Evaluation method

Abstract

To provide an evaluation method which performs evaluation based on timing and a variation pattern when the intensity of a dynamic physical amount occurring between the skin and a motion body varies.SOLUTION: An evaluation method acquires time series data of a dynamic physical amount occurring between the skin and a motion body, identifies a significant point when the pattern trend of the waveform of the time series data of the dynamic physical amount varies timewise, calculates a feature amount at the significant point, and evaluates a skin condition, a drug, a procedure, or an environment based on the calculated feature amount.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to an evaluation method for evaluating a skin condition, agent, procedure, or environment. [Background technology]

[0002] There is an evaluation method in which vibrations generated by moving a moving object while it is in contact with cosmetics applied to the skin, etc., are detected, and the tactile sensation of the cosmetics when used is evaluated based on the change over time in the frequency spectrum of the detected vibrations (Patent Document 1). There is also an evaluation method in which a contactor is moved while being in contact with the skin, etc., and vibrations are detected by a sensor attached to the contactor, and the condition of the skin, etc. is evaluated based on differences in the detected vibration information (differences in vibration intensity) (Patent Document 2). Furthermore, in Patent Application No. 2022-020264 previously filed by the applicant, there is an evaluation method in which the mechanical physical quantities generated by moving a moving body while it is in contact with cosmetics applied to the skin, etc. are measured, time-related feature quantities are extracted from the measured mechanical physical quantities, and the tactile feel of the skin surface or the applied cosmetics is evaluated based on the extracted feature quantities. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2019 / 039466 [Patent Document 2] Japanese Patent Application Publication No. 2019-095263 Summary of the Invention [Problem to be solved by the invention]

[0004] Patent Document 1 merely quantifies the change in vibration intensity over time, and is unable to evaluate the tactile sensation based on the timing or pattern of the change. In Patent Document 2, evaluation is made only based on differences in detected vibration information (differences in vibration intensity), and therefore evaluation cannot be made based on the timing or change pattern of the vibration intensity. Furthermore, since the above-mentioned Patent Application No. 2022-020264 only evaluates based on the timing at which the feature changes within one cycle of the contact movement, it was desirable to evaluate based on the timing of changes that occur over time.

[0005] The present invention has been made in consideration of the above-mentioned problems, and relates to an evaluation method for evaluating skin condition, agents, procedures, or environments based on the timing of changes that occur over time in time-series data of mechanical physical quantities that occur between the skin and a moving object. [Means for solving the problem]

[0006] The present invention relates to a method for analyzing how skin changes over time after application of a specific agent, procedure, or environment, by repeatedly operating a moving object in contact with the skin to obtain time series data of mechanical physical quantities occurring between the skin and the moving object, identifying singular points where the tendency of a repeated waveform pattern in the obtained time series data changes over time, obtaining feature quantities that represent the characteristics of the waveform at the identified singular points or within a local time period starting or ending at the singular points, and evaluating the condition of the skin, the agent, the procedure, or the environment based on the obtained feature quantities.

[0007] The present invention also relates to an evaluation system that analyzes and evaluates how skin changes over time after a specific agent, procedure, or environment has been applied, and includes an acquisition unit that repeatedly moves a moving object in contact with the skin to acquire time series data of mechanical physical quantities occurring between the skin and the moving object; an identification unit that identifies singular points where the tendency of a repeated waveform pattern in the acquired time series data changes over time; a calculation unit that calculates feature quantities that represent the characteristics of the waveform at the identified singular point or within a local time period starting or ending at the singular point; and an evaluation unit that evaluates the condition of the skin, the agent, the procedure, or the environment based on the calculated feature quantities. [Effects of the Invention]

[0008] The method provided by the present invention makes it possible to quantitatively and comprehensively evaluate the timing of changes that occur over time in time series data of mechanical physical quantities occurring between the skin and the moving body, thereby making it possible to evaluate the condition of the skin, or the agents, procedures, or environments applied to the skin with high accuracy. [Brief explanation of the drawings]

[0009] [Figure 1] This is an image of the evaluator touching the surface of their skin with a finger equipped with a sensor. [Figure 2] FIG. 2 is a diagram showing a time-series waveform signal. [Figure 3] 1 is a flowchart showing an evaluation method (present method) of the present embodiment. [Figure 4] FIG. 1 is a diagram showing an overview of analysis method 1. [Figure 5] FIG. 10 is a diagram showing the results of analyzing the original signal of Cream P using Analysis Method 1. [Figure 6] FIG. 10 is a diagram showing the results of analyzing the original signal of Cream Q using analysis method 1. [Figure 7] FIG. 10 is a diagram showing the evaluation results based on the analysis results using analysis method 1. [Figure 8] FIG. 10 is a diagram showing the evaluation results based on the analysis results using analysis method 1. [Figure 9] FIG. 10 is a diagram showing the evaluation results based on the analysis results using analysis method 1. [Figure 10] FIG. 10 is a diagram showing an outline of analysis method 2. [Figure 11] FIG. 10 is a diagram showing the results of analyzing the original signal of Cream P using Analysis Method 2. [Figure 12] FIG. 10 is a diagram showing the results of analyzing the original signal of Cream Q using analysis method 2. [Figure 13] FIG. 10 is a diagram showing an overview of analysis method 3. [Figure 14] FIG. 10 is a diagram showing the results (skewness) of analyzing the original signals of cream P and cream Q using analysis method 3. [Figure 15] 10 is a diagram showing the results (kurtosis) of analyzing the original signals of cream P and cream Q using analysis method 3. FIG. [Figure 16] FIG. 10 is a diagram showing the evaluation content (similarity evaluation) based on the results of analysis using analysis method 1. [Figure 17] FIG. 2 is a block diagram of an evaluation system 200. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. Note that the drawings of the present embodiments are intended to explain the technical concept, configuration, and operation of the present invention, and are not intended to specifically limit the configuration. In addition, in all drawings, similar components are given similar reference numerals, and duplicated explanations will be omitted as appropriate.

[0011] <Summary> An overview of the evaluation method in this embodiment will be described. The evaluation method of this embodiment (hereinafter, may be referred to as this method) is a method including a step of analyzing how skin changes over time to which a predetermined agent, procedure, or environment has been applied, and is characterized in that it involves repeatedly moving a moving object in contact with the skin to obtain time series data of mechanical physical quantities occurring between the skin and the moving object, identifying singular points where the tendency of a repeated waveform pattern in the obtained time series data changes over time, obtaining feature quantities that represent the characteristics of the waveform at the identified singular points or within a local time period starting or ending at the singular points, and evaluating the condition of the skin, the agent, the procedure, or the environment based on the obtained feature quantities.

[0012] Previous technologies, for example, in Patent Document 1, detected vibrations generated by moving a moving object while it was in contact with cosmetics applied to the skin, etc., and evaluated the feel of the cosmetics in use based on changes over time in the detected frequency spectrum, but because it was not possible to perform an evaluation based on the timing or pattern of changes in the frequency spectrum, it was not possible to evaluate, for example, the timing when the feel of the cosmetics in use changed, and therefore an insufficient evaluation could not be performed.Furthermore, for example, in Patent Document 2, a contactor was moved while it was in contact with the skin, etc., and vibrations were detected by a sensor attached to the contactor, and the condition of the skin, etc. was evaluated based on differences in the detected vibration information (differences in vibration intensity), but because it was not possible to perform an evaluation based on the timing or pattern of changes in the vibration intensity, it was not possible to evaluate, for example, the timing when the feel of the cosmetics in use changed, and therefore an insufficient evaluation could not be performed. Therefore, in this method, a moving object in contact with the skin is repeatedly moved to obtain time series data of the mechanical physical quantities occurring between the skin and the moving object, singular points where the pattern of the repeated waveform changes are identified, feature quantities that represent the characteristics of the waveform at the singular points are obtained, and the skin condition, the agent, the procedure, or the environment are evaluated based on the obtained feature quantities.

[0013] This method will now be described in more detail.

