Sagging diagnosis method, sagging diagnostic device, cosmetic apparatus, information processing system, and program

Abstract

Provided is a more beneficial technology. According to one embodiment of the present invention, provided is a sagging diagnostic device comprising: an acquisition unit that acquires state information indicating the state of the skin; and a diagnostic unit that diagnoses sagging of the skin on the basis of the acquired state information.

Description

Wrinkling diagnosis method, wrinkling diagnosis device, beauty device, information processing system, and program

[0001] The present invention relates to a wrinkling diagnosis method, a wrinkling diagnosis device, a beauty device, an information processing system, and a program.

[0002] Recently, various technologies have been developed. Patent Document 1 discloses a technique for estimating various skin state characteristic quantities by simply sending the stratum corneum collected by sticking a tape on the face to an analysis institution. On the other hand, the development of more beneficial technologies is required. Also, a method for evaluating sagging is known based on the difference in visual sagging impressions. For example, Patent Document 2 discloses a method for evaluating sagging by observing the shape from the side of the jaw to the neck. However, since the criteria for evaluating sagging are limited to appearance information, only the aging phenomena appearing in the appearance are known, and there is a problem that the evaluation results differ depending on the evaluator.

[0003] Japanese Patent Application Laid-Open No. 2024-039083, Japanese Patent Application Laid-Open No. 2013-59529

[0004] In view of the above circumstances, the present invention aims to provide a more beneficial technology. Specifically, compared with the conventional technology, it is intended to provide a method capable of more accurately classifying sagging by obtaining state information indicating the internal information of the skin and specifying and evaluating the factors of sagging.

[0005] According to one aspect of the present invention, there is provided a wrinkling diagnosis device including an acquisition unit that acquires state information indicating the state of the skin, and a diagnosis unit that diagnoses the sagging of the skin based on the acquired state information.

[0006] According to such an aspect, a more beneficial technology can be provided. Specifically, it becomes possible to more accurately classify sagging and propose a treatment method suitable for each sagging state.

[0007] This figure shows an example of the overall configuration of the beauty device 10. This figure shows an example of the detailed configuration of the acquisition unit 30. It shows the distribution of target age groups and BMI. It shows a scatter plot of age and upper cheek Merz Score (Upper Cheek Fullness). It shows a scatter plot of age and lower cheek Merz Score (Jawline). It shows a scatter plot of age and mandibular Merz Score (Neck Volume). It shows a list of correlation coefficients R between the dermal viscoelasticity of the cheek acquired by Cutometer, age, and the three Merz Scores. It shows a list of correlation coefficients R between the dermal viscoelasticity R7 of the cheek, outer corner of the eye, and under the chin acquired by Cutometer, age, and the three Merz Scores. This shows a scatter plot of cheek dermal elasticity R7 and upper cheek Merz Score (Upper Cheek Fullness). This shows a scatter plot of cheek dermal viscoelasticity R7 and lower cheek Merz Score (Jawline). This shows a scatter plot of cheek dermal viscoelasticity R7 and mandibular Merz Score (Neck Volume). This shows a list of correlation coefficients R between cheek dermal condition, age, and the three Merz Scores obtained by DermaLab. This shows a list of correlation coefficients R between subcutaneous fat thickness in four areas: upper cheek, lower cheek, lateral cheek, and submandibular, and age and the three Merz Scores. This shows a scatter plot of mandibular subcutaneous fat thickness and mandibular Merz Score (Neck Volume). This document presents a list of correlation coefficients (R) between subcutaneous fat brightness in four areas: upper cheek, lower cheek, lateral cheek, and submandibular region, age, and three Merz Scores. It also shows a scatter plot between subcutaneous fat brightness in the lateral cheek and Merz Score (Upper Cheek Fullness) in the upper cheek. Furthermore, it presents a list of correlation coefficients (R) between zygomaticus major muscle thickness, masseter muscle thickness, age, and three Merz Scores. Finally, it shows a scatter plot between zygomaticus major muscle thickness and Merz Score (Upper Cheek Fullness) in the upper cheek, and a scatter plot between masseter muscle thickness and Merz Score (Neck Volume) in the mandibular region. The document also presents a list of correlation coefficients (R) between zygomaticus major muscle brightness, masseter muscle brightness, age, and three Merz Scores. The scatter plots of zygomaticus major muscle brightness and Merz Score (Upper Cheek Fullness) in the upper cheek are shown. The scatter plots of masseter muscle brightness and Merz Score (Upper Cheek Fullness) in the upper cheek are also shown.This is a block diagram showing an example of the electrical configuration of the electrical characteristics measurement unit 31. This is a block diagram of a two-stage measuring device. This is an example of a perspective view of a two-stage measuring device. This is a diagram showing another example of the overall configuration of a beauty device. This is a diagram showing an example of the overall configuration of an information processing system. This is a diagram showing an example of the hardware configuration of the analysis server 50. This is a diagram showing an example of the hardware configuration of the user terminal 60. This is a diagram showing an example of a diagnostic result. This is a diagram showing another example of a diagnostic result. This is a diagram for explaining fat sagging. This is a diagram for explaining muscle sagging. This is a diagram for explaining the scoring of the diagnostic level. This is a diagram for explaining the linkage between the measuring device and the application.

[0008] [Embodiments] Embodiments will be described below with reference to the drawings. The various features shown in the embodiments below can be combined with each other.

[0009] Figure 1 shows an example of the overall configuration of the beauty device 10. The beauty device 10 is a device that has a function to enhance beauty, and in particular has a function to improve or suppress skin sagging. Specifically, the beauty device 10 improves or suppresses sagging by tightening the skin and strengthening the muscles by outputting electrical signals to the skin to warm the skin and contract the muscles. The beauty device 10 comprises a sagging diagnosis unit 20, a display unit 11, a treatment unit 12, a power supply unit 13, and a housing unit 14.

[0010] The housing 14 is a hollow container shaped to be easily held in the hand, and is configured to house the other parts. The power supply unit 13 is configured to supply power to each part of the beauty device 10. The power supply unit 13 has, for example, a secondary battery or a primary battery, but it may also be an AC / DC power supply that converts household alternating current to direct current.

[0011] The treatment unit 12 has electrodes and is configured to perform treatments such as warming the skin or contracting muscles by bringing the electrodes into contact with a person's skin and outputting electrical signals. The treatment unit 12 outputs, for example, RF (Radio Frequency) electrical signals and EMS (Electrical Muscle Stimulation) electrical signals. The display unit 11 has a panel for displaying images and is configured to display the operating status of the treatment unit 12 and the diagnostic results from the sagging diagnosis unit 20.

[0012] The sagging diagnosis unit 20 is an example of a sagging diagnosis device configured to diagnose skin sagging. The sagging diagnosis unit 20 comprises an acquisition unit 30 and a diagnosis unit 40. The acquisition unit 30 is configured to acquire state information indicating the internal state of the skin. The acquisition unit 30 acquires, for example, measurement results from a contact-type sensor that comes into contact with the skin or measurement results from a non-contact-type sensor that does not come into contact with the skin as state information. Each sensor will be described with reference to Figure 2.

[0013] Figure 2 shows an example of the detailed configuration of the acquisition unit 30. The acquisition unit 30 includes an electrical characteristic measurement unit 31 having a contact-type sensor, a pressure measurement unit 32, an optical characteristic measurement unit 33, and an ultrasonic measurement unit 34, an appearance measurement unit 35 having a non-contact-type sensor, and an external information acquisition unit 36 ​​that acquires measurement results from an external sensor. The electrical characteristic measurement unit 31 has a signal generation unit (AC power supply), electrodes, a signal measurement unit, etc., and is configured to measure electrical characteristics from the relationship between voltage and current by passing an AC current through the skin. For example, the electrical characteristic measurement unit 31 measures impedance and phase as electrical characteristics.

[0014] The pressure measuring unit 32 has a pressure sensor and is configured to measure pressure. The optical properties measuring unit 33 has a light source and an optical measuring unit, etc., and is configured to measure the properties of light (transmitted light) that is reflected back from inside the skin after being irradiated by the light source. The optical properties measuring unit 33 measures, for example, the transmittance of the transmitted light, the absorption characteristics of the transmitted light at different frequencies, the transmission and scattering characteristics, the frequency change, and the time-frequency characteristics by measuring optical properties such as the intensity, wavelength, or frequency of the transmitted light.

[0015] The ultrasound measurement unit 34 is a measurement unit that measures the internal structure of the skin using an ultrasound diagnostic device. The ultrasound measurement unit 34 places an ultrasound probe in contact with the skin, transmits ultrasound waves into the skin, and receives echo signals reflected from the internal tissue. Based on the received echo signals, an image of the subcutaneous fat layer or muscle layer is generated. The generated image includes information indicating the thickness or brightness of the subcutaneous fat layer, or the thickness or brightness of the muscle layer. In addition, if ultrasound elastography is used, it may also include information indicating the hardness or elasticity of the subcutaneous fat layer or muscle layer.

[0016] The appearance measurement unit 35 measures the characteristics of electromagnetic waves emitted from the surface of the skin. Electromagnetic waves include visible light, infrared rays, or millimeter waves. Electromagnetic waves include both those reflected by the skin and those emitted by the skin itself. Characteristics of electromagnetic waves include wavelength, amplitude, or phase. The appearance measurement unit 35 has a lens and a planar sensor for measuring electromagnetic waves, and outputs an electrical signal representing the image formed on the sensor. By sequentially reading out the output electrical signals, an image representing the appearance of the skin is generated.

[0017] As described above, the external information acquisition unit 36 ​​is the part that acquires measurement results from external sensors. Examples of external sensors include Cutometer® manufactured by Courage+Khazaka, an ultrasound diagnostic device, a BIA sensor (Bioelectrical Impedance Analysis), an EMG sensor (Electromyography), a near-infrared light sensor, an image sensor, etc.

[0018] The diagnostic unit 40 is, for example, an integrated circuit (IC) chip that integrates a central processing unit (CPU), memory (Random Access Memory: RAM) / Read Only Memory: ROM), and I / O ports, and is a microcomputer that operates according to a program stored in memory. The diagnostic unit 40 performs predetermined information processing using, for example, the state information acquired by the acquisition unit 30. In this way, the sagging diagnostic unit 20 and the beauty device 10 equipped with the diagnostic unit 40 function as information processing devices.

[0019] The diagnostic unit 40 diagnoses the factors causing skin sagging based on the acquired condition information. The diagnostic unit 40 diagnoses the factors causing sagging that correlate with the skin condition indicated by the acquired condition information, for example, based on reference information that shows the correlation between the condition information and the factors causing skin sagging. The reference information is, for example, a table that associates the condition information with the factors causing sagging. The reference information is also a table that associates the condition information with the type of sagging. In the following, a table that associates the condition information with the diagnosis results of sagging will be called a "diagnosis table".

[0020] Types of sagging refer to classifications based on the causes of sagging, such as dermal sagging, fatty sagging, and muscular sagging. Dermal sagging is caused by a decrease or deterioration of collagen and other components in the dermis, resulting in a loss of skin elasticity. Fatty sagging is caused by the weight of fat stretching the fibers connecting the skin and bone to the fat layer. Muscular sagging is caused by muscle weakness, which causes the skin and fat to droop because they can no longer support their own weight.

[0021] A diagnostic table is created, for example, as follows: First, the subject is measured using a measuring instrument capable of precise measurement, such as an ultrasound diagnostic device, CT (Computed Tomography), MRI (Magnetic Resonance Imaging), microscope, stratum corneum moisture meter, skin elasticity meter, body composition analyzer, or subcutaneous fat thickness meter. Meanwhile, a specialist such as a doctor grades the subject's facial images according to reference photographs. Next, the correlation between the graded appearance changes and the measured values ​​is analyzed, and items showing a strong correlation are extracted. In addition, condition information is acquired for the same subject using the acquisition unit 30. A table is created as a diagnostic table by analyzing and associating the items showing a strong correlation with the condition information acquired using the acquisition unit 30.

[0022] Furthermore, the correlation analysis may be performed by AI (Artificial Intelligence). In that case, the reference information is a learning model generated by learning based on training data that shows condition information indicating the state of the skin and the results of a diagnosis by an expert.

