force (N) can be used instead of the coefficient of friction, or frictional force (N) can be used in addition to the coefficient of friction.

[0052] Figure 3 It is a diagram used to illustrate vibration. For example... Figure 3 As shown, the acceleration (G) was measured at various times. The amplitude spectrum (G / Hz) (the average value between 250 Hz and 1000 Hz) was used as the value representing the vibration.

[0053] <Experimental Results>

[0054] The results of the experiment are explained below.

[0055] Figure 4 This indicates that various cosmetics have been applied (see reference). Figure 1 The graph illustrates the change in the coefficient of friction after using skincare products A, B, C, and D. Figure 4 It represents the average value of the coefficient of friction and a standard deviation (error range) at various times (0 seconds, 30 seconds, 60 seconds, 90 seconds, 120 seconds, 180 seconds, and 240 seconds after applying the cosmetic.

[0056] like Figure 4 As shown, the coefficient of friction varies among different cosmetics. Furthermore, the coefficient of friction differs significantly among the subjects.

[0057] Figure 5This indicates that various cosmetics have been applied (see reference). Figure 1 The chart illustrates the changes in the amplitude spectrum after applying skincare toners A, B, C, and D. Figure 5 It represents the average value of the amplitude spectrum at each time point (0 seconds, 30 seconds, 60 seconds, 90 seconds, 120 seconds, 180 seconds, and 240 seconds after applying the cosmetic) and a standard deviation (error range).

[0058] like Figure 5 As shown, the amplitude spectrum differs among the various cosmetics. Furthermore, the amplitude spectrum varies significantly among the subjects.

[0059] By based on Figure 4 and Figure 5 The friction coefficients and amplitude spectra shown were analyzed using cluster analysis (also known as grouping or clustering), and the subjects were classified into three clusters. Cluster analysis is a data analysis method that classifies data without external criteria. (Refer to...) Figure 6 and Figure 7 The changes in friction and vibration of each cluster are explained.

[0060] Figure 6 It is a graph showing the changes in friction among different clusters. For example... Figure 6 As shown, the friction coefficient of cluster 1 is greater than that of other clusters (that is, clusters 2 and 3).

[0061] Figure 7 It is a graph showing the changes in vibration in each cluster. For example... Figure 7 As shown, the amplitude spectrum of cluster 3 is smaller than that of the other clusters (that is, clusters 1 and 2). Furthermore, the correlations between cosmetics differ between clusters.

[0062] <The state of bare skin>

[0063] Reference Figure 8 and Figure 9 This describes the bare skin state of each cluster.

[0064] Figure 8 It is a diagram used to illustrate the bare skin state of each cluster. Figure 8 It represents the stratum corneum's water content (Capacitance), skin groove state (VC1), skin elasticity (R7), and stratum corneum softness (Resonant frequency change) of each cluster.

[0065] Figure 9 This is a diagram used to illustrate the bare skin state of each cluster. For example... Figure 9As shown, in cluster 1, the stratum corneum moisture content is "average," the skin groove condition is "average," the skin elasticity is "average," the stratum corneum softness is "soft," and the age group is "average." In cluster 2, the stratum corneum moisture content is "low," the skin groove condition is "uneven," the skin elasticity is "low," the stratum corneum softness is "hard," and the age group is "high." In cluster 3, the stratum corneum moisture content is "average," the skin groove condition is "average," the skin elasticity is "average," the stratum corneum softness is "average," and the age group is "low."

[0066] according to Figure 8 and Figure 9 The results showed that the skin of the subjects in cluster 1 was "skin with a soft stratum corneum", the skin of the subjects in cluster 2 was "skin with a hard and dry stratum corneum, lack of elasticity, and disordered texture", and the skin of the subjects in cluster 3 was "standard skin".

[0067] Figure 10 This is a graph used to illustrate the sensory evaluation results of each cluster. For example... Figure 10 As shown, sensory evaluation results differed between clusters. This indicates that the state of the bare skin also affects sensory evaluation.