[0014] Figure 1 shows how this method acquires time-series data of the mechanical physical quantities that occur between the skin and the moving object. "Skin" refers to the surface of human skin or artificial skin. The term "skin surface" includes not only bare skin but also the surface of skin on which a specific agent, as described below, has been applied. In other words, contacting a skin surface with a finger, palm, or the like includes not only direct contact of the finger, palm, or the like with the bare skin, but also indirect contact of the finger, palm, or the like with the bare skin via a coating film of a specific agent applied to the skin. The location of the human skin surface, i.e., the part of the body, is not important. When evaluating the tactile sensation of a specific agent, it is preferable to evaluate a part of the skin surface that is free of irregularities, such as warts or acne scars. This is because it is difficult to evaluate whether the tactile sensation when a finger touches the skin surface is due to the specific agent or the shape of the skin surface. However, this is not limited to cases where it is desired to evaluate by tactile sensation whether the application of a specific agent to uneven skin has covered the irregularities (whether the skin surface has become flat). It is desirable to determine the skin surface to be evaluated according to the conditions to be evaluated. Artificial skin is an artificial imitation of the surface of skin, and has properties similar to those of human skin. In this embodiment, unless otherwise specified, "skin" refers to the skin of a human arm (the skin surface of a human arm) shown in Figure 1. The "moving object" refers to an object that is brought into contact with the skin, such as a finger 20, a palm, a skin care product, a makeup product, a massager, or a measurement jig. A sensor 30 shown in FIG. 1 is attached to the finger 20, palm, skin care product, makeup product, massager, or measurement jig. The finger 20 may be brought into contact with the skin at any position on the finger 20, but the finger pad is preferred because the tactile sensation is often confirmed with the finger pad. When checking the tactile sensation of the skin, not only one finger but multiple fingers may be used, and the entire palm may also be used to check the sensation, so the palm may be brought into contact with the skin surface. The measurement jig is a jig that is brought into contact with the skin surface in the same way as a finger. The structure of the portion of the measurement jig that comes into contact with the skin surface is not limited, but by constructing this portion with artificial skin, it becomes possible to measure physical quantities similar to those that would occur when a person touches the skin surface with their finger or palm.

[0015] The term "predetermined agent" refers to a liquid or solid such as a powder that is applied to the skin (skin surface). Examples include topical skin preparations, cosmetics, sheet-type skin care cosmetics, and cleansers, including, but not limited to, skin care cosmetics such as lotions, emulsions, creams, serums, massage lotions, packs, lip balms, eye care sheets, mouth sheets, pack masks, sheet lotions, and sheet makeup removers; makeup cosmetics such as foundations, makeup bases, liquid foundations, oil-based foundations, powder foundations, concealers, color control products, eye shadows, blushers, lipsticks, lip glosses, lip liners, and body and décolleté products; UV protection cosmetics such as sunscreen emulsions, sunscreen gels, and sunscreen creams; cleansers; facial cleansers, cleansers, body soaps, and shaving foams. "Procedures" include skin care procedures (cleansing), procedures to improve dullness and acne scars, and cosmetic procedures to improve fine lines and hollows. However, the procedures referred to here are non-medical procedures. The "environment" refers to the location and condition of the skin (skin surface), such as whether it is indoors or outdoors, humidity, temperature, whether it is exposed to sunlight or lighting, whether it is exposed to wind, etc., and includes both environments in everyday life and environments outside of everyday life (for example, hot and humid environments such as saunas and yoga studios, cold environments such as refrigerated warehouses, and brightly lit environments such as photography studios). "Skin to which a specific agent, procedure, or environment has been applied" refers to skin to which the above-mentioned specific agent has been applied (painted), skin to which the above-mentioned procedure has been applied, or skin to which the above-mentioned environment has been applied (is present in the environment), and skin to which a procedure has been applied and skin to which an environment has been applied may be either bare skin or skin to which a specific agent has been applied. "Changes in skin texture over time" refers to the changes in the texture of the skin over time due to the application of a specific agent, the application of a technique, or the influence of the location of the skin. Examples of textures include "sticky," "refreshing," "moist," "sticky," "moisturizing," "dry," "firm," "elastic," "soft and firm," "glue," "soft and firm," "sticky," "plump," "smooth," "slippery," "oily," "rich," "comfortable," "close contact," "dry," "rough," "tough," and "tight." The texture referred to here refers to the tactile sensation felt through the receptors of the skin or the fingers when a moving object such as a finger or palm (hereinafter referred to as "fingers, etc.") comes into contact with the skin (skin surface). Changes in thermal sensations such as cold and warmth are not evaluated. "Sticky" here refers to the sticky, adhesive feeling of the skin sticking to the fingers, etc., when the fingers, etc., come into contact with the skin surface. "Refreshing" refers to a smooth, refreshing feeling when a finger or other object touches the skin surface, without any sticky feeling. "Moist" refers to a slightly damp and smooth feeling when a finger or other object touches the skin surface. "Sticky" refers to a feeling where a finger or other object sticks slightly when a finger or other object touches the skin surface. "Moist" refers to a feeling of moderate dampness when a finger or other object touches the skin surface. "Dry" refers to a dry feeling when a finger or other object touches the skin surface. "Firm" refers to a feeling where the skin is stiff and taut when a finger or other object touches the skin surface. "Elasticity" refers to a feeling where the skin bounces back without sinking when a finger or other object touches the skin surface. "Hardness" refers to the degree to which the skin deforms when a finger or other object touches the skin surface. "Sticky" refers to a feeling where a finger or other object adheres to the skin surface when a finger or other object touches the skin surface. "Springy" refers to the feeling that when a finger or other object is brought into contact with the skin surface, the finger or other object adheres slightly to the skin and bounces back. "Fluffy" refers to the feeling that when a finger or other object is brought into contact with the skin surface, the finger or other object is slightly elastic and does not stick to the skin, giving a refreshing feeling. "Smooth" refers to the feeling that when a finger or other object is brought into contact with the skin surface, the finger or other object moves without getting caught, and the feeling that the finger or other object moves naturally, especially when an agent is applied."Slippery" refers to the feeling of fingers slipping easily when they are brought into contact with the skin surface, especially when a formulation is applied, due to the adhesiveness of the formulation. "Smooth" refers to the feeling of softness of the skin and the ability of fingers to move without catching when they are brought into contact with the skin surface. "Oily" refers to the feeling of sticking when fingers are brought into contact with the skin surface. "Rich" refers to the feeling of fingers feeling the texture of the formulation when they are brought into contact with the skin surface, especially when applying a formulation, the texture when spreading, and the weight when spreading. "Fitness" refers to the feeling of no discomfort when fingers are brought into contact with the skin surface, especially when applying a formulation, and the feeling of the formulation fitting into the skin. "Adhesion" refers to the feeling of adhesion to the skin when the formulation is applied to the skin. "Rough" refers to the feeling of roughness when fingers are brought into contact with the skin surface.

[0016] "Repeatedly moving the moving object in contact with the skin" means to continue the action of continuously contacting the moving object with the skin, or to repeat the action of intermittently contacting the moving object with the skin. Specifically, this means repeatedly moving the finger in an outward, approximately vertical direction against the skin (tapping action), or repeatedly sliding the finger horizontally against the skin. In the case of sliding movement, any of the modes may be used, such as repeatedly moving in one direction, repeatedly moving back and forth, or repeatedly moving in a circular motion.

[0017] "Mechanical physical quantities occurring between the skin and a moving object" are physical quantities related to mechanics occurring between the skin and a moving object (e.g., a finger) when the moving object is repeatedly moved in contact with the skin. Examples include the magnitude of the elastic force or frictional force that the moving object receives from the skin, the amount of current or voltage generated by the displacement of the skin, the pressure that the moving object receives, the strain that occurs in the moving object, or the vibration amount (amplitude) or frequency of the vibrating moving object. The tactile sensations evaluated in this method are those that occur when a finger or palm comes into contact with the skin surface, such as stickiness, freshness, or moistness. Thermal sensations such as coldness or warmth are not evaluated, so the acquired physical quantities do not include physical quantities that only indicate thermal characteristics.

[0018] The "tendency of the repeated waveform pattern" refers to the overall characteristics of the shape (pattern) of each waveform acquired periodically over multiple times by repeatedly moving the moving body multiple times. The "singular points at which the trend changes over time" refer to points at which the overall characteristics of the acquired waveform pattern change. The "intensity in the waveform pattern" refers to the magnitude of a mechanical physical quantity determined from an individual waveform or multiple waveforms, or the calculated value of such a mechanical physical quantity. Specific examples of the above-mentioned singular points include points at which the trend of the magnitude of a mechanical physical quantity changes, and points at which the sensory quantity changes. More specifically, examples of such points include the point where a first indicator line indicating the trend for each first period of the time series data intersects with a second indicator line indicating the trend for each second period different from the first period (first singular point); the point where the time series data intersects with a standard deviation line indicating a variation within a predetermined range at least either above or below a third indicator line indicating the trend for each third period of the time series data (second singular point); and the point where a change of a predetermined value or more occurs when the skewness or kurtosis of the time series data for each fourth period is extracted and the extracted skewness or kurtosis is differentiated with respect to time (third singular point). In this way, a singular point is a point where the intensity in a waveform pattern changes, a point where the strength, magnitude, or amount of a mechanical physical quantity changes, or a point where the strength, magnitude, or amount of a sensation changes.

