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 the state of the skin, agents, techniques, or environment.

Background Art

[0002] There is an evaluation method in which vibrations generated by moving an operating body while contacting the operating body with a cosmetic applied to the skin or the like are detected, and the tactile feeling of the cosmetic is evaluated based on the change over time of the frequency spectrum of the detected vibrations (Patent Document 1). Also, there is an evaluation method in which a contact element is moved while contacting the contact element with the skin or the like, vibrations are detected by a sensor provided on the contact element, and the state of the skin or the like is evaluated based on the difference in the detected vibration information (difference in vibration intensity) (Patent Document 2). Furthermore, in Japanese Patent Application No. 2022-020264 previously filed by the present applicant, a mechanical physical quantity generated by moving an operating body while contacting the operating body with a cosmetic applied to the skin or the like is measured, a feature quantity related to time is extracted from the measured mechanical physical quantity, and the tactile feeling of the skin surface or the applied cosmetic is evaluated based on the extracted feature quantity.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] Patent Document 1 only quantifies the temporal change in the intensity of vibrations and has not been able to perform an evaluation based on the timing and change pattern of the changed tactile feeling. Patent Document 2 only performs evaluations based on differences in detected vibration information (differences in vibration intensity), and therefore fails to perform evaluations based on the timing or pattern of changes in vibration intensity. Furthermore, since the aforementioned Japanese Patent Application No. 2022-020264 only performs evaluations based on the timing of changes in feature quantities within one cycle of contact operation, it was desirable to perform evaluations based on the timing of changes that occur over time.

[0005] The present invention has been made in view of the above problems, and relates to an evaluation method for evaluating the condition of the skin, agents, techniques, or environment 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 body. [Means for solving the problem]

[0006] The present invention relates to an evaluation method that includes the step of analyzing how skin changes over time when a predetermined agent, technique, or environment is applied, the method comprising: repeatedly operating a moving body in contact with the skin to acquire time-series data of mechanical and physical quantities generated between the skin and the moving body; identifying singularities in the acquired time-series data where the tendency of the repeating waveform pattern changes over time; determining feature quantities that represent the characteristics of the waveform at the identified singularity, or within a local time period starting or ending at the singularity; and evaluating the state of the skin, the agent, the technique, or the environment based on the determined feature quantities.

[0007] Furthermore, the present invention relates to an evaluation system for analyzing and evaluating how skin changes over time when a predetermined agent, technique, or environment is applied, comprising: an acquisition unit that repeatedly operates an action body in contact with the skin to acquire time-series data of mechanical and physical quantities generated between the skin and the action body; an identification unit that identifies singularities in which the tendency of the repeating waveform pattern in the acquired time-series data changes over time; a calculation unit that determines feature quantities that represent the characteristics of the waveform at the identified singularity, or within a local time period starting or ending at the singularity; and an evaluation unit that evaluates the state of the skin, the agent, the technique, or the environment based on the determined feature quantities. [Effects of the Invention]

[0008] According to the method provided by the present invention, it is possible to quantitatively and comprehensively evaluate the timing of changes in mechanical physical quantities occurring over time in time-series data between the skin and the moving body, making it possible to evaluate the condition of the skin, or the agents, techniques, or environment applied to the skin with high accuracy. [Brief explanation of the drawing]

[0009] [Figure 1] This is an illustrative diagram showing a finger with a sensor attached being placed in contact with the evaluator's skin surface. [Figure 2] This is a diagram showing a time-series waveform signal. [Figure 3] This is a flowchart showing the evaluation method (this method) of this embodiment. [Figure 4] This figure shows an overview of analysis method 1. [Figure 5] This figure shows the results of analyzing the original signal of Cream P using analysis method 1. [Figure 6] This figure shows the results of analyzing the original signal of Cream Q using analysis method 1. [Figure 7] This figure shows the evaluation results based on the analysis using analysis method 1. [Figure 8] This figure shows the evaluation results based on the analysis using analysis method 1. [Figure 9] It is a diagram showing evaluation contents based on the result of analysis using analysis method 1. [Figure 10] It is a diagram showing an outline of analysis method 2. [Figure 11] It is a diagram showing the result of analyzing the original signal of Cream P using analysis method 2. [Figure 12] It is a diagram showing the result of analyzing the original signal of Cream Q using analysis method 2. [Figure 13] It is a diagram showing an outline of analysis method 3. [Figure 14] It is a diagram showing the result (skewness) of analyzing the original signals of Cream P and Cream Q using analysis method 3. [Figure 15] It is a diagram showing the result (kurtosis) of analyzing the original signals of Cream P and Cream Q using analysis method 3. [Figure 16] It is a diagram showing the evaluation content (similarity evaluation) based on the result of analysis using analysis method 1. [Figure 17] It is a block diagram of evaluation system 200.

Embodiments for Carrying Out the Invention

[0010] Hereinafter, examples of preferred embodiments of the present invention will be described with reference to the drawings. Note that the drawings of this embodiment are all for explaining the technical idea, configuration, and operation of the present invention, and do not specifically limit the configuration. Also, in all the drawings, the same components are denoted by the same reference numerals, and duplicate explanations will be omitted as appropriate.

[0011] <Outline> The outline of the evaluation method in this embodiment will be described. The evaluation method of this embodiment (hereinafter sometimes referred to as this method) is a method including a step of analyzing how the skin to which a predetermined agent, technique, or environment is applied changes over time. The method includes repeatedly operating an operating body that contacts the skin to obtain time-series data of a mechanical physical quantity generated between the skin and the operating body, identifying a singular point at which the tendency of the pattern of the waveform repeated in the obtained time-series data changes over time, obtaining a feature quantity representing the characteristics of the waveform at the identified singular point or within a local time period having the singular point as a starting point or an ending point, and evaluating the state of the skin, the agent, the technique, or the environment based on the obtained feature quantity.

[0012] In the prior art, for example, in Patent Document 1, vibrations generated by moving an operating body while contacting the operating body with a cosmetic applied to the skin or the like were detected, and the tactile sensation of using the cosmetic was evaluated based on the change over time of the detected frequency spectrum. However, since evaluation based on the timing and change pattern of the change in the frequency spectrum could not be performed, for example, the timing of the change in the tactile sensation of use could not be evaluated, and sufficient evaluation could not be performed. Further, for example, in Patent Document 2, a contactor was moved while contacting the contactor with the skin or the like, vibrations were detected by a sensor provided in the contactor, and the state of the skin or the like was evaluated based on the difference in the detected vibration information (difference in vibration intensity). However, since evaluation could not be performed based on the timing and change pattern of the change in the vibration intensity, for example, the timing of the change in the tactile sensation of use could not be evaluated, and sufficient evaluation could not be performed. Therefore, in this method, an operating body that contacts the skin is repeatedly operated to obtain time-series data of a mechanical physical quantity generated between the skin and the operating body, a singular point at which the pattern of the repeatedly occurring waveform changes is identified, a feature quantity representing the characteristics of the waveform at the singular point is obtained, and the state of the skin, the agent, the technique, or the environment is evaluated based on the obtained feature quantity.

[0013] Hereinafter, this method will be described in more detail.

