Skin state estimation device, product recommendation system, skin state estimation method, product recommendation method, and program

Abstract

This skin state estimation device comprises: a measurement unit for measuring reflected light that has a wavelength range including a specific wavelength and is reflected by skin; and a skin state estimation unit for estimating, as a skin state, at least one among skin elasticity and skin density on the skin on the basis of the intensity at the specific wavelength included in the reflected light measured by the measurement unit.

Description

Skin condition estimation device, product recommendation system, skin condition estimation method, product recommendation method and program

[0001] The present disclosure relates to a skin condition estimation device, a product recommendation system, a skin condition estimation method, a product recommendation method, and a program.

[0002] An example of an index for evaluating skin condition is skin elasticity (skin resilience), which is evaluated using a cutometer, for example (see, for example, Patent Documents 1 and 2).

[0003] JP 2022-103507 A Patent No. 7276913 A

[0004] For example, when skin diagnosis is performed in a store, there is a demand for a device that is easy to use and can easily estimate skin conditions such as skin elasticity.

[0005] The present disclosure provides a skin condition estimating device that is easy to use.

[0006] The present disclosure provides a skin condition estimation device including a measurement unit that measures reflected light in a wavelength range that includes a specific wavelength reflected by the skin, and a skin condition estimation unit that estimates at least one of skin elasticity and skin density of the skin as a skin condition based on the intensity at the specific wavelength included in the reflected light measured by the measurement unit.

[0007] According to the present disclosure, it is possible to provide a skin condition estimating device that is easy to use.

[0008] FIG. 1 is a diagram illustrating an overview of a skin condition estimation device according to a first embodiment. FIG. 2 is a diagram illustrating the hardware configuration of a processing unit in the skin condition estimation device according to the first embodiment. FIG. 3 is a diagram illustrating the functional configuration of the skin condition estimation device according to the first embodiment. FIG. 4 is a diagram illustrating the functional configuration and processing flow of the skin condition estimation device according to the first embodiment. FIG. 5 is a flow diagram illustrating processing in the skin condition estimation device according to the first embodiment. FIG. 6 is a diagram illustrating the relationship between reflection intensity at a specific wavelength and skin elasticity. FIG. 7 is a diagram illustrating the reflection intensity of light when skin density is high. FIG. 8 is a diagram illustrating the reflection intensity of light when skin density is low. FIG. 9 is a diagram illustrating the functional configuration and processing flow of a skin condition estimation device according to a second embodiment. FIG. 10 is a diagram illustrating the functional configuration and processing flow of a skin condition estimation device according to a third embodiment. FIG. 11 is a diagram illustrating the display of a display unit in the skin condition estimation device according to the third embodiment. FIG. 12 is a diagram illustrating the display of a display unit in the skin condition estimation device according to the third embodiment. FIG. 13 is a diagram illustrating the display of a display unit in the skin condition estimation device according to the third embodiment. FIG. 14 is a diagram illustrating the display of a display unit in a skin condition estimation device according to the third embodiment. FIG. 15 is a diagram illustrating the functional configuration and processing flow of a skin condition estimation device according to the fourth embodiment. FIG. 16 is a diagram illustrating the relationship between input makeup type and application amount and correction values ​​in a skin condition estimation device according to the fourth embodiment. FIG. 17 is a diagram illustrating the functional configuration and processing flow of a skin condition estimation device according to the fifth embodiment. FIG. 18 is a diagram illustrating processing in the skin condition estimation device according to the fifth embodiment. FIG. 19 is a diagram illustrating processing in the skin condition estimation device according to the fifth embodiment. FIG. 20 is a diagram illustrating the functional configuration and processing flow of a skin condition estimation device according to the sixth embodiment. FIG. 21 is a diagram illustrating processing in the skin condition estimation device according to the sixth embodiment. FIG. 22 is a diagram illustrating processing in the skin condition estimation device according to the sixth embodiment. FIG. 23 is a diagram illustrating the functional configuration and processing flow of a skin condition estimation device according to the seventh embodiment. FIG. 24 is a diagram illustrating the functional configuration and processing flow of a skin condition estimation device according to the eighth embodiment.FIG. 25 is a diagram illustrating the relationship between body parts and recommended cosmetics in a skin condition estimation device according to the eighth embodiment. FIG. 26 is a diagram illustrating a display on a display unit of a skin condition estimation device according to the eighth embodiment. FIG. 27 is a diagram illustrating the functional configuration and processing of a skin condition estimation device according to the ninth embodiment. FIG. 28 is a diagram illustrating a first example of reflected light measurement in a skin condition estimation device according to the present embodiment. FIG. 29 is a diagram illustrating a second example of reflected light measurement in a skin condition estimation device according to the present embodiment. FIG. 30 is a diagram illustrating a third example of reflected light measurement in a skin condition estimation device according to the present embodiment. FIG. 31 is a diagram illustrating a fourth example of reflected light measurement in a skin condition estimation device according to the present embodiment. FIG. 32 is a diagram illustrating advance measurement in the fourth example of reflected light measurement in a skin condition estimation device according to the present embodiment. FIG. 33 is a diagram illustrating advance measurement in the fourth example of reflected light measurement in a skin condition estimation device according to the present embodiment. FIG. 34 is a diagram illustrating advance measurement in the fourth example of reflected light measurement in a skin condition estimation device according to the present embodiment.

[0009] Hereinafter, each embodiment of the present disclosure will be described with reference to the accompanying drawings. Note that, in the description of the specification and drawings relating to each embodiment, components having substantially the same or corresponding functional configurations may be designated by the same reference numerals, and redundant description may be omitted.

[0010] To facilitate understanding, the scale of each part in the drawings may differ from the actual scale. Directions such as parallel, right-angled, orthogonal, horizontal, vertical, up-down, left-right, and the like are permitted to have deviations that do not impair the effects of the embodiments. The shape of corners is not limited to right angles and may be rounded. Parallel, right-angled, orthogonal, horizontal, and vertical may include approximately parallel, approximately right-angled, approximately orthogonal, approximately horizontal, and approximately vertical.

[0011] First Embodiment A skin condition estimating device according to the first embodiment will be described. The skin condition estimating device according to the first embodiment includes a measurement unit that measures reflected light in a wavelength range that includes a specific wavelength reflected by the skin. The skin condition estimating device according to the first embodiment also includes a skin condition estimating unit that estimates at least one of skin elasticity and skin density as the skin condition based on the intensity at the specific wavelength included in the reflected light measured by the measurement unit.

[0012] A skin condition estimating device according to a first embodiment will be described with reference to the drawings. Fig. 1 is a diagram showing an overview of a skin condition estimating device 1, which is an example of a skin condition estimating device according to the first embodiment.

[0013] The skin condition estimation device 1 estimates, for example, skin elasticity of the skin SKN of the measurement target OBJ. Specifically, the skin condition estimation device 1 measures reflected light RL in a wavelength range Rλ that includes at least a specific wavelength λs reflected by the skin SKN of the measurement target OBJ. The skin condition estimation device 1 then estimates the skin elasticity of the skin SKN based on the intensity Qs at the specific wavelength λs contained in the measured reflected light RL.

[0014] The skin condition estimation device 1 includes a photodetector 10, a computing unit 20, a display unit 30, and an input unit 40. The photodetector 10, the computing unit 20, the display unit 30, and the input unit 40 included in the skin condition estimation device 1 will be described in detail below.

[0015] [Photodetector 10] The photodetector 10 measures reflected light RL in a wavelength range Rλ including a specific wavelength λs, which is generated when illumination light IL is reflected by the skin SKN of the measurement object OBJ. The photodetector 10 then outputs an intensity Qs at the specific wavelength λs included in the reflected light RL to the calculator 20.