[0023] In this configuration, the user can understand the factors causing skin sagging, such as the type of sagging occurring in their skin, based on the diagnostic results from the diagnostic unit 40. Once the user understands the factors causing skin sagging, they can use this information to determine, for example, the intensity and frequency of treatment performed by the treatment unit 12. Thus, the beauty device 10 can provide the user with more beneficial technology compared to a device without a sagging diagnostic unit 20. In detail, compared to conventional technology, by acquiring condition information indicating internal skin information and identifying and evaluating the factors causing sagging, it is possible to classify sagging more accurately, and as a result, it becomes possible to propose treatment methods that are appropriate for each individual's sagging condition.

[0024] As described above, the inside of the skin is made up of multiple tissues. The diagnostic unit 40 diagnoses which of these multiple tissues is causing the skin to sag. For example, the diagnostic unit 40 diagnoses the type of sagging that is occurring in the skin (for example, dermal sagging, fatty sagging, and muscle sagging as described above). These types represent the tissues that are causing the sagging. For example, dermal sagging is sagging caused by the deterioration of the dermis, and fatty sagging is sagging caused by the enlargement of fat. Muscle sagging is sagging caused by the deterioration of muscles. The diagnostic unit 40 diagnoses the cause of sagging by using reference information that shows the correlation between each type of sagging and the condition information. With this configuration, the user can understand which tissues are causing the sagging.

[0025] <Experiment Description> Facial sagging is one of the major factors influencing the impression of aging, and it is thought to be caused not only by changes in the skin surface but also by changes in the internal structure of the skin (dermis, subcutaneous fat, and muscle). Many studies to date have been limited to evaluating the skin surface, and the relationship between the quantitative evaluation of each internal structure and changes in appearance has not been sufficiently clarified. The inventor conducted an experiment with the aim of clarifying whether the difference in the impression of sagging is caused by the skin surface or the internal structure (dermis, subcutaneous fat layer, or muscle layer), and constructing a mathematical model to predict the impression of sagging, thereby obtaining basic knowledge that will lead to the evaluation of the internal structural state of individuals and the optimal intervention for them.

[0026] This experiment was conducted as a cross-sectional observational study of Japanese women from July to October 2025. The study included 220 Japanese women aged 20 to 77 with a BMI between 15.0 and less than 30.0, consisting of 40 women in each age group (20s, 30s, 40s, 40s, 40s, 40s, 40s, 40s, and 20s). Exclusion criteria included a history of cosmetic medical treatments (laser, injections, surgery, etc.), facial skin diseases, serious underlying medical conditions, and pregnancy. Figure 3 shows the distribution of age groups and BMI. The mean BMI was 21.1 ± 3.0, and the analysis of variance across age groups yielded a p-value of 0.879, indicating no significant difference in BMI between age groups.

[0027] The perceived sagging of the face was evaluated based on 3D facial images obtained using 3D-LifeViz Mini (registered trademark). For three areas (upper cheek fullness, lower cheek sagging, and jawline sagging), two expert evaluators visually assessed each area and determined the Merz Score on a 5-point scale of The Merz Facial Sagging Scale, and the average value was calculated.

[0028] For measurements of the inside of the skin, each layer of the skin structure was evaluated using the following equipment and methods: • Dermis: Dermal viscoelasticity was evaluated in three areas: cheek, outer corner of the eye, and under the chin using Cutometer® (Courage + Khazaka, φ6 mm probe, suction pressure 450 mbar). Dermal collagen density, dermal thickness, and LEB were also evaluated using DermaLab. • Subcutaneous fat: Ultrasound imaging was used to acquire ultrasound images of subcutaneous adipose tissue in four locations: upper cheek, lower cheek, lateral cheek, and mandible. Fat thickness and fat brightness were calculated using the image analysis software WinRoof. • Muscle: Ultrasound imaging was used to acquire ultrasound images of the zygomaticus major and masseter muscles. Muscle thickness and muscle brightness were calculated using the image analysis software WinRoof.

[0029] The relationship between these internal structures and the external sag, known as Merz Score, was examined using correlation and multiple regression analyses.

[0030] Before the measurements were taken, the subjects' skin was washed, and then they were allowed to rest for 20 minutes in an environment with a temperature of 21.8 ± 0.6°C and a relative humidity of 50.8 ± 2.30%.

[0031] The relationships between continuous variables were analyzed using Pearson or Spearman correlation coefficient tests. One-way analysis of variance (ANOVA) was used for group comparisons. Multiple regression analysis was used to evaluate the influence of each measurement item on the sagging index. The significance level was set at p<0.05 using two-tailed tests for all analyses.

[0032] Figure 4 shows a scatter plot of age and the Merz Score (Upper Cheek Fullness) in the upper cheek. Figure 5 shows a scatter plot of age and the Merz Score (Jawline) in the lower cheek. Figure 6 shows a scatter plot of age and the Merz Score (Neck Volume) in the lower jaw. The correlation coefficients R between age and the three Merz Scores (Upper Cheek Fullness, Jawline, and Neck Volume) were 0.872, 0.849, and 0.501, respectively (all p<0.01), indicating that sagging increased with age.

[0033] <Measurement of dermal properties correlating with Merz Score> To investigate the correlation between visible sagging and the state of the dermis, dermal viscoelasticity was measured using a Cutometer Φ6 mm at three locations: the cheeks, outer corners of the eyes, and under the chin. Dermal collagen density (intensity), dermal thickness (Skin Thickness), and dermal low-resonance zone (LEB) were measured using a DermaLab.

[0034] Figure 7 shows a list of correlation coefficients (R) between dermal viscoelasticity of the cheek, age, and three Merz scores, obtained by Cutometer. Dermal viscoelasticity worsened with age, and R0, R1, R2, R4, R5, R6, R7, and R8 showed significant correlations with all three Merz scores: Upper Cheek Fullness, Jawline, and Neck Volume. A particularly high correlation was observed with R7.

[0035] Figure 8 shows a list of correlation coefficients R between the dermal viscoelasticity R7 of the cheeks, outer corners of the eyes, and subchinenchyma, obtained by Cutometer, and age and the three Merz Scores. When comparing by area, the correlation between the dermal viscoelasticity of the cheeks and subchinenchyma and sagging was similar, while the correlation coefficient R was relatively small for the outer corners of the eyes. Figure 9 shows a scatter plot of cheek dermal elasticity R7 and upper cheek Merz Score (Upper Cheek Fullness). Figure 10 shows a scatter plot of cheek dermal viscoelasticity R7 and lower cheek Merz Score (Jawline). Figure 11 shows a scatter plot of cheek dermal viscoelasticity R7 and mandibular Merz Score (Neck Volume).

[0036] Next, Intensity, Skin Thickness, and LEB were measured in the cheek area using DermaLab. Figure 12 shows a list of correlation coefficients (R) between the dermal condition of the cheek obtained by DermaLab, age, and three Merz scores. Intensity and LEB worsened with age and showed significant correlations with both of the two Merz scores, Upper Cheek Fullness and Jawline. Skin Thickness showed a significant correlation only with Upper Cheek Fullness.

[0037] From the above findings, it became clear that apparent sagging is more strongly correlated with the viscoelastic properties of the dermis than with quantitative indicators such as dermal collagen density and dermal thickness. In particular, viscoelastic parameters centered on R7 obtained by Cutometer consistently correlated with age and multiple Merz Score values, with this correlation being particularly pronounced in the cheek area. These results suggest that the essence of sagging is not simply a "quantitative decrease," but rather strongly depends on changes in the skin's ability to support and recover from mechanical loads.

[0038] It is thought that age-related disruption of collagen fiber arrangement and changes in cross-linking structure lead to a decrease in dermal viscoelasticity, increasing deformation under load, and consequently resulting in perceived sagging. On the other hand, collagen density, dermal thickness, and LEB measured by DermaLab showed a relatively weak correlation with Merz score. This suggests that in dermal evaluation, the functional aspect of "how it responds to force" is more important than "how much it is present," and that quantitative evaluation alone cannot adequately explain visual sagging.

[0039] <Measurement of subcutaneous adipose tissue characteristics correlated with Merz Score> To investigate the correlation between visible sagging and the condition of subcutaneous adipose tissue, the thickness and brightness of subcutaneous fat in four areas—upper cheek, lower cheek, lateral cheek, and subchinenchymal region—were obtained using an ultrasound diagnostic device and evaluated through image analysis.

[0040] Figure 13 shows a list of correlation coefficients (R) between subcutaneous fat thickness and age and three Merz scores in four areas: upper cheek, lower cheek, lateral cheek, and submandibular region. Significant correlations were observed between Jawline and Neck Volume in the upper cheek and mandibular region, between Neck Volume in the lower cheek, and between age and Neck Volume in the lateral cheek region, revealing that sagging in the lower cheek and submandibular region is influenced by subcutaneous fat thickness. Figure 14 shows a scatter plot of subcutaneous fat thickness in the mandibular region and Merz score (Neck Volume) in the mandibular region.

[0041] Figure 15 shows a list of correlation coefficients (R) between subcutaneous fat brightness in four areas: upper cheek, lower cheek, lateral cheek, and submandibular region, age, and three Merz Score values. In all areas, subcutaneous fat brightness significantly increased with age. Significant correlations were observed between Jawline and Neck Volume in the upper cheek and submandibular region, between Neck Volume in the lower cheek, and between Upper Cheek Fullness and Jawline in the lateral cheek region. Figure 16 shows a scatter plot of subcutaneous fat brightness in the lateral cheek region and Merz Score (Upper Cheek Fullness) in the upper cheek region.

[0042] From the above, a correlation with the appearance of sagging was observed for both subcutaneous fat thickness and subcutaneous fat brightness depending on the site. In particular, sagging under the chin (Neck Volume) showed a moderate correlation with subcutaneous fat thickness, indicating that the amount of fat may contribute to sagging in appearance. On the other hand, since a significant increase in brightness was observed with aging in all sites, it was suggested that it is useful as an indicator of age-related qualitative changes. Although fat brightness showed a weak correlation with sagging depending on the site, this may be due to the enhanced fibrosis in adipose tissue, which reduces the elasticity of the fat layer and increases deformation under mechanical load, ultimately contributing to sagging in appearance. Additionally, it is known that aging of the fat layer enhances inflammatory factors in the extracellular environment and also has an adverse effect on the dermal ECM structure, suggesting that an increase in fat layer brightness may contribute to sagging caused by qualitative changes in both the fat layer and the dermal layer.

[0043] <Measurement of muscle characteristics correlated with Merz Score> To examine the correlation between the appearance of sagging and the state of muscles, echo images were obtained using an ultrasonic diagnostic apparatus for muscle thickness and muscle brightness at two sites, the zygomatic major muscle and the masseter muscle, and evaluated by image analysis.

[0044] Figure 17 shows a list of the correlation coefficients R between the zygomatic major muscle thickness, masseter muscle thickness, age, and three Merz Scores. The thickness of the zygomatic major muscle thinned with aging, and a significant negative correlation was observed with Upper Cheek Fullness and Jawline. The thickness of the masseter muscle showed a significant positive correlation only with Neck Volume. Figure 18 shows a scatter plot of the zygomatic major muscle thickness and the Merz Score (Upper Cheek Fullness) of the upper cheek. Figure 19 shows a scatter plot of the masseter muscle thickness and the Merz Score (Neck Volume) of the lower jaw.

[0045] Figure 20 shows a list of correlation coefficients (R) between zygomaticus major muscle brightness, masseter muscle brightness, age, and three Merz Scores. Brightness of both the zygomaticus major and masseter muscles increased with age, and significant correlations were found between zygomaticus major muscle brightness and Upper Cheek Fullness and Jawline, and between masseter muscle brightness and Upper Cheek Fullness. Figure 21 shows a scatter plot of zygomaticus major muscle brightness and Merz Score (Upper Cheek Fullness) in the upper cheek. Figure 22 shows a scatter plot of masseter muscle brightness and Merz Score (Upper Cheek Fullness) in the upper cheek.

[0046] Based on the above, both muscle thickness and muscle brightness were found to be related to sagging appearance depending on the area. The zygomaticus major muscle is involved in the elevation and support of the midfacial skin, and its thinning is thought to exacerbate cheek sagging through a decrease in the supporting capacity of the skin and adipose tissue. On the other hand, the masseter muscle is a deep muscle mainly responsible for mastication and has little direct contribution to skin support, but it is presumed that the increase in volume of the mandible due to increased thickness contributed to sagging under the chin. In addition, an increase in brightness was observed with age in both the zygomaticus major and masseter muscles, suggesting that they are useful as indicators of age-related qualitative changes. It is generally known that in skeletal muscles, brightness increases and muscle function decreases with age due to degeneration of muscle tissue and an increase in non-contractile tissues such as fat and connective tissue within the muscle tissue, and this suggests that the same may be true for facial muscles.