[0014] Figure 1 shows how to acquire time-series data of mechanical physical quantities occurring between the skin and the moving body in this method. "Skin" refers to the surface of human skin or artificial skin. Furthermore, the skin surface includes not only bare skin but also the surface of skin to which a specified agent (described later) has been applied. That is, contact with the skin surface by fingers or palms includes not only direct contact between fingers or palms and bare skin, but also indirect contact with bare skin via the application film of the specified agent. The location of the human skin surface, i.e., the body part, is irrelevant. When evaluating the tactile sensation of a specified agent, it is preferable to evaluate areas of the skin surface that are free of irregularities such as warts or acne scars. This is because it is difficult to determine whether the tactile sensation when touching the skin surface is due to the specified agent or the shape of the skin surface. However, this is not limited to cases where, for example, you want to evaluate by touch whether the irregularities have been covered (whether the skin surface has become flat) by applying the specified agent to uneven skin. It is desirable to determine the skin surface to be evaluated according to the conditions to be evaluated. Furthermore, artificial skin is a material that artificially mimics the surface of skin and has properties similar to human skin. In this embodiment, unless otherwise specified, "skin" refers to the skin of a human arm (the surface of the skin on a human arm) as shown in Figure 1. A "moving object" is an object that comes into contact with the skin, such as a finger 20, palm, skincare products, makeup products, a massager, or a measuring jig. The finger 20, palm, skincare products, makeup products, massager, or measuring jig is equipped with the sensor 30 shown in Figure 1. Any part of the finger 20 can come into contact with the skin, but the fingertip is preferred as it is often used to confirm tactile sensation. When confirming the tactile sensation of the skin, multiple fingers may be used instead of just one, and sometimes the entire palm may be used in contact with the skin, so the palm may also be used in contact with the skin surface. A measuring jig is a jig that comes into contact with the skin surface, similar to a finger. The structure of the part of the measuring jig that comes into contact with the skin surface is not limited, but by constructing this part with artificial skin, it becomes possible to measure physical quantities similar to those when a person touches the skin surface with their finger or palm.

[0015] "Specified agent" refers to a liquid or solid such as a powder applied to the skin (skin surface). Examples include topical skin preparations, cosmetics, sheet-type skincare cosmetics, and cleansing agents. Examples include skincare cosmetics such as lotions, emulsions, creams, serums, massage products, 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 correctors, eyeshadows, blushes, lipsticks, lip glosses, lip liners, and body décolleté products; UV protection cosmetics such as sunscreen emulsions, sunscreen gels, and sunscreen creams; cleansing agents; and facial cleansers, makeup removers, body soaps, and shaving foams. However, it is not limited to these. "Techniques" include skincare techniques (cleansing), cosmetic procedures such as those to improve dullness and acne scars, and those to improve fine lines and depressions. However, the term "procedure" here refers to non-medical procedures. "Environment" refers to the location and condition of the skin (skin surface), including indoors / outdoors, humidity, temperature, whether or not it is exposed to sunlight or artificial light, and whether or not it is exposed to wind. This includes both everyday environments and non-everyday environments (for example, high-temperature and high-humidity environments such as saunas and yoga studios, low-temperature environments such as refrigerated warehouses, and high-lighting environments such as photography studios). "Skin to which the specified agent, technique, or environment is applied" means skin to which the specified agent described above is applied (applied), skin to which the technique described above is applied, or skin to which the environment described above is applied (existing in the environment). Skin to which the technique is applied and skin to which the environment is applied may be either bare skin or skin to which the specified agent is applied. "The way the skin changes over time" refers to how the tactile sensation of the skin changes over time due to the application of a specific agent, the application of a specific technique, or the influence of the location where the skin is located. Examples of tactile sensations include "stickiness," "refreshing," "moist," "sticky," "hydrated," "dry," "firm," "elasticity," "hardness / softness," "clinginess," "bouncy," "plump," "smooth," "slippery," "slippery," "oily," "rich," "absorbent," "adherent," "rough," "stiff," and "tightness." It should be noted that the tactile sensation referred to here is the sensation felt through receptors in the skin or on the fingers, etc., when a moving object such as a finger or palm (hereinafter referred to as "fingers, etc.") is brought into contact with the skin (skin surface), and changes in thermal sensations such as coldness or warmth are not included in the evaluation. Here, "stickiness" refers to the feeling of the skin sticking to the fingers, etc., when they are brought into contact with the skin surface. "Refreshing" refers to a smooth and clean feeling when fingers or other objects are touched to the skin's surface, without any sticking sensation. "Moist" refers to a slightly damp and smooth feeling when fingers or other objects are touched to the skin's surface. "Sticky" refers to a feeling where fingers or other objects slightly adhere to the skin's surface when fingers or other objects are touched to the skin's surface. "Hydrated" refers to a feeling of appropriate moisture when fingers or other objects are touched to the skin's surface. "Dry" refers to a rough, dry feeling when fingers or other objects are touched to the skin's surface. "Firm" refers to a feeling where the skin's surface is stiff and rigid when fingers or other objects are touched to the skin's surface. "Elastic" refers to a feeling where the skin's surface bounces back without sinking when fingers or other objects are touched to the skin's surface. "Hardness" refers to the degree to which the skin deforms when fingers or other objects are touched to the skin's surface. "Sticky" refers to a feeling where fingers or other objects adhere tightly to the skin's surface when fingers or other objects are touched to the skin's surface. "Mochi-mochi" refers to the feeling of slight adhesion and rebound when fingers or other objects are placed on the skin's surface. "Plump" refers to a refreshing feeling when fingers or other objects are placed on the skin's surface, with a slight elasticity and no sticky feeling. "Smooth" refers to the feeling of fingers or other objects moving freely without resistance when touching the skin's surface, especially when a product is applied, where fingers or other objects move naturally."Slippery" refers to the feeling that fingers slide easily when touching the skin's surface, especially when a product is applied, due to the product's stickiness. "Smooth" refers to the feeling that fingers move freely and smoothly when touching the skin's surface. "Oily" refers to the feeling that something clings to the skin's surface when touching it. "Rich" refers to the feeling that fingers perceive the texture of the product when touching the skin's surface, especially when applying a product, the texture when spreading it, and the feeling of heaviness when spreading it. "Comfortable" refers to the feeling that fingers do not feel uncomfortable when touching the skin's surface, especially when a product is applied, and how well it blends into the skin. "Adhering" refers to the feeling that the product adheres well to the skin when applied. "Rough" refers to the feeling that fingers feel rough when touching the skin's surface.

[0016] "Repeatedly performing an action with the body in contact with the skin" means continuing to perform an action that involves continuous contact with the body against the skin, or repeatedly performing an action that involves intermittent contact with the body against the skin. Specifically, this includes repeatedly moving the fingers outward and approximately perpendicular to the skin (tapping action), or repeatedly sliding the fingers horizontally against the skin. In the case of sliding action, any of the following forms are acceptable: repeatedly moving in one direction, repeatedly moving back and forth, or repeatedly moving in a circular motion.

[0017] "Mechanical physical quantities arising between skin and a moving object" refer to mechanical physical quantities arising between 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 or frictional force the moving object receives from the skin, the amount of electric current or voltage value resulting from skin displacement, the pressure the moving object receives, the strain generated in the moving object, or the amount (amplitude) or frequency of vibration of a vibrating moving object. The tactile sensations evaluated in this method are those resulting from contact between fingers, palms, etc., with the skin surface, such as stickiness, freshness, and moisture. Thermal sensations such as coldness and warmth are not evaluated, so the physical quantities obtained will not include physical quantities that only exhibit thermal characteristics.