[0016] [Calculator 20] The calculator 20 estimates the skin elasticity of the skin SKN of the measurement object OBJ based on the intensity Qs at a specific wavelength λs contained in the reflected light RL measured by the photodetector 10.

[0017] A description will now be given of the hardware configuration of the computing unit 20. Fig. 2 is a diagram illustrating the hardware configuration of the computing unit 20 in the skin condition estimating device 1, which is an example of a skin condition estimating device according to the first embodiment.

[0018] The calculator 20 is, for example, a computer. The calculator 20 includes a CPU (Central Processing Unit) 21, a RAM (Random Access Memory) 22, and a ROM (Read Only Memory) 23. The calculator 20 also includes a storage I / F (Interface) 24i, a communication I / F 25i, an external I / F 26i, a display I / F 27i, and an input I / F 28i. The CPU 21, RAM 22, ROM 23, storage I / F 24i, communication I / F 25i, external I / F 26i, display I / F 27i, and input I / F 28i are each connected to a bus B2. For example, a storage medium 24 is connected to the storage I / F 24i. The external I / F 26i is connected to the photodetector 10. The display I / F 27i is connected to the display device 30. The input I / F 28i is connected to the input device 40.

[0019] The CPU 21 is a computing device that reads a program (application) from a storage device such as the ROM 23 or the storage medium 24 onto the RAM 22 and executes processing.

[0020] The RAM 22 is a volatile semiconductor memory that temporarily stores, for example, programs (applications) and the like.

[0021] The ROM 23 is a non-volatile semiconductor memory that can retain programs (applications) even when the power is turned off, and stores programs such as the BIOS that is executed at startup, and various settings such as OS settings and network settings.

[0022] The storage I / F 24i is an interface with an external storage device such as the storage medium 24. The computing unit 20 reads and writes data from and to the storage medium 24 using the storage I / F 24i.

[0023] The storage medium 24 is, for example, a hard disk drive (HDD) or a solid state drive (SSD).

[0024] The communication I / F 25i is an interface that connects to an external network such as the Internet, etc. The communication I / F 25i connects to the external network using, for example, a wired communication method.

[0025] The external I / F 26i is an interface that connects the arithmetic unit 20 with an external device. The external I / F 26i is, for example, a USB (Universal Serial Bus) or a GP-IB (General Purpose Interface Bus).

[0026] The display I / F 27i is an interface that connects the computing unit 20 to an external display device. The display I / F 27i is, for example, a Video Graphics Array (VGA) or a Digital Visual Interface (DVI). Alternatively, the display I / F 27i may be, for example, a High-Definition Multimedia Interface (HDMI) (registered trademark), DisplayPort, or the like.

[0027] The input I / F 28i is an interface that connects the arithmetic unit 20 to an external input device. The input I / F 28i is, for example, a USB (Universal Serial Bus).

[0028] The computing unit 20 executes various processes (described later) by executing a program (application) in the above-described hardware configuration. The processing of the computing unit 20 will be described in detail later.

[0029] [Display 30] The display 30 displays the results of the calculations performed by the calculator 20. The display 30 is, for example, a liquid crystal display or an organic electroluminescence display.

[0030] [Input Unit 40] The input unit 40 receives input from the user and outputs the received input from the user to the computing unit 20. The input unit 40 is, for example, a keyboard, a mouse, or a touch panel.

[0031] <Functional Configuration of Skin Condition Estimation Device According to First Embodiment> The following describes the functional configuration of the skin condition estimation device according to First Embodiment. Fig. 3 is a diagram illustrating the functional configuration of a skin condition estimation device 1, which is an example of a skin condition estimation device according to First Embodiment.

[0032] The skin condition estimation device 1 includes a reflected light measurement unit 1A, a reflected light intensity calculation unit 1B, a skin elasticity coefficient calculation unit 1C, a skin elasticity evaluation unit 1D, a display unit 1E, and a storage unit 1S. The reflected light measurement unit 1A and the reflected light intensity calculation unit 1B may be collectively referred to as a measurement unit 1M. The skin elasticity coefficient calculation unit 1C and the skin elasticity evaluation unit 1D may be collectively referred to as a skin condition estimation unit 1P.

[0033] [Reflected Light Measuring Unit 1A] The reflected light measuring unit 1A measures the reflected light RL from the skin SKN of the measurement object OBJ. The reflected light measuring unit 1A is composed of a photodetector 10 and a calculator 20.

[0034] The calculator 20 controls the photodetector 10 to measure the reflected light RL reflected by the skin SKN of the measurement object OBJ. The calculator 20 also acquires intensity information about the reflected light RL measured by the photodetector 10.

[0035] The processing in the reflected light measurement unit 1A executed by the calculator 20 is realized by the CPU 21 executing a program.

[0036] [Reflected Light Intensity Calculation Unit 1B] The reflected light intensity calculation unit 1B calculates the intensity Qs at a specific wavelength λs of the reflected light RL reflected by the skin SKN of the measurement object OBJ, based on the intensity information of the reflected light RL acquired from the reflected light measurement unit 1 A. The reflected light intensity calculation unit 1B is configured with a calculator 20.

[0037] The processing in the reflected light intensity calculation unit 1B executed by the calculator 20 is realized by the CPU 21 executing a program.

[0038] [Skin Elasticity Coefficient Calculation Unit 1C] The skin elasticity coefficient calculation unit 1C calculates a skin elasticity coefficient SCR for evaluating the state of the skin SKN of the measurement target OBJ based on the intensity Qs of the reflected light RL at the skin SKN calculated by the reflected light intensity calculation unit 1B. The skin elasticity coefficient calculation unit 1C is composed of an arithmetic unit 20.

[0039] The processing in the skin elasticity coefficient calculation unit 1C executed by the calculator 20 is realized by the CPU 21 executing a program.

[0040] [Skin Elasticity Evaluation Unit 1D] The skin elasticity evaluation unit 1D estimates the skin elasticity of the skin SKN of the measurement subject OBJ based on the skin elasticity coefficient SCR calculated by the skin elasticity coefficient calculation unit 1C. The skin elasticity evaluation unit 1D is configured with a calculator 20.

[0041] The processing in the skin elasticity evaluation unit 1D executed by the computing unit 20 is realized by the CPU 21 executing a program.

[0042] [Display Unit 1E] The display unit 1E displays the results of evaluation by the skin elasticity evaluation unit 1D on the display device 30. The display unit 1E is configured by a calculator 20 and a display device 30.

[0043] The processing in the display unit 1E executed by the computing unit 20 is realized by the CPU 21 executing a program.

[0044] [Storage Unit 1S] The storage unit 1S stores information necessary for processing. The storage unit 1S is configured by at least one of the RAM 22, the ROM 23, and the storage medium 24 in the computing unit 20.

[0045] <Functional Configuration and Processing Flow of Skin Condition Estimation Device According to First Embodiment> The processing flow of the skin condition estimation device according to First Embodiment will be described. Fig. 4 is a diagram illustrating the functional configuration and processing flow of skin condition estimation device 1, which is an example of the skin condition estimation device according to First Embodiment.

[0046] The measurement unit 1M calculates the intensity Qs at a specific wavelength λs contained in the reflected light RL reflected by the skin SKN, and outputs the calculated intensity Qs to the skin condition estimation unit 1P.

[0047] The skin condition estimation unit 1P calculates a skin elasticity coefficient SCR for evaluating the condition of the skin SKN based on the intensity Qs measured by the measurement unit 1M. Then, the skin condition estimation unit 1P outputs the result RES of the evaluation of the skin condition of the skin SKN based on the skin elasticity coefficient SCR to the display unit 1E.

[0048] The display unit 1E displays the result based on the result RES of the evaluation by the skin condition estimation unit 1P.