[0019] The "feature quantity representing the characteristics of a waveform" is a quantitative index that represents the characteristics related to the shape or magnitude of an individual waveform or multiple waveforms. Examples include the amount of change in a mechanical physical quantity, the change pattern of the amount of change, the duration until the pattern changes, and the shape of the pattern (slope, intensity). Specifically, examples include the intensity (second feature quantity) based on the difference data between the time series data at the second singular point and the value of the standard deviation line, the amount of change (third feature quantity) when the skewness or kurtosis is differentiated with respect to time at the third singular point, the pattern of the difference data between the first indicator line and the second indicator line within a local time period starting or ending at the first singular point, the peak top, the amount of deviation, the duration, the slope, the shape, the pattern intensity, or the pattern steepness (first feature quantity).

[0020] "Evaluating the skin condition, agent, procedure, or environment based on the obtained feature quantities" refers to evaluation of the skin condition, such as tactile sensation or a change in tactile sensation; evaluation of the agent, such as the time it takes for the agent to blend into the skin, the tactile sensation on the skin, or the physical properties that produce the change in tactile sensation on the skin; evaluation of the procedure, such as the tactile sensation on the skin due to the procedure or the procedure content that brought about the change in tactile sensation on the skin; and evaluation of the environment, such as evaluation of the skin tactile sensation or the environment when the change in tactile sensation on the skin was evaluated. Furthermore, evaluation does not only mean plotting the extracted feature quantities on a single axis or multiple axes and quantitatively evaluating them based on the plotted positions, but also includes comparing the extracted feature quantities with predetermined reference values ​​and evaluating their correlation with the sensory quantities that are the subject of evaluation using a calibration curve or the like.

[0021] <Method for acquiring time-series data of mechanical physical quantities> As shown in FIG. 1, in this embodiment, the skin is the skin of a human arm (the skin surface of a human arm), and the moving object is a finger 20 in contact with the human arm. As shown in FIG. 1, a sensor 30 is attached to the finger 20. When the finger 20, particularly the finger pad (hereinafter, the finger pad is also referred to as the finger), touches the surface of the arm (the skin surface) and the touching finger 20 is moved, vibrations and deformations occur in the finger skin, and the sensor 30 detects these vibrations and deformations and outputs them as electrical signals to the computing device 10. Because the vibrations and deformations occurring in the finger skin differ depending on the tactile sensation, the output electrical signals also differ depending on the tactile sensation. This output electrical signal corresponds to the "mechanical physical quantity" of the present invention, and the electrical signal is acquired over time. The sensor 30 is only required to acquire the mechanical physical quantity generated by the touch with the finger 20. For example, it may be a sensor (such as a multi-axis sensor or a force sensor) that can acquire the acceleration or force generated when the finger 20 is released from contact with the skin. Acquiring a physical quantity over time includes not only a mode in which the sensor 30 continuously acquires analog information (electrical signals in this embodiment) indicating the physical quantity over a predetermined time period, but also a mode in which the sensor 30 acquires the physical quantity as digital information multiple times at short intervals, such as on the order of milliseconds or submilliseconds. When the sensor 30 continuously acquires the physical quantity as analog information, the computing device 10 may sample and discretize the analog information at predetermined short intervals, such as on the order of milliseconds or submilliseconds. 1, a finger 20 equipped with a sensor 30 is brought into contact with the skin (skin surface), and the finger 20 is repeatedly slid in a substantially horizontal direction relative to the skin. The repeated movement may be any of a repeated movement in one direction, a repeated movement back and forth, a repeated movement in a circular motion, or the like. When measuring using a measuring jig, sensor 30 is provided on a measuring jig (not shown) instead of finger 20 in Fig. 1, and the measuring jig is brought into contact with the skin (skin surface) and moved so as to slide horizontally relative to the skin (skin surface), thereby making it possible to measure the generated physical quantity in the same manner. When measuring by moving the measuring jig in contact with the skin, the movement of the measuring jig may be controlled using a predetermined device (not shown) so that the movement is uniform.

[0022] The conditions for the vibration waveform data used in analysis methods 1 to 3 are explained below. Agents used Two types of cream (cream P and cream Q) were used, which have different texture changes when applied. "Cream P": A cream with a light texture, lasting stickiness, and blends in slowly. The overall impression is one of monotonous change. "Cream Q": This cream has a rich, smooth texture when first applied, and then quickly absorbs into the skin. The overall impression is one of a clear change. FIG. 2 shows the vibration waveform and sensation amount for each cream. -Method of measuring vibration waveform The vibration sensor was attached to the finger 20 of the evaluator, and each cream was dropped onto the inside of the forearm, and measurements were taken from the start of application to the end of application (end of absorption). The end of application was defined as the point at which the evaluator felt that the cream had completely absorbed into the skin. From the start of application, the evaluator was asked to sequentially respond to the tactile sensation, which was recorded as the amount of sensation. Original signal Signal data of vibration amplitude values ​​(root mean square: RMS) in the 10-500 Hz band was created and used as the original signal. In this embodiment, frequency analysis was performed and RMS processing was performed on the signal data, but such processing is not necessary and can be set taking into consideration the evaluation target and the acquired data.

[0023] <Outline of evaluation method> Figure 3 shows an overview of this evaluation method. This evaluation method includes a step of acquiring mechanical physical quantities (step S100), a step of identifying singular points and calculating feature quantities (step S110), and a step of evaluating the skin condition, agent, technique, or environment (step S120). In this embodiment, the evaluation method shown in FIG. 3 was used to evaluate the skin condition and agent for skin to which a predetermined agent, cream P, was dropped and applied, and for skin to which a predetermined agent, cream Q, which changes in texture when applied differently from cream P, was dropped and applied. In this embodiment, the finger 20 was repeatedly moved on skin (skin surface) to which the predetermined agent had been dropped to acquire time-series data of the mechanical physical quantities occurring between the skin and the finger 20. However, it is also possible to evaluate the skin condition by repeatedly moving the finger 20 on bare skin to acquire time-series data of the mechanical physical quantities occurring between the skin and the finger 20. The conditions of the skin to be contacted with the finger 20 can be determined depending on the evaluation target (evaluation purpose).

[0024] The step (step S100) is a step of acquiring time-series data of mechanical physical quantities by the method described above. FIG. 2(1) shows vibration waveform signals acquired when cream P is dropped onto the skin, finger 20 is brought into contact with the skin, and a repetitive motion is performed, and this is the "time series data of mechanical physical quantities" of the present invention. The horizontal axis represents elapsed time, and the vertical axis represents physical quantity. The finger 20 is brought into contact with the skin and a repetitive motion is performed from the timing of elapsed time 0 seconds (corresponding to the start of application in the figure), and this repetitive motion is continued until the timing of elapsed time 120 seconds (corresponding to the end of application in the figure). The end of application is defined as when the evaluator feels that the dropped cream has completely absorbed into the skin. FIG. 2(2) shows vibration waveform signals acquired when cream Q was dripped onto the skin, finger 20 was placed in contact with the skin, and the repeated motion was performed, and this is the "time series data of mechanical physical quantities" of the present invention. The horizontal axis represents elapsed time, and the vertical axis represents physical quantity. The finger was placed in contact with the skin from the timing of elapsed time 0 seconds (corresponding to the start of application in the figure), and the repeated motion was performed until the timing of elapsed time 70 seconds (corresponding to the end of application in the figure). The end of application was defined as when the evaluator felt that the dripped cream had completely absorbed into the skin. The "sensational amount" shown in Figure 2 represents the tactile sensation felt by the subject on the skin when the finger 20 is in contact with the skin and the action is repeated. The sensational amount in Figure 2(1) is a light, moist sensation at the start of application of Cream P, which changes to a slimy sensation as the action is repeated, and then the slimy sensation subsides and begins to change to a sensation of the cream fitting the skin, and the cream P feels as if it has been absorbed into the entire skin where it has been applied. The application is completed when the cream P feels as if it has been absorbed into the entire skin where it has been applied. The sensational amount in Figure 2(2) is a moderately heavy, rich sensation at the start of application of Cream Q, which then changes to a smooth sensation and a sensation of adhesion and the cream starting to fit in, and the application is completed when the cream Q feels as if it has been absorbed into the entire skin where it has been applied. Here, the following relationship exists between vibration intensity and tactile sensation. Increased vibration strength: This is related to the condition where the fingers feel heavy when moving them or where vibrations are easily generated when the fingers come into contact with the skin. - Reduction in vibration intensity: This is related to the state in which the fingers feel lighter when moving them, or the state in which vibration is less likely to occur when the fingers come into contact with the skin. Therefore, by analyzing time-series data of mechanical physical quantities, it is possible to quantitatively and comprehensively evaluate the timing and pattern of changes in the tactile sensation that changes over time when a cream such as that shown in Figure 2 is applied to the skin.

[0025] In step S110, specific points where the tendency of the repeated waveform pattern in the acquired time-series data of the mechanical physical quantity changes over time are identified and feature quantities are obtained. The specific points are identified and feature quantities are obtained by analyzing the time-series data of the mechanical physical quantity using a predetermined algorithm. The step (step S120) is a step of evaluating the skin condition, agent, procedure, or environment based on the identified specific points and feature amounts. In this embodiment, three types of analysis methods are used to find the specific points and feature amounts, and evaluate the skin condition and agent. Each analysis method and evaluation method will be described below.