[0018] "The tendency of repeating waveform patterns" refers to the overall characteristics of the shape (pattern) of individual waveforms acquired periodically over multiple repetitions of an object's operation. "Singularities where this tendency changes over time" refers to points where the overall characteristics of the acquired waveform pattern change. "Intensity in the waveform pattern" refers to the magnitude of a mechanical physical quantity obtained from individual or multiple waveforms, or the calculated value of such a mechanical physical quantity. Specifically, singularities include points where the tendency of the magnitude of the mechanical physical quantity changes, and points where the perceived quantity changes. More specifically, examples include the point where the first indicator line, which shows the trend for each of the first periods of time series data, intersects with the second indicator line, which shows the trend for each of the second periods that differ from the first period (first singularity); the point where the time series data intersects with the standard deviation line, which shows the variability within a predetermined range above or below the third indicator line, which shows the trend for each of the third periods of time series data (second singularity); and the point where, after extracting the skewness or kurtosis for each of the fourth periods of time series data and differentiating the extracted skewness or kurtosis with respect to time, there is a change greater than a predetermined value (third singularity). Thus, a singularity is a point where the intensity of a waveform pattern changes, and it is a point where the strength, magnitude, or quantity of a mechanical physical quantity changes, or where the strength, magnitude, or quantity of a sensation changes.

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

[0020] "Evaluating skin condition, agent, technique, or environment based on the required features" means that, in the case of skin condition, it refers to the tactile sensation or changes in tactile sensation; in the case of agent evaluation, it refers to the time it takes for the agent to absorb into the skin, the tactile sensation it gives to the skin, or the evaluation of the physical properties that produce changes in tactile sensation; in the case of technique evaluation, it refers to the tactile sensation it gives to the skin as a result of the technique, or the evaluation of the technique that caused changes in tactile sensation; and in the case of environment evaluation, it refers to the evaluation of the environment when skin tactile sensation or changes in skin tactile sensation were evaluated. Furthermore, evaluation includes not only plotting the extracted features on a single or multi-axis and quantitatively evaluating them based on the plotted position, but also comparing the extracted features with predetermined reference values ​​and evaluating their correlation with the sensory quantity that is the target of evaluation using calibration curves, etc.

[0021] <Method for obtaining time-series data of mechanical physical quantities> As shown in Figure 1, in this embodiment, the skin is the skin of a human arm (the surface of the skin on a person's arm), and the moving body is a finger 20 in contact with the human arm. As shown in Figure 1, a sensor 30 is attached to the finger 20. When the finger 20, especially the pad of the finger (hereinafter referred to as the finger even when referring to the pad of the finger), touches the surface of the arm (skin surface), and the touching finger 20 is moved, vibrations and deformations occur in the finger skin. The sensor 30 detects these vibrations and deformations and outputs them as electrical signals to the computing device 10. Since the vibrations and deformations that occur in the finger skin differ depending on the difference in tactile sensation, the electrical signals output also differ depending on the difference in tactile sensation. These output electrical signals correspond to the "mechanical physical quantities" of the present invention, and these electrical signals are acquired over time. The sensor 30 only needs to be able to acquire mechanical physical quantities that occur when the finger 20 touches the surface, and for example, it may be a sensor (multi-axis sensor, force sensor) that can acquire acceleration and force that occur when the finger 20 that has been in contact with the skin is released. 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) representing the physical quantity over a predetermined period of time, but also a mode in which the sensor 30 acquires the physical quantity as digital information multiple times at short intervals such as milliseconds or sub-milliseconds. When the sensor 30 continuously acquires the physical quantity as analog information, the arithmetic unit 10 may sample and discretize the analog information at predetermined short intervals such as milliseconds or sub-milliseconds. In this embodiment, as shown in Figure 1, the finger 20 fitted with the sensor 30 is brought into contact with the skin (skin surface), and the finger 20 is repeatedly moved in a substantially horizontal direction relative to the skin. The repeated movement can be any of the following: repeated movement in one direction, repeated movement back and forth, repeated movement in a circular motion, etc. When measuring using a measuring jig, a sensor 30 can be provided on the measuring jig (not shown) instead of the finger 20 in Figure 1. By bringing the measuring jig into contact with the skin (skin surface) and moving it so that it slides horizontally against the skin (skin surface), the generated physical quantity can be measured in the same way. Furthermore, 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) to ensure uniform movement.

[0022] The conditions for the vibration waveform data used in analysis methods 1 to 3, as shown below, are described below. • Agents used Two types of creams (Cream P and Cream Q) that exhibited different changes in texture upon application were used. "Cream P": A light-textured cream that leaves a lingering, slightly sticky feeling and blends in gradually. The overall impression is one of monotonous variation. "Cream Q": This cream provides a rich, smooth texture upon initial application, followed by a quick absorption into the skin. The overall impression is one of clear and noticeable improvement. Figure 2 shows the vibration waveform and sensory value for each cream. • Method for measuring vibration waveforms A vibration sensor was attached to the evaluator's finger 20, and each cream was dropped onto the inside of the forearm. The time from the start of application to the end of application (when it had absorbed) was measured. The end of application was defined as the point when the evaluator felt that the cream had finished absorbing into the skin. The evaluator was asked to report the tactile sensation sequentially from the start of application, and this was used as the sensory quantity. • Original signal Signal data of the amplitude value (root mean square: RMS) of vibrations in the 10-500Hz band was created and used as the original signal. In this embodiment, frequency analysis was performed and the signal data processed with RMS was used as the original signal, but such processing is not required, and the settings should be determined considering the object to be evaluated and the acquired data.

[0023] <Overview of the evaluation method> Figure 3 shows an overview of this evaluation method. This evaluation method consists of a step of acquiring mechanical physical quantities (step S100), a step of identifying singularities and calculating feature quantities (step S110), and a step of evaluating the skin condition, agent, technique, or environment (step S120). In this embodiment, using the evaluation method shown in Figure 3, the skin condition and agent were evaluated for skin to which cream P was dropped and applied, and for skin to which cream Q, which has a different change in tactile sensation upon application than cream P, was dropped and applied. In this embodiment, time-series data of mechanical physical quantities generated between the skin and finger 20 was acquired by repeatedly moving finger 20 on skin (skin surface) to which the predetermined agent was dropped. However, it is also possible to evaluate the skin condition by repeatedly moving finger 20 on bare skin to acquire time-series data of mechanical physical quantities generated between the skin and finger 20. The conditions of the skin to which finger 20 is in contact should be determined according to the evaluation target (evaluation purpose).

[0024] The process (step S100) is the process of acquiring time-series data of mechanical physical quantities. The acquisition method is as described above. Figure 2(1) shows the vibration waveform signal obtained when cream P is dropped onto the skin, finger 20 is brought into contact with the skin, and the action is repeated. 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 the physical quantity. From the timing of 0 seconds elapsed (corresponding to the start of application in the figure), finger 20 is brought into contact with the skin and the action is repeated until approximately 120 seconds have elapsed (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 finished to blend into the skin. Figure 2(2) shows the vibration waveform signal obtained when cream Q is dropped onto the skin, finger 20 is brought into contact with the skin, and the action is repeated. 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 the physical quantity. The action is repeated from the moment of 0 seconds elapsed (corresponding to the start of application in the figure) to the moment of approximately 70 seconds elapsed (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 finished to be absorbed into the skin. The "sensory quantity" shown in Figure 2 represents the tactile sensation felt by the subject when repeatedly touching the skin with finger 20. In Figure 2(1), the sensory quantity is light and fresh to the touch at the start of applying cream P, then changes to a slippery feel as the action is repeated, then the slippery feeling subsides and the sensation changes to one of blending with the skin, until the entire skin to which cream P has been applied feels blended. Application is stopped when the entire skin to which cream P has been applied feels blended. In Figure 2(2), the sensory quantity is a moderately heavy richness at the start of applying cream Q, then becomes smooth, then changes to a feeling of adhesion and blending, and application is stopped when the entire skin to which cream Q has been applied feels blended. Here, the relationship between vibration intensity and tactile sensation is as follows: • Increased vibration intensity: This is related to a state where the fingers feel heavy when moving them, or a state where vibration is easily generated due to contact between the fingers and skin. • Reduced vibration intensity: This is related to a state where the fingers feel lighter when moving them, or where vibrations are less likely to occur due to contact between the fingers and 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 tactile sensation when applying a cream to the skin as shown in Figure 2, as these changes over time.