[0047] The results of the above experiment demonstrated a correlation between apparent sagging and various structural elements, confirming that sagging is not caused by a single factor, but rather by the overlapping of multiple structural changes in the dermis, fat layer, and muscle layer. By quantitatively acquiring structural information of each layer related to sagging and evaluating its condition, it is expected that this will lead to the development of individualized treatment indicators optimized for each person's structural characteristics and aging stage.

[0048] <Factor of sagging> Based on the above experimental results, the sagging diagnosis unit 20 diagnoses skin sagging as described below. The acquisition unit 30 of the sagging diagnosis unit 20 acquires information on the fat layer of the skin as state information. The acquisition unit 30 acquires, for example, at least one image of the upper cheek, lower cheek, side of the cheek, or submandibular area taken by an ultrasonic diagnostic apparatus as information on the fat layer. Images of the upper cheek, lower cheek, side of the cheek, and submandibular area acquired by the ultrasonic diagnostic apparatus are included in the "information on the fat layer" because they include information indicating the thickness and brightness (echo intensity) of the subcutaneous fat layer.

[0049] Then, when the acquired information on the fat layer satisfies a predetermined condition, the diagnosis unit 40 diagnoses the tissue that causes skin sagging as fat. For example, when the thickness or brightness of the subcutaneous fat shown in the acquired image satisfies a predetermined condition, the diagnosis unit 40 diagnoses the tissue that causes skin sagging as fat. Specifically, for example, when the thickness of the subcutaneous fat shown in the acquired image is equal to or greater than a predetermined thickness, the diagnosis unit 40 diagnoses the tissue that causes skin sagging as fat. This is because the thicker the subcutaneous fat, that is, the larger the amount of fat, the easier it is for gravitational sagging to occur and the more likely it is to be a cause of sagging.

[0050] Further, for example, when the brightness of the subcutaneous fat shown in the acquired image is equal to or greater than a predetermined brightness, the diagnosis unit 40 diagnoses the tissue that causes skin sagging as fat. It has been confirmed that the brightness of subcutaneous fat increases with aging and is an index reflecting the progress of fibrosis in adipose tissue. When the elasticity of the fat layer decreases due to fibrosis, the support against gravity weakens, which can contribute to sagging. Therefore, by using brightness information, the qualitative change of the fat layer can be estimated, and sagging involving the fat layer can be evaluated more appropriately.

[0051] According to such an aspect, it is possible to grasp that the factor of skin sagging is fat. In addition, by quantitatively evaluating the increase in brightness reflecting the thickness of subcutaneous fat and the degree of fibrosis, the state of the fat layer contributing to sagging in appearance can be specified with high accuracy. As a result, when the amount of fat is large or fibrosis has progressed, sagging mainly caused by the fat layer can be appropriately detected, and a treatment suitable for the factor (for example, subcutaneous heating by RF or treatment on the fat layer) can be selected.

[0052] Note that the information regarding the fat layer is not limited to the above information. The acquisition unit 30 may acquire BMI (Body Mass Index) or body fat percentage as information regarding the fat layer. In that case, if the acquired BMI or body fat percentage meets predetermined conditions, the diagnostic unit 40 diagnoses the tissue that causes skin sagging as fat. Since higher BMI and body fat percentage tend to indicate a larger amount of subcutaneous fat in the face, these are included in the "information regarding the fat layer." More specifically, for example, if the acquired BMI or body fat percentage is above a predetermined value, the diagnostic unit 40 diagnoses the tissue that causes skin sagging as fat. This is because higher BMI and body fat percentage increase the amount of subcutaneous fat in the face, making it easier for gravity to cause ptosis and thus more likely to cause sagging.

[0053] Furthermore, values ​​that change according to the thickness, brightness, BMI, or body fat percentage of the fat layer may also be used as information about the fat layer. "Values ​​that change according to" here include normalized values, score values, ratio values, composite values, or estimated values ​​calculated based on the thickness, brightness, BMI, or body fat percentage of the fat layer. Additionally, the thickness of superficial or deep fat in the face obtained from CT or MRI, or the width of the face (especially the width of the face below the nasal alae) obtained from facial images, may also be used as information about the fat layer.

[0054] In those cases, the diagnostic unit 40 diagnoses fat as the tissue causing skin sagging if, for example, the thickness of the superficial and deep fat on the face is greater than a predetermined thickness. The diagnostic unit 40 also diagnoses fat as the tissue causing skin sagging if the width of the face is greater than a predetermined width. This is because the thicker the fat or the wider the face, the greater the amount of subcutaneous fat on the face, making it more susceptible to gravity-induced ptosis and thus more likely to cause sagging.

[0055] This approach allows us to understand that fat is a contributing factor to skin sagging. Furthermore, by using other information about the fat layer, such as BMI or body fat percentage, it is possible to estimate the state of the fat layer even when ultrasound images cannot be obtained, and to easily and reliably grasp the trends in the thickness and volume of the fat layer. In addition, by combining local information such as ultrasound images with whole-body indicators such as BMI or body fat percentage, the accuracy of fat layer evaluation is improved, and sagging caused primarily by fat can be detected more reliably. As a result, it becomes possible to optimize treatment settings (e.g., adjustment of the heating depth by RF) for each individual, corresponding to the fat layer.

[0056] <Muscles are a factor> The acquisition unit 30 also acquires information about the muscle layer of the skin as state information. The acquisition unit 30 acquires, for example, an image of at least one of the muscles of the head taken by an ultrasound diagnostic device as information about the muscle layer. Images of the muscles of the head taken by an ultrasound diagnostic device are included in the "muscle layer information" because they include information indicating the thickness of the muscle layer. The muscles of the head include muscles located in the facial region, and the muscles located in the facial region include, for example, the zygomaticus major (facial expression muscle) or the masseter (masticatory muscle).

[0057] The diagnostic unit 40 then diagnoses the tissue causing skin sagging as muscle if the acquired information on the muscle layer meets predetermined conditions. For example, the diagnostic unit 40 diagnoses the tissue causing skin sagging as muscle if the thickness, brightness, or hardness of the muscles of the head shown in the acquired image meets predetermined conditions.

[0058] In detail, the diagnostic unit 40 diagnoses the tissue causing skin sagging as muscle if, for example, the thickness of the head muscles shown in the acquired image is less than a predetermined thickness. This is because the thinner the head muscles (for example, the zygomaticus major or masseter muscle), the weaker the lifting force of the cheeks, making it more likely to cause muscle sagging.

[0059] Furthermore, the diagnostic unit 40 diagnoses the tissue causing skin sagging as muscle if, for example, the brightness of the head muscles shown in the acquired image is above a predetermined value. High brightness of the head muscles may indicate that fibrosis, fat infiltration, or increased connective tissue are progressing within the muscle, suggesting a decrease in the muscle's supporting or contractile function. Supporting capacity refers to the force that holds the skin and fat in place. Therefore, it can be determined that the muscle layer is a contributing factor to skin sagging.

[0060] Furthermore, the diagnostic unit 40 diagnoses muscle as the tissue causing skin sagging if, for example, the stiffness of the head muscles shown in the acquired image is lower or higher than a predetermined range. This is because if the muscle stiffness is outside the predetermined range (either excessively low or excessively high), it indicates that the normal support and mobility function of the muscle is impaired. Muscle stiffness is an indicator that reflects the amount of muscle fibers, connective tissue, and muscle tension.

[0061] If muscle stiffness is below a specified range, it may indicate muscle atrophy or decreased support capacity, leading to reduced lifting power of the skin and fat, and making sagging more likely. On the other hand, if muscle stiffness is above a specified range, it may indicate decreased mobility due to muscle fibrosis or hypertonicity, leading to changes in the shape of the face line or drooping of the skin. Therefore, if muscle stiffness is outside the specified range, it can be determined that the muscle layer is a contributing factor to skin sagging.

[0062] This approach allows us to understand that muscle is the cause of skin sagging. Furthermore, by quantitatively evaluating the thickness, brightness, or hardness of the muscle layer, we can accurately identify the condition of the muscle layer, such as decreased muscle mass, decreased support capacity, decreased contractile function, or decreased mobility. As a result, we can detect sagging primarily caused by muscle and optimize treatment settings suitable for the muscle layer, such as adjusting the output intensity or stimulation site of EMS.

[0063] Note that the information on the muscle layer is not limited to the above information. The acquisition unit 30 may acquire the amount of muscle mass in the body, the amount of change in muscle thickness during muscle movement, the amount of change in muscle length, the muscle contraction speed, or the muscle contraction time as information on the muscle layer. In that case, the diagnostic unit 40 diagnoses the tissue that is a factor in skin sagging as muscle if the acquired muscle mass, amount of change, contraction speed, or contraction time meets predetermined conditions. The total muscle mass, amount of change in muscle, contraction speed, or contraction time are indicators of the total muscle mass and function of the body, and have a certain correlation with the quantitative or functional state of the facial muscles, so these are included in the "information on the muscle layer".

[0064] Furthermore, values ​​that change according to the thickness, mass, or contraction speed of the muscle layer may also be considered as information about the muscle layer. "Values ​​that change according to" here include normalized values, score values, ratio values, composite values, or estimated values ​​calculated based on the thickness, mass, or contraction speed of the muscle layer. Additionally, muscle thickness measured by CT / MRI, muscle stiffness / elasticity measured by elastography, or muscle fatigue measured by electromyography may also be considered as information about the muscle layer. All of these values ​​are indicators that reflect the quantitative state (muscle thickness / mass) or functional state (contraction ability, stiffness, fatigue) of the muscle layer and are included in "information about the muscle layer" that indicates the state of the muscle layer.

[0065] In detail, the diagnostic unit 40 diagnoses muscle as the tissue causing sagging if, for example, the acquired muscle mass is less than a predetermined amount. This is because, generally, when the total muscle mass of the body is low, the facial muscles also tend to atrophy, reducing the lifting power of the cheeks and making it more likely to cause sagging. Furthermore, the diagnostic unit 40 diagnoses muscle as the tissue causing sagging if, for example, the amount of change in muscle thickness or muscle length during exercise of the acquired muscle is less than a predetermined amount, the muscle contraction speed is slower than a predetermined speed, or the muscle contraction time is longer than a predetermined time. This is because a decrease in the amount of change in muscle thickness or muscle length, a decrease in contraction speed, and a prolongation of contraction time are indicators that reflect decreased muscle strength, muscle atrophy, or decreased neuromuscular function, and can be used to estimate a decrease in the supporting capacity of the muscles.

[0066] Furthermore, the diagnostic unit 40 may diagnose muscle as the tissue causing sagging of the cheeks if, for example, the muscle thickness measured by CT / MRI is thinner than a predetermined thickness, the muscle stiffness / elasticity measured by elastography is below a predetermined value indicating a decrease in muscle support capacity or tension, or the degree of muscle fatigue measured by electromyography is greater than a predetermined value. Since all of these indicators reflect a quantitative decrease in muscle, a decrease in mechanical support capacity, or a state of functional fatigue, it can be determined that the cause of sagging lies in the muscles.

[0067] This configuration allows for the identification of muscle as the cause of skin sagging. Furthermore, even in situations where acquiring ultrasound images is difficult, the condition of the head muscles can be estimated using alternative information based on body composition, enabling a highly accurate determination of whether muscle is the cause of skin sagging. Additionally, if the muscle layer is determined to be the cause, treatment control can be optimized to suit the muscle layer, such as optimizing the EMS output intensity, stimulation frequency, and treatment area, thereby realizing personalized treatment tailored to each individual's sagging cause.

[0068] <Dermis and Fat are Factors> The acquisition unit 30 also acquires information about the dermis layer and the fat layer of the skin as state information. The acquisition unit 30 acquires, for example, the values ​​of R2, R5, or R7 in a viscoelasticity measurement method using Cutometer (registered trademark) manufactured by Courage + Khazaka as information about the dermis layer. The values ​​of R2 (total elasticity of the dermis), R5 (pure elasticity of the dermis), or R7 (the ability of the skin to recover after deformation) all represent the elasticity of the dermis layer and are therefore included in the "information about the dermis layer".

[0069] Furthermore, the acquisition unit 30 acquires the above-mentioned fat layer information, that is, for example, an image of at least one location from the upper cheek, lower cheek, side of the cheek, or under the chin taken by an ultrasound diagnostic device, BMI, or body fat percentage as state information.

