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WO2025041729A1 - Méthode d'estimation de l'état de la peau, dispositif d'estimation de l'état de la peau, système d'estimation de l'état de la peau et programme - Google Patents

Méthode d'estimation de l'état de la peau, dispositif d'estimation de l'état de la peau, système d'estimation de l'état de la peau et programme Download PDF

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Publication number
WO2025041729A1
WO2025041729A1 PCT/JP2024/029268 JP2024029268W WO2025041729A1 WO 2025041729 A1 WO2025041729 A1 WO 2025041729A1 JP 2024029268 W JP2024029268 W JP 2024029268W WO 2025041729 A1 WO2025041729 A1 WO 2025041729A1
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Prior art keywords
skin condition
skin
subject
estimating
components
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PCT/JP2024/029268
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English (en)
Japanese (ja)
Inventor
楓子 深田
竜海 辻
綾汰 脇
良治 鈴木
慎也 美濃部
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Shiseido Co Ltd
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Shiseido Co Ltd
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Publication of WO2025041729A1 publication Critical patent/WO2025041729A1/fr
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/487—Physical analysis of biological material of liquid biological material
    • G01N33/493—Physical analysis of biological material of liquid biological material urine
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance

Definitions

  • the present invention relates to a skin condition estimation method, a skin condition estimation device, a skin condition estimation system, and a program.
  • JP 2019-025071 A discloses a skin condition evaluation method.
  • This skin condition evaluation method includes an acquisition step (S11) of acquiring blood flow information of the facial skin of a subject, and an evaluation step (S13) of evaluating the facial skin condition of the subject based on the acquired blood flow information.
  • the blood flow information includes a blood flow index value, which is obtained from a light intensity image obtained by irradiating the skin with laser light and capturing an image of scattered light.
  • JP 2019-025071 A estimates skin condition using an optical method.
  • the accuracy of estimating the skin condition is limited because the living body itself is not the specimen and the method is affected by the measurement environment (e.g., ambient light).
  • the objective of the present invention is to improve the accuracy of skin condition estimation.
  • One aspect of the present invention is Measuring components in the urine of a subject, and estimating a future skin condition of the subject based on the measurement results of the components.
  • a method for estimating skin condition is Measuring components in the urine of a subject, and estimating a future skin condition of the subject based on the measurement results of the components.
  • FIG. 1 is a functional block diagram showing a configuration of a skin condition estimating device according to an embodiment of the present invention.
  • FIG. 1 is an explanatory diagram of an overview of the present embodiment.
  • FIG. 2 is a diagram showing a data structure of a subject database of the present embodiment.
  • FIG. 4 is a diagram showing a data structure of a measurement database according to the present embodiment. 4 is a flowchart of a skin condition estimation process according to the present embodiment.
  • 6A and 6B are diagrams showing examples of screens displayed in the information processing of FIG. 5 .
  • FIG. 13 is an explanatory diagram of an overview of a first modified example. 4 is a flowchart of a skin condition estimation process according to the present embodiment.
  • 9A and 9B are diagrams showing examples of screens displayed in the information processing of FIG.
  • FIG. 13 is an explanatory diagram of an overview of modified example 2.
  • 13 is a flowchart of a skin condition estimation process according to a second modified example.
  • FIG. 13 is an explanatory diagram of an overview of modified example 3.
  • FIG. 13 is a functional block diagram of a skin condition estimating system according to a third modified example.
  • FIG. 13 is a sequence diagram of a skin condition estimation process according to Modification 3.
  • a "user” is a person who uses the skin condition estimating device (e.g., a subject or an examiner).
  • Fig. 1 is a functional block diagram showing the configuration of the skin condition estimation device of this embodiment.
  • the skin condition estimating device 10 is, for example, a smartphone, a tablet terminal, or a personal computer. As shown in FIG. 1, the skin condition estimating device 10 includes a storage device 11, a processor 12, an input/output interface 13, and a communication interface 14.
  • the storage device 11 is configured to store programs and data.
  • the storage device 11 is, for example, a combination of ROM (Read Only Memory), RAM (Random Access Memory), and storage (e.g., flash memory or a hard disk).
  • the programs include, for example, the following programs: OS (Operating System) program Parameters, functions, and models used in information processing Applications (e.g., skin condition estimation processing) programs for executing information processing
  • OS Operating System
  • information processing Applications e.g., skin condition estimation processing
  • the data includes, for example, the following data: - Databases referenced in information processing - Data obtained by executing information processing (i.e., the results of executing information processing)
  • the processor 12 is configured to realize the functions of the skin condition estimation device 10 by starting a program stored in the storage device 11.
  • the processor 12 is, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination of these.
  • the input/output interface 13 is configured to acquire user instructions from an input device connected to the skin condition estimating device 10 , and to output information to an output device connected to the skin condition estimating device 10 .
  • the input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof.
  • the output device is, for example, a display.
  • the communication interface 14 is configured to control communication between the skin condition estimation device 10 and an external device (e.g., a server).
  • an external device e.g., a server
  • the subject hands over their urine sample to the user.
  • the user performs a test on the collected urine sample and measures the components in the subject's urine.
  • a user inputs the measurement results of components in the subject's urine to the skin condition estimating device 10.
  • the skin condition estimation device 10 estimates the subject's future skin condition based on the input measurement results.
  • Subject information is stored in the subject database of Fig. 3.
  • the subject information is information relating to subjects.
  • the subject information database includes a "subject ID” field, a "subject name” field, a "subject attribute” field, and a "urinary extracellular data” field. Each field is associated with the other fields.
  • Subject ID field stores subject identification information.
  • Subject identification information is information that identifies the subject.
  • Subject Name is information about the subject's name.
  • the "Subject Attributes” field stores subject attribute information.
  • Subject attribute information is information about the attributes of the subject.
  • the "Subject Attributes” field includes a "Gender” field and an "Age” field.
  • the "Gender” field stores gender information. Gender information is information about the subject's gender.
  • the "Age” field stores age information.
  • Age information is information about the subject's age.
  • the "Extra-urinary” field stores extra-urinary information.
  • Extra-urinary information is information other than the measurement result information of the components in urine, and is information that is referenced for estimating skin condition.
  • the "Extra-urinary” field includes a "Lifestyle” field, a “Medical Interview” field, and a "Blood” field.
  • the "Lifestyle” field stores lifestyle information