[0025] Step S110 is a process for identifying singularities and determining features in the time-dependent changes in the repeating waveform patterns of the acquired time-series data of mechanical physical quantities. By analyzing the time-series data of mechanical physical quantities using a predetermined algorithm, singularities are identified and features are determined. The process (step S120) is a process of evaluating the skin condition, agent, technique, or environment based on the identified singularities and characteristics. In this embodiment, three types of analysis methods are used to determine singularities and feature quantities, and to evaluate the skin condition and the agent. Each analysis method and evaluation method will be described below.

[0026] (i) Regarding analysis method 1 Analysis method 1 is shown in Figure 4. Figure 4(1) shows the RMS value of the acquired time-series waveform signal. The acquired time-series waveform signal shown in Figure 2 is also "time-series data of mechanical physical quantities" according to the present invention, but in this embodiment, the RMS value of the time-series waveform signal is also considered "time-series data of mechanical physical quantities (also called the original signal)". Figure 4 shows the time-series data of the mechanical physical quantities of cream Q. Figure 4(2) shows the calculation of a simple moving average of two different periods for the waveform of the original signal. In this embodiment, the simple moving average of a first period (e.g., 6 [s]) and a second period (e.g., 10 [s]), which is a different period from the first, is calculated. In Figure 4(2), the thick line shows the moving average of the first period (6 [s]), and the thin line shows the moving average of the second period (10 [s]). The first and second periods can be determined by considering the evaluation target, evaluation conditions, etc. The shorter the period of the simple moving average, the more pronounced the fluctuations of the original signal will be, while the longer the period, the more the directionality of the fluctuations of the original signal will be revealed. 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. When the moving average for the first period (6 seconds) deviates above the moving average for the second period (10 seconds), it is an increasing pattern (upward-sloping solid line in Figure 4(2)). When the moving average for the first period (6 seconds) deviates below the moving average for the second period (10 seconds), it is a decreasing pattern (downward-sloping dotted line 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 divergence between the two moving averages, the greater the change in the original signal; the smaller the divergence between the two moving averages, the smaller the change in the original signal. c) Analyze the rate of change of 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 averages, the more abrupt the change in the original signal; and the gentler the slope of the divergence between the two moving averages, the more gradual the change in the original signal. These analyses can be performed by calculating the difference between moving averages, making it possible to identify the change points (also called singularities) and characteristics of the change patterns of the original signal.

[0027] Figure 5 shows the process of determining the characteristics of the change point and change pattern from the original signal for cream P. Figure 5(1) shows the time-series data (original signals) of mechanical physical quantities obtained when finger 20 was in contact with skin to which cream P had been dropped and the action was repeated. Figure 5(2) shows two moving averages for the first period (6[s]) and the second period (10[s]). Figure 5(3) shows the difference data between two moving averages. Figure 5(4) shows the data from Figure 5(3) in black for positive values ​​and gray for negative values ​​to make it easier to see. In Figure 5(4), the positive values, i.e., the black areas, indicate an increasing pattern, and the negative values, i.e., the gray areas, indicate a decreasing pattern. In this way, by taking the difference between two moving averages, it is possible to clearly identify the change points and the characteristics of the change patterns.

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

[0029] Next, we will explain the evaluation results based on the change points and change patterns obtained in Analysis Method 1, using Figures 7 to 9.

[0030] Figure 7(1) shows the difference data of the two moving averages of Cream P shown in Figure 5(4), color-coded for positive and negative values. Patterns in which positive or negative values ​​persist for a predetermined time (4 [s] or more in this embodiment) are marked with a sign. Patterns that persist for a predetermined time can be said to be patterns with clear changes. The predetermined time can be determined by considering the evaluation target, evaluation conditions, etc. Patterns 1, 2, 6, and 9 are decreasing patterns, and patterns 3, 4, 5, 7, and 8 are increasing patterns. Figure 7(2) shows the difference data of the two moving averages of Cream Q shown in Figure 6(4), color-coded for positive and negative values. Patterns in which positive or negative values ​​persist for a predetermined time (4 [s] or more in this embodiment) are marked with a sign. Patterns that persist for a predetermined time can be considered patterns with clear changes. The predetermined time can be determined by considering the evaluation target, evaluation conditions, etc. Patterns 1, 4, and 6 are decreasing patterns, while patterns 2, 3, 5, and 7 are increasing patterns.

[0031] Here, we will explain the indexed values ​​(also called features) using the "increase pattern of 5" and the "decrease pattern of 6" in Figure 7(1). 1) Pattern Whether the difference data is a positive or negative value can determine whether the pattern is increasing or decreasing. 2) Peak Top In the case of an increasing pattern of 5, this is the part with the most positive value within the increasing pattern of 5, and in the case of a decreasing pattern of 6, this is the part with the most negative value within the decreasing pattern of 6, representing the point where the pattern's momentum 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 represents the duration of the pattern and is a feature related to the pattern's intensity. 5) Slope This represents the slope of the pattern, and is a feature related to the rate of increase of the pattern. For example, a pattern with a steep slope is considered a steep increase pattern, and a pattern with a gentle slope is considered a gentle increase pattern. 6) Shape Using the above 1) to 5), the characteristics of each pattern can be determined based on the shape of the pattern. 7) Pattern strength By dividing the above-mentioned 3) deviation amount by 4) duration, the "pattern intensity" can be determined. 8) Patterns of varying tempo The "rate of the pattern" can be determined by how the timing (time) of the peak top (as described above) relates to the duration (as described in 4). For example, the time position of the peak top relative to the duration is located to the left if the pattern is steeper, and to the right if the pattern is gentler. Also, for example, if we consider the increasing pattern of 5 as the shape of a histogram, the time position of the mean relative to the duration is located to the left if the pattern is steeper, and to the right if the pattern is gentler. Similarly, if we consider the increasing pattern of 5 as the shape of a histogram, the steeper the pattern, the more the histogram is skewed to the right, resulting in a positive skewness value, and the more gentle the pattern, the more the histogram is skewed to the left, resulting in a negative skewness value.