[0049] <Processing of Skin Condition Estimation Device According to First Embodiment> Processing performed by the skin condition estimation device according to the first embodiment will be described using skin condition estimation device 1, which is an example of a skin condition estimation device according to the first embodiment. By describing the processing performed by the skin condition estimation device according to the first embodiment, steps included in the skin condition estimation method by the skin condition estimation device according to the first embodiment will be described.

[0050] FIG. 5 is a flowchart illustrating processing in the skin condition estimating device 1, which is an example of a skin condition estimating device according to the first embodiment.

[0051] (Step S10) When processing begins, the reflected light measurement unit 1A in the skin condition estimation device 1 measures the reflected light RL from the skin SKN of the measurement object OBJ (reflected light measurement step). The calculator 20 controls the photodetector 10 to measure the reflected light RL from the skin SKN of the measurement object OBJ. Then, the calculator 20 acquires measurement data Dm related to the intensity Qs at a specific wavelength λs measured by the photodetector 10.

[0052] The specific wavelength λs will be described. The specific wavelength λs is a wavelength included in the near-infrared wavelength range, specifically, the wavelength range of 800 nanometers to 2500 nanometers. The specific wavelength λs is a wavelength included in the near-infrared wavelength range, specifically, the wavelength range of 800 nanometers to 2500 nanometers. ２ 0), excluding the wavelength range absorbed by the near-infrared wavelength range.

[0053] The absorption bands of water are wavelength ranges near 970 nanometers, 1190 nanometers, 1450 nanometers, and 1940 nanometers. Therefore, it is preferable that the specific wavelength λs is included in a wavelength range excluding wavelength ranges near the absorption bands of water in the near-infrared wavelength range (800 nanometers to 2500 nanometers).

[0054] Specific examples of the specific wavelength λs will be described. The specific wavelength λs may be, for example, a wavelength included in the wavelength range of 800 nanometers or more and 950 nanometers or less. The specific wavelength λs may also be, for example, a wavelength included in the wavelength range of 1000 nanometers or more and 1150 nanometers or less. The specific wavelength λs may also be a wavelength included in the wavelength range of 1230 nanometers or more and 1415 nanometers or less. The specific wavelength λs may also be a wavelength included in the wavelength range of 1485 nanometers or more and 1900 nanometers or less. The specific wavelength λs may also be a wavelength included in the wavelength range of 1980 nanometers or more and 2500 nanometers or less.

[0055] The specific wavelength λs may exclude the range affected by lipids and hemoglobin, which are major components of skin, in addition to the absorption band of water described above. For example, lipids have an absorption band around 1750 nanometers. Hemoglobin has an absorption band from 800 nanometers to 1000 nanometers. Furthermore, the absorption bands of primary amides and secondary amides include the wavelength ranges of 1950 to 1970 nanometers and 1990 to 2010 nanometers. Furthermore, the absorption bands of primary amides and secondary amides include the wavelength ranges of 2040 to 2060 nanometers and 2100 to 2130 nanometers. Furthermore, the absorption bands of primary amides and secondary amides include the wavelength ranges of 2140 to 2170 nanometers. Therefore, it is preferable that the specific wavelength λs is included in the near-infrared wavelength range, excluding the wavelength ranges near the absorption bands of water, lipids, hemoglobin, and primary and secondary amides.

[0056] Specific examples of the specific wavelength λs taking into account the absorption bands of water, lipids, hemoglobin, and primary and secondary amides will be described. The specific wavelength λs may be, for example, a wavelength included in the wavelength range of 1,230 nanometers to 1,415 nanometers. The specific wavelength λs may also be, for example, a wavelength included in the wavelength range of 1,485 nanometers to 1,710 nanometers. The specific wavelength λs may also be a wavelength included in the wavelength range of 1,785 nanometers to 1,900 nanometers. The specific wavelength λs may also be a wavelength included in the wavelength range of 1,970 nanometers to 1,990 nanometers. The specific wavelength λs may also be a wavelength included in the wavelength range of 2,010 nanometers to 2,040 nanometers. The specific wavelength λs may also be a wavelength included in the wavelength range of 2,060 nanometers to 2,100 nanometers. The specific wavelength λs may also be a wavelength included in the wavelength range of 2,130 nanometers to 2,140 nanometers. The specific wavelength λs may be a wavelength included in the wavelength range of 2180 nanometers to 2500 nanometers.

[0057] For example, the skin condition estimation device 1 may have a mode (first measurement mode) in which an approximate measurement of the skin condition is performed in a wavelength range excluding the wavelength range near the absorption band of water. The skin condition estimation device 1 may also have a mode (second measurement mode) in which the skin condition is measured with improved accuracy in a wavelength range excluding the range affected by lipids and hemoglobin, which are major components of skin, in addition to the absorption band of water. Furthermore, the skin condition estimation device 1 may perform measurements by switching the measurement wavelength restrictions between the first measurement mode and the second measurement mode.

[0058] In the above example, the measurement is performed in the near-infrared wavelength range, but the specific wavelength λs may be set in the visible light range, which has a shorter wavelength than near-infrared light, or in the visible light range, which has a longer wavelength than near-infrared light. In other words, the wavelength range of the specific wavelength λs is not limited as long as the reflection intensity changes depending on the elasticity of the skin.

[0059] (Step S20) Next, the reflected light intensity calculation unit 1B in the skin condition estimation device 1 calculates the intensity Qs at the specific wavelength λs from the measurement data Dm acquired by the reflected light measurement unit 1A (reflected light intensity calculation step).

[0060] For example, the reflected light intensity calculation unit 1B converts the measurement data Dm to calculate the intensity Qs at a specific wavelength λs.

[0061] (Step S30) Next, the skin elasticity coefficient calculation unit 1C in the skin condition estimating device 1 calculates the skin elasticity coefficient SCR based on the strength Qs.

[0062] For example, the skin elasticity coefficient calculation unit 1C calculates the skin elasticity coefficient SCR based on the relationship between the intensity Qs at a specific wavelength λs measured in advance and the skin elasticity coefficient SCR.

[0063] 6 is a diagram illustrating the processing executed by the skin condition estimating device 1, which is an example of a skin condition estimating device according to the first embodiment. Fig. 6 shows a summary of the results of measurements taken by the measuring unit 1M in the skin condition estimating device 1 and the results of evaluation using a cutometer on the inner arms and cheeks of four subjects, including males and females.

[0064] The horizontal axis of Fig. 6 represents the measurement result (unit: dimensionless) of the intensity Qs at a specific wavelength λs of the reflected light RL measured by the measurement unit 1M. The horizontal axis of Fig. 6 represents a value obtained by calculating the logarithm of the intensity Qs and then multiplying it by a negative value. In other words, the horizontal axis of Fig. 6 represents the light absorption coefficient. Therefore, the smaller the value on the horizontal axis of Fig. 6, the greater the amount of reflection.

[0065] The vertical axis of Fig. 6 shows the results of measuring skin elasticity using a Cutometer manufactured by Courage+Khazaka Co., Ltd. Specifically, the vertical axis of Fig. 6 shows the measurement parameter R7 (the ratio of the instantaneous return after the release of negative pressure to the maximum suction height) measured using the Cutometer.

[0066] 6, the correlation coefficient of skin elasticity with the intensity of reflected light was +0.6510. Therefore, there is a positive correlation between the skin elasticity measured using the cutometer and the intensity of reflected light.

[0067] Here, the relationship between skin elasticity and reflected light will be explained in principle. Fig. 7 is a diagram that schematically explains the reflected light when the skin density is high. Fig. 8 is a diagram that schematically explains the reflected light when the skin density is low.

[0068] In each of Figures 7 and 8, cells CEL are represented by circles. In Figure 7, arrow L11 indicates light incident on the skin. Arrows L12 and L13 indicate light propagating inside the skin. In Figure 8, arrow L21 indicates light incident on the skin. Arrows L22 and L23 indicate light propagating inside the skin. Arrows L22d and L23d indicate light diffused at the boundary surfaces of cells.