[0068] Thus, a relationship was discovered between the state of bare skin and the tactile sensation of cosmetics on skin after application. That is, it can be seen that classification or regression models can be used to infer the tactile sensation of cosmetics on skin after application (also known as the post-application sensation) from the state of bare skin. Furthermore, it can be seen that classification or regression models can be used to infer the state of bare skin from the tactile sensation of cosmetics on skin after application (also known as the post-application sensation). The following explains the methods for inferring (classifying or regressing) the post-application sensation and the methods for inferring (classifying or regressing) the state of bare skin using this relationship.

[0069] <Method>

[0070] The following describes the processes for "prediction of the feel after application" and "prediction of the bare skin state". Furthermore, while the evaluation device 10 (described later) will be used to perform each process, a person may also perform at least some of the processes.

[0071] In addition, skin care water was used in the above experiment, but any cosmetic product (such as skin care water, lotion, serum, cream, etc.) can also be used to generate the relationship between the feel of bare skin and the feel of cosmetics on skin with cosmetics applied.

[0072] Figure 11 This is a flowchart of a process for predicting the tactile sensation after application, according to one embodiment of the present invention.

[0073] In step 11 (S11), the evaluation device 10 acquires information related to the user's bare skin condition. For example, the information related to the bare skin condition includes the moisture content of the stratum corneum, the condition of the skin grooves, the elasticity of the skin, the softness of the stratum corneum, the amount of moisture lost from the epidermis, and information about sebum.

[0074] In step 12 (S12), the evaluation device 10 uses a classification model or a regression model to infer the feel of the cosmetics on the user's skin from the user's bare skin state in S11.

[0075] <In the case of classification>

[0076] In S12, the evaluation device 10 can use a classification model to infer the type of texture of the cosmetics on the user's skin based on the user's bare skin condition. For example, the texture type can be divided into three categories based on the degree of moisturization (hydration) (e.g., "moisturized", "normal", "refreshing"). Alternatively, the texture type can also be based on the degree of dryness, the degree of unevenness, etc. The classification can also be different from three types, such as two, four, five, etc.

[0077] <In the case of regression>

[0078] In S12, the evaluation device 10 can use a regression model (e.g., a single regression model, a multiple regression model, etc.) to infer from the user's bare skin state the value representing the tactile sensation of the cosmetic on the user's skin (e.g., the value representing at least one of the friction and vibration generated on the user's skin after applying the cosmetic).

[0079] <<Inferring the feel after application from the feel before application>>

[0080] exist Figure 11 In the processing, information related to the state of bare skin can also be information representing the tactile feel of bare skin (e.g., information related to at least one of friction and vibration generated on bare skin). In this case, the evaluation device 10 can use a classification model or a regression model to infer the tactile feel of the cosmetic on the user's skin based on information representing the tactile feel of the user's bare skin. That is, the evaluation device 10 can infer the tactile feel of the user's skin after applying cosmetic from the tactile feel of the user's bare skin.

[0081] Figure 12 This is a flowchart of a process for predicting the state of bare skin according to one embodiment of the present invention.

[0082] In step 21 (S21), the evaluation device 10 acquires information related to the tactile sensation of the cosmetic on the skin of the user who has applied the cosmetic (e.g., information related to at least one of friction and vibration generated on the skin of the user who has applied the cosmetic).

[0083] In step 22 (S22), the evaluation device 10 uses a classification model or a regression model to infer the user's bare skin condition from the feel of the cosmetics on the user's skin in S21.

[0084] <In the case of classification>

[0085] In S22, the evaluation device 10 can use a classification model to infer the type of a user's bare skin condition from the feel of the cosmetics on the user's skin. For example, the type of bare skin condition can be one of three types: "skin with a soft stratum corneum", "skin with a hard and dry stratum corneum, lack of elasticity, and irregular texture", and "standard skin". The classification can also be different from three types, such as two, four, five, etc.

[0086] <In the case of regression>

[0087] In S22, the evaluation device 10 can use a regression model (e.g., a single regression model, a multiple regression model, etc.) to infer a value representing the state of the user's bare skin from the feel of the cosmetics on the user's skin after applying cosmetics.