[0032] Figure 7(3) is a graph showing the intensity and pattern variation of the pattern as described above. The graph shown in Figure 7(3) shows the pattern's skewness (degree of deviation) on the horizontal axis (first axis) and the pattern's intensity (deviation amount / duration) on the vertical axis (second axis). On the horizontal axis, a positive value indicates a steeper pattern, and a negative value indicates a gentler pattern. On the vertical axis, a positive value indicates an increasing pattern, and a negative value indicates a decreasing pattern. A larger absolute value of intensity indicates a stronger pattern, and a smaller absolute value of intensity indicates a weaker pattern. The Cream P pattern is plotted as a circle, and the Cream Q pattern is plotted as a black triangle. By comparing the patterns in which the sensations of each cream occurred regarding richness (weight when spreading) and blendability, using the sensory values ​​shown in Figure 2 and the graph in Figure 7(3), the following can be evaluated. "Richness (weight when spreading)": For cream P, the decreasing pattern of 1 (circle marked P-1) and for cream Q, the decreasing pattern of 1 (black triangle marked Q-1) indicate the point where richness (weight when spreading) is felt. Since both P-1 and Q-1 are plotted in the fourth quadrant (decreasing pattern), it is shown that richness is a phenomenon that occurs when the fingers change from a state where force is applied when initially spreading the cream (state of high vibration intensity) to a state where the fingers become lighter as the cream begins to break down (state of low vibration intensity). P-1 is plotted to the lower right compared to Q-1, meaning that the decrease in vibration intensity when spreading the cream is large (strong) and the change is abrupt. From this, it is shown that the characteristic of the weight when spreading cream P is that the cream becomes light immediately after it breaks down and richness is not felt. Q-1 is plotted to the upper left compared to P-1, meaning that the decrease in vibration intensity when spreading the cream is small (weak) and the change is gradual. This demonstrates the characteristic weight of Cream Q when spreading it: the cream doesn't become too light, maintaining its weight and giving it a rich texture. "Combination": For cream P, the point at which it begins to blend is indicated by an increasing pattern of 5 (circle marked P-5), and for cream Q, it is indicated by an increasing pattern of 3 (black triangle marked Q-3). Since P-5 is plotted in the second quadrant (increasing pattern) and Q-3 is plotted in the first quadrant (increasing pattern), it shows that when the cream blends into the skin, the fingers become heavier and the vibration intensity increases. Since P-5 is located in the second quadrant, it means that the increase in vibration intensity is a gradual change. This shows that the blending characteristic of cream P is that the fingers become heavier and blends in gradually. Since Q-3 is located in the first quadrant, it means that the increase in vibration intensity is a more rapid change compared to P-5. This shows that the blending characteristic of cream Q is that the fingers suddenly become heavier and the feeling of blending into the skin comes quickly. In this way, by quantifying the characteristics of the P-5 and Q-3 patterns, the differences in blending characteristics can be clearly evaluated.

[0033] As shown in Figure 7, by analyzing and quantifying the intensity, speed, and shape of each pattern, it becomes possible to evaluate the characteristics of each tactile sensation.

[0034] Thus, this evaluation method generates first graph data (corresponding to the graph in Figure 7(3)) plotting the pattern speed and pattern intensity of the first feature on a coordinate system that includes a first axis (horizontal axis) indicating the pattern speed and pattern intensity of the first feature, for patterns (corresponding to patterns 1 to 9 in Figure 7(1) and patterns 1 to 7 in Figure 7(2)) whose duration is longer than a predetermined time (for example, 4 [s] or longer) (corresponding to patterns 1 to 9 in Figure 7(1) and patterns 1 to 7 in Figure 7(2)). This first graph data allows for the evaluation of skin condition and the agent based on this first graph data.

[0035] Figure 8 provides a more visually clear representation of the evaluation results shown in Figure 7. Figure 8(1) visualizes the gradual changes in the graph of Figure 7(3) by dividing the horizontal axis, which represents skewness, into three sections and coloring them white, gray, and black in order from lowest to highest skewness. Additionally, the vertical axis, which represents the strength of the pattern, is divided into six sections and visualizes the intensity of the pattern by using diagonal lines that descend from left to right with wide spacing, diagonal lines that descend from left to right with medium spacing, diagonal lines that descend from left to right with narrow spacing, diagonal lines that ascend from left to right with narrow spacing, diagonal lines that ascend from left to right with medium spacing, and diagonal lines that ascend from left to right with wide spacing, in order from the strongest decreasing pattern to the strongest increasing pattern. Figure 8(2) is similar to Figures 7(1) and 7(2), respectively. Figure 8(3) shows time on the horizontal axis and illustrates the gradual change (skewness) and pattern intensity corresponding to the patterns shown in Figure 8(2). For example, the decrease pattern of cream P at 1 in Figure 8(2) is a steep decrease with high pattern intensity, and is represented by a diagonal line with wide spacing between black lines sloping downwards from left to right. The increase pattern of cream P at 5 is a gradual increase with high pattern intensity, and is represented by a diagonal line with wide spacing between white lines sloping upwards from left to right. The decrease pattern of cream Q at 1 in Figure 8(2) is a moderate decrease with slightly high pattern intensity, and is represented by a diagonal line with medium spacing between gray lines sloping downwards from left to right. The increase pattern of cream Q at 3 is a moderate increase with high pattern intensity, and is represented by a diagonal line with medium spacing between black lines sloping upwards from left to right. Representing the patterns in this way makes it easier to visually grasp the changes and characteristics of the patterns.

[0036] Figures 9(1) and 9(2) are similar to Figures 7(1) and 7(2), respectively. Figure 9(3) is a graph consisting of a horizontal axis showing the bias towards the increasing pattern in duration and a vertical axis showing the bias towards the increasing pattern in duration, based on the deviation amount and duration described above. The bias in the amount of deviation towards the increasing pattern and the bias in the duration towards the increasing pattern are calculated as follows. Find the sum (positive value) of the deviations in the increasing patterns (let's call this Da). Calculate the sum of the durations of the increasing patterns (let's call this Ta). Calculate the sum (negative value) of the deviations in the decreasing pattern (let's call this Db). Calculate the sum of the durations of the decreasing patterns (let this be Tb). The bias towards the increasing pattern = Difference between the deviation amount of the increasing pattern and the deviation amount of the decreasing pattern (Da + Db) ÷ Total deviation amount (Da - Db) The bias in duration towards the increasing pattern = Difference between the duration of the increasing pattern and the duration of the decreasing pattern (Ta-Tb) ÷ Total duration (Ta+Tb) In the graph shown in Figure 9(3), the vertical axis (deviation of deviation amount) / horizontal axis (deviation of duration) is: Cream P: 1.16 < Cream Q: 1.87 That is the case. The following can be observed from Figure 9(3). Compared to Cream P, Cream Q shows less bias in duration towards the increasing pattern, but a greater bias in deviation amount. This indicates that, rather than the higher value of the vertical axis (deviation amount bias) / horizontal axis (duration bias) for Cream Q, Cream Q exhibits a stronger momentum (clearer sense of change) in the amplitude increasing direction throughout the entire application process.

[0037] As shown in Figure 9, by analyzing and quantifying the bias in change patterns, it becomes possible to evaluate the overall impression.

[0038] Thus, this evaluation method includes patterns of difference data 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)), which include increasing patterns where the difference data is positive (for example, the increasing pattern in Figure 7(1)5 and the increasing pattern in Figure 7(2)3) and decreasing patterns where the difference data is negative (for example, the decreasing pattern in Figure 7(1)1 and the decreasing pattern in Figure 7(2)1). For patterns where the duration of the first feature (corresponding to the patterns in Figure 7(1) and Figure 7(2)) is longer than a predetermined time (for example, 4[s]), the total duration of the increasing pattern (corresponding to Ta) is considered. The total deviation of the increasing pattern (corresponding to Da), the total duration of the decreasing pattern (corresponding to Tb), and the total deviation of the decreasing pattern (corresponding to Db) are calculated. From the calculation results, the bias in duration (for example, the difference between the duration of the increasing pattern and the duration of the decreasing pattern (Ta-Tb) ÷ total duration (Ta+Tb)) and the bias in deviation amount (for example, the bias in deviation amount toward the increasing pattern = the difference between the deviation amount of the increasing pattern and the deviation amount of the decreasing pattern (Da+Db) ÷ total deviation amount (Da-Db)) are determined. A second graph data (corresponding to the graph in Figure 9(3)) is generated by plotting the bias in duration and the bias in deviation amount on a coordinate system that includes a first axis (corresponding to the horizontal axis) showing the bias in duration and a second axis (corresponding to the vertical axis) showing the bias in deviation amount. Based on this second graph data, it becomes possible to evaluate the skin condition and the agent.