[0070] The diagnostic unit 40 then diagnoses the tissues that cause skin sagging as the dermis and fat if the acquired information on the dermis and fat layers meets predetermined conditions. For example, the diagnostic unit 40 diagnoses the tissues that cause skin sagging as the dermis and fat if the values ​​of R2, R5, or R7 are less than predetermined values ​​and the thickness of the subcutaneous fat shown in the image is greater than or equal to a predetermined thickness. This is because the smaller the values ​​of R2, R5, or R7, i.e., the less elasticity of the dermis, the more likely gravity-induced sagging is to occur and the more likely it is to cause dermal sagging. Also, the thicker the subcutaneous fat, i.e., the larger the amount of fat, the more likely gravity-induced sagging is to occur and the more likely it is to cause fat sagging.

[0071] Furthermore, the diagnostic unit 40 also diagnoses the tissues causing skin sagging as the dermis and fat if the values ​​of R2, R5, or R7 are less than predetermined values, and the brightness of the subcutaneous fat shown in the image is above a predetermined brightness, or if the BMI or body fat percentage is above a predetermined value.

[0072] Furthermore, the information on the dermis layer is not limited to the above information. The acquisition unit 30 may acquire AGEs (Advanced Glycation End Products), pore area, number of fine wrinkles, or size of nasolabial folds as information on the dermis layer. In that case, the diagnostic unit 40 will diagnose the tissues that cause skin sagging as the dermis and fat if, for example, the AGEs, pore area, number of fine wrinkles, or size of nasolabial folds are above a predetermined value, and the thickness of the subcutaneous fat shown in the above image is above a predetermined thickness. This is because the larger the values ​​for AGEs, pore area, number of fine wrinkles, or size of nasolabial folds, the more likely the dermis is to cause sagging.

[0073] Furthermore, values ​​that change in accordance with numerical values ​​of AGEs, pore area, number of fine wrinkles, or size of nasolabial folds may also be considered as information about the dermis. Here, "values ​​that change in accordance with" includes normalized values, score values, ratio values, composite values, or estimated values ​​calculated based on numerical values ​​of AGEs, pore area, number of fine wrinkles, or size of nasolabial folds. In addition, physical property values ​​against mechanical stress such as suction, pressure, and twisting may be considered as information about the dermis, or dermal thickness, collagen density, or age band measured by ultrasound diagnostic equipment, CT, or MRI may be considered as information about the dermis. All of these are indicators that directly or indirectly evaluate the dermal structure and are included in the information about the dermis.

[0074] As mentioned above, various types of information can be used for the dermis and adipose tissue, but any combination of this information is acceptable as long as it is effective in diagnosing the causes of sagging. Since the dermis and adipose tissue contribute to sagging through different physiological mechanisms, the information representing each can be evaluated independently or complementaryly. Therefore, by arbitrarily combining the obtainable information from the dermis and adipose tissue, the causes of sagging can be diagnosed flexibly and with high accuracy.

[0075] In this configuration, by evaluating both the decrease in elasticity of the dermis and the increase or fibrosis of the fat layer, it is possible to accurately grasp that the factors causing skin sagging are the dermis and fat, that is, the multifactorial nature of sagging. Therefore, it becomes possible to accurately identify sagging caused by combined factors of the dermis and fat, and to select the optimal treatment (RF for the dermis, heating / suction for fat, etc.) for each area.

[0076] <Dermis and Muscle Factors> The acquisition unit 30 also acquires information about the dermis layer and the muscle layer of the skin as state information. The acquisition unit 30 acquires, for example, the values ​​of R2, R5, or R7 mentioned above as information about the dermis layer. The acquisition unit 30 also acquires the information about the muscle layer mentioned above, i.e., for example, images of the zygomaticus major or masseter muscle taken by an ultrasound diagnostic device, the muscle mass of the body, or the reaction speed of the muscles as state information.

[0077] The diagnostic unit 40 then diagnoses the tissues causing skin sagging as the dermis and muscle if the acquired information on the dermis and muscle layers meets predetermined conditions. For example, the diagnostic unit 40 diagnoses the tissues causing skin sagging as the dermis and muscle if the values ​​of R2, R5, or R7 are less than predetermined values ​​and the muscles of the head shown in the image are less than predetermined thickness. This is because the smaller the values ​​of R2, R5, or R7, i.e., the less elasticity the dermis has, the more likely gravity-induced sagging is to occur, making it more likely to be a cause of dermal sagging. Also, the thinner the muscles of the head (for example, the zygomaticus major or masseter muscle), the less the lifting force of the cheeks is reduced, making it more likely to be a cause of muscle sagging.

[0078] The information on the dermis layer may also include AGEs, pore area, number of fine wrinkles, or size of nasolabial folds, as described above. In that case, the diagnostic unit 40 will diagnose the tissues causing skin sagging as the dermis and muscles if, for example, the AGEs, pore area, number of fine wrinkles, or size of nasolabial folds are above a predetermined value, and the thickness of the scalp muscles shown in the image is less than a predetermined thickness.

[0079] Furthermore, information about the dermis layer may include values ​​that change depending on the numerical values ​​of AGEs, pore area, number of fine wrinkles, or size of nasolabial folds, physical property values ​​against mechanical stress such as suction, pressure, and twisting, and dermal thickness, collagen density, or age bands measured by ultrasound, CT, or MRI. In addition, information about the muscle layer may include muscle thickness, muscle mass, or muscle contraction speed, values ​​that change accordingly, muscle thickness measured by CT or MRI, muscle stiffness and elasticity measured by elastography, or muscle fatigue level measured by electromyography.

[0080] Thus, any combination of information from the dermis and muscle layer is acceptable, as long as it is effective in diagnosing the causes of sagging. Since the dermis and muscle layer contribute to sagging through different physiological mechanisms, the information representing each can be evaluated independently or complementaryly. Therefore, by arbitrarily combining the obtainable information from the dermis and muscle layer, the causes of sagging can be diagnosed flexibly and with high accuracy.

[0081] This approach allows us to understand that the factors contributing to skin sagging are the dermis and muscles. In other words, it is possible to simultaneously detect deterioration in both the dermal and muscular layers, enabling highly accurate evaluation of the multifactorial nature of sagging. When decreased dermal elasticity and decreased support from facial muscles coincide, the visible sagging becomes more pronounced. This diagnosis can identify these combined factors, allowing for the optimization of the combination of dermal treatments (RF, electroporation, etc.) and muscle treatments (EMS, thermal stimulation, etc.). As a result, it is possible to provide individually optimized treatments tailored to each user's internal structure, thereby improving the effectiveness of sagging improvement.

[0082] <Fat and Muscle Factors> The acquisition unit 30 also acquires information on the fat layer of the skin and information on the muscle layer of the skin as state information. The acquisition unit 30 acquires the above-mentioned fat layer information, i.e., images of at least one location from the upper cheek, lower cheek, side of the cheek, or under the chin taken by an ultrasound diagnostic device, BMI, or body fat percentage as state information. The acquisition unit 30 also acquires the above-mentioned muscle layer information, i.e., images of the muscles of the head (e.g., zygomaticus major or masseter muscle) taken by an ultrasound diagnostic device, body muscle mass, muscle layer thickness, muscle mass, or muscle contraction speed as state information.

[0083] The diagnostic unit 40 then diagnoses the tissues causing skin sagging as fat and muscle if the acquired information on the fat layer and muscle layer meets predetermined conditions. For example, if the thickness of the subcutaneous fat shown in the above image is greater than or equal to a predetermined thickness, and the thickness of the muscles of the head shown in the above image is less than a predetermined thickness, the diagnostic unit 40 diagnoses the tissues causing skin sagging as fat and muscle.

[0084] Furthermore, the diagnostic unit 40 diagnoses the tissues contributing to skin sagging as fat and muscle when, for example, the acquired BMI or body fat percentage is above a predetermined value, and the acquired muscle mass is less than a predetermined amount, the amount of muscle change is less than a predetermined amount, the contraction speed is slower than a predetermined speed, or the contraction time is longer than a predetermined time. Thus, any combination of information from the fat layer and the muscle layer is acceptable, as long as it is effective in diagnosing the causes of sagging. Since the fat layer and the muscle layer contribute to sagging through different physiological mechanisms, the information representing each can be evaluated independently or complementarily. Therefore, by arbitrarily combining the acquired information from the fat layer and the muscle layer, the causes of sagging can be diagnosed flexibly and with high accuracy.

[0085] This configuration allows us to understand that the causes of skin sagging are fat and muscle. In other words, it is possible to simultaneously understand sagging factors with different mechanisms: quantitative changes in the fat layer (increased fat thickness or increased fat volume) and functional changes in the muscle layer (decreased support or changes in contour due to increased muscle mass). In particular, when there is a large amount of fat and weak muscle support, the apparent sagging is exaggerated synergistically, but this configuration allows us to accurately identify these complex factors. As a result, treatments for the fat layer (RF, heating, fat layer stimulation, etc.) and treatments for the muscle layer (EMS, muscle stimulation, etc.) can be optimized individually or in combination, enabling highly personalized treatments tailored to the user's skin condition and maximizing the effect of improving sagging.

[0086] <Dermis, Fat, and Muscle are the Factors> The acquisition unit 30 also acquires information on the dermis layer, fat layer, and muscle layer of the skin as condition information. Any combination of information on the dermis, fat layer, and muscle layer that is acquired is acceptable, as long as it is effective in diagnosing the factors causing sagging. The diagnosis unit 40 then diagnoses the tissues that cause skin sagging as the dermis, fat, and muscle if the acquired information on the dermis, fat layer, and muscle layer of the skin meets predetermined conditions.

[0087] In detail, the diagnostic unit 40 diagnoses the tissues causing skin sagging as dermis, fat, and muscle if, for example, the values ​​of R2, R5, or R7 of Cutometer® are less than predetermined values, the thickness of subcutaneous fat shown in images of at least one location among the upper cheek, lower cheek, side cheek, or submandibular region taken by the ultrasound diagnostic device is greater than or equal to a predetermined thickness, and the thickness of the head muscles (e.g., zygomaticus major or masseter muscle) shown in images of the head muscles taken by the ultrasound diagnostic device is less than a predetermined thickness.

[0088] Furthermore, the information from the dermis, adipose layer, and muscle layer used for diagnosis may be any of the above-mentioned information, and any combination thereof is acceptable as long as it is effective in diagnosing the causes of sagging. Since the dermis, adipose layer, and muscle layer contribute to sagging through different physiological mechanisms, the information representing each can be evaluated independently or complementaryly. Therefore, by arbitrarily combining the obtainable information from the dermis, adipose layer, and muscle layer, the causes of sagging can be diagnosed flexibly and with high accuracy.

[0089] This configuration allows for the identification of factors contributing to skin sagging as being related to the dermis, fat, and muscle. Specifically, it enables simultaneous evaluation of sagging factors with different mechanisms, such as decreased elasticity in the dermis, increased volume and fibrosis in the fat layer, and decreased support capacity in the muscle layer. This allows for more accurate identification of the contribution of the causative structures of sagging (dermis, fat, and muscle) compared to conventional methods that estimate sagging solely from skin surface information. Therefore, treatment settings can be automatically adjusted by individually or in combination optimizing dermal treatments (RF, electroporation, etc.), fat treatments (subcutaneous heating, ultrasound stimulation, etc.), and muscle treatments (EMS, muscle stimulation, etc.), enabling personalized treatments tailored to each user's condition. As a result, the immediate and sustained effectiveness of sagging improvement is enhanced, maximizing the effects of the cosmetic device.

[0090] <Impedance and Phase> The details of the state information are explained below. The inside of the skin is made up of multiple tissues (also called body tissues). These multiple tissues include the epidermis of the skin and tissues that lie deeper than the epidermis. Tissues that lie deeper than the epidermis include, for example, the dermis, subcutaneous tissue, SMAS fascia, facial muscles, and deep muscles. The acquisition unit 30 acquires at least one of the impedance or phase measured by passing an alternating current through these multiple tissues as state information.

[0091] The acquisition unit 30 acquires the impedance of multiple tissues forming the skin as state information by bringing the electrical characteristic measurement unit 31 into contact with the skin and performing measurements. Similarly, the acquisition unit 30 acquires the phase measured when an alternating current is passed through multiple tissues forming the skin as state information by performing measurements. It is also possible for the acquisition unit 30 to acquire at least one of the real part and imaginary part that can be calculated from the impedance and phase as state information, and to input this state information into a calculation formula to calculate and acquire new state information.