[0088] <<Inferring the feel before application from the feel after application>>

[0089] exist Figure 12 In the processing, the bare skin state can also be the tactile sensation of bare skin (e.g., at least one of friction and vibration generated on bare skin). In this case, the evaluation device 10 can use a classification model or a regression model to infer the tactile sensation of the user's bare skin based on information related to the tactile sensation of the cosmetic on the user's skin. That is, the evaluation device 10 can infer the tactile sensation of the user's bare skin from the tactile sensation of the user's skin after applying cosmetic. In the case of <<inferring the tactile sensation before application from the tactile sensation after application>>, the type of bare skin state can also be classified based on at least one of friction and vibration generated on bare skin.

[0090] In addition, Figure 11 S11 and Figure 12 After the classification in S22, the evaluation device 10 can output the predicted results. Furthermore, based on the predicted results, the evaluation device 10 can recommend suitable cosmetics for the user.

[0091] Figure 13This is an overall configuration diagram relating to one embodiment of the present invention. (See diagram below.) Figure 13 As shown, the evaluation device 10 can transmit and receive data with the bare skin condition measuring device 20, the friction / vibration measuring device 30, and the cosmetic dispenser 40 via any network. Furthermore, the evaluation device 10 can also transmit and receive data with the bare skin condition measuring device 20, the friction / vibration measuring device 30, and the cosmetic dispenser 40 via a storage medium. These will be explained separately below.

[0092] The evaluation device 10 estimates the tactile sensation after application and the state of the skin without makeup. The evaluation device 10 consists of one or more computers.

[0093] <<Speculation on the feel after application>>

[0094] The evaluation device 10 can obtain information related to the user's bare skin condition from the bare skin condition measuring device 20 or the friction / vibration measuring device 30. In addition, the evaluation device 10 can use a classification model or a regression model to infer the feel of the cosmetics on the user's skin based on the user's bare skin condition.

[0095] <<Speculations on the state of bare skin>>

[0096] The evaluation device 10 can obtain information from the friction / vibration measuring device 30 related to at least one of the friction and vibration generated on the skin of a user who has applied cosmetics. Furthermore, the evaluation device 10 can use a classification model or a regression model to infer the user's bare skin condition from at least one of the friction and vibration generated on the skin of a user who has applied cosmetics.

[0097] The bare skin condition measuring device 20 is a device used to measure the bare skin condition of a user. For example, the bare skin condition measuring device 20 measures the moisture content of the stratum corneum, the condition of the skin grooves, the elasticity of the skin, the softness of the stratum corneum, the amount of water loss from the epidermis, and the amount of sebum on the user's bare skin.

[0098] The friction / vibration measuring device 30 is used to measure friction and vibration generated on a user's skin after applying cosmetics and on the user's bare skin (i.e., skin before applying cosmetics). The friction / vibration measuring device 30 measures the coefficient of friction and acceleration (G) at various times. For example, the friction / vibration measuring device 30 is a sensor that measures friction and vibration while a motor rotates and a probe touches the skin. Furthermore, the probe of this sensor is made of metal with a surface that mimics a fingerprint. Additionally, in this sensor, friction is measured by a 6-axis force sensor, and vibration is measured by a 3-axis accelerometer.

[0099] The cosmetic dispenser 40 is a device that mixes and dispenses multiple cosmetics. Based on the recommendations of the evaluation device 10, the cosmetic dispenser 40 can mix and dispense multiple cosmetics.

[0100] <Function Block>

[0101] Figure 14 This is a functional block diagram of an evaluation device 10 according to one embodiment of the present invention. For example... Figure 14 As shown, the evaluation device 10 includes a bare skin state acquisition unit (also simply called the acquisition unit) 101, a post-application tactile sensation estimation unit 102, a friction / vibration acquisition unit (also simply called the acquisition unit) 103, a bare skin state estimation unit 104, a correspondence storage unit 105, an estimation result output unit 106, and a recommendation unit 107. Furthermore, the evaluation device 10 functions as the bare skin state acquisition unit 101, the post-application tactile sensation estimation unit 102, the friction / vibration acquisition unit 103, the bare skin state estimation unit 104, the estimation result output unit 106, and the recommendation unit 107 by executing a program. These will be described separately below.