[0039] In analysis method 1, a singularity (corresponding to a change point) is the first singularity, which is the point where the first indicator line (for example, the thick line in Figure 5(2) and the thick line in Figure 6(2)) that shows the trend for each first period of time series data (for example, a predetermined period of 6 [s]) intersects with the second indicator line (for example, the thin line in Figure 5(2) and the thin line in Figure 6(2)) that shows the trend for each second period different from the first period (for example, a predetermined period of 10 [s]). The features can be evaluated using the first feature, which is at least one of the following: pattern, peak top, deviation amount, duration, slope, shape, pattern intensity, or pattern variability 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 singularity.

[0040] (b) Analysis Method 2 Analysis method 2 is shown in Figure 10. Figure 10(1) shows time-series data of a mechanical physical quantity (original signal) (corresponding to the thin line in Figure 10(1)), a moving average line calculated by taking the simple moving average of the waveform of the original signal over a predetermined period (third period) (corresponding to the thick line in Figure 10(1)), a standard deviation line (upper band) showing upward dispersion around the moving average line (corresponding to the dotted line in Figure 10(1)), and a standard deviation line (lower band) showing downward dispersion around the moving average line (corresponding to the dashed line in Figure 10(1)). In this embodiment, the predetermined period is set to 6 [s], but it can be determined by considering the evaluation target, evaluation conditions, etc. Using Figure 10(2), we will explain the moving average and the standard deviation line. As shown in Figure 10(2), the portion of the standard deviation that exceeds a predetermined range relative to the moving average (anomaly points) is identified. Here, in a normal distribution, approximately 68% of the data falls within the range of mean ± 1σ, approximately 95% falls within the range of mean ± 2σ, and approximately 99% falls within the range of mean ± 3σ. In this embodiment, the predetermined range of the standard deviation is set to ± 2σ, and signals exceeding the ± 2σ range are identified as anomaly signals. The points exceeding 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 limit the range to this, and the appropriate range should be determined by considering the evaluation target, evaluation conditions, etc.

[0041] Figure 11 shows the process of determining the change point (singularity) from the original signal for cream P. Figure 11(1) shows the time-series data (original signal) of mechanical physical quantities obtained when a finger is repeatedly brought into contact with skin coated with cream P, the moving average line for the third period (6 [s]) of the original signal waveform, the standard deviation line (upper band) showing the upward dispersion around the moving average line, and the standard deviation line (lower band) showing the downward dispersion around the moving average line. Figure 11(2) shows the point where the original signal crosses the upper band, and this point where it crosses the upper band is defined as the change point. Figure 11(3) shows the cumulative values ​​of the points where the upper band was exceeded, as shown in Figure 11(2). Representing the points as cumulative values ​​makes it easier to visually grasp the timing and intensity of the change points. Note that while Figure 11(2) calculated the points where the upper band was exceeded, a similar evaluation can be performed by calculating the points where the lower band was exceeded.

[0042] Figure 12 shows the process of finding the change point (singularity) from the original signal for cream Q. Figures 12(1) to 12(3) are the same as Figure 11, so their explanation is omitted. In this way, it becomes possible to clearly identify points of change (also called singularities) where the standard deviation exceeds a predetermined range relative to the moving average line. Furthermore, from Figures 11 and 12, it can be clearly seen that the points of change are different for cream P and cream Q. Moreover, because points of change were extracted near the points of change determined by analysis method 1, it is possible to capture changes in tactile sensation.

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

[0044] Thus, this evaluation method generates a third graph data (corresponding to the graphs in Figure 11(3) and Figure 12(3)) plotting elapsed time and cumulative values ​​on a coordinate system that includes a first axis (corresponding to the horizontal axis) showing elapsed time and a second axis (vertical axis) showing the cumulative value of the second feature (corresponding to the intensity of the difference data between the time series data and the standard deviation line value at the second singularity). Based on this third graph data, it becomes possible to evaluate the skin condition and the agent.

[0045] Next, we will explain the evaluation performed based on the change points obtained using analysis method 2. The change point intensity per unit time is calculated from the change points obtained using analysis method 2 as follows. Intensity of change point per unit time: Sum of the intensity of each change point (original signal - upper band) / coating time Table 1 shows the intensity of the change point per unit time.

[0046] [Table 1]

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

[0048] In analysis method 2, the singularity (corresponding to the change point) is the point where the time series data intersects with the standard deviation line (for example, the upper or lower band in Figures 11(1) and 12(1)) which shows the variability within a predetermined range, either above or below the third indicator line (for example, the moving average line in Figures 11(1) and 12(1)) that shows the trend of the time series data (for example, the original signal) for every third period (for example, a predetermined period of 6 [s]). This is the second singularity (for example, the point where the data exceeds the upper band in Figure 11(1) or the point where it exceeds the upper band in Figure 12(1)). The feature is the second feature (for example, the change point intensity per unit time: the sum of the intensities of each change point (original signal - upper band) / coating time), which is the intensity based on the difference data between the time series data and the standard deviation line values ​​at the second singularity. Evaluation can be performed using the second feature.

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

[0050] Figure 13(2) shows the data obtained by differentiating the moving distortion in Figure 13(1) (corresponding to the thick line in Figure 13(2)). The spike signals in the data obtained by differentiating the moving distortion represent the timing of large changes, so they are identified as change points, and analysis is performed on these change points.

[0051] Figure 14(1) shows the time-series data (original signal) of mechanical physical quantities obtained when a finger is repeatedly brought into contact with skin to which cream P has been dropped, and the data obtained by differentiating the moving distortion, which is calculated from the waveform of the original signal at predetermined intervals. The spike signals in the differential distortion data are defined as change points. Figure 14(2) shows the time-series data (original signal) of mechanical physical quantities obtained when a finger is repeatedly brought into contact with skin to which cream Q has been dropped, and the data obtained by differentiating the moving distortion, which is calculated from the waveform of the original signal at predetermined intervals. The spike signals in the differential distortion data are defined as change points. In this way, change points can be clearly extracted based on spike signals obtained by differentiating the movement distortion. Furthermore, because change points are extracted near the change points determined by analysis method 1, changes in tactile sensation can be captured.

[0052] Figure 15(1) shows the time-series data (original signal) of mechanical quantities obtained when a finger is repeatedly brought into contact with skin to which cream P has been dropped, and the data obtained by differentiating the moving kurtosis, which is calculated from the waveform of the original signal at predetermined intervals. The spike signals in the derivative data of kurtosis are defined as change points. Figure 15(2) shows the time-series data (original signal) of mechanical quantities obtained when a finger is repeatedly brought into contact with skin to which cream Q has been dropped, and the data obtained by differentiating the moving kurtosis, which is calculated from the waveform of the original signal at predetermined intervals. The spike signals in the derivative data of kurtosis are defined as change points. In this way, change points can be clearly extracted based on spike signals obtained by differentiating kurtosis data. Furthermore, because change points are extracted near the change points determined by analysis method 1, changes in tactile sensation can be captured.

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

[0054] [Table 2]

[0055] Table 2 shows that Cream Q has a greater change point intensity per unit time compared to Cream P. This indicates that Cream Q provides a more distinct change in sensation. In this way, it is possible to clearly evaluate the overall difference in tactile characteristics from the start to the end of application. As shown above, Table 2 allows for the calculation of the intensity per unit time at the third singularity based on the time the operating device was in operation (for example, the application time) and the total of the third features that are above a predetermined value (in this embodiment, above the threshold (mean + 1.65σ)) during that time (for example, the sum of the intensities of spike signals above the threshold). Based on the calculation results, it is possible to evaluate the condition of the skin or the agent.