[0092] The acquired impedance and phase vary depending on the compositional state of the multiple tissues that make up the inside of the skin. The compositional state refers to, for example, the thickness, water content, water distribution, or cell density of each tissue layer. These compositional states correlate with factors of skin sagging, and this correlation is represented by the reference information described above. The diagnostic unit 40 diagnoses the factors of skin sagging based on the reference information and the compositional states of the multiple tissues indicated by the acquired state information. Specifically, the diagnostic unit 40 diagnoses the factors of skin sagging based on the compositional state indicated by the impedance, the compositional state indicated by the phase, or the compositional state indicated by both. In this embodiment, the user can understand the factors of sagging caused by the influence of the deeper layers of the skin.

[0093] Figure 23 is a block diagram showing an example of the electrical configuration of the electrical characteristics measurement unit 31. The electrical characteristics measurement unit 31 is an example of a bioimpedance measuring device and comprises a first electrode 311, a second electrode 312, and a measuring unit 313. The measuring unit 313 applies power to the first electrode 311 and the second electrode 312 to measure the bioimpedance of the face or local area where the first electrode 311 and the second electrode 312 are in contact.

[0094] The electrical characteristics measurement unit 31 measures bioimpedance by passing currents of two or more different frequencies through them. The two or more frequencies referred to here belong to one or more of the frequency bands of several kHz, several tens of kHz, and several hundred kHz, and may include multiple frequencies belonging to the same kHz band. For example, the two or more frequencies could be 50 kHz (several tens of kHz band), 100 kHz (several hundred kHz band), and 145 kHz (several hundred kHz band).

[0095] This configuration allows for the measurement of a wider range of impedance characteristics in the depth direction of the skin compared to the case of a single frequency. Bioimpedance has the characteristic that the path through which current flows changes with frequency. At low frequencies (several kHz band), the resistance components of the stratum corneum and epidermis become dominant, while at high frequencies (tens to hundreds of kHz band), the influence of capacitive reactance of cell membranes decreases, making it easier for current to penetrate deeper into the extracellular fluid and dermis. Therefore, by using multiple different frequencies, the electrical characteristics from the superficial to the deep layers of the skin can be separated and evaluated, resulting in a greater amount of information in the depth direction compared to measurements using a single frequency.

[0096] Furthermore, by using multiple signals with different frequency bands, error factors specific to each frequency band (e.g., the effect of the amount of coating agent in the low frequency band, the effect of noise in the high frequency band, etc.) can be mutually compensated for. This reduces bias dependent on a specific frequency compared to using a single frequency, allowing for more stable bioimpedance measurements. As a result, more robust measurements can be achieved that are less affected by differences in the measurement environment and the subject's condition compared to using a single frequency.

[0097] <Pressure> The acquisition unit 30 also acquires the pressure generated when force is applied to the skin as state information. The acquisition unit 30 also acquires the pressure measured when the pressure measuring unit 32 is in contact with the skin as state information. The state of skin elasticity is correlated with the factors of skin sagging, and this correlation is represented by the reference information described above. The diagnostic unit 40 diagnoses the factors of sagging based on the reference information and the state of skin elasticity indicated by the acquired state information. Skin elasticity is affected by components such as collagen, elastin, and hyaluronic acid. In this configuration, the user can understand the factors of sagging caused by a deficiency of these components that affect skin elasticity.

[0098] The pressure measuring unit 32 includes, for example, a "two-stage" pressure sensor. Figure 24 is a block diagram of a two-stage measuring device. Figure 25 is an example of a perspective view of a two-stage measuring device. The pressure measuring unit 32 is an example of a measuring device for measuring the viscoelasticity of skin. The pressure measuring unit 32 includes a first sensor 321, a second sensor 322, a measuring unit 323, a main body 324, and a waterproof unit 325.

[0099] Both the first sensor 321 and the second sensor 322 measure skin pressure. The measuring unit 323 measures the viscoelasticity of the skin based on the measurement results of the first sensor 321 and the measurement results of the second sensor 322. With this configuration, a mechanical movable mechanism that automatically presses in to measure the amount of indentation is not required, so the viscoelasticity measuring device can be made smaller compared to the case in which a movable mechanism is included.

[0100] The details of the method for measuring the viscoelasticity of the skin are described below. The measuring unit 323 measures the viscoelasticity of the skin based on the time change of the measurement result of the first sensor 321 and the time change of the measurement result of the second sensor 322. Here, "time change" means the amount of increase in the sensor value during a predetermined period after the start of application, i.e., the rate of change (slope) per unit time. By measuring viscoelasticity based on the time change of the measurement result of the first sensor 321 and the time change of the measurement result of the second sensor 322, it is possible to directly obtain the dynamic response of the skin when it deforms, without depending on the absolute pressure value at the time of application.

[0101] Skin is a viscoelastic material, and its response changes more significantly depending on the "speed" and "how the force rises" than on the applied force itself. Therefore, evaluating the change over time allows for a more accurate capture of the material's properties. Furthermore, since the change over time strongly reflects the viscous behavior in the deeper layers of the skin, it is less affected by the surface layer and allows for stable evaluation of viscoelasticity even when there are differences in location or environmental conditions.

[0102] Furthermore, the measurement unit 323 measures viscoelasticity based on the time changes in the measurement results of the first sensor 321 and the second sensor 322 over the same period. By comparing the time changes of both sensors over the same period in this way, it is possible to match the effects caused by temporal fluctuations such as the pressing speed and hand tremor at that point in time. As a result, error components dependent on the pressing motion are reduced, and the responses of both sensors can be compared fairly to calculate viscoelasticity more accurately. This improves the reproducibility and stability of the measurement.

[0103] More specifically, the measuring unit 323 measures viscoelasticity using a period during which the measurement result of the second sensor 322 changes within a predetermined range. The predetermined range is, for example, the range in which the pressing speed of the second sensor 322 is stable, that is, the range in which the sensor value increases at a nearly constant slope. During the pressing operation, the slope is unstable and noise increases in sections where the force changes rapidly, so the viscoelastic value also becomes unstable. On the other hand, a period in which the value changes at a constant slope means that the pressing speed is stable, and disturbances due to the time change of force are minimized during that period. Therefore, by using a period in which the measurement result of the second sensor 322 changes stably within a predetermined range, the pressing speed becomes constant, and errors caused by fluctuations in speed can be suppressed. As a result, the time changes of the first sensor 321 and the second sensor 322 can be accurately compared, and viscoelastic evaluation that is less affected by the pressing operation becomes possible. This improves the reproducibility and reliability of the measurement.

[0104] Then, as shown in Equation 1, the measurement unit 323 measures viscoelasticity based on the ratio of the slope of the measurement result of the first sensor 321 and the slope of the measurement result of the second sensor 322 during the same period. By using the ratio of the slopes of the first sensor 321 and the second sensor 322 in this way, the pressure speed component common to both sensors is canceled out, and speed-dependent errors can be eliminated. As a result, only the pure viscoelastic component derived from the viscosity and elasticity of the deep layers of the skin can be extracted, enabling highly accurate measurements that are not affected by individual differences in pressure application. This significantly improves the stability and reproducibility of viscoelasticity evaluation.

[0105] <Diagnosis of Each Area> The skin diagnosed by the sagging diagnosis unit 20 is, for example, the skin of the face. In this case, the acquisition unit 30 may acquire information indicating the internal condition of the skin for each part of the face as condition information. Parts of the face include the cheeks, mouth area, eye area, or jawline. The diagnosis unit 40 then diagnoses the cause of skin sagging using, for example, different reference information for each part of the face (information representing the correlation between the condition information of the relevant part and the cause of sagging). Since the structure differs for each part of the face, such as dermal thickness, subcutaneous fat volume, and muscle attachment location, using reference information specific to each part is effective in improving diagnostic accuracy. With this configuration, the user can understand the cause of skin sagging for each part of the face.

[0106] <Beauty Device> As described above, the beauty device 10 shown in Figure 1 comprises a sagging diagnosis unit 20, a display unit 11, and a treatment unit 12. The display unit 11 displays the diagnosis results of the sagging factors by the sagging diagnosis unit 20. The treatment unit 12 performs a treatment that applies stimulation to the face to improve or suppress skin sagging. Improving sagging means reducing or eliminating sagging. Suppressing sagging means preventing the progression of sagging.

[0107] The treatment unit 12 has an operating part such as a button or dial switch. The intensity, type, or duration of stimulation from the treatment unit 12 can be changed by the user operating these operating parts. The types of stimulation include, for example, stimulation by RF electrical signals and stimulation by EMS electrical signals. The former mainly improves and suppresses dermal sagging and fat sagging by promoting collagen contraction and production. The latter mainly improves and suppresses muscle sagging by improving muscle strength. Furthermore, even if the causes of sagging differ from area to area, the user can manually adjust the type, intensity, and duration of stimulation while referring to the diagnostic results to enable more appropriate treatment. With this configuration, the user can perform treatment that is appropriate to the cause of skin sagging by operating the device to apply stimulation of intensity, type, or duration according to the displayed diagnostic results of the causes of sagging.

[0108] Furthermore, the treatment unit 12 may perform the treatment with an intensity, type, or duration corresponding to the diagnosis of the cause of sagging by the sagging diagnosis unit 20, even without user intervention. For example, the treatment unit 12 uses a stimulation table that associates the diagnosis results with the intensity or type of stimulation to determine the intensity, type, or duration of stimulation according to the diagnosis results. The diagnosis results include, for example, the cause of sagging or the area where sagging is occurring. In this configuration, the intensity, type, or duration of stimulation is automatically adjusted according to the diagnosis of the cause of sagging, so the user can perform treatment appropriate to the cause of sagging without being aware of the diagnosis results.

[0109] Furthermore, the sagging diagnosis unit 20 may be configured to diagnose the causes of sagging even during treatment by the treatment unit 12. Specifically, for example, by placing the sensor of the acquisition unit 30 and the electrode of the treatment unit 12 on the same surface, it is possible to acquire state information even during treatment, and the diagnosis unit 40 performs a diagnosis based on the acquired state information. In this case, the treatment unit 12 performs the treatment with an intensity, type, or duration corresponding to the diagnosis results during the treatment. For example, the treatment unit 12 increases the intensity of stimulation or increases the duration of stimulation as the degree of improvement or suppression of the causes of sagging during treatment decreases. With this configuration, the user can standardize the effects of the treatment.

[0110] Furthermore, if diagnosis is possible during the procedure as described above, the beauty device may also be equipped with a notification unit. Figure 26 shows another example of the overall configuration of the beauty device. The beauty device 10a shown in Figure 26 is equipped with a notification unit 15 in addition to the parts shown in Figure 1. The notification unit 15 provides notification according to the degree of improvement or suppression of the cause of sagging diagnosed during the procedure. The notification unit 15, for example, has a speaker and notifies the user by outputting a predetermined sound when the degree of improvement or suppression of the cause of sagging diagnosed during the procedure reaches a predetermined level.

[0111] The notification method is not limited to sound. The notification unit 15 may, for example, light up or flash an LED (Light Emitting Diode), or vibrate a vibrator. The notification unit 15 may also display the diagnostic result of the degree of improvement or suppression on the display unit 11. Furthermore, the notification unit 15 may, for example, provide notifications in stages each time the degree of improvement or suppression progresses. With such a configuration, the user can feel the effects of the treatment.

[0112] <Information Processing System> The beauty device 10 may be linked with an external device to constitute an information processing system. Figure 27 is a diagram showing an example of the overall configuration of the information processing system. The beauty support system 1 shown in Figure 27 is an information processing system comprising a beauty device 10b, a communication line 2, an analysis server 50, and a user terminal 60. In addition to the parts of the beauty device 10 shown in Figure 1, the beauty device 10b includes a communication unit 16.

[0113] The communication unit 16 is composed of a communication module. The communication module may be a wireless communication module compliant with standards such as IEEE 802.11a / b / g / n / ac / ax, LTE, 5G, 6G, etc., or a wired communication module compliant with standards such as IEEE 802.3. The communication unit 16 is configured to transmit various electrical signals from the beauty device 10 to external components. The communication unit 16 is also configured to receive various electrical signals from external components to the beauty device 10. More preferably, the communication unit 16 has a network communication function, thereby enabling the communication of various information between the beauty device 10 and external devices via the communication line 2.

[0114] Communication line 2 is not particularly limited, but for example, it is composed of the Internet network. Communication line 2 may also include a local area network, a mobile communication network, and a VPN (Virtual Private Network), etc. Communication line 2 mediates the exchange of data between devices connected to its own line. In the example in Figure 27, the analysis server 50 is connected to communication line 2 by wire, and the beauty equipment 10 and user terminal 60 are connected wirelessly. Note that the connection of each device to communication line 2 may be wired or wireless.