[0026] (a) Analysis Method 1 Analysis method 1 is shown in Figure 4. Fig. 4(1) shows the RMS value of the acquired time-series waveform signal. The acquired time-series waveform signal shown in Fig. 2 is also "time-series data of mechanical physical quantities" of the present invention, but in this embodiment, the RMS value of the time-series waveform signal is also "time-series data of mechanical physical quantities (also called original signal)." Fig. 4 shows the time-series data of mechanical physical quantities of Cream Q. FIG. 4(2) shows the calculation of a simple moving average of two different periods for the waveform of the original signal. In this embodiment, a simple moving average is calculated for a first period (e.g., 6 [s]) and a second period (e.g., 10 [s]) that is different from the first period. The thick line in FIG. 4(2) indicates the moving average line for the first period (6 [s]), and the thin line indicates the moving average line for the second period (10 [s]). Note that the first and second periods can be determined to be preferable values ​​taking into consideration the evaluation target, evaluation conditions, etc. The shorter the period of the simple moving average, the more pronounced the fluctuations in the original signal become, and the longer the period, the more the direction of the fluctuations in the original signal become apparent. The following can be analyzed from the two moving average lines. a) Analyze the increase / decrease pattern of the original signal from the relative positions of the two moving averages If the moving average line for the first period (6 s) diverges above the moving average line for the second period (10 s), it is an increasing pattern (solid line rising to the right in Figure 4(2)), and if the moving average line for the first period (6 s) diverges below the moving average line for the second period (10 s), it is a decreasing pattern (dotted line falling to the right in Figure 4(2)). b) Analyze the magnitude of the change in the original signal based on the degree of divergence between the two moving averages The greater the difference between the two moving averages, the greater the change in the original signal; the smaller the difference between the two moving averages, the smaller the change in the original signal. c) Analyze the rate of change in the original signal from the slope of the divergence between the two moving averages The steeper the slope of the divergence between the two moving average lines, the steeper the change in the original signal, and the gentler the slope of the divergence between the two moving average lines, the gradualer the change in the original signal. These analyses can be performed by calculating the difference between moving average lines, making it possible to determine the change points (also called singular points) and characteristics of the change patterns in the original signal.

[0027] FIG. 5 shows the process of determining the characteristics of the change points and change patterns from the original signal for cream P. FIG. 5(1) shows time-series data (raw signals) of mechanical physical quantities acquired when a finger 20 is brought into contact with skin onto which cream P has been dropped and the finger 20 is repeatedly moved. FIG. 5(2) shows two moving average lines for the first period (6 [s]) and the second period (10 [s]). Figure 5(3) shows the difference data between the two moving averages. In Figure 5(4), positive values ​​are shown in black and negative values ​​in gray to make the data in Figure 5(3) easier to see. Positive values ​​in Figure 5(4), i.e., the black parts, indicate an increasing pattern, while negative values, i.e., the gray parts, indicate a decreasing pattern. In this way, by taking the difference between the two moving averages, it is possible to clearly determine the change points and the characteristics of the change pattern.

[0028] Figure 6 shows the process of determining the change points (also called singular points) and change pattern characteristics from the original signal for Cream Q. Figures 6(1) to 6(4) are the same as Figure 5, so their explanation will be omitted. In this way, by taking the difference between the two moving averages, it is possible to clearly determine the characteristics of the change points and change patterns. Furthermore, from Figures 5 and 6, it is clear that the change points and change patterns are different between Cream P and Cream Q.

[0029] Next, the evaluation results based on the change points and change patterns obtained by analysis method 1 will be described with reference to FIGS.

[0030] Figure 7(1) shows the difference data between the two moving average lines of Cream P shown in Figure 5(4), color-coded by positive and negative values. A code is assigned to a pattern in which a positive or negative value continues for a predetermined time (4 seconds or more in this embodiment). This is because a pattern that continues for a predetermined time can be said to be a pattern in which a clear change occurs. The predetermined time can be determined taking into consideration the evaluation target, evaluation conditions, etc. 1, 2, 6, and 9 are decreasing patterns, and 3, 4, 5, 7, and 8 are increasing patterns. Figure 7(2) shows the difference data between the two moving average lines of Cream Q shown in Figure 6(4), color-coded by positive and negative values. A code is assigned to patterns in which positive or negative values ​​continue for a predetermined period of time (4 seconds or more in this embodiment). This is because a pattern that continues for a predetermined period of time can be said to be a pattern in which a clear change occurs. The predetermined period of time can be determined taking into consideration the evaluation target, evaluation conditions, etc. 1, 4, and 6 are decreasing patterns, and 2, 3, 5, and 7 are increasing patterns.

[0031] Here, the indexed values ​​(also called feature amounts) will be explained using the "increase pattern of 5" and the "decrease pattern of 6" in FIG. 7(1). 1) Pattern Depending on whether the difference data is a positive value or a negative value, it is possible to determine whether the pattern is an increasing pattern or a decreasing pattern. 2) Peak Top In the case of an increasing pattern of 5, it is the most positive part of the increasing pattern of 5, and in the case of a decreasing pattern of 6, it is the most negative part of the decreasing pattern of 6, and is the point where the momentum of the pattern is greatest. 3) Deviation amount This corresponds to the area of ​​the pattern and is a feature quantity related to the intensity of the pattern. 4) Duration This is the duration of the pattern and is a feature quantity related to the intensity of the pattern. 5) Incline The gradient of the pattern is a feature quantity relating to the steepness of the pattern. For example, if the gradient of the increase pattern is steep, it is a steep increase pattern, and if the gradient of the increase pattern is gentle, it is a gentle increase pattern. 6) Shape Using the above 1) to 5), the characteristics of each pattern are determined based on the pattern shape. 7) Pattern strength The "pattern strength" can be calculated by dividing the deviation amount (3) by the duration (4). 8) Pattern tempo The "pattern steepness" can be determined based on the timing (time) of the peak top described above (2) relative to the duration (4). For example, the steeper the pattern, the more to the left the time position of the peak top is relative to the duration, and the more gentle the pattern, the more to the right it is. Also, for example, if the increase pattern of 5 is considered as the shape of a histogram, the steeper the pattern, the more to the left the time position of the average value relative to the duration, and the more gentle the pattern, the more to the right it is. Similarly, if the increase pattern of 5 is considered as the shape of a histogram, the steeper the pattern, the more the histogram shape is skewed to the right, and the more gentle the pattern, the more the histogram shape is skewed to the left, and the more gentle the pattern, the more the skewness is negative.

[0032] FIG. 7(3) is a graph showing the pattern strength and the pattern steepness obtained as described above. The graph shown in Figure 7(3) shows the steepness (skewness) of the pattern on the horizontal axis (first axis) and the strength of the pattern (deviation / duration) on the vertical axis (second axis). The more positive the value on the horizontal axis, the steeper the pattern, and the more negative the value, the gentler the pattern. Also, on the vertical axis, positive values ​​indicate an increasing pattern and negative values ​​indicate a decreasing pattern, and the larger the absolute value of the strength, the stronger the pattern strength, and the smaller the absolute value of the strength, the weaker the pattern strength. The pattern of Cream P is plotted as a circle, and the pattern of Cream Q is plotted as a black triangle. By comparing the sensation of each cream shown in Figure 2 and the graph in Figure 7(3) in terms of richness (weight when spread) and familiarity, the following can be evaluated. "Body (weight when spreading)": For Cream P, the decrease pattern 1 (circle marked with P-1) and for Cream Q, the decrease pattern 1 (black triangle marked with Q-1) are the points at which body (weight when spreading) is felt. Both P-1 and Q-1 are plotted in the fourth quadrant (decreasing pattern), indicating that body is a phenomenon that occurs when the finger changes from a state in which the finger is firm when initially spreading the cream (high vibration intensity) to a state in which the finger becomes lighter as the cream begins to crumble (low vibration intensity). P-1 is plotted to the lower right compared to Q-1, indicating a large (strong) decrease in vibration intensity when spreading the cream, and a sudden change. This indicates that the characteristic of the weight when spreading Cream P is that the cream crumbles and becomes lighter immediately, resulting in a lack of body. Q-1 is plotted to the upper left compared to P-1, indicating a small (weak) decrease in vibration intensity when spreading the cream, and a gradual change. This shows that the characteristic weight of Cream Q when spread is that the cream does not become too light, but rather maintains its weight and feels rich. "Break-in": This is the point where Cream P begins to break in with an increase pattern of 5 (circle marked with P-5), and Cream Q begins to break in with an increase pattern of 3 (black triangle marked with Q-3). P-5 is plotted in the second quadrant (increase pattern), and Q-3 is plotted in the first quadrant (increase pattern), indicating the phenomenon in which the finger becomes heavier and vibration intensity increases as the cream breaks into the skin. P-5's location in the second quadrant means that the increase in vibration intensity is gradual. This indicates that the break-in characteristic of Cream P is that the finger becomes heavier and breaks in gradually. Q-3's location in the first quadrant means that the increase in vibration intensity is more abrupt than P-5. This indicates that the break-in characteristic of Cream Q is that the finger suddenly becomes heavier and the feeling of break-in occurs more quickly. In this way, by quantifying the characteristics of the patterns P-5 and Q-3, the difference in break-in characteristics can be clearly evaluated.