[0056] In analysis method 3, the singularity (corresponding to the change point) is the third singularity (corresponding to the spike signals in Figures 14(1), 14(2), 15(1), and 15(2)), which is the point where the change exceeds a predetermined value when the skewness (e.g., moving skewness) or kurtosis (e.g., moving kurtosis) is extracted for every fourth period (e.g., the original signal) of the time series data (e.g., the original signal), and the time derivative (e.g., Figures 14(1), 14(2), 15(1), and 15(2)) of the extracted skewness or kurtosis has occurred (e.g., the spike signals in Figures 14(1), 14(2), 15(1), and 15(2)) is obtained. The feature quantity is the third feature quantity, which is the amount of change when the skewness or kurtosis is differentiated with respect to time at the third singularity (e.g., change point intensity per unit time: sum of the intensities of spike signals above the threshold / coating time), and evaluation can be performed using the third feature quantity.

[0057] Thus, regardless of which of the three analysis methods (1 to 3) was used, it was possible to identify the change point at approximately the same time interval from the start of application. Although the evaluation results using each of the three analysis methods were described above, evaluations may also be performed using methods 1 and 2, methods 1 and 3, methods 2 and 3, or methods 1 to 3.

[0058] <Evaluation of similarity between formulations> Next, we will explain the method for evaluating the similarity between agents. Evaluating the similarity between agents involves comparing the points of change and change patterns of each agent to determine whether the agents are similar in type, have similar texture, etc. The measurement methods and data used for evaluation are described below. • Method for measuring vibration waveforms Three different creams (reference cream R, comparison cream S, and comparison cream T) were applied one drop at a time to the skin of the same evaluator (same as in Figure 1), and the time from the start of application to the end of application (when it was fully absorbed) was measured for each. • Data used for evaluation A raw signal is created containing the amplitude values ​​(root mean square: RMS) of vibrations in the 10-500Hz band. The change points and change patterns are then determined from the raw signal using analysis method 1. Figure 16 shows the difference data of two moving averages created using analysis method 1 for Figure 16(1) Reference Cream R, Figure 16(2) Comparison Cream S, and Figure 16(3) Comparison Cream T. 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 ÷ Value of the moving average line over 10 [s] × 100

[0059] Next, we will explain the evaluation performed based on the change points and change patterns obtained in Analysis Method 1. To evaluate the similarity between each cream, the similarity is calculated as follows. • Create a vector from the difference data of two moving averages. • Calculate the similarity between the vectors of reference cream R, comparison cream S, and comparison cream T. The similarity between vectors is calculated, for example, using the angle (cosθ) between vectors obtained from the dot product calculation or the Euclidean distance. Here, we will explain two methods for creating vectors. a) A vector whose components are index values Using the method described in the evaluation method using analysis method 1, we determine the bias in the amount of deviation toward the increasing pattern and the bias in the duration toward the increasing pattern. Find the sum (positive value) of the deviations in the increasing patterns (let's call this Da). Calculate the sum of the durations of the increasing patterns (let's call this Ta). Calculate the sum (negative value) of the deviations in the decreasing pattern (let's call this Db). Calculate the sum of the durations of the decreasing patterns (let this be Tb). The bias towards the increasing pattern = Difference between the deviation amount of the increasing pattern and the deviation amount of the decreasing pattern (Da + Db) ÷ Total deviation amount (Da - Db) The bias in duration towards the increasing pattern = Difference between the duration of the increasing pattern and the duration of the decreasing pattern (Ta-Tb) ÷ Total duration (Ta+Tb) b) A vector whose components are the difference values ​​of the moving averages. Furthermore, in both methods a) and b), it is possible to create vectors using multiple frequency bands. Table 3 shows the vector components obtained by method a).

[0060] [Table 3]

[0061] Table 3 shows the results of calculating the similarity from the angle (cosθ) between vectors whose components are the index values ​​shown. The similarity (cosθ) to the reference cream R was 0.97 for comparison cream S and 0.091 for comparison cream T. Therefore, comparison cream S can be evaluated as having a higher similarity to the reference cream R than comparison cream T. By evaluating the similarity between creams in this way, it becomes possible to classify creams by type, which can then be used for user promotion. Furthermore, it is possible to evaluate the similarity of data obtained by applying the same cream to multiple evaluators. By evaluating such similarity, it becomes possible to classify skin types, for example, into those that adapt quickly and those that adapt slowly, and this can be used to evaluate the similarity or difference in how evaluators perceive tactile sensations.

[0062] <About the evaluation system> The evaluation system 200 will be explained using Figure 17. The evaluation system 200 in this embodiment consists of an operating unit 110, an acquisition unit 120, a identification unit 130, a calculation unit 140, and an evaluation unit 150. It also includes an information processing terminal 100 capable of performing various processes, and the identification unit 130, the calculation unit 140, and the evaluation unit 150 are provided within this information processing terminal 100. The information processing terminal 100 includes input devices such as a keyboard and a pointing device, an arithmetic processing unit, a storage unit, etc. Preferably, the information processing terminal 100 is also equipped with a display unit 160 (display device), but it may be provided outside the information processing terminal 100 and connected via a network.

[0063] The moving body 110 is a finger 20, palm, or measuring jig that comes into contact with the surface of the skin. The acquisition unit 120 is a means for acquiring mechanical physical quantities generated by moving the finger 20 over time, using a sensor 30 attached to the finger 20 as shown in Figure 1. The mechanical physical quantities (electrical signals) acquired by the sensor 30 are configured to be acquired by the information processing terminal 100 via a network line, medium, etc. The identification unit 130 identifies singularities in which the trend of repeating waveform patterns changes over time in the time-series data of mechanical physical quantities acquired by the acquisition unit 120. The singularities to be identified are the same as those described above in analysis methods 1 to 3. The calculation unit 140 obtains feature quantities that represent the characteristics of the waveform at the identified singularity, or within a local time frame starting or ending at the singularity. The feature quantities to be obtained are the same as those described above in analysis methods 1 to 3. The evaluation unit 150 uses the feature quantities calculated by the calculation unit 140 to evaluate the skin condition, agent, technique, or environment. The evaluation content is the same as described above. Preferably, the evaluation results from the evaluation unit 150 are displayed on the display unit 160 in a way that is easy for the evaluator to understand. The display unit 160 displays the evaluation results from the evaluation unit 150, for example, the graphs shown in Figures 5 to 9, 11, 12, 14, and 15. Furthermore, the processing unit may control the output of a predetermined sound from the sound output unit (not shown) based on the evaluation results from the evaluation unit 150. Specifically, for the graphs (evaluation content) in Figures 5(4) and 6(4), for example, different sounds may be used for increasing and decreasing patterns, with different volumes to match the strength of the intensity, and different pitches to match the tempo. In this way, the subject can grasp the difference in tempo through sudden changes in pitch, and the difference in intensity through differences in volume. In this way, the calculated feature quantities may be converted to predetermined volumes and / or types of sounds, and the resulting sound may be output, allowing the subject to grasp the changes in the feature quantities. Similarly, for other evaluation results (other graphs), the calculated feature quantities may be converted to predetermined volumes and / or types of sounds, and the resulting sound may be output.

[0064] Similarly, just as the system is configured to allow the acquisition of mechanical physical quantities (electrical signals) obtained by sensor 30 via a network line, medium, etc., by information processing terminal 100, the evaluation results may also be acquired via a network line, medium, etc., by another information processing terminal (not shown) different from information processing terminal 100. In this way, a user (subject) located in a different location from information processing terminal 100 may transmit mechanical physical quantities (electrical signals) acquired using sensor 30 to information processing terminal 100, the information processing terminal may calculate feature quantities, and the evaluated results may be transmitted to another information processing terminal via a network line, medium, etc. This allows the user to easily evaluate the condition of their skin, the agent, the procedure, or the environment.