[0115] The hardware configuration according to the embodiment will be described below. Figure 28 is a diagram showing an example of the hardware configuration of the analysis server 50. The analysis server 50 comprises a control unit 501, a storage unit 502, a communication unit 503, and a bus 504. The bus 504 electrically connects each part of the analysis server 50.

[0116] (Control Unit 501) The control unit 501 has at least one processor. The at least one processor may consist of, for example, a central processing unit (CPU), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), one or more Integrated Circuits, one or more Discrete Circuits, and a combination thereof.

[0117] The control unit 501 is a computer that realizes various functions related to the beauty support system 1 by reading predetermined programs stored in the memory unit 502. In other words, information processing by software stored in the memory unit 502 is concretely realized by the control unit 501, which is an example of hardware, and can be executed as each functional unit included in the control unit 501. Note that the control unit 501 is not limited to being a single unit, and may be implemented with multiple control units 501 for each function, or a combination thereof.

[0118] (Storage Unit 502) The storage unit 502 stores various information as defined above. This can be implemented, for example, as a storage device such as a solid-state drive (SSD) or HDD (Hard Disk Drive) that stores various programs related to the beauty support system 1 executed by the control unit 501, or as memory such as random access memory (RAM) that stores temporarily necessary information (arguments, arrays, etc.) related to program calculations. The storage unit 502 stores various programs and variables related to the beauty support system 1 executed by the control unit 501.

[0119] (Communication Unit 503) The communication unit 503 is composed of a communication module. The communication module may be a wireless communication module compliant with standards such as IEEE 802.11a / b / g / n / ac / ax, LTE, 5G, 6G, etc., or a wired communication module compliant with standards such as IEEE 802.3. The communication unit 503 is configured to transmit various electrical signals from the analysis server 50 to external components. The communication unit 503 is also configured to receive various electrical signals from external components to the analysis server 50. More preferably, the communication unit 503 has a network communication function, thereby enabling the communication of various information between the analysis server 50 and external devices via the communication line 2.

[0120] Figure 29 shows an example of the hardware configuration of a user terminal 60. The user terminal 60 comprises a control unit 601, a storage unit 602, a communication unit 603, an input unit 604, an output unit 605, and a bus 606. The bus 606 electrically connects each part of the user terminal 60. The control unit 601, storage unit 602, and communication unit 603 are similar hardware to the control unit 501, storage unit 502, and communication unit 503 shown in Figure 75, although their specifications and models may differ.

[0121] (Input Unit 604) The input unit 604 has input receiving means such as keys, buttons, touchscreens, and mice, and accepts input from the user. The input unit 604 may also have sound receiving means such as a microphone, and may have a function to collect the user's voice and accept the input of the collected voice.

[0122] (Output Unit 605) The output unit 605 has display means such as a display and sound emission means such as a speaker, and outputs visual information and auditory information. For example, the output unit 605 displays visual information such as a screen, image, icon, text, etc., which is generated in a manner that can be seen by the user, on the display surface of the display. The output unit 605 also outputs audible sound such as speech or synthesized sound from the speaker. The output unit 605 also has imaging means such as a lens and an image sensor, and outputs an electrical signal representing an image formed on the image sensor (for example, an image showing the appearance of skin).

[0123] As described above, the beauty support system 1 is equipped with one or more processors. The one or more processors referred to here are the processors in the analysis server 50, the processors in the user terminal 60, or both of them, and are hereinafter simply referred to as "processors". The processor functions as an example of an acquisition unit that acquires state information acquired by the acquisition unit 30 of the sagging diagnosis device and the diagnosis results of the cause of sagging by the diagnosis unit 40. The processor acquires the state information and diagnosis results from the beauty device 10, for example, via the communication unit 16 and the communication line 2.

[0124] The processor functions as an example of an analysis unit that analyzes the state of the tissues that make up the skin based on acquired state information. The state of the tissue here refers to the state that affects the factors of skin sagging. Specifically, the processor analyzes the amount of collagen, hyaluronic acid, elastin, subcutaneous fat, or facial muscles contained in the tissues that make up the skin, for example, based on the impedance, phase, pressure, and transmitted light characteristics indicated by the acquired state information. The "amount" of collagen, hyaluronic acid, elastin, etc., is analyzed as an index value estimated from the state information, based on the fact that these components affect the electrical, optical, and mechanical properties of the skin.

[0125] For example, the amount of collagen can be analyzed from impedance, phase, and the intensity of transmitted light at a specific wavelength. Similarly, the amount of hyaluronic acid can be analyzed from impedance, phase, and pressure. The amount of elastin can be analyzed from pressure and the intensity of transmitted light at a specific wavelength. The amount of subcutaneous fat can be analyzed from impedance, phase, pressure, and the intensity of transmitted light at a specific wavelength. The amount of facial muscle can be analyzed from impedance and phase.

[0126] The processor functions as an example of an output unit that outputs sagging analysis information representing the diagnostic results of the acquired sagging factors and the analysis results of the tissue condition. The processor outputs the diagnostic results and analysis information to a display means provided by the user terminal 60, for example, to display the information. The output destination for the analysis information and diagnostic results is not limited to this, and may be, for example, a storage means, an email address, or an SNS (Social Networking Service) account. The user can understand the factors of skin sagging from the output diagnostic results and understand the factors of that sagging from the output analysis information. Factors of sagging include, for example, a deficiency of components such as collagen, hyaluronic acid, or elastin, hypertrophy of subcutaneous fat, or deterioration of facial muscles.

[0127] Furthermore, the processor functions as an example of an improvement suggestion unit that presents methods for improving the condition of the tissue indicated by the outputted sagging analysis information. For example, if the cause of sagging is collagen deficiency, the processor suggests a method of applying RF electrical signals using the beauty device 10 as an improvement method. When stimulated with RF electrical signals, collagen contraction and production are promoted, and sagging is improved. Other improvement methods include consuming foods rich in collagen, moderate exercise, and quality sleep. Avoiding lifestyle habits that hinder collagen production (such as smoking, excessive alcohol consumption, or dry skin) is also included as an improvement method.

[0128] Furthermore, if the cause of sagging is deterioration of facial muscles, the processor suggests a method of improvement using the beauty device 10 to apply electrical signals for EMS stimulation. When this stimulation is applied, the muscles contract, increasing their activity, strengthening and growing the muscles, improving their ability to support the skin and fat, and thus improving sagging. Chewing food thoroughly and performing oral exercises are also included as improvement methods. With this configuration, compared to cases where no improvement methods are presented, users can understand the appropriate improvement method according to the cause of their own sagging, making it easier for them to work on improving sagging.

[0129] Furthermore, the processor functions as an example of an analytical unit that analyzes factors that may cause future skin sagging. For example, if fat mass is increasing while muscle mass is decreasing, the processor analyzes that even if sagging is not currently present, a future lack of muscle strength is predicted, and therefore there are factors that will cause sagging. In addition, a decreasing trend in components that suppress sagging (collagen, hyaluronic acid, or elastin, etc.) can also be analyzed as a factor that may cause future sagging.

[0130] The processor then functions as an example of a prevention suggestion unit that presents preventive methods to eliminate the factors that indicate future sagging and prevent future sagging. The methods for preventing sagging are generally the same as the improvement methods described above, and sagging is prevented by eliminating the factors that indicate future sagging in advance. For example, if muscle weakness is predicted, preventive methods such as training the muscles in advance by applying electrical signals for EMS using the beauty device 10, or making an effort to chew food thoroughly and perform oral exercises are presented. In this manner, the user can prevent the occurrence of sagging.

[0131] [Modified Example] In the example shown in Figure 2, the sagging diagnosis unit 20 is equipped with four types of measurement units, and the measurement results from each are used as state information to diagnose the causes of sagging, but it is not limited to this. For example, the acquisition unit 30 acquires the characteristics of electromagnetic waves emitted from the surface of the skin as state information indicating the condition of the skin. Then, the diagnosis unit 40 diagnoses the causes of skin sagging based on the acquired state information. In detail, the diagnosis unit 40 diagnoses the causes of sagging that correlate with the state of the skin's appearance indicated by the acquired state information, based on reference information that shows the correlation between sagging caused by the internal condition of the skin and the external condition of the skin.

[0132] In this case, for example, a diagnostic table created by a human analyzing the correlation between the electromagnetic wave characteristics indicated by the state information acquired for the subject and the measurement results from various measuring devices that indicate the internal state of the skin is used. Alternatively, the reference information may be a learning model generated by learning based on training data that indicates the internal state of the skin, the external state of the skin, and the factors causing skin sagging. With this configuration, reference information can be created more easily than when AI is not used.

[0133] Furthermore, this configuration makes it possible to understand the factors causing sagging based on the internal condition of the skin from its appearance. Also, in the above example, since it is only necessary to acquire the characteristics of electromagnetic waves emitted from the surface of the skin as state information, for example, a facial image taken by the user terminal 60 can be acquired as state information and the factors causing sagging can be diagnosed.

[0134] The configuration shown in Figure 1, etc. (overall configuration and hardware configuration, etc.) is just an example, and other configurations can be used as long as they do not cause inconvenience in implementation. For example, the analysis server 50 may be distributed across two or more devices, or it may be provided in the form of SaaS (Software as a Service) or a cloud computing system. Also, the beauty device 10 (sagging diagnosis unit 20) may perform the processing that the analysis server 50 and user terminal 60 perform, or the analysis server 50 and user terminal 60 may perform the processing that the beauty device 10 (sagging diagnosis unit 20) performs. In short, as long as the necessary information processing is performed throughout the beauty support system 1, the devices that perform that information processing are not limited.

[0135] The output destination for information or data (hereinafter referred to as "information, etc.") may be other devices, displays, storage units (including built-in and external storage units), email addresses, or accounts in other systems. Acquisition of information, etc. includes not only acquiring information, etc. transmitted from other devices, but also acquiring information, etc. generated by the device itself or information, etc. stored by the device itself.

[0136] The embodiments described above included information processing devices such as a beauty device 10 (sagging diagnosis unit 20), an analysis server 50, and a user terminal 60, or an information processing system such as a beauty support system 1 equipped with these information processing devices. However, it may also be a sagging diagnosis method. The sagging diagnosis method comprises operation steps performed by these information processing devices. Furthermore, the embodiments described above may also be programs. Such programs cause a computer to perform the operation steps performed by these information processing devices. The operation steps here include, for example, an acquisition step to acquire condition information indicating the condition of the skin, and a diagnosis step to diagnose the factors causing skin sagging based on the acquired condition information. Other operation steps (analysis steps, output steps, improvement suggestion steps, or prevention suggestion steps, etc.) may also be included.

[0137] Figure 30 shows an example of a diagnostic result. Figure 30 shows the relationship between facial sagging type and the condition of the skin's internal structure in young women (25-32 years old). In the example in Figure 30, three subjects were classified into "fat sagging type," "muscle sagging type," and "dermal sagging type," and their facial features and internal skin data were compared. The three subjects were evaluated by two judges on a 6-point scale from 0 to 5 for sagging scores in three areas—upper cheek, lower cheek, and chin—based on 3D facial data in a standing position. The average of these scores, the perceived sagging score, was similar, indicating that there were no significant differences in appearance. However, the measured internal skin data showed that the characteristics of each sagging type were different.

[0138] "Dermal viscoelasticity R7" is a measure of elasticity, and a higher value indicates better dermal elasticity. A skin viscoelasticity measuring device is used to measure elasticity. In the example in Figure 30, a Cutometer (registered trademark of Courage + Khazaki Electronic GmbH) probe with an aperture diameter of 6 mm was used for measurement. The measurement site can be anywhere on the face, but the area from the outer corner of the eye to the temple, cheek, and side of the mouth are preferred. Areas with less UV exposure compared to the face, such as under the chin, are not suitable measurement sites. Measurement can be performed on only one site, or multiple sites can be measured.

[0139] While various parameters can be obtained with Cutometer, parameters related to dermal viscoelasticity such as R2, R5, and R7 are preferred. Figures 30 and 31 show the measurement results on the cheek. The value of "dermal viscoelasticity R7" was highest for subject No. 1 at 73.8 and lowest for subject No. 3 at 65.5. From this, it can be concluded that even among young people, the condition of the dermis differs from person to person, and subject No. 3 is diagnosed with sagging due to decreased skin elasticity, i.e., a state of dermal sagging.