[0069] For example, as shown in Figure 7, when skin density is high, the distance between cells CEL is short, and the difference in refractive index at the boundary between cells is reduced, resulting in less diffused light. Therefore, the denser the skin, the less diffused light there is, and the more light is returned as reflected light.

[0070] On the other hand, as shown in Figure 8, when the skin density is low, the distance between cells CEL is long, and light is diffused due to the difference in refractive index at the boundary surface between cells. Therefore, the lower the skin density, the more light is diffused, and the less light is reflected back.

[0071] Skin with a high skin density is more elastic than skin with a low skin density. Therefore, the reflection intensity at the specific wavelength λs varies depending on the skin density. Since skin elasticity differs depending on the skin density, measuring the reflection intensity at the specific wavelength λs allows estimation of skin elasticity.

[0072] The skin condition estimating device 1 calculates the skin elasticity coefficient SCR using the intensity Qs at a specific wavelength λs as the intensity of reflected light.

[0073] A specific method for calculating the skin elasticity coefficient SCR will be described. For example, before operating the skin condition estimating device 1, data on, for example, 100 subjects is collected in advance. The collected data is the intensity Qs at a specific wavelength λs measured using the skin condition estimating device 1. Then, the skin elasticity coefficient calculation unit 1C calculates the skin elasticity coefficient SCR using the collected data.

[0074] For example, for a set of intensities Qs at a specific wavelength λs collected in advance, the maximum value of the intensity Qs is defined as Qmax, and the minimum value of the intensity Qs is defined as Qmin. When the intensity at the specific wavelength λs is Qm, the skin elasticity coefficient calculation unit 1C calculates the skin elasticity coefficient SCR based on Equation 1.

[0075]

[0076] The number of subjects is not limited to the above number. The more subjects there are, the more desirable it is. Also, it is desirable to have subjects with different characteristics such as gender, age, and place of residence. Note that the characteristics such as gender, age, and place of residence may be limited, and the distribution of skin elasticity relative to the intensity of reflected light may be calculated within a limited range of subjects.

[0077] Furthermore, the method of calculating the skin elasticity coefficient SCR is not limited to the above, and for example, the relationship between the intensity Qs at a specific wavelength λs and the skin elasticity measured using a cutometer may be subjected to regression analysis, and the skin elasticity coefficient SCR may be calculated from the measured intensity Qm using the regression curve obtained by regression analysis.

[0078] Furthermore, in the above example, the skin elasticity coefficient SCR is calculated using the intensity Qm, which is the intensity of the reflected light, but it may also be calculated using the absorption spectrum. A method for calculating the skin elasticity coefficient using the absorption spectrum will be described.

[0079] For example, for a set of absorption spectrum intensities SP at a specific wavelength λs collected in advance, the maximum value of the absorption spectrum intensity SP at the specific wavelength λs is defined as SPmax, and the minimum value is defined as SPmin. When the absorption spectrum intensity at the specific wavelength λs is SPm, the skin elasticity coefficient calculation unit 1C calculates the skin elasticity coefficient SCR1 based on Equation 2.

[0080]

[0081] (Step S40) Next, the skin elasticity evaluation unit 1D in the skin condition estimating device 1 evaluates skin elasticity based on the skin elasticity coefficient SCR calculated in step S30 (skin elasticity evaluation step). For example, if the skin elasticity coefficient SCR is equal to or greater than a predetermined value, the skin elasticity evaluation unit 1D evaluates the skin as having "good elasticity." Also, for example, if the skin elasticity coefficient SCR is within a predetermined range, the skin elasticity evaluation unit 1D evaluates the skin as having "normal elasticity." Furthermore, for example, if the skin elasticity coefficient SCR is equal to or less than a predetermined value, the skin elasticity evaluation unit 1D evaluates the skin as having "insufficient elasticity."

[0082] (Step S50) Next, the display unit 1E in the skin condition estimating device 1 displays on the display 30 the results of the evaluation by the skin elasticity evaluation unit 1D.

[0083] In the skin condition estimating device 1, the evaluation results may be displayed as text, such as "good elasticity," "normal elasticity," or "lack of elasticity," or as a numerical value, such as the skin elasticity coefficient SCR or skin elasticity coefficient SCR1.

[0084] In the skin condition estimation device 1, when the skin condition is displayed numerically using the skin elasticity coefficient SCR or the skin elasticity coefficient SCR1, for example, the elasticity condition may be presented to the user on the display 30 in a range from 0 to 100 points.

[0085] In the above description, skin elasticity is estimated as a skin condition, but skin density may also be estimated. As described above, there is a correlation between skin elasticity and skin density, so skin density can be measured by the skin condition estimation device.

[0086] The skin condition estimating device according to the first embodiment can estimate skin conditions such as skin elasticity more easily than, for example, a cutometer. Furthermore, the skin condition estimating device according to the first embodiment does not require suction, as is the case with, for example, a cutometer, and is therefore easier to maintain. Furthermore, the skin condition estimating device according to the first embodiment can measure skin even when made up, as it does not require suction, as is the case with, for example, a cutometer. In other words, the first embodiment can provide a skin condition estimating device that is easy to use.

[0087] Second Embodiment A skin condition estimating device according to the second embodiment will be described. The skin condition estimating device according to the second embodiment further comprises an attribute information input unit in addition to the components of the skin condition estimating device according to the first embodiment. The skin condition estimating device according to the second embodiment estimates at least one of skin elasticity and skin density as the skin condition based on the intensity measured by the measuring unit and the attribute information input from the attribute information input unit.

[0088] FIG. 9 is a diagram illustrating the functional configuration and processing flow of a skin condition estimating device 2, which is an example of a skin condition estimating device according to the second embodiment.

[0089] The skin condition estimation device 2 includes an attribute information input unit 2K in addition to the components of the skin condition estimation device 1. The attribute information input unit 2K is composed of a calculator 20 and an input unit 40. The skin condition estimation device 2 also includes a skin condition estimation unit 2P instead of the skin condition estimation unit 1P in the skin condition estimation device 1.

[0090] The measurement unit 1M calculates the intensity Qs at a specific wavelength λs contained in the reflected light RL reflected by the skin SKN, and outputs the calculated intensity Qs to the skin condition estimation unit 2P.

[0091] The attribute information input unit 2K inputs attribute information ATI of the subject to be measured. The attribute information ATI is input from the attribute information input unit 2K to the skin condition estimation device 2. For example, the attribute information input unit 2K accepts, as the attribute information ATI, the measurement subject's identification information, age, place of residence, store information used, etc. The attribute information input unit 2K outputs the accepted attribute information ATI to the skin condition estimation unit 2P.

[0092] The skin condition estimation unit 2P calculates a skin elasticity coefficient SCR2 for evaluating the condition of the skin SKN based on the intensity Qs measured by the measurement unit 1M and the attribute information ATI input from the attribute information input unit 2K. Then, the skin condition estimation unit 2P outputs a result RES2 of evaluating the skin condition of the skin SKN based on the skin elasticity coefficient SCR2 to the display unit 1E.

[0093] The display unit 1E displays the result based on the result RES2 of the evaluation by the skin condition estimation unit 2P.

[0094] A specific example of the processing performed by the skin condition estimating device 2 will now be described.

[0095] First, an example will be described in which age is input as attribute information ATI from the attribute information input unit 2K.

[0096] For example, assume that measurements are taken in advance for each age group to obtain data for each age group before using the skin condition estimating device 2. For example, assume that data is obtained for each of the age groups: teens, twenties, thirties, forties, and fifties. The skin condition estimating unit 2P then calculates the maximum value Qmax and minimum value Qmin in Equation 1 using a population of the same age group as the age input from the attribute information input unit 2K. The skin condition estimating unit 2P then calculates the skin elasticity coefficient SCR2 based on the calculated maximum value Qmax and minimum value Qmin.