[0102] The bare skin condition acquisition unit 101 acquires information related to the user's bare skin condition measured by the bare skin condition measuring device 20.

[0103] The post-application texture estimation unit 102 uses a classification model or regression model stored in the correspondence storage unit 105 to infer the texture of the cosmetic on the user's skin based on the user's bare skin condition. Furthermore, it can utilize one or more pieces of information related to the bare skin condition.

[0104] The friction / vibration acquisition unit 103 acquires information related to at least one of the friction and vibration generated on the user's skin with cosmetics applied and on the user's bare skin, as measured by the friction / vibration measuring instrument 30. As described above, the temperature (°C) measured by a temperature sensor and the surface shape (μm) measured by a laser displacement meter, confocal laser microscope, white light interferometer, or contact roughness measuring instrument can also be used as values ​​representing tactile sensation.

[0105] <<Friction>>

[0106] For example, information related to friction is the coefficient of friction at different times. The friction / vibration acquisition unit 103 calculates the average value of the coefficient of friction (Fx (force in the x-axis direction) / Fz (force in the x-axis direction)) as a value representing friction.

[0107] <<Vibration>>

[0108] For example, information related to vibration is the acceleration (G) at various times. The friction / vibration acquisition unit 103 calculates the amplitude spectrum (an average value between 250 Hz and 1000 Hz) as a value representing the vibration.

[0109] The bare skin state estimation unit 104 uses a classification model or regression model stored in the correspondence storage unit 105 to infer the user's bare skin state from the feel of the cosmetics on the user's skin. Furthermore, it can use one or more pieces of information related to the feel of the cosmetics on the skin.

[0110] In the correspondence storage unit 105, a classification model or regression model is stored for each cosmetic product, which can infer the feel of the cosmetic on the skin after applying the cosmetic from the state of bare skin. Additionally, in the correspondence storage unit 105, a classification model or regression model is stored for each cosmetic product, which can infer the state of bare skin from the feel of the cosmetic on the skin after applying the cosmetic.

[0111] The prediction result output unit 106 outputs the results predicted by the post-application touch sensation prediction unit 102 and the bare skin state prediction unit 104. For example, the prediction result output unit 106 can display the type of touch sensation of the cosmetic on the user's skin after applying cosmetic, or a value representing the touch sensation of the cosmetic on the user's skin after applying cosmetic, on the evaluation device 10 or a device other than the evaluation device 10. Additionally, for example, the prediction result output unit 106 can display the type of the user's bare skin state, or a value representing the user's bare skin state, on the evaluation device 10 or a device other than the evaluation device 10.

[0112] Based on the results estimated by the post-application feel estimation unit 102 and the bare skin state estimation unit 104, the recommendation unit 107 recommends cosmetics suitable for the user. For example, the recommendation unit 107 can display the recommended cosmetics on the evaluation device 10 or a device other than the evaluation device 10. In addition, for example, the recommendation unit 107 can notify the cosmetic dispenser 40 of the recommended cosmetics (information such as information required for mixing multiple cosmetics).

[0113] <Hardware Configuration>

[0114] Figure 15 This is a block diagram illustrating an example of the hardware configuration of an evaluation device 10 according to an embodiment of the present invention. The evaluation device 10 includes a CPU (Central Processing Unit) 1001, a ROM (Read Only Memory) 1002, and a RAM (Random Access Memory) 1003. The CPU 1001, ROM 1002, and RAM 1003 form a so-called computer.

[0115] Additionally, the evaluation device 10 may include an auxiliary storage device 1004, a display device 1005, an operation device 1006, an I / F (Interface) device 1007, and a drive device 1008. Furthermore, the various hardware components of the evaluation device 10 are interconnected via bus B.

[0116] CPU 1001 is a computing device that executes various programs installed in auxiliary storage device 1004.