[0140] Subcutaneous fat thickness was calculated as the average thickness using an ultrasound diagnostic device. For the cheek area, the fat thickness was defined as the distance from the cheekbone to the subdermis, while for the submandibular area, the fat thickness itself was used. Measurement can be taken anywhere on the face, but the area from the outer corner of the eye to the temple, cheek, side of the mouth, and submandibular area are preferred. Measurement can be taken at one location or multiple locations. In the example in Figure 30, subject No. 1 had the thickest subcutaneous fat thickness compared to the other subjects, at 12.6 mm in the cheek and 4.3 mm under the mandibular area. From this, subject No. 1 is diagnosed with a condition of fat sagging.

[0141] Regarding the quality of facial muscles, it is generally known that muscles undergo age-related changes such as increased muscle brightness and thinning. In Figures 30 and 31, the brightness of facial muscles is calculated using image analysis software from images acquired with an ultrasound diagnostic device, targeting a specific muscle area. Any muscle in the head can be used as the measurement site, but the zygomaticus major, zygomaticus minor, and masseter muscles are preferred. The probe may be applied parallel to the muscle to evaluate the longitudinal section, or it may be applied perpendicular to the muscle to evaluate the transverse section.

[0142] In addition, minimum, maximum, mean, and median values ​​can be used. Figure 30 shows the muscle brightness of the zygomaticus major muscle. Subject No. 2 had a muscle brightness of 17, the highest among the subjects. This indicates that there is an increase in non-contractile tissue within the muscle, resulting in sagging due to muscle laxity and weakening, i.e., a state of muscle sagging. Subject No. 1, who had a fat-related sagging type, had a score of "6," and Subject No. 3, who had a dermal-related sagging type, had a score of "7," both of which are good values, indicating that muscle sagging is not occurring in these subjects.

[0143] Figure 31 shows another example of the diagnostic results. In the example in Figure 31, the type of facial sagging and the condition of the skin's internal structure are compared in middle-aged women (49-54 years old). In the example in Figure 31, as in the example in Figure 30, three subjects with similar visual sagging scores were classified into "fat sagging type," "muscle sagging type," and "dermal sagging type," and their facial features and internal skin data were compared.

[0144] The lowest value for "Dermal Viscoelasticity R7" was 39.2 for subject No. 6. This indicates that subject No. 6 is experiencing a decline in dermal elasticity and sagging due to aging. While the "Dermal Viscoelasticity R7" values ​​for subject No. 4 (50.5) and subject No. 5 (44.9) are higher than those of subject No. 6, their elasticity is still declining compared to younger individuals.

[0145] Regarding subcutaneous fat thickness, subject No. 4 had the thickest subcutaneous fat at 14.2 mm in the cheeks and 8.5 mm under the chin, numerically supporting the idea that fat is the main cause of sagging. Subjects No. 5 and No. 6 had thin subcutaneous fat in both the cheeks and under the chin, suggesting that sagging was caused by factors other than fat. It can also be seen that people with high cheek fat thickness do not necessarily have high under-chin fat, suggesting that it is preferable to measure fat in both the cheeks and under the chin.

[0146] Regarding the quality of facial muscles, subject No. 5 had the highest muscle brightness at "38," indicating a noticeable decline in muscle quality and thus being diagnosed with muscle sagging. This trend is common among younger age groups, suggesting that muscle weakness is the main cause of sagging. Subject No. 4 had a muscle brightness of 32, and subject No. 6 had a muscle brightness of 28, suggesting that the influence of muscles was less significant compared to subject No. 5.

[0147] The diagnostic results in Figures 30 and 31 clearly show that "even with similar levels of sagging, the internal condition of the skin differs." Furthermore, since changes in the internal structure of the skin progress with age, it is necessary to change the approach depending on the cause in each different layer. Such quantitative evaluation is essential for selecting appropriate anti-aging care.

[0148] Figure 32 is a diagram illustrating fat sagging. Figure 32 shows a three-level "level evaluation criterion" for fat sagging, classifying the cheeks and sub-chin from "Grade 1 (Good)" to "Grade 3 (Poor)". Since fat thickness is more influenced by individual differences and body type than age, age categories are not included. A correlation is observed between fat thickness in the cheeks and sub-chin, but generally, the lower the BMI, the thinner the fat thickness in the sub-chin. On the other hand, in some subjects, the trend of fat thickness differs between the cheeks and sub-chin, and the grades may not match between the two areas. Therefore, in the example in Figure 32, fat sagging is evaluated with separate grades for the cheeks and sub-chin. In addition, since a change in fat thickness of about 3 mm in the sub-chin is easily recognizable as a difference in appearance, grades are set at intervals of about 2.5 mm to allow for the evaluation of changes smaller than that in stages.

[0149] Figure 33 is a diagram illustrating muscle sagging. Figure 33 shows the "sagging level evaluation criteria" for muscle quality, which are classified into three stages from G1 (good condition) to G3 (poor condition). Muscle sagging correlates with age, so a gradient is applied according to age. For example, muscle echogenicity is about 30% higher in people in their 30s compared to those in their 20s. Also, for example, muscle thickness increases by about 0.5 mm after 12 weeks of EMS training. Therefore, the range of G2 is set to 1.0 to 2.0 mm so that the grade of approximately 30% of people improves in 12 weeks.

[0150] Figure 34 is a diagram illustrating the scoring of diagnostic levels. In Figure 34(a), the evaluation axes for each type of sagging (dermis, fat, and muscle) are listed. The dermis is evaluated in three stages according to age, fat in both the cheeks and under the chin is evaluated in three stages, and muscle is also evaluated in three stages according to age. In total, the results of the sagging measurement can be diagnosed in 81 different ways depending on age.

[0151] Figure 34(b) shows an image of how sagging measurement results are displayed, with dermal tension score, submandibular fat, cheek fat, and facial muscle thickness shown as specific examples. These measurement results may be expressed as actual measured values ​​(mm), or the values ​​may be replaced with any unit (pt). In the example in Figure 34(b), the dermal tension score is expressed as a percentage, submandibular fat and cheek fat are expressed in pt, and facial muscle thickness is expressed as an actual measured value.

[0152] Figure 34(c) shows an image of the output when the lift-up mode is automatically personalized to suit the individual based on the sagging measurement results. The output time of the treatment waveform corresponding to each tissue (dermis, fat, muscle) is adjusted based on the diagnostic levels of each sagging: dermal level, fat level, and muscle level. The fat level is treated as an integrated fat level based on the evaluation results of the cheeks and under the chin, and the waveform output is controlled based on three axes: dermal level, integrated fat level, and muscle level.

[0153] For example, in Example 1, the dermal level, fat level, and muscle level are all "good" or "standard," so the output time of the sagging waveform is equal for the dermal waveform, fat waveform, and muscle waveform. In Example 2, the dermal level is "poor," the fat level is "standard," and the muscle level is "good," so the output time of the dermal waveform is the longest, followed by the fat waveform, and the muscle waveform. In Example 3, the dermal level is "good," the fat level is "poor," and the muscle level is "standard," so the output time of the fat waveform is the longest, followed by the muscle waveform, and the dermal waveform. Since there are three levels each for the dermal level, fat level, and muscle level (good, standard, and poor), 27 different waveform outputs can be adjusted.

[0154] Figure 35 illustrates the interaction between the measuring device and the app. Figure 35 shows that the device used for skin measurement and sagging care is equipped with Bluetooth communication and supports OTA (Over-The-Air) firmware updates. This enables bidirectional communication between the device and the smartphone app, enhancing convenience and expandability.

[0155] Figure 35(a) lists the data that can be sent from the device to the smartphone app, specifically including the following information: user information (gender and age), skin analysis results for the day (grades for dermis, fat, and muscle sagging), mode and level change history, elapsed time of mode use, and information regarding the temperature sensor and touch sensor. In this way, it becomes possible to visualize and record the user's treatment status and trends on the app.

[0156] On the other hand, Figure 35(b) shows the communication content from the smartphone app to the main unit, mainly allowing for "OTA (firmware update)" and "mode / level changes." This allows for remote updates to the latest functions and instructions for individual modes from the app side, improving operational flexibility and maintenance efficiency.

[0157] In the center of the image, a structure is shown where Bluetooth communication takes place between the smartphone and the main unit, establishing two-way communication for "data" and "OTA". Thus, Figure 35 illustrates the evolution from a standalone beauty device to an IoT-enabled beauty device that enables data management, remote control, and updates through smartphone connectivity.

[0158] [Other] Furthermore, the product may be provided in the following embodiments.

[0159] (1) A sagging skin diagnostic device comprising an acquisition unit for acquiring condition information indicating the condition of the skin, and a diagnostic unit for diagnosing the sagging of the skin based on the acquired condition information.

[0160] This method allows for the assessment of the degree of skin sagging.

[0161] (2) A sagging diagnostic device as described in (1) above, wherein the skin is formed by a plurality of tissues, and the diagnostic unit diagnoses the tissue among the plurality of tissues that is the cause of the sagging of the skin.

[0162] This method allows for the identification of the factors causing sagging.

[0163] (3) A sagging diagnostic device as described in (1) above, wherein the skin is formed of a plurality of tissues, the plurality of tissues include the epidermis of the skin and tissues deeper than the epidermis, the acquisition unit acquires at least one of impedance or phase measured by passing an alternating current through the plurality of tissues as state information, and the diagnosis unit diagnoses the sagging based on the state of composition of the plurality of tissues indicated by the acquired state information.

[0164] This approach allows for the identification of sagging caused by influences in the deeper layers of the skin.

[0165] (4) A sagging diagnostic device as described in (1) above, wherein the acquisition unit acquires the pressure generated when force is applied to the skin as state information, and the diagnostic unit diagnoses the sagging based on the state of elasticity of the skin indicated by the acquired state information.

[0166] This approach makes it possible to identify sagging caused by a deficiency in components that affect skin elasticity.

[0167] (5) A sagging diagnostic device as described in (4) above, wherein the acquisition unit acquires a first pressure generated when a first force is applied to the skin and a second pressure generated when a second force greater than the first force is applied to the skin as state information, and the diagnostic unit diagnoses the sagging based on the difference between the first pressure and the second pressure indicated by the acquired state information.

[0168] This configuration makes it possible to understand the viscoelasticity of deeper layers of the skin.

[0169] (6) A sagging diagnostic device as described in (1) above, wherein the acquisition unit acquires the characteristics of light transmitted through the inside of the skin as state information, and the diagnostic unit diagnoses the sagging based on at least one of the blood state or pulse wave state indicated by the acquired state information.

[0170] This approach allows for the identification of sagging caused by reduced blood flow.

[0171] (7) A sagging diagnostic device as described in (1) above, wherein the acquisition unit acquires the characteristics of electromagnetic waves emitted from the surface of the skin as state information, and the diagnostic unit diagnoses the sagging based on the state of the skin's appearance indicated by the acquired state information.

[0172] In this configuration, it is possible to grasp the sagging that is visible in the exterior.

[0173] (8) A sagging diagnostic device as described in (1) above, wherein the skin is formed of a plurality of tissues, the plurality of tissues include the epidermis of the skin and tissues deeper than the epidermis, the acquisition unit acquires two or more of the following as state information: impedance, phase, pressure generated when force is applied to the skin, and characteristics of light transmitted through the inside of the skin, measured by passing an alternating current through the plurality of tissues, the diagnosis unit diagnoses the sagging based on the state indicated by the two or more acquired state information, the state includes the state of composition of the plurality of tissues if impedance or phase is acquired, the state of elasticity of the skin if pressure is acquired, and the state of blood or pulse wave if characteristics of light are acquired.

[0174] This approach allows for the understanding of the complex conditions that affect sagging.

[0175] (9) A sagging diagnostic device as described in (8) above, wherein the acquisition unit further acquires the characteristics of electromagnetic waves emitted from the surface of the skin as state information, and the diagnostic unit diagnoses the sagging based on the state and the appearance of the skin indicated by the acquired characteristics of the electromagnetic waves.

[0176] This configuration allows for the assessment of sagging based on both the external and internal conditions of the skin.

[0177] (10) A sagging diagnostic device comprising: an acquisition unit that acquires the characteristics of electromagnetic waves emitted from the surface of the skin as state information indicating the condition of the skin; and a diagnostic unit that diagnoses the sagging of the skin based on the acquired state information, wherein the diagnostic unit diagnoses sagging that correlates with the state of the skin's appearance indicated by the acquired state information, based on reference information that represents the correlation between sagging caused by the internal condition of the skin and the external condition of the skin.