[0033] As shown in Figure 7, by analyzing the strength, speed, shape, etc. of each pattern and creating indices, it is possible to evaluate the characteristics of each tactile sensation.

[0034] In this way, the present evaluation method generates first graph data (corresponding to the graph in Figure 7(3)) in which the pattern steepness and pattern intensity of the first feature quantity are plotted in a coordinate system including a first axis (horizontal axis) indicating the pattern steepness of the first feature quantity and a second axis (vertical axis) indicating the pattern intensity of the first feature quantity for patterns (corresponding to patterns 1 to 9 in Figure 7(1) and patterns 1 to 7 in Figure 7(2)) in which the duration of the first feature quantity (corresponding to the patterns in Figure 7(1) and patterns in Figure 7(2)) is a predetermined time or more (e.g., 4 [s] or more), and makes it possible to evaluate the skin condition and agent based on the first graph data.

[0035] Figure 8 shows the evaluation results in Figure 7 in a more visually understandable way. In Figure 8(1), the horizontal axis showing the skewness of the graph in Figure 7(3) is divided into three parts, and by filling in white, gray, and black in order from low to high skewness, it is possible to visualize the level of intensity information. Also, the vertical axis showing the pattern strength is divided into six parts, and by filling in the following lines in order from a strong decreasing pattern to a strong increasing pattern, it is possible to visualize the intensity information: a diagonal line with wide line spacing descending from left to right, a diagonal line with medium line spacing descending from left to right, a diagonal line with narrow line spacing descending from left to right, a diagonal line with narrow line spacing ascending from left to right, a diagonal line with medium line spacing ascending from left to right, and a diagonal line with wide line spacing ascending from left to right. FIG. 8(2) is a diagram similar to FIGS. 7(1) and 7(2), respectively. In Figure 8(3), the horizontal axis represents time, and the graph shows the skewness and pattern intensity according to the pattern shown in Figure 8(2). For example, the decrease pattern of Cream P at 1 in Figure 8(2) is a strong and rapid decrease pattern, so it is shown with widely spaced black lines descending from left to right. The increase pattern of Cream P at 5 is a strong and gradual increase pattern, so it is shown with widely spaced white lines ascending from left to right. The decrease pattern of Cream Q at 1 in Figure 8(2) is a slightly stronger and less rapid decrease pattern, so it is shown with medium-spaced gray lines descending from left to right. The increase pattern of Cream Q at 3 is a slightly stronger and more rapid increase pattern, so it is shown with medium-spaced black lines ascending from left to right. This representation makes it easier to visually grasp the changes and characteristics of the patterns.

[0036] 9(1) and 9(2) are similar to FIGS. 7(1) and 7(2), respectively. FIG. 9(3) is a graph with a horizontal axis indicating the bias of duration toward the increasing pattern side and a vertical axis indicating the bias of deviation amount toward the increasing pattern side, calculated based on the deviation amount and duration described above. The deviation amount bias towards the increasing pattern side and the bias of the duration towards the increasing pattern side are calculated as follows. Calculate the sum (positive value) of the deviations of the increasing pattern (Da) Calculate the total duration of the increase pattern (Ta) Calculate the sum (negative value) of the deviations of the decreasing pattern (Db) Calculate the total duration of the decreasing pattern (Tb) Deviation bias towards increasing patterns = Difference between deviations of increasing patterns and decreasing patterns (Da+Db) ÷ Total deviation (Da-Db) Bias in duration towards increasing patterns = Difference between duration of increasing patterns and duration of decreasing patterns (Ta-Tb) ÷ Total duration (Ta+Tb) The vertical axis (deviation amount deviation) and horizontal axis (duration deviation) of the graph shown in Figure 9(3) are: Cream P: 1.16 < Cream Q: 1.87 is. The following can be evaluated from Figure 9(3). Cream Q has a smaller bias in duration towards the increasing pattern side than Cream P, but a larger bias in deviation amount. This indicates that Cream Q has a stronger momentum (clear sense of change) in the original signal in the direction of increasing amplitude throughout the entire application, rather than the fact that Cream Q has a higher value on the vertical axis (deviation amount bias) / horizontal axis (deviation in duration) of the graph.

[0037] As shown in Figure 9, by analyzing the bias in the change pattern and converting it into an index, it becomes possible to evaluate the overall impression.

[0038] In this way, the present evaluation method evaluates the difference data patterns between the first indicator line (corresponding to the 6 [s] moving average line in Figure 5(2) and the 6 [s] moving average line in Figure 6(2)) and the second indicator line (corresponding to the 10 [s] moving average line in Figure 5(2) and the 10 [s] moving average line in Figure 6(2)) including increase patterns in which the difference data is positive (e.g., increase pattern 5 in Figure 7(1) and increase pattern 3 in Figure 7(2)) and decrease patterns in which the difference data is negative (e.g., decrease pattern 1 in Figure 7(1) and decrease pattern 1 in Figure 7(2)), and evaluates the total duration of the increase pattern (equivalent to Ta) for patterns in which the duration of the first feature amount (equivalent to the patterns in Figure 7(1) and each pattern in Figure 7(2)) is a predetermined time or more (equivalent to 4 [s], for example) (equivalent to each of the patterns 1 to 9 in Figure 7(1) and each of the patterns 1 to 7 in Figure 7(2)). The total deviation amount of the increase pattern (corresponding to Da), the total duration of the decrease pattern (corresponding to Tb), and the total deviation amount of the decrease pattern (corresponding to Db) are calculated, and from the calculation results, the bias in duration (e.g., the difference between the duration of the increase pattern and the duration of the decrease pattern (equivalent to Ta-Tb) ÷ total duration (Ta+Tb)) and the bias in deviation amount (e.g., the bias in deviation amount towards the increase pattern = the difference between the deviation amount of the increase pattern and the deviation amount of the decrease pattern (equivalent to Da+Db) ÷ total deviation amount (Da-Db)) are determined, and second graph data (corresponding to the graph in Figure 9(3)) is generated in which the bias in duration and the bias in deviation amount are plotted on a coordinate system including a first axis (equivalent to the horizontal axis) indicating the bias in duration and a second axis (equivalent to the vertical axis) indicating the bias in deviation amount, and it becomes possible to evaluate the skin condition and the agent based on the second graph data.

[0039] In analysis method 1, the singular point (corresponding to a change point) is a first singular point, which is a point where a first indicator line (corresponding to, for example, the thick line in FIG. 5(2) and the thick line in FIG. 6(2)) indicating a trend for each first period (corresponding to, for example, a predetermined period of 6 [s]) of the time series data intersects with a second indicator line (corresponding to, for example, the thin line in FIG. 5(2) and the thin line in FIG. 6(2)) indicating a trend for each second period different from the first period (corresponding to, for example, a predetermined period of 10 [s]). The feature amount can be evaluated using at least one of the pattern, peak top, deviation amount, duration, slope, shape, pattern intensity, or pattern steepness of the difference data between the first indicator line and the second indicator line within a local time period starting or ending at the first singular point.

[0040] (b) Analysis Method 2 Analysis method 2 is shown in Figure 10. Fig. 10(1) shows time-series data of mechanical physical quantities (original signal) (corresponding to the thin line in Fig. 10(1)), a moving average line (corresponding to the thick line in Fig. 10(1)) obtained by calculating a simple moving average of the waveform of the original signal for a predetermined period (third period), a standard deviation line (upper band) (corresponding to the dotted line in Fig. 10(1)) showing upward variations around the moving average line, and a standard deviation line (lower band) (corresponding to the dashed-dotted line in Fig. 10(1)) showing downward variations around the moving average line. In this embodiment, the predetermined period is set to 6 [s], but may be determined taking into consideration the evaluation target, evaluation conditions, etc. The moving average line and standard deviation line will be explained using Figure 10(2). As shown in FIG. 10(2), portions (abnormal points) that exceed a predetermined range of the standard deviation for the moving average are determined. Here, the normal distribution and standard deviation are such that approximately 68% of the total falls within a range of ±1σ of the mean value, approximately 95% falls within a range of ±2σ of the mean value, and approximately 99% falls within a range of ±3σ of the mean value. In this embodiment, the predetermined range of the standard deviation is set to ±2σ, and signals that exceed the ±2σ range are determined as abnormal signals. Points that exceed the ±2σ range are then analyzed as change points. Note that, although the predetermined range of the standard deviation is set to ±2σ in this embodiment, it is not necessary to be limited to this range; the range can be determined taking into consideration the evaluation target, evaluation conditions, etc.