[0097] Note that the information input as the attribute information ATI is not limited to age. For example, the information input as the attribute information ATI may be a place of residence, store information, etc. Then, for example, the skin elasticity coefficient SCR2 may be calculated using a population having attribute information similar to the attribute information ATI input from the attribute information input unit 2K as the population.

[0098] By calculating the skin elasticity coefficient SCR2 as described above, it is possible to perform a relative evaluation in a group having attribute information similar to the attribute information ATI input from the attribute information input unit 2K.

[0099] Third Embodiment A skin condition estimating device according to the third embodiment will be described. The skin condition estimating device according to the third embodiment further accumulates measured intensities in addition to the components of the skin condition estimating device according to the second embodiment.

[0100] 10 is a diagram illustrating the functional configuration and processing flow of a skin condition estimating device 3, which is an example of a skin condition estimating device according to the third embodiment. The skin condition estimating device 3 further comprises a storage unit 3S in addition to the components of the skin condition estimating device 2. The skin condition estimating device 3 also comprises a skin condition estimating unit 3P instead of the skin condition estimating unit 2P in the skin condition estimating device 2.

[0101] The skin condition estimation device 3 stores the intensity Qs measured by the measurement unit 1M and the attribute information ATI input from the attribute information input unit 2K in the memory unit 3S, while associating them with each other. The stored data DAT is then used for processing by the skin condition estimation unit 3P. The skin condition estimation unit 3P calculates a skin elasticity coefficient SCR3 using the intensity Qs measured by the measurement unit 1M and the attribute information ATI input from the attribute information input unit 2K. The skin condition estimation unit 3P then compares the attribute information input from the attribute information input unit 2K with a representative value, for example, an average, in a set similar to the attribute information input from the attribute information input unit 2K and outputs a result RES3. The display unit 1E displays the result RES3 to display the representative value in a set similar to the attribute information input from the attribute information input unit 2K. By displaying the representative value for comparison, comparison with a specific group is possible.

[0102] For example, age, place of residence, store used, etc. are used as attribute information. Calculation using the accumulated data stored in the storage unit 3S may be performed, for example, by age group, store, region, season, or individual. Furthermore, calculation using the accumulated data stored in the storage unit 3S may be performed based on data for all stores. Furthermore, calculation using the accumulated data stored in the storage unit 3S may be performed by classifying the activity record by wake-up time, sleep time, and activity time using a mobile terminal such as a smartphone.

[0103] Examples of comparative displays will be described. FIGS. 11 to 14 are diagrams illustrating examples of displays on the display unit 1E of a skin condition estimation device 3, which is an example of a skin condition estimation device according to the third embodiment. FIG. 11 is a diagram illustrating a display DP1, which is an example of a display in which evaluation coefficients (scores) are calculated for people of the same age group and compared with the average value (mean score). FIG. 12 is a diagram illustrating a display DP2, which is an example of a display in which evaluation coefficients (scores) are calculated for people in the same region and compared with the average value (mean score). FIG. 13 is a diagram illustrating a display DP3, which is an example of a display in which evaluation coefficients (scores) are calculated using the user's own past data and compared with the average value (mean score). FIG. 14 is a diagram illustrating a display DP4, which is an example of a display in which evaluation coefficients (scores) are calculated for people with the same lifestyle in an activity record and compared with the average value (mean score).

[0104] Fourth Embodiment A skin condition estimating device according to the fourth embodiment will be described. The skin condition estimating device according to the fourth embodiment further comprises a cosmetic information input unit in addition to the components of the skin condition estimating device according to the first embodiment. The skin condition estimating device according to the fourth embodiment estimates at least one of skin elasticity and skin density as the skin condition based on the intensity measured by the measuring unit and the cosmetic information input from the cosmetic information input unit.

[0105] If the subject is wearing makeup, the cosmetics may prevent accurate measurement. In order to suppress the influence of makeup, the skin condition estimating device according to the fourth embodiment corrects the estimation results based on the makeup information.

[0106] FIG. 15 is a diagram illustrating the functional configuration and processing flow of a skin condition estimating device 4, which is an example of a skin condition estimating device according to the fourth embodiment.

[0107] The skin condition estimating device 4 includes a makeup information input unit 4K and a correction value calculation unit 4H in addition to the components of the skin condition estimating device 1. The skin condition estimating device 4 also includes a skin condition estimating unit 4P instead of the skin condition estimating unit 1P in the skin condition estimating device 1. The makeup information input unit 4K is composed of a calculator 20 and an input unit 40. The correction value calculation unit 4H is composed of the calculator 20.

[0108] The measurement unit 1M calculates the intensity Qs at a specific wavelength λs contained in the reflected light RL reflected by the skin SKN, and outputs the calculated intensity Qs to the skin condition estimation unit 4P.

[0109] The makeup information input unit 4K inputs makeup information CSI of the target to be measured. The makeup information CSI is input from the makeup information input unit 4K to the skin condition estimating device 4. For example, the makeup information input unit 4K receives, as the makeup information CSI, the type of makeup and the amount of makeup applied. The makeup information input unit 4K outputs the received makeup information CSI to the correction value calculation unit 4H.

[0110] The correction value calculation unit 4H calculates the correction value CRV based on the makeup information CSI input from the makeup information input unit 4K. The correction value calculation unit 4H calculates the correction value CRV based on, for example, the makeup type and application amount in the makeup information CSI. A specific example of the correction value CRV calculated by the correction value calculation unit 4H will be described with reference to FIG. 16 . FIG. 16 is a diagram illustrating the processing performed by the correction value calculation unit 4H included in the skin condition estimation device 4, which is an example of a skin condition estimation device according to the fourth embodiment. For example, when the makeup type in the makeup information CSI is "powder foundation" and the application amount is "heavy," the correction value calculation unit 4H calculates the correction value CRV to "20." The correction value calculation unit 4H outputs the calculated correction value CRV to the skin condition estimation unit 4P.

[0111] The skin condition estimation unit 4P calculates a skin elasticity coefficient SCR4 for evaluating the condition of the skin SKN based on the intensity Qs measured by the measurement unit 1M and the cosmetic information CSI input from the cosmetic information input unit 4K. Specifically, the skin condition estimation unit 4P calculates a skin elasticity coefficient SCR4 for evaluating the condition of the skin SKN based on the intensity Qs measured by the measurement unit 1M and the correction value CRV calculated by the correction value calculation unit 4H based on the cosmetic information CSI input from the cosmetic information input unit 4K. The skin condition estimation unit 4P then outputs a result RES4 of the skin condition evaluation of the skin SKN based on the skin elasticity coefficient SCR4 to the display unit 1E.

[0112] The display unit 1E displays the result based on the result RES4 of the evaluation by the skin condition estimation unit 4P.

[0113] Fifth Embodiment A skin condition estimating device according to the fifth embodiment will be described. The skin condition estimating device according to the fifth embodiment estimates the skin condition of multiple parts of a measurement target OBJ. The skin condition estimating device according to the fifth embodiment includes a measurement unit that receives and measures light reflected from multiple areas of the skin, and a skin condition estimating unit that estimates the skin condition for each of the multiple areas.

[0114] FIG. 17 is a diagram illustrating the functional configuration and processing flow of a skin condition estimating device 5, which is an example of a skin condition estimating device according to the fifth embodiment.

[0115] Skin condition estimation device 5 includes measurement unit 5M, skin condition estimation units 5P(1) to 5P(n), and display unit 1E, where n is an integer greater than or equal to 4. In other words, skin condition estimation device 5 includes n skin condition estimation units. Note that, while n is an integer greater than or equal to 4 in the above example, the skin condition estimation device according to the fifth embodiment may include two or more, i.e., multiple, skin condition estimation units.