[0178] In this configuration, it is possible to understand sagging caused by the internal condition of the skin from its external appearance.

[0179] (11) A sagging diagnostic device as described in (10) above, wherein the reference information is a learning model generated by learning based on training data indicating the internal state of the skin, the external state of the skin, and the sagging of the skin.

[0180] According to this configuration, reference information can be easily created.

[0181] (12) A sagging diagnostic device as described in (1) above, wherein the skin is the skin of the face, the acquisition unit acquires information indicating the condition of the skin of each part of the face as condition information, and the diagnosis unit diagnoses the sagging of the skin of each part of the face based on the acquired condition information for each part.

[0182] This configuration makes it possible to understand the degree of skin sagging in each part of the face.

[0183] (13) A beauty device comprising a sagging diagnostic device described in any one of (1) to (12) above, a display unit, and a treatment unit, wherein the display unit displays the diagnostic results from the sagging diagnostic device, and the treatment unit performs a treatment that applies stimulation to the face to improve or suppress the sagging of the skin, and the intensity or type of stimulation can be changed by user operation.

[0184] This approach allows for treatment tailored to the degree of sagging.

[0185] (14) A beauty device comprising a sagging diagnostic device described in any one of (1) to (12) above, and a treatment unit, wherein the treatment unit performs a treatment that applies stimulation to the face to improve or suppress sagging of the face, the intensity or type of stimulation is changeable, and the treatment unit performs the treatment with an intensity or type corresponding to the diagnostic result of the sagging diagnostic device.

[0186] This approach allows for treatment tailored to the degree of sagging.

[0187] (15) A beauty device as described in (14) above, wherein the sagging diagnostic device diagnoses the sagging during treatment by the treatment unit, and the treatment unit performs the treatment with an intensity or type corresponding to the diagnosis result during treatment.

[0188] According to this configuration, the effects of the treatment can be made uniform.

[0189] (16) A beauty device as described in (14) above, further comprising a notification unit, wherein the sagging diagnostic device diagnoses the sagging during treatment by the treatment unit, and the notification unit provides notification according to the degree of improvement or suppression of the sagging diagnosed during treatment.

[0190] In this manner, the effects of the treatment can be felt.

[0191] (17) An information processing system comprising one or more processors, wherein in an acquisition step, the processor acquires the state information acquired by the acquisition unit of the sagging diagnostic device described in any one of (1) to (12) above, and the sagging diagnosis result by the diagnosis unit; in an analysis step, the processor analyzes the state of the tissue forming the skin based on the acquired state information, and the state is a state that affects the sagging of the skin; and in an output step, the processor outputs sagging analysis information representing the acquired sagging diagnosis result and the analysis result of the tissue state.

[0192] This configuration makes it possible to understand the state of sagging and its causes.

[0193] (18) An information processing system as described in (17) above, wherein in the improvement suggestion step, the processor suggests an improvement method for improving the state of the tissue indicated by the output sagging analysis information.

[0194] This approach makes it easier to address sagging skin.

[0195] (19) An information processing system as described in (17) above, wherein in the analysis step, the processor analyzes factors that will cause the skin to sag in the future, and in the prevention suggestion step, the processor suggests a prevention method to eliminate the factors indicated by the output sagging analysis information and prevent future sagging.

[0196] According to this method, sagging can be prevented.

[0197] (20) A program that causes a computer to perform an acquisition step of acquiring condition information indicating the condition of the skin, and a diagnostic step of diagnosing skin sagging based on the acquired condition information.

[0198] According to this method, sagging can be prevented.

[0199] (21) A method for diagnosing sagging, comprising: an acquisition step in which an information processing device acquires condition information indicating the condition of the skin; and a diagnosis step in which the information processing device diagnoses the sagging of the skin based on the acquired condition information.

[0200] According to this method, sagging can be prevented. Of course, this is not always the case.

[0201] Finally, various embodiments of the present invention have been described, but these are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims and their equivalents.

[0202] 1: Beauty support system, 2: Communication line, 10: Beauty equipment, 10a: Beauty equipment, 10b: Beauty equipment, 11: Display unit, 12: Treatment unit, 13: Power supply unit, 14: Housing unit, 15: Notification unit, 16: Communication unit, 20: Sagging diagnosis unit, 30: Acquisition unit, 31: Electrical characteristics measurement unit, 32: Pressure measurement unit, 33: Optical characteristics measurement unit, 34: Ultrasonic measurement unit, 35: Appearance measurement unit, 36: External information acquisition unit, 40: Diagnosis unit, 50: Analysis server, 60: User terminal, 501: Control unit, 601: Control unit

Claims

1. A method for diagnosing sagging skin, comprising: an acquisition step of acquiring condition information indicating the internal state of the skin; and a diagnosis step of diagnosing the factors causing the sagging skin based on the acquired condition information.

2. A method for diagnosing sagging skin according to claim 1, wherein the inside of the skin is formed by a plurality of tissues, and the diagnostic step involves diagnosing which of the plurality of tissues is the cause of the sagging skin.

3. A sagging diagnosis method according to claim 2, wherein in the acquisition step, information of the fat layer of the skin is acquired as the state information, and in the diagnosis step, if the acquired information of the fat layer satisfies predetermined conditions, the tissue that is the cause of the sagging of the skin is diagnosed as fat.

4. A sagging diagnosis method according to claim 3, wherein in the acquisition step, an image of at least one location from the upper cheek, lower cheek, side of the cheek, or under the chin, captured by an ultrasound diagnostic device, is acquired as information of the fat layer, and in the diagnosis step, if the thickness or brightness of the subcutaneous fat shown in the acquired image satisfies predetermined conditions, the tissue causing the sagging of the skin is diagnosed as fat.

5. A sagging diagnosis method according to claim 3, wherein in the acquisition step, BMI (Body Mass Index) or body fat percentage is acquired as information on the fat layer, and in the diagnosis step, if the acquired BMI or body fat percentage satisfies predetermined conditions, the tissue causing the sagging of the skin is diagnosed as fat.

6. A sagging diagnosis method according to claim 2, wherein in the acquisition step, information of the muscle layer of the skin is acquired as the state information, and in the diagnosis step, if the acquired information of the muscle layer satisfies predetermined conditions, the tissue that is the cause of the sagging of the skin is diagnosed as muscle.

7. A sagging diagnosis method according to claim 6, wherein in the acquisition step, an image of at least one of the muscles of the head captured by an ultrasound diagnostic device is acquired as information of the muscle layer, and in the diagnosis step, if the thickness, brightness, or hardness of the muscles of the head shown in the acquired image satisfies predetermined conditions, the tissue causing the sagging of the skin is diagnosed as muscle.

8. A sagging diagnosis method according to claim 6, wherein in the acquisition step, the amount of muscle mass of the body, the amount of change in muscle thickness during muscle movement, the amount of change in muscle length, the contraction speed, or the contraction time are acquired as information of the muscle layer, and in the diagnosis step, if the acquired muscle mass, the amount of change, the contraction speed, or the contraction time satisfies predetermined conditions, the tissue that is the cause of skin sagging is diagnosed as muscle.

9. A sagging diagnosis method according to claim 2, wherein in the acquisition step, information on the dermis layer of the skin and information on the fat layer of the skin are acquired as the state information, and in the diagnosis step, if the acquired information on the dermis layer and the fat layer satisfies predetermined conditions, the tissues that cause sagging of the skin are diagnosed as the dermis and fat.

10. A sagging diagnosis method according to claim 2, wherein in the acquisition step, information on the dermis layer of the skin and information on the muscle layer of the skin are acquired as the state information, and in the diagnosis step, if the acquired information on the dermis layer and the muscle layer satisfies predetermined conditions, the tissues that cause sagging of the skin are diagnosed as the dermis and muscle.

11. A sagging diagnosis method according to claim 2, wherein in the acquisition step, information on the fat layer of the skin and information on the muscle layer of the skin are acquired as the state information, and in the diagnosis step, if the acquired information on the fat layer and the muscle layer satisfies predetermined conditions, the tissues that cause sagging of the skin are diagnosed as fat and muscle.

12. A sagging diagnosis method according to claim 2, wherein in the acquisition step, information on the dermis layer of the skin, information on the fat layer of the skin, and information on the muscle layer of the skin are acquired as the state information, and in the diagnosis step, if the acquired information on the dermis layer of the skin, information on the fat layer, and information on the muscle layer of the skin satisfies predetermined conditions, the tissues that cause sagging of the skin are diagnosed as the dermis, fat, and muscle.

13. A method for diagnosing sagging according to claim 2, wherein the plurality of tissues include the epidermis of the skin and tissues located deeper than the epidermis, the acquisition step involves obtaining at least one of impedance or phase measured by passing an alternating current through the plurality of tissues as state information, and the diagnosis step involves diagnosing the tissues that are the cause of sagging based on the compositional state of the plurality of tissues indicated by the acquired state information.

14. A sagging diagnosis method according to claim 2, wherein in the acquisition step, the pressure generated when force is applied to the skin is acquired as state information, and in the diagnosis step, the tissue that is the cause of sagging is diagnosed based on the state of elasticity of the skin indicated by the acquired state information.

15. A method for diagnosing sagging, comprising: an acquisition step of acquiring the characteristics of electromagnetic waves emitted from the surface of the skin as condition information indicating the condition of the skin; and a diagnosis step of diagnosing the factors of sagging of the skin based on the acquired condition information, wherein the diagnosis step diagnoses the factors of sagging that are correlated with the condition of the skin indicated by the acquired condition information, based on reference information representing the correlation between the factors of sagging caused by the internal condition of the skin and the external condition of the skin.

16. A sagging diagnosis method according to claim 15, wherein the reference information is a learning model generated by learning based on training data indicating the internal state of the skin, the external state of the skin, and the factors causing the sagging of the skin.

17. A sagging diagnosis method according to claim 15, wherein the skin is facial skin, in the acquisition step, information indicating the internal state of the skin of each part of the face is acquired as condition information, and in the diagnosis step, the factors of sagging of the skin of each part of the face are diagnosed based on the acquired condition information for each part.

18. A sagging skin diagnostic device comprising: an information processing device comprising: an acquisition unit that acquires state information indicating the internal state of the skin; and a diagnostic unit that diagnoses the causes of skin sagging based on the acquired state information.

19. A beauty device comprising a display unit and a treatment unit, wherein the display unit displays the diagnostic results of the sagging factors by the sagging diagnostic device described in claim 18, and the treatment unit performs a treatment that applies stimulation to the skin to improve or suppress the factors of skin sagging, wherein the intensity, type, or duration of the stimulation can be changed by user operation.

20. A beauty device comprising a treatment unit, wherein the treatment unit performs a treatment that provides stimulation to the skin for the purpose of improving or suppressing sagging of the skin, the intensity or type of stimulation is adjustable, and the treatment unit performs the treatment with an intensity, type or duration corresponding to the diagnosis result of the sagging factors by the sagging diagnostic device described in claim 18.

21. The beauty device according to claim 20, wherein the sagging diagnostic device diagnoses the cause of sagging during treatment by the treatment unit, and the treatment unit performs the treatment with an intensity, type, or duration corresponding to the diagnosis result during treatment.

22. The beauty device according to claim 20, further comprising a notification unit, wherein the sagging diagnostic device diagnoses the cause of sagging during treatment by the treatment unit, and the notification unit provides notification according to the degree of improvement or suppression of the cause of sagging diagnosed during treatment.

23. An information processing system comprising one or more processors, wherein in an acquisition step, the processor acquires the state information acquired by the acquisition unit of the sagging diagnostic device described in claim 18 and the diagnostic result of the sagging factors by the diagnostic unit; in an analysis step, the processor analyzes the state of the tissue forming the skin based on the acquired state information, the state being a state that affects the factors of skin sagging; and in an output step, the processor outputs sagging analysis information representing the acquired diagnostic result of the sagging factors and the analysis result of the tissue state.

24. An information processing system according to claim 23, wherein in the improvement suggestion step, the processor suggests an improvement method for improving the state of the tissue indicated by the output sagging analysis information.

25. An information processing system according to claim 23, wherein in the analysis step, the processor analyzes factors that will cause the skin to sag in the future, and in the prevention suggestion step, the processor suggests a prevention method for eliminating the factors indicated by the output sagging analysis information and preventing future sagging.

26. A program that causes a computer to perform an acquisition step of acquiring condition information indicating the internal state of the skin, and a diagnostic step of diagnosing the factors of skin sagging based on the acquired condition information.

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