[0041] FIG. 11 shows the process of finding change points (singular points) from the original signal for cream P. Figure 11(1) shows time series data (original signal) of mechanical physical quantities obtained when a finger is placed in contact with skin with cream P on it and the finger is repeatedly moved, and for the waveform of the original signal, a moving average line for the third period (6 [s]), a standard deviation line (upper band) showing upward variations around the moving average line, and a standard deviation line (lower band) showing downward variations around the moving average line. FIG. 11(2) shows the point where the original signal exceeds the upper band, and this point where the original signal exceeds the upper band is defined as the change point. Figure 11(3) shows the cumulative values ​​of the points at which the upper band shown in Figure 11(2) is exceeded. Expressing the points as cumulative values ​​makes it easier to visually grasp the timing and intensity of the change points. Note that Figure 11(2) shows the points at which the upper band is exceeded, but the same evaluation can be performed by calculating the points at which the lower band is exceeded.

[0042] Fig. 12 shows the process of finding change points (singular points) from the original signal for Cream Q. Fig. 12(1) to Fig. 12(3) are the same as Fig. 11, so the explanation will be omitted. In this way, it is possible to clearly identify the change points (also called singular points) that exceed a predetermined range of standard deviation for the moving average line. Furthermore, from Figures 11 and 12, it is clear that the change points for Cream P and Cream Q are different. Furthermore, by extracting change points near the change points found by analysis method 1, it is possible to capture the change in texture.

[0043] As is clear from Figures 11 and 12, change points can be clearly extracted using analysis method 2. Furthermore, because change points are extracted near the change points obtained using analysis method 1, it is possible to detect signs of changes in tactile sensation.

[0044] In this way, this evaluation method generates third graph data (corresponding to the graph in Figure 11(3) or Figure 12(3)) in which the elapsed time and the cumulative value are plotted on a coordinate system including a first axis (corresponding to the horizontal axis) indicating the elapsed time and a second axis (vertical axis) indicating the cumulative value of the second feature amount (corresponding to the intensity of the difference data between the time series data at the second singular point and the value of the standard deviation line), and makes it possible to evaluate the skin condition and the agent based on the third graph data.

[0045] Next, the evaluation results based on the change points obtained by analysis method 2 will be explained. The change point intensity per unit time is calculated from the change points obtained by analysis method 2 as follows: Change point intensity per unit time: Sum of the intensity of each change point (original signal - upper band) / application time Table 1 shows the change point intensity per unit time.

[0046] [Table 1]

[0047] As shown in Table 1, Cream Q has a greater change intensity per unit time than Cream P. This indicates that Cream Q has a more distinct change sensation. In this way, it is possible to clearly evaluate the overall difference in the characteristics of the tactile sensation from the start to the end of application.

[0048] In analysis method 2, the singular point (corresponding to the change point) is a second singular point (e.g., a point beyond the upper band in FIG. 11(1) or the point beyond the upper band in FIG. 12(1)) where the time series data intersects with a third indicator line (e.g., a moving average line in FIG. 11(1) or FIG. 12(1)) that indicates the trend of the time series data (e.g., the original signal) for each third period (e.g., a predetermined period of 6 [s]) and a standard deviation line (e.g., an upper band or a lower band in FIG. 11(1) or FIG. 12(1)) that indicates the variation within a predetermined range above or below the third indicator line (e.g., a moving average line in FIG. 11(1) or FIG. 12(1)). The feature value is a second feature value (e.g., a change point intensity per unit time: a sum of the intensities of each change point (original signal - upper band) / application time) that is an intensity based on the difference data between the time series data at the second singular point and the value of the standard deviation line. Evaluation can be performed using the second feature value.

[0049] (c) Analysis Method 3 Analysis method 3 is shown in FIG. Fig. 13(1) shows time-series data of mechanical physical quantities (original signal) (corresponding to the thin line in Fig. 13(1)) and data (referred to as "moving skewness" in this embodiment) (corresponding to the thick line in Fig. 13(1)) obtained by calculating the skewness of the waveform of the original signal for each predetermined period (fourth period). In this embodiment, the predetermined period is set to 6 [s], but it may be determined taking into consideration the evaluation target, evaluation conditions, etc.

[0050] Figure 13(2) shows the data obtained by differentiating the moving skewness in Figure 13(1) (corresponding to the thick line in Figure 13(2)). The spike signals in the data obtained by differentiating the moving skewness indicate the timing of a large change, so they are identified as change points and analyzed.

[0051] Figure 14(1) shows time series data (original signal) of mechanical physical quantities acquired when a finger is placed in contact with skin onto which cream P has been applied and the finger is repeatedly moved, and data obtained by differentiating the moving skewness calculated from the waveform of the original signal for each predetermined period. The spike signals in the differential data of the skewness are taken as change points. Figure 14(2) shows the time series data (original signal) of mechanical physical quantities acquired when a finger is placed in contact with skin on which Cream Q has been applied and the finger is repeatedly moved, and the data obtained by differentiating the moving skewness calculated from the waveform of the original signal for each predetermined period. The spike signals in the differential data of the skewness are taken as change points. In this way, the change point can be clearly extracted based on the spike signal from the data obtained by differentiating the movement skewness. Furthermore, by extracting the change point near the change point obtained by analysis method 1, the change in tactile sensation can be captured.

[0052] Figure 15(1) shows time series data (original signal) of mechanical physical quantities acquired when a finger is placed in contact with skin onto which cream P has been applied and the finger is repeatedly moved, and data obtained by differentiating the moving kurtosis, which is calculated as the kurtosis for each predetermined period of time for the waveform of the original signal. The spike signals in the differential data of kurtosis are taken as change points. Figure 15(2) shows the time series data (original signal) of mechanical physical quantities acquired when a finger is placed in contact with skin on which Cream Q has been applied and the finger is repeatedly moved, and the data obtained by differentiating the moving kurtosis, which is the kurtosis calculated for each predetermined period of time for the waveform of the original signal. The spike signals of the differential data of kurtosis are taken as change points. In this way, the change point can be clearly extracted based on the spike signal from the data obtained by differentiating the kurtosis. Furthermore, by extracting a change point near the change point obtained by analysis method 1, the change in tactile sensation can be captured.

[0053] Next, the evaluation performed based on the change points obtained by analysis method 3 will be described. The change point intensity per unit time is calculated from the change points obtained by analysis method 3 as follows: "Change point intensity per unit time": Sum of spike signal intensities above the threshold / application time In this embodiment, the sum of spike signal intensities is calculated using spike signals (top 5%) with a threshold greater than the average +1.65σ, but it is preferable to determine the threshold taking into consideration the evaluation target, evaluation conditions, etc. Table 2 shows the change intensity per unit time.

[0054] [Table 2]

[0055] From Table 2, Cream Q has a greater change point intensity per unit time than Cream P. This indicates that Cream Q has a more distinct change sensation. In this way, it is possible to clearly evaluate the overall difference in the characteristics of the tactile sensation from the start to the end of application. In this way, in Table 2, the intensity per unit time at the third singular point is calculated based on the time for which the operating body is operated (e.g., equivalent to the application time) and the total third feature quantity (e.g., equivalent to the sum of the intensities of spike signals above the threshold) of third feature quantities that are above a predetermined value (in this embodiment, above the threshold (average + 1.65σ)) during that time, and the skin condition or agent can be evaluated based on the calculation results.

[0056] In analysis method 3, the singular point (corresponding to the change point) is a third singular point (corresponding to the spike signals in Figures 14(1), 14(2), 15(1), and 15(2)), which is a point where a change of a predetermined value or more occurs when the skewness (e.g., moving skewness) or kurtosis (e.g., moving kurtosis) of each fourth period (e.g., a predetermined period of 6 [s]) of time series data (e.g., an original signal) is extracted, and the extracted skewness or kurtosis is differentiated with respect to time (e.g., Figures 14(1), 14(2), 15(1), and 15(2)). The feature is a third feature (e.g., change point intensity per unit time: equivalent to the sum of spike signal intensities above a threshold / application time), which is the amount of change when the skewness or kurtosis is differentiated with respect to time at the third singular point. Evaluation can be performed using the third feature.

[0057] In this way, it was possible to identify the change point at approximately the same time after the start of application using any of analysis methods 1 to 3. Although the evaluation results using each of analysis methods 1 to 3 have been described above, evaluation may also be performed using analysis methods 1 and 2, analysis methods 1 and 3, analysis methods 2 and 3, or analysis methods 1 to 3.