[0116] The measurement unit 5M receives and measures reflected light RL in multiple zones on the skin SKN of the measurement object OBJ. The measurement unit 5M includes, for example, a near-infrared camera. The measurement unit 5M then outputs the intensity Qs of the corresponding area to each of the multiple skin condition estimation units. Specifically, the measurement unit 5M outputs the intensity Qs(1) that is the measurement result for the first zone to the skin condition estimation unit 5P(1). Similarly, the measurement unit 5M outputs the intensity Qs(i) that is the measurement result for the i-th zone to the skin condition estimation unit 5P(i), where i is an integer between 1 and n. The same applies below.

[0117] The skin condition estimation unit 5P(i) estimates the skin condition based on the intensity Qs(i) measured by the measurement unit 5M, and outputs the estimation result RES5(i) to the display unit 1E.

[0118] The display unit 1E displays the result based on the result RES5(i) of the evaluation by the skin condition estimation unit 5P(i).

[0119] Measurement using the skin condition estimation device 5 will now be described. Measurement of the entire face using the skin condition estimation device 5 will now be described. Fig. 18 is a diagram illustrating processing in the skin condition estimation device 5, which is an example of a skin condition estimation device according to the fifth embodiment.

[0120] An example will be described in which the skin condition estimation device 5 measures the entire face FCE. The measurement unit 5M performs measurements so that the face FCE is roughly contained within the measurement range MR. The measurement unit 5M then measures the parts of the face FCE contained within each of multiple areas AR. The measurement unit 5M outputs the results of measurements for the multiple areas to each of the skin condition estimation units 5P(1) to 5P(n).

[0121] Each of skin condition estimation units 5P(1) to 5P(n) outputs the skin condition estimation result to display unit 1E. Display unit 1E displays the skin condition estimation result of each of skin condition estimation units 5P(1) to 5P(n).

[0122] The results displayed by the display unit 1E in the skin condition estimation device 5 will be described. FIG. 19 is a diagram illustrating processing in the skin condition estimation device 5, which is an example of a skin condition estimation device according to the fifth embodiment. In FIG. 19 , for example, the display unit 1E in the skin condition estimation device 5 highlights and displays, as display R1, an area AR that is above average compared to the results for a group based on age or the like. Furthermore, the display unit 1E in the skin condition estimation device 5 highlights and displays, as display R2, an area AR that is below average compared to the results for a group based on age or the like. When highlighting a specific area AR, the display unit 1E may highlight it using, for example, color, brightness, hatching, or the like. Furthermore, when highlighting a specific area AR, the display unit 1E may thicken the line width of the frame of the area AR or change the line color, for example.

[0123] Sixth Embodiment A skin condition estimation device according to the sixth embodiment will be described. The skin condition estimation device according to the sixth embodiment estimates the skin condition for multiple regions of a measurement target OBJ. Like the skin condition estimation device according to the fifth embodiment, the skin condition estimation device according to the sixth embodiment includes a skin condition estimation unit that estimates the skin condition for each of multiple regions. The skin condition estimation device according to the sixth embodiment further includes a measurement unit that measures reflected light in a wavelength range that includes a specific wavelength reflected by the skin at a specific region, a region input unit that specifies the region to be measured, and a region determination unit that determines the region selected by the region input unit.

[0124] FIG. 20 is a diagram illustrating the functional configuration and processing flow of a skin condition estimating device 6, which is an example of a skin condition estimating device according to the sixth embodiment.

[0125] Skin condition estimation device 6 includes measurement unit 1M, area input unit 6L that specifies the area to be measured, area determination unit 6Q that determines the area selected by area input unit 6L, and skin condition estimation units 5P(1) to 5P(n) that estimate the skin condition in each of a plurality of areas. Note that skin condition estimation units 5P(1) to 5P(n) are the same as the skin condition estimation units in skin condition estimation device 5.

[0126] The user uses the measurement unit 1M to measure the area of ​​the skin they wish to measure. The area input unit 6L inputs area information ARI, which is area information that includes the area to be measured by the measurement unit 1M. The area information ARI is input from the area input unit 6L to the skin condition estimating device 6. The area input unit 6L accepts, for example, the area in which the area to be measured is located as the area information ARI. The area input unit 6L outputs the accepted area information ARI to the area determination unit 6Q.

[0127] The region determination unit 6Q receives the intensity Qs from the measurement unit 1M. Then, the region determination unit 6Q associates the intensity Qs with the region information ARI based on the region information ARI input from the region input unit 6L. In FIG. 20 , it is assumed that the i-th region in the region information ARI is selected as the region measured by the measurement unit 1M, where i is an integer between 1 and n. The region determination unit 6Q outputs the intensity Qs to the skin condition estimation unit 5P(i) as the intensity Qs(i) of the i-th region.

[0128] The skin condition estimation unit 5P(i), which has received the intensity Qs(i) from the part determination unit 6Q, outputs the skin condition estimation result RES6(i) to the display unit 1E. The display unit 1E displays the estimation result RES6(i) by the skin condition estimation unit 5P(i).

[0129] An example of processing in the skin condition estimation device 6 will be described. Figures 21 and 22 are diagrams illustrating processing in the skin condition estimation device 6, which is an example of a skin condition estimation device according to the sixth embodiment. As shown in Figure 21, it is assumed that measurement is performed by the measurement unit 1M in area R11 and area R11 is selected in the area input unit 6L. The skin condition estimation device 6 estimates the skin condition for the area of ​​the face FCE corresponding to area R11. Then, in Figure 22, it is assumed that measurement is performed by the measurement unit 1M in area R12 and area R12 is selected in the area input unit 6L. The skin condition estimation device 6 estimates the skin condition for the area of ​​the face FCE corresponding to area R12.

[0130] The skin condition estimation device 6 is configured to be able to measure only one location at a time, but by specifying the measurement location using the area input unit 6L, the skin condition estimation device 5 can measure skin conditions in multiple areas despite having a simple configuration (low-cost configuration).

[0131] Seventh Embodiment A skin condition estimation device according to the seventh embodiment will be described. The skin condition estimation device according to the seventh embodiment estimates a skin condition by changing the measurement depth on the skin. The skin condition estimation device according to the seventh embodiment includes a measurement unit that is capable of changing the measurement depth and measures reflected light reflected by the skin. The skin condition estimation device according to the seventh embodiment also includes a skin condition estimation unit that estimates at least one of skin elasticity and skin density as a skin condition based on the intensity at a specific wavelength contained in the reflected light measured by the measurement unit. The skin condition estimation device according to the seventh embodiment also includes a depth information input unit that inputs the measurement depth.

[0132] FIG. 23 is a diagram illustrating the functional configuration and processing flow of a skin condition estimating device 7, which is an example of a skin condition estimating device according to the seventh embodiment.

[0133] The skin condition estimating device 7 includes a measuring unit 7M, a skin condition estimating unit 7P, a measurement depth input unit 7G, and a display unit 1E.

[0134] The measurement unit 7M measures the light reflected by the skin at a changeable measurement depth, which can be changed depending on, for example, the wavelength and the light intensity (e.g., luminous flux (unit: lumens)).

[0135] For example, it is known that changing the wavelength in the near-infrared wavelength range changes the measurement depth. For example, the measurement depth is deeper at wavelengths around 1700 nanometers than at wavelengths around 1600 nanometers. Furthermore, it becomes even deeper at wavelengths around 1000 nanometers. Therefore, when measuring the intensity of reflected light, the measurement unit 7M can change the measurement depth by changing the specific wavelength λs.

[0136] Furthermore, the measurement depth can be changed, for example, by changing the intensity of the illumination light IL for generating the reflected light RL. For example, increasing the intensity of the illumination light IL allows measurement to be performed to a deeper depth. In other words, increasing the intensity of the illumination light IL increases the measurement depth. On the other hand, for example, decreasing the intensity of the illumination light IL allows measurement only to a shallower depth. In other words, decreasing the intensity of the illumination light IL decreases the measurement depth. Therefore, when measuring the intensity of the reflected light, the measurement unit 7M can change the measurement depth by changing the intensity of the illumination light.