[0117] ROM 1002 is a non-volatile memory. ROM 1002 functions as the main storage device for storing various programs and data required by the CPU 1001 to execute various programs installed in the auxiliary storage device 1004. Specifically, ROM 1002 functions as the main storage device for storing boot programs such as BIOS (Basic Input / Output System) and EFI (Extensible Firmware Interface).

[0118] RAM1003 is a volatile memory such as DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory). RAM1003 functions as a main storage device, providing a working area for various programs installed on the auxiliary storage device 1004 to be expanded when executed by the CPU 1001.

[0119] Auxiliary storage device 1004 is an auxiliary storage device that stores various programs and information used when these programs are executed.

[0120] The display device 1005 is a display device that displays the internal state of the evaluation device 10, etc.

[0121] The operating device 1006 is an input device for the manager of the evaluation device 10 to input various instructions to the evaluation device 10.

[0122] I / F device 1007 is a communication device that is connected to a network and used to communicate with other devices.

[0123] The drive device 1008 is a device for setting the storage medium 1009. The storage medium 1009 referred to here includes media that record information optically, electrically, or magnetically, such as CD-ROMs, floppy disks, and optical discs. Alternatively, the storage medium 1009 may also include semiconductor memories that record information electrically, such as EPROMs (Erasable Programmable Read Only Memory) and flash memory.

[0124] Furthermore, various programs installed on the auxiliary storage device 1004 can be installed, for example, by being set on the drive device 1008 via the distributed storage medium 1009 and by the drive device 1008 reading the various programs recorded on the storage medium 1009. Alternatively, various programs installed on the auxiliary storage device 1004 can also be installed by downloading from the network via the I / F device 1007.

[0125] <Effect>

[0126] Thus, in one embodiment of the present invention, the feel of the cosmetic on skin after applying it can be evaluated considering the condition of the skin. Specifically, the feel of the cosmetic on a user's skin after applying it can be inferred from the condition of the user's bare skin. Conversely, the condition of a user's bare skin can be inferred from the feel of the cosmetic on a user's skin after applying it.

[0127] The embodiments of the present invention have been described in detail above, but the present invention is not limited to the specific embodiments described above, and various modifications / changes can be made within the scope of the spirit of the present invention as set forth in the claims.

[0128] This international application claims priority based on Japanese Patent Application No. 2020-171808, filed on October 12, 2020, the entire contents of which are incorporated herein by reference.

[0129] Label Explanation

[0130] 10 Evaluation device; 20 Bare skin condition measuring device; 30 Friction / vibration measuring device; 40 Cosmetic dispenser; 101 Bare skin condition acquisition unit; 102 Post-application tactile sensation estimation unit; 103 Friction / vibration acquisition unit; 104 Bare skin condition estimation unit; 105 Correspondence storage unit; 106 Estimation result output unit; 107 Recommendation unit; 1001 CPU; 1002 ROM; 1003 RAM; 1004 Auxiliary storage device; 1005 Display device; 1006 Operation device; 1007 I / F device; 1008 Drive device; 1009 Storage medium.

Claims

1. A method comprising: Steps to determine the user's bare skin condition; and The step of inferring the feel of the cosmetic on the user's skin after applying it, based on the correspondence between the bare skin state and the tactile sensation of the cosmetic on the skin after applying it. The state of bare skin refers to the feel of bare skin. The correspondence is a classification model or a regression model. When the correspondence is the classification model, the type of texture of the cosmetic on the user's skin after applying the cosmetic is inferred from the state of the bare skin, and the type of texture is classified according to the degree of moisturization. In the case where the correspondence is the regression model, the tactile value of the cosmetic on the user's skin after applying the cosmetic is inferred from the state of the bare skin, and the tactile value represents the value of friction generated on the user's skin after applying the cosmetic.