[0058] <Evaluation of similarity between agents> Next, a method for evaluating the similarity between preparations will be described. Evaluating the similarity between preparations involves comparing the change points and change patterns of each preparation to evaluate whether the preparations are similar in type or texture. The measurement method and data used for evaluation are shown below. -Method of measuring vibration waveform Three different creams (reference cream R, comparison cream S, comparison cream T) were dropped one by one onto the skin of the same evaluator (similar to Figure 1), and measurements were taken from the start of application to the end of application (end of absorption). Data used in the evaluation Create a raw signal of the vibration amplitude (root mean square: RMS) in the 10-500 Hz band. Use analysis method 1 to find the change points and change patterns for the raw signal. FIG. 16 shows the difference data between two moving averages created using analysis method 1 for Reference Cream R (FIG. 16(1)), Comparative Cream S (FIG. 16(2)), and Comparative Cream T (FIG. 16(3)). In this embodiment, the two moving averages are 6 [s] and 10 [s] moving averages. The vertical axis of each graph: the deviation rate, is calculated as follows: Deviation rate = Difference value ÷ 10 [s] moving average value × 100

[0059] Next, we will explain the evaluation carried out based on the change points and change patterns obtained by analysis method 1. To evaluate the similarity between each cream, the similarity was calculated as follows. Create a vector from the difference data of two moving averages. Calculate the similarity between the vectors of the reference cream R and the comparison creams S and T. The similarity between the vectors is calculated using, for example, the angle (cosθ) between the vectors obtained by calculating the dot product or the Euclidean distance. Here, two methods for creating vectors will be described. a) A vector whose components are index values The deviation amount bias towards the increasing pattern side and the bias of the duration towards the increasing pattern side are determined by the method explained in the evaluation method using analysis method 1. Calculate the sum (positive value) of the deviations of the increasing pattern (Da) Calculate the total duration of the increase pattern (Ta) Calculate the sum (negative value) of the deviations of the decreasing pattern (Db) Calculate the total duration of the decreasing pattern (Tb) Deviation bias towards increasing patterns = Difference between deviations of increasing patterns and decreasing patterns (Da+Db) ÷ Total deviation (Da-Db) Bias in duration towards increasing patterns = Difference between duration of increasing patterns and duration of decreasing patterns (Ta-Tb) ÷ Total duration (Ta+Tb) b) A vector whose components are the difference values ​​of the moving average line In either method a) or b), it is also possible to create a vector using multiple frequency bands. Table 3 shows the vector components obtained by method a).

[0060] [Table 3]

[0061] The results of calculating the similarity from the angle (cosθ) between vectors whose components are the index values ​​shown in Table 3 are shown below. The similarity (cosθ) to the reference cream R was 0.97 for the comparative cream S and 0.091 for the comparative cream T. Therefore, it can be evaluated that the comparative cream S is more similar to the reference cream R than the comparative cream T. By evaluating the similarity between creams in this way, it becomes possible to classify creams by type, which can also be used for promotions to users. It is also possible to evaluate the similarity of data obtained by applying the same cream to multiple evaluators. By evaluating this similarity, it is possible to classify skin types, such as those that adapt quickly or those that adapt slowly, and this can also be used to evaluate the similarity or difference in the way evaluators feel the texture.

[0062] <About the evaluation system> The evaluation system 200 will be described with reference to FIG. The evaluation system 200 in this embodiment is composed of a moving object 110, an acquisition unit 120, an identification unit 130, a calculation unit 140, and an evaluation unit 150. The evaluation system 200 also includes an information processing terminal 100 capable of executing various processes, and the information processing terminal 100 is equipped with the identification unit 130, the calculation unit 140, and the evaluation unit 150. The information processing terminal 100 is equipped with input devices such as a keyboard and a pointing device, an arithmetic processing unit, a storage unit, etc. The information processing terminal 100 is also preferably equipped with a display unit 160 (display device), but may be provided external to the information processing terminal 100 and connected via a network.

[0063] The moving object 110 is a finger 20, a palm, or a measurement tool that is brought into contact with the surface of the skin. The acquisition unit 120 is a means for acquiring, over time, a mechanical physical quantity generated by moving the finger 20, using the sensor 30 attached to the finger 20 shown in Fig. 1. The mechanical physical quantity (electrical signal) acquired by the sensor 30 can be acquired by the information processing terminal 100 via a network line, a medium, etc. The identifying unit 130 identifies singular points where the tendency of the repeated waveform pattern changes over time in the time-series data of the mechanical physical quantity acquired by the acquiring unit 120. The singular points to be identified are the same as those described above in the analysis methods 1 to 3. The calculation unit 140 calculates a feature quantity that represents the characteristics of the waveform at the identified singular point or within a local time period starting or ending at the singular point. The calculated feature quantity is the same as those described above in the analysis methods 1 to 3. The evaluation unit 150 evaluates the skin condition, agent, technique, or environment using the feature amounts calculated by the calculation unit 140. The evaluation content is the same as that described above. It is preferable that the evaluation results by the evaluation unit 150 be displayed on the display unit 160 so that the evaluator can easily understand them. The display unit 160 displays the evaluation results by the evaluation unit 150, for example, the graphs shown in FIGS. 5 to 9, 11, 12, 14, and 15. Furthermore, the arithmetic processing device may be controlled to output a predetermined sound from an audio output unit (not shown) based on the evaluation results by the evaluation unit 150. Specifically, for the graphs (evaluation contents) of FIG. 5(4) and FIG. 6(4), for example, different sounds may be output for the increasing and decreasing patterns, with different volumes corresponding to the strength of the intensity and different pitches corresponding to the speed of the sound. In this way, the subject can grasp the difference in speed from the sudden change in pitch, and the difference in intensity from the difference in volume. In this way, the calculated feature may be converted to a predetermined volume and / or type of sound, and the sound may be output so that the subject can grasp the change in the feature. Note that the calculated feature may also be converted to a predetermined volume and / or type of sound, and the sound may be output in the same way for other evaluation results (other graphs).

[0064] Just as the mechanical physical quantity (electrical signal) acquired by the sensor 30 can be acquired by the information processing terminal 100 via a network line, medium, etc., the evaluation results may be acquired by another information processing terminal (not shown) different from the information processing terminal 100 via a network line, medium, etc. In this way, a user (subject) in a location different from the information processing terminal 100 may transmit a mechanical physical quantity (electrical signal) acquired using the sensor 30 to the information processing terminal 100, calculate feature quantities in the information processing terminal, and transmit the evaluation results to the other information processing terminal via a network line, medium, etc. In this way, the user can easily evaluate the skin condition, agent, procedure, or environment.

[0065] <Modification> In this embodiment, frequency analysis is performed and RMS-processed signal data is used as the original signal, but such processing is not necessary. Furthermore, frequency analysis may be performed by using a signal that has passed through a predetermined filter when acquiring a time-series waveform signal, extracting a desired frequency (band), modulating the signal intensity of a desired frequency (band), or modulating the signal intensity without selecting a frequency (band). Furthermore, during analysis, predetermined calculations such as Fourier transform or wavelet transform may be performed, so that time-series data for each frequency band can be used for analysis and evaluation. Frequency analysis may be performed, for example, using frequencies at which the vibratory sense (Pachinko corpuscles) is highly sensitive.

[0066] In this embodiment, the two moving averages used in analysis method 1 are simple moving averages (SMA), but they may also be, for example, exponentially smoothed moving averages (EMA) or weighted moving averages (WMA), which strongly reflect recent fluctuations. A preferred calculation may be used taking into consideration the evaluation target, evaluation conditions, etc. Furthermore, while moving averages are used to grasp the trends for each first period and each second period, they are not limited to moving averages and may also be standard deviations or variances as long as they can grasp the trends.

[0067] In the analysis method 1, the "pattern steepness" is calculated based on the timing (time) of the peak top relative to the duration, but this is not limiting. For example, the index may be calculated based on the time position that is the half-width of the deviation relative to the duration.

[0068] In analysis method 1, when determining the bias in duration and the bias in deviation, the total deviation amount of the increase patterns is calculated as the sum of the deviation amounts of the increase patterns, the total duration of the increase patterns is calculated as the sum of the durations of the increase patterns, the total deviation amount of the decrease patterns is calculated as the sum of the deviation amounts of the decrease patterns, and the total duration of the decrease patterns is calculated as the sum of the durations of the decrease patterns, but this is not limitative. For example, the total duration and the total deviation amount may be calculated after noise removal is performed on the data of each pattern.

[0069] In analysis method 1, each feature amount is calculated and evaluated using the difference data between the first index line and the second index line, but this is not limiting. For example, feature amounts may be calculated based on the positions of the first index line and the second index line (when the first index line is located closer to 0 on the horizontal axis than the second index line and closer to a larger value on the vertical axis than the second index line, this is an increasing pattern).