[0137] The method for changing the measurement depth is not limited to the above, and the measurement depth may be adjusted, for example, by changing the position or angle of the light source for generating the illumination light IL to adjust the optical path.

[0138] The measurement unit 7M changes the measurement depth based on the measurement depth information MDI input from the measurement depth input unit 7G.

[0139] The skin condition estimation unit 7P estimates at least one of skin elasticity and skin density as the skin condition based on the intensity Qs2 at a specific wavelength λs contained in the reflected light measured by the measurement unit 7M. For specific estimation methods used by the skin condition estimation unit 7P, please refer to the description of the skin condition estimation unit 1P, and detailed description will be omitted here. The measurement depth input unit 7G outputs measurement depth information MDI to the skin condition estimation unit 7P. The skin condition estimation unit 7P may appropriately correct the estimation results based on the measurement depth information MDI.

[0140] The measurement depth input unit 7G inputs measurement depth information MDI, which is information related to the measurement depth. The measurement depth information MDI is input from the measurement depth input unit 7G to the skin condition estimation device 7. For example, the measurement depth input unit 7G accepts, for example, a depth to be measured as the measurement depth information MDI. The measurement depth input unit 7G outputs the accepted measurement depth information MDI to the measurement unit 7M and the skin condition estimation unit 7P.

[0141] Eighth Embodiment A skin condition estimating device according to the eighth embodiment will be described. The skin condition estimating device according to the eighth embodiment estimates the skin condition of multiple parts of a measurement target OBJ. The skin condition estimating device according to the eighth embodiment also includes a recommendation unit that recommends products based on the estimation results.

[0142] FIG. 24 is a diagram illustrating the functional configuration and processing flow of a skin condition estimating device 8, which is an example of a skin condition estimating device according to the eighth embodiment.

[0143] In addition to the components of the skin condition estimation device 5, the skin condition estimation device 8 includes a product database 8T in which recommended products corresponding to the area to be measured are recorded, and recommended product determination units 8R(1) to 8R(n).

[0144] The recommended product determination unit 8R(i) determines a product to recommend based on the skin condition estimation result from the skin condition estimation unit 5P(i). Here, i is an integer between 1 and n. The same applies to i below. The recommended product determination unit 8R(i) acquires from the skin condition estimation unit 5P(i) a result RES8(i) which is the result of the skin condition estimated by the skin condition estimation unit 5P(i). Then, the recommended product determination unit 8R(i) selects and determines a product to recommend from a recommended product determination table stored in the product database 8T based on the result RES8(i).

[0145] 25 is a diagram showing an example of a recommended product determination table provided in a skin condition estimating device 8, which is an example of a skin condition estimating device according to the eighth embodiment. In FIG. 25, a case will be described in which cosmetics are recommended as recommended products.

[0146] For example, for area 1, if the score of the estimation result by the skin condition estimation unit is below average ("below average score"), the recommended product determination unit selects "eye care cream A." For area 1, if the score of the estimation result by the skin condition estimation unit is about average ("about average score"), the recommended product determination unit selects "eye care cream B." For area 1, if the score of the estimation result by the skin condition estimation unit is above average ("above average score"), the recommended product determination unit selects "eye care cream C."

[0147] Furthermore, for example, if the score of the estimation result by the skin condition estimation unit for region 2 is below average ("below average score"), the recommended product determination unit selects "lotion." If the score of the estimation result by the skin condition estimation unit for region 2 is about average ("about average score"), the recommended product determination unit selects "cream A." If the score of the estimation result by the skin condition estimation unit for region 2 is above average ("above average score"), the recommended product determination unit selects "cream B."

[0148] The results displayed by the display unit 1E in the skin condition estimation device 8 will be described. FIG. 26 is a diagram illustrating processing in the skin condition estimation device 8, which is an example of a skin condition estimation device according to the eighth embodiment. In FIG. 26 , for example, the display unit 1E in the skin condition estimation device 8 displays recommended cosmetics for the three zones (the worst three) in the region where the skin condition was estimated, where the estimation results were poor. In FIG. 26 , for zone R21, which had the poorest results, the display unit 1E displays, for example, "Cosmetic A" as the recommended product. Also, in FIG. 26 , for zone R22, which had the second poorest results, the display unit 1E displays, for example, "Cosmetic B" as the recommended product. Furthermore, in FIG. 26 , for zone R23, which had the third poorest results, the display unit 1E displays, for example, "Cosmetic C" as the recommended product.

[0149] The recommended products may be displayed as a character string superimposed on an image, or may be displayed as a list in a table containing the corresponding colors by indicating the areas with colors.

[0150] Ninth Embodiment Although the skin condition estimation device according to the eighth embodiment has been described as including a recommended product determination unit, a recommendation device that recommends products may also be provided separately from the skin condition estimation device. As the ninth embodiment, a product recommendation system including a skin condition estimation device and a recommendation device will be described.

[0151] FIG. 27 is a diagram showing an overview of a product recommendation system 100, which is an example of a product recommendation system according to the ninth embodiment.

[0152] The product recommendation system 100 includes a skin condition estimation device 110 and a recommendation device 120. The skin condition estimation device 110 is, for example, any of the skin estimation devices according to the first to seventh embodiments. The skin condition estimation device 110 outputs a skin condition estimation result RES9 to the recommendation device 120. The recommendation device 120 presents recommended products based on the skin condition estimated by the skin condition estimation device 110. Note that the processing of the recommendation device 120 is similar to that of the recommended product determination unit in the skin condition estimation device 8, and therefore a detailed description thereof will be omitted.

[0153] <<Measurement of reflected light in the skin condition estimation device according to this embodiment>> The skin condition estimation device according to this embodiment measures the intensity of reflected light at a specific wavelength λs. The following describes the configuration for measuring the intensity of reflected light at a specific wavelength λs in the skin condition estimation device according to this embodiment.

[0154] 28 is a diagram illustrating a first example of reflected light measurement in the skin condition estimation device according to the present embodiment. In the first example, the skin condition estimation device includes a photodetector 10 and a light source 15.

[0155] The light source 15 is, for example, an LED (Light Emitting Diode), an incandescent lamp, a fluorescent lamp, a discharge lamp, etc. The light source 15 emits light in a relatively wide wavelength range including a specific wavelength λs. The light source 15 illuminates the skin SKN of the measurement object OBJ with illumination light IL. The illumination light IL is reflected by the skin SKN and enters the photodetector 10 as reflected light RL.

[0156] The photodetector 10 receives the reflected light RL and converts it into an electrical signal. The photodetector 10 includes an optical filter 11 and a light receiving element 12.

[0157] The optical filter 11 is, for example, an optical band-pass filter that passes a range including a specific wavelength λs. When the reflected light RL passes through the optical filter 11, light in a narrow wavelength range including the specific wavelength λs contained in the reflected light RL passes through.

[0158] The light receiving element 12 converts the received light into an electrical signal. The light receiving element 12 is, for example, a photodiode.

[0159] The photodetector 10 is provided with the optical filter 11 and is therefore able to detect light of a specific wavelength λs within the wavelength range included in the light source 15 .

[0160] [Second Example] The number of light sources is not limited to one. Fig. 29 is a diagram illustrating a second example of reflected light measurement in the skin condition estimation device according to this embodiment. In the second example, the skin condition estimation device includes a photodetector 10 and multiple light sources 15. The number of light sources 15 may be, for example, two, or three or more.

[0161] Furthermore, it is desirable to arrange the multiple light sources 15 so as to surround the area where skin SKN is to be measured. A diffusion plate that diffuses light from the light sources 15 may be provided between the light sources 15 and the object to be measured. Furthermore, the light sources 15 may be surface-emitting elements such as organic electroluminescence elements.

[0162] 30 is a diagram illustrating a third example of reflected light measurement in the skin condition estimation device according to the present embodiment. In the third example, the skin condition estimation device includes a photodetector 10A and a light source 16.

[0163] The light source 16 is a light-emitting element with a narrow emission wavelength range. The light source 16 is, for example, a laser such as an LD (Laser Diode). The light source 16 emits light in a narrow wavelength range that includes a specific wavelength λs. The light source 16 illuminates the skin SKN of the measurement object OBJ with illumination light IL. The illumination light IL is reflected by the skin SKN and enters the photodetector 10A as reflected light RL.

[0164] The photodetector 10A receives the reflected light RL and converts it into an electrical signal. The photodetector 10A includes a light-receiving element 12. In the third example, since the light source 16 has a narrow emission wavelength range, the optical filter 11 in the photodetector 10 may be omitted. Note that the optical filter 11 may be provided in consideration of the influence of ambient light.

[0165] [Fourth Example] In the first to third examples, a light source was provided separately from the photodetector 10. However, the photodetector 10 may perform measurements using ambient light such as room illumination light or external light.

[0166] 31 is a diagram illustrating a fourth example of reflected light measurement in a skin condition estimation device according to the present embodiment. In the fourth example, the skin condition estimation device includes a photodetector 10. In the fourth example, the skin condition estimation device estimates the skin condition using reflected light RL that is reflected off skin SKN by ambient light NL.

[0167] When estimating the skin condition of the skin SKN using the ambient light NL, the estimation of the skin condition may differ due to the influence of the ambient light NL. Therefore, in the fourth example, correction is performed to suppress the influence of the ambient light NL.

[0168] 32 to 34 are diagrams illustrating preliminary measurement in a fourth example of reflected light measurement in the skin condition estimating device according to this embodiment.

[0169] First, preliminary preparations are made. As preliminary preparations, as shown in FIG. 32 , reference light source 17 is used to measure reference reflector REF using the skin condition estimating device. As shown in FIG. 32 , reference reflector REF is illuminated by reference light source 17. Then, the skin condition estimating device measures the intensity of reflected light RL1, which is light from reference light source 17 reflected by surface SUF of reference reflector REF. The intensity of the measured reflected light RL1 is designated as intensity Qr1. Then, as shown in FIG. 33 , measurements are made of reflected light RL reflected by multiple measurement targets OBJ, and the maximum value Qmax and minimum value Qmin in Equation 1 are measured.

[0170] 34, the skin condition estimating device measures the intensity of reflected light RL2 of the ambient light NL reflected by the surface SUF of the reference reflector REF. The intensity of the measured reflected light RL2 is defined as intensity Qr2.

[0171] The skin condition estimating device then calculates an offset value from the intensity Qr1 of reflected light RL1 emitted from the reference light source 17 and reflected by the reference reflector REF, and the intensity Qr2 of reflected light RL2 of the ambient light NL reflected by the reference reflector REF. Specifically, the offset value Qof is determined as the difference between the intensity Qr2 and the intensity Qr1.

[0172] Next, as shown in Fig. 31, the skin condition estimating device measures the intensity Qs of reflected light RL, which is ambient light NL reflected by the skin SKN of the measurement object OBJ. Then, the intensity Qs is corrected by subtracting an offset value Qof. The skin condition estimating device estimates the skin condition using the corrected intensity Qs.

[0173] Although the embodiments have been described above, it will be understood that various changes in form and details are possible without departing from the spirit and scope of the claims. Various modifications and improvements, such as combinations with or substitutions for part or all of other embodiments, are possible.

[0174] This application claims priority from basic patent application No. 2023-143548, filed with the Japan Patent Office on September 5, 2023, the entire contents of which are incorporated herein by reference.

[0175] 1, 2, 3, 4, 5, 6, 7, 8 Skin condition estimation device 1M, 5M, 7M Measurement unit 1P, 2P, 3P, 4P, 7P Skin condition estimation unit 5P(1), 5P(2), 5P(3), ..., 5P(n) Skin condition estimation unit 2K Attribute information input unit 2P Skin condition estimation unit 4H Correction value calculation unit 4K Cosmetic information input unit 6L Part input unit 6Q Part determination unit 7G Measurement depth input unit 8R(1), 8R(2), 8R(3), ..., 8R(n) Recommended product determination unit 8T Product database 10, 10A Photodetector 11 Optical filter 12 Light receiving element 15, 16 Light source 17 Reference light source 100 Product recommendation system 110 Skin condition estimation device 120 Recommendation device IL Illumination light NL Ambient light OBJ Measured object RL, RL1, RL2 Reflected light

Claims

1. A skin condition estimating device comprising: a measuring unit that measures reflected light in a wavelength range including a specific wavelength reflected by the skin; and a skin condition estimating unit that estimates at least one of skin elasticity and skin density of the skin as a skin condition based on the intensity of the specific wavelength contained in the reflected light measured by the measuring unit.

2. The skin condition estimating device according to claim 1, wherein the skin condition estimating unit estimates the skin condition based on a plurality of measurement results obtained by measuring in advance the intensity measured by the measuring unit and the intensity at the specific wavelength.

3. The skin condition estimating device according to claim 2, wherein the skin condition estimating unit estimates the skin condition based on a maximum value and a minimum value of the intensity in the multiple measurement results.

4. The skin condition estimating device according to any one of claims 1 to 3, wherein the specific wavelength is a wavelength excluding a wavelength range in which the main component of the skin is absorbed.

5. A skin condition estimating device as described in any one of claims 1 to 3, further comprising an attribute information input unit, wherein the skin condition estimating unit estimates the skin condition based on the intensity measured by the measuring unit and the attribute information input from the attribute information input unit.

6. A skin condition estimation device as described in any one of claims 1 to 3, comprising: an attribute information input unit; and a display unit for displaying an estimation result, wherein the display unit displays a comparison with a representative value in a set similar to the attribute information input from the attribute information input unit.

7. A skin condition estimating device as described in any one of claims 1 to 3, further comprising a makeup information input unit, wherein the skin condition estimating unit estimates the skin condition based on the intensity measured by the measuring unit and the makeup information input from the makeup information input unit.

8. The skin condition estimating device according to claim 1, wherein the measuring unit receives the reflected light at a plurality of parts of the skin, and the skin condition estimating unit estimates the skin condition at each of the plurality of parts.

9. The skin condition estimation device of claim 1, wherein the measurement unit receives reflected light of ambient light reflected by the skin as the reflected light, and the skin condition estimation unit corrects the intensity based on a first intensity at the specific wavelength of first reflected light emitted from a reference light source and reflected by a reference reflector, and a second intensity at the specific wavelength of second reflected light of the ambient light reflected by the reference reflector.

10. A product recommendation system comprising: a skin condition estimation device according to any one of claims 1 to 3; and a recommendation device that presents recommended products based on the skin condition estimated by the skin condition estimation device.

11. A skin condition estimating method comprising: a step of measuring reflected light in a wavelength range including a specific wavelength reflected by the skin; and a step of estimating at least one of skin elasticity and skin density of the skin as a skin condition based on the intensity at the specific wavelength included in the measured reflected light.

12. A product recommendation method comprising: a step of measuring reflected light in a wavelength range including a specific wavelength reflected by the skin; a step of estimating at least one of skin elasticity and skin density of the skin as a skin condition based on the intensity at the specific wavelength included in the measured reflected light; and a step of presenting recommended products based on the estimated skin condition.

13. A program for causing a computer to execute the steps of: acquiring intensity at a specific wavelength contained in reflected light in a wavelength range including a specific wavelength reflected by skin; and estimating at least one of skin elasticity and skin density of the skin as a skin condition based on the acquired intensity.

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