2. A method comprising: The steps to determine the feel of the cosmetic on the skin of a user who has applied it; and The step of inferring the user's bare skin state based on the correspondence between the tactile feel of the cosmetic on the skin after applying it and the state of the bare skin. The state of bare skin refers to the feel of bare skin. The correspondence is a classification model or a regression model. When the correspondence is the classification model, the type of the user's bare skin condition is inferred from the feel of the cosmetic on the user's skin after applying the cosmetic. The type of bare skin condition is one of three types: "skin with a soft stratum corneum", "skin with a hard and dry stratum corneum, lack of elasticity, and irregular texture", and "standard skin". In the case where the correspondence is the regression model, a value representing the state of the user's bare skin is inferred from the tactile sensation of the cosmetic on the user's skin after applying the cosmetic, the value representing the friction generated on the bare skin.

3. A method comprising: Steps to determine the user's bare skin condition; and The step of inferring the feel of the cosmetic on the user's skin after applying it, based on the correspondence between the bare skin state and the tactile sensation of the cosmetic on the skin after applying it. The tactile sensation is determined by at least one of friction and vibration generated on the skin. The correspondence is determined by clustering the users based on friction and vibration generated on the skin. The clusters are "skin with a soft stratum corneum", "skin with a hard and dry stratum corneum, inelastic and irregular texture", and "standard skin".

4. The method according to any one of claims 1 to 3, It also includes steps for recommending cosmetics that correspond to the predicted results.

5. The method according to any one of claims 1 to 3, It also includes the step of generating and spraying cosmetics corresponding to the predicted results.

6. The method according to any one of claims 1 to 3, The correspondence is based on the types of cosmetics.

7. An apparatus comprising: The acquisition department determines the user's bare skin condition; and The touch sensation estimation unit infers the touch sensation of the cosmetic on the user's skin based on the correspondence between the state of bare skin and the touch sensation of the cosmetic on the skin after applying the cosmetic. The correspondence is determined by clustering the user's skin based on friction and vibration generated on the skin. The clusters are "skin with a soft stratum corneum", "skin with a hard and dry stratum corneum, inelastic and irregular texture", and "standard skin".

8. A computer program product comprising a program that enables a computer to function as an acquisition unit and a post-application tactile sensing unit. The acquisition unit determines the user's bare skin condition. The post-application tactile sensation estimation unit infers the tactile sensation of the cosmetic on the user's skin based on the correspondence between the bare skin state and the tactile sensation of the cosmetic on the skin after application, from the determined bare skin state. The correspondence is a classification model or a regression model. When the correspondence is the classification model, the type of texture of the cosmetic on the user's skin after applying the cosmetic is inferred from the state of the bare skin, and the type of texture is classified according to the degree of moisturization. In the case where the correspondence is the regression model, the tactile value of the cosmetic on the user's skin after applying the cosmetic is inferred from the state of the bare skin, and the tactile value represents the value of friction generated on the user's skin after applying the cosmetic.

9. An apparatus comprising: The obtaining department determines the tactile feel of the cosmetic on the skin of a user who has applied it; and The bare skin state estimation unit infers the user's bare skin state based on the correspondence between the feel of the cosmetics on the skin and the state of the bare skin. The correspondence is determined by clustering the user's skin based on friction and vibration generated on the skin. The clusters are "skin with a soft stratum corneum", "skin with a hard and dry stratum corneum, lack of elasticity, and irregular texture", and "standard skin".

10. A computer program product comprising programs for enabling a computer to function as an acquisition unit and a skin state estimation unit. The obtaining unit determines the tactile feel of the cosmetic on the skin of the user who has applied it. The bare skin state estimation unit infers the user's bare skin state based on the correspondence between the tactile feel of the cosmetics on the skin and the bare skin state, determined by the tactile feel. The correspondence is a classification model or a regression model. When the correspondence is the classification model, the type of the user's bare skin condition is inferred from the feel of the cosmetic on the user's skin after applying the cosmetic. The type of bare skin condition is one of three types: "skin with a soft stratum corneum", "skin with a hard and dry stratum corneum, lack of elasticity, and irregular texture", and "standard skin". In the case where the correspondence is the regression model, a value representing the state of the user's bare skin is inferred from the tactile sensation of the cosmetic on the user's skin after applying the cosmetic, the value representing the friction generated on the bare skin.

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