[0070] In analysis method 2, each feature amount is calculated and evaluated using the difference data between the time series data and the value of the standard deviation line, but this is not limiting. For example, the feature amount may be calculated based on the position of the time series data and the standard deviation line.

[0071] The evaluation results of the agent using this evaluation method make it possible to quantitatively evaluate whether the developed agent has achieved its development objectives, for example, whether a cream that is quickly absorbed has been developed, or whether a cream that feels just right has been developed.

[0072] In this embodiment, a predetermined agent is dropped onto the skin, and time-series data from the start of application to the end of application is analyzed and evaluated, but this is not limited to this. For example, time-series data obtained after a predetermined time has elapsed after the application of a predetermined agent may be acquired and analyzed and evaluated. In this way, by comparing the evaluation from the start of application to the end of application with the analysis and evaluation based on the time-series data after the predetermined time has elapsed, it is possible to evaluate the skin condition and the influence (effect) of the agent over time.

[0073] In this embodiment, the evaluation of the skin condition and the evaluation of the agent by evaluating the tactile sensation have been described, but the evaluation method can also be used to evaluate the procedure or the environment. In this embodiment, the term "technique" refers to skin care techniques such as cleansing and massage, techniques for improving dullness and acne scars, and techniques for reducing fine wrinkles and depressions. These techniques can be evaluated by acquiring and analyzing vibration waveform data from the start to the end of the procedure. For example, in the case of cleansing (using water only), changes occur in the amount of dirt and sebum on the skin (skin surface) between the start and end of washing, and the points and patterns of these changes can be evaluated. Furthermore, if a specific agent is used during the procedure, this also corresponds to an evaluation of the agent and an evaluation of the feel of the skin during the procedure. Furthermore, if cleansing is performed with cold water or lukewarm water, this also corresponds to an evaluation of the conditions of the water used for cleansing, i.e., the environment. In this embodiment, the "environment" refers to the location and condition of the skin (skin surface), such as indoors / outdoors, humidity, temperature, whether it is exposed to sunlight or lighting, whether it is exposed to wind, etc. For example, two spaces with different humidity levels are prepared, and the moving body starts moving when the skin is in one space, and while continuing the movement, the skin is moved to the other space, and the vibration waveform data obtained is continuously acquired and analyzed, thereby evaluating the environment and also the texture of the skin. In this way, this evaluation method makes it possible to evaluate the skin condition, agent, technique, or environment.

[0074] In this embodiment, the sensor 30 is attached to the moving object, but this is not limiting, and the sensor 30 may be attached to the skin. In this way, time-series data of the mechanical physical quantity occurring between the skin and the moving object can be obtained, so that it becomes possible to evaluate the skin condition, agent, procedure, or environment even in the case of a moving object to which the sensor 30 is difficult to attach (for example, a thin object such as a cotton swab).

[0075] In FIG. 8 , which shows the evaluation results based on the analysis using analysis method 1, the horizontal axis indicating the skewness is divided into three, but the number of divisions is not limited to this and may be further divided into smaller stages, for example. Furthermore, although the slowness / slowness information is expressed by filling in white, gray, and black in order from low to high skewness, any color may be used. Furthermore, although different colors are used for each division, for example, the colors may be continuously changed according to the skewness value, or the color intensity may be continuously changed. Furthermore, although the slowness / slowness information is expressed by different colors, it may also be expressed by different shapes (different fill patterns). Similarly, although the vertical axis indicating the pattern strength is divided into six, the number of divisions is not limited to this and may be further divided into smaller or more coarse stages, for example. Furthermore, the intensity information is expressed by a diagonal line with wide spacing descending from left to right, a diagonal line with medium spacing descending from left to right, a diagonal line with narrow spacing descending from left to right, a diagonal line with narrow spacing ascending from left to right, a diagonal line with medium spacing ascending from left to right, and a diagonal line with wide spacing ascending from left to right, in the order from a decreasing pattern with a strong intensity to a increasing pattern with a strong intensity. However, the spacing and type of diagonal lines may be any, and the information may be expressed by different shapes (different fill patterns), different colors, or different color intensities. When expressing the information by different colors or color intensities, in addition to varying the colors for each division, for example, the colors may be continuously changed according to the intensity value, or the color intensities may be continuously changed. The number of divisions, the types of colors, the types of fill patterns, etc. may be determined in a visually easy-to-understand manner, taking into consideration the evaluation target and evaluation conditions. [Explanation of symbols]

[0076] 10 Arithmetic unit 20 fingers 30 sensors 100 Information processing terminal 110 Action 120 Acquisition Department 130 Specific section 140 Calculation Unit 150 Evaluation Department 160 Display section 200 Rating System

Claims

1. A method executed by an information processing terminal, comprising a step of analyzing changes over time in skin to which a predetermined agent, procedure, or environment has been applied, The information processing terminal, a moving object in contact with the skin is repeatedly moved to acquire time-series data of a mechanical physical quantity occurring between the skin and the moving object; Identifying singular points where the tendency of a repeated waveform pattern in the acquired time series data changes over time; determining a feature quantity representing a waveform characteristic at the identified singular point or within a local time period starting or ending at the singular point; An evaluation method for evaluating the skin condition, the agent, the procedure, or the environment based on the obtained feature amount.

2. 2. The evaluation method according to claim 1, wherein the specific point is a point where the intensity of the waveform pattern changes.

3. The singular point is a first singular point which is a point where a first indicator line indicating a trend for each first period of the time series data and a second indicator line indicating a trend for each second period different from the first period intersect; The feature amount is 3. The evaluation method according to claim 1, wherein the first feature amount is at least one of a pattern, a peak top, a deviation amount, a duration, a slope, a shape, a pattern intensity, or a pattern steepness / slowness of the difference data between the first index line and the second index line within a local time period starting or ending at the first singular point.

4. The singular point is a second singular point which is a point where the time series data intersects with a standard deviation line which indicates a variation in a predetermined range at least either above or below a third indicator line which indicates a trend of the time series data for each third period, The feature amount is The evaluation method according to claim 1 or 2, wherein the second feature amount is an intensity based on difference data between the time series data at the second singular point and the value of the standard deviation line.

5. The singular point is a third singular point being a point at which a change of a predetermined value or more occurs when the skewness or kurtosis of the time series data for each fourth period is extracted and the extracted skewness or kurtosis is differentiated with respect to time; The feature amount is The evaluation method according to claim 1 or 2, wherein the third feature amount is a change amount when the skewness or the kurtosis is differentiated with respect to time at the third singular point.

6. generating first graph data by plotting the slope and the deviation of the first feature amount in a coordinate system including a first axis indicating the pattern steepness of the first feature amount and a second axis indicating the pattern intensity of the first feature amount, for a pattern whose duration of the first feature amount is equal to or longer than a predetermined time; The evaluation method according to claim 3 , wherein the skin condition, the agent, the technique, or the environment is evaluated based on the first graph data.

7. a pattern of difference data between the first index line and the second index line includes an increasing pattern in which the difference data is a positive value and a decreasing pattern in which the difference data is a negative value; For patterns in which the duration of the first feature amount is equal to or longer than a predetermined time, a total duration of the increase pattern, a total deviation amount of the increase pattern, a total duration of the decrease pattern, and a total deviation amount of the decrease pattern are calculated, and a bias in the duration and a bias in the deviation amount are obtained from the calculation results; generating second graph data in which the bias in the duration and the bias in the deviation amount are plotted on a coordinate system including a first axis indicating the bias in the duration and a second axis indicating the bias in the deviation amount; The evaluation method according to claim 3 , wherein the skin condition, the agent, the technique, or the environment is evaluated based on the second graph data.

8. generating third graph data in which the elapsed time and the cumulative value of the second feature amount are plotted on a coordinate system including a first axis indicating the elapsed time and a second axis indicating the cumulative value of the second feature amount; The evaluation method according to claim 4 , wherein the skin condition, the agent, the procedure, or the environment is evaluated based on the third graph data.

9. 6. The evaluation method according to claim 5, further comprising: calculating an intensity per unit time at the third singular point based on a time period during which the moving object is operated and a total third feature quantity of the third feature quantities that are equal to or greater than a predetermined value during that time period; and evaluating the skin condition, the agent, the procedure, or the environment based on the calculation result.

10. An evaluation system that analyzes and evaluates how skin changes over time after application of a specific agent, procedure, or environment, an acquisition unit that acquires time-series data of mechanical physical quantities occurring between the skin and the moving object by repeatedly moving the moving object that is in contact with the skin; an identifying unit that identifies a singular point where a tendency of a repeated waveform pattern in the acquired time series data changes over time; a calculation unit that calculates a feature quantity that represents a feature of a waveform at the identified singular point or within a local time period starting or ending at the singular point; and an evaluation unit that evaluates the skin condition, the agent, the procedure, or the environment based on the obtained feature amount.

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