[0065] <Variation> In this embodiment, frequency analysis was performed and the signal data processed using RMS was used as the original signal, but such processing is not required. Furthermore, in frequency analysis, the signal that has passed through a predetermined filter when acquiring the time-series waveform signal may be used to extract an arbitrary frequency (band), or the signal intensity of an arbitrary frequency (band) may be modulated, or the signal intensity may be modulated without selecting a frequency (band), or predetermined operations such as Fourier transform or wavelet transform may be performed during analysis so that the time-series data for each frequency band is used for analysis and evaluation. Frequency analysis may be performed and, for example, analysis and evaluation may be performed using frequencies in which the sensitivity of vibration sensation (Pacinian corpuscle) is high.

[0066] In this embodiment, the two moving averages in analysis method 1 were simple moving averages (SMA), but other methods such as exponential moving averages (EMA) or weighted moving averages (WMA), which strongly reflect recent fluctuations, may also be used. A preferred calculation method should be used considering the evaluation target, evaluation conditions, etc. Furthermore, while moving averages were used to grasp the trends for each first and second period, other methods such as standard deviation or variance may also be used as long as the trend can be grasped.

[0067] In analysis method 1, the "pattern's intensity" was determined by the timing (time) of the peak top relative to the duration, but this is not the only method. For example, the index could also be determined by the position of the time at which the half-width of the deviation is equal to the duration.

[0068] In analysis method 1, when determining the bias in duration and deviation, the total deviation for increasing patterns was calculated as the sum of the deviations of increasing patterns, the total duration for increasing patterns was calculated as the sum of the durations of increasing patterns, the total deviation for decreasing patterns was calculated as the sum of the deviations of decreasing patterns, and the total duration for decreasing patterns was calculated as the sum of the durations of decreasing patterns. However, this is not the only method. For example, the total duration and total deviation may be calculated after denoising the data for each pattern.

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

[0070] In analysis method 2, each feature was calculated and evaluated using the difference data between the time series data and the standard deviation line values, but this is not the only method. For example, features may be calculated based on the positions of the time series data and the standard deviation line.

[0071] The evaluation results obtained using this evaluation method allow for quantitative assessment of whether the developed product has achieved its development objectives, such as whether it is a cream that absorbs quickly or a cream that feels appropriately weighted.

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

[0073] In this embodiment, we have described the evaluation of skin condition and the evaluation of agents by evaluating tactile sensation, but this evaluation method can also be used to evaluate techniques or the environment. In this embodiment, "techniques" refer to skincare techniques such as cleansing and massage, techniques for improving dullness and acne scars, and techniques for improving fine wrinkles and depressions. By acquiring and analyzing vibration waveform data from the start to the end of these techniques, the techniques can be evaluated. For example, in the case of cleansing (water only), there is a change in the amount of dirt and sebum on the skin (skin surface) between the start and end of washing, so the point of change and the pattern of change can be evaluated. Furthermore, if a specific agent is used when performing the technique, it also corresponds to the evaluation of the agent, and also to the evaluation of the tactile sensation of the skin when performing the technique. In addition, if the cleansing is performed with cold water or lukewarm water, it also corresponds to the evaluation of the water conditions used for cleansing, i.e., the environment. In this embodiment, "environment" refers to the location and condition of the skin (skin surface), including indoor / outdoor, humidity, temperature, whether it is exposed to sunlight or artificial light, and whether it is exposed to wind. For example, by preparing two spaces with different humidity levels, starting the operation of a device with skin in one space, and continuing the operation while moving the skin to the other space, the vibration waveform data acquired continuously can be obtained and analyzed to evaluate the environment and simultaneously evaluate the tactile sensation of the skin. Thus, this evaluation method makes it possible to evaluate the condition of the skin, the agent, the procedure, or the environment.

[0074] In this embodiment, the sensor 30 is attached to the moving body, but it is not limited to this, and the sensor 30 may also be attached to the skin. In this case as well, it is possible to obtain time-series data of mechanical physical quantities that occur between the skin and the moving body, so even in the case of a moving body to which it is difficult to attach the sensor 30 (for example, a thin object like a cotton swab), it is possible to evaluate the condition of the skin, the agent, the technique, or the environment.

[0075] In Figure 8, which shows the evaluation results based on the analysis using analysis method 1, the horizontal axis representing skewness is divided into three sections, but the number of divisions is not limited to this; for example, it could be further divided into finer stages. Also, the intensity information was represented by using white, gray, and black colors in order from low to high skewness, but any color could be used to represent it. Furthermore, although the color was different for each division, for example, the color could be continuously changed according to the skewness value, or the intensity of the color could be continuously changed. Also, although the intensity information was represented by the difference in color, it could be represented by the difference in shape (difference in fill pattern). Similarly, the vertical axis representing the strength of the pattern was divided into six sections, but the number of divisions is not limited to this; for example, it could be further divided into finer or broader stages. Furthermore, the intensity information was represented by using diagonal lines that descend from left to right with wide spacing, diagonal lines that descend from left to right with medium spacing, diagonal lines that descend from left to right with narrow spacing, diagonal lines that ascend from left to right with narrow spacing, diagonal lines that ascend from left to right with medium spacing, and diagonal lines that ascend from left to right with wide spacing, in order from a decreasing pattern with strong pattern intensity to an increasing pattern with strong pattern intensity. However, the spacing and type of diagonal lines can be anything, and the information can also be represented by differences in shapes (differences in fill patterns), colors, or color intensity. When representing the information by differences in color or color intensity, the colors can be made different for each division, or for example, the colors can be continuously changed according to the intensity value, or the color intensity can be continuously changed. The number of divisions, the types of colors, the types of fill patterns, etc., should be set to a visually easy-to-understand representation method, taking into consideration the evaluation target and evaluation conditions. [Explanation of symbols]

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

Claims

1. A method comprising a step of analyzing how skin changes over time after application of a specific agent, technique, or environment, a moving object in contact with the skin is repeatedly moved to obtain time series data of a mechanical physical quantity occurring between the skin and the moving object; Identifying a singular point where a trend of a repeated waveform pattern changes over time in the acquired time series data; determining a feature quantity that represents a feature of the waveform 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 technique, 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 showing a trend for each first period of the time series data and a second indicator line showing 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 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 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 a 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 in which the slope and the deviation of the first feature amount are plotted in a coordinate system including a first axis indicating the pattern speed of the first feature amount and a second axis indicating the pattern strength 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 , further comprising the step of evaluating the skin condition, the agent, the technique, or the environment based on the first graph data.

7. a pattern of difference data between the first index line and the second index line includes an increase pattern in which the difference data is a positive value and a decrease pattern in which the difference data is a negative value, calculating 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 for a pattern in which the duration of the first feature is equal to or longer than a predetermined time, and determining a bias in the duration and a bias in the deviation amount 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 , further comprising the step of evaluating the skin condition, the agent, the technique, or the environment 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 in 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 , further comprising the step of evaluating the skin condition, the agent, the technique, or the environment based on the third graph data.

9. The evaluation method according to claim 5, further comprising the steps of: calculating an intensity per unit time at the third singular point based on a time for 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; and evaluating the skin condition, the agent, the technique, or the environment based on the calculation result.

10. An evaluation system that analyzes and evaluates changes in skin over time to which a specific agent, technique, or environment is applied, comprising: an acquisition unit that acquires time-series data of a mechanical physical quantity occurring between the skin and the moving object by repeatedly moving the moving object brought into contact with the skin; an identification unit that identifies a singular point where a tendency of a repeated waveform pattern changes over time in the acquired time series data; a calculation unit that calculates a feature quantity that represents a feature of a waveform at the specified singular point or within a local time period starting or ending at the specified singular point; and an evaluation unit that evaluates the skin condition, the agent, the technique, or the environment based on the obtained feature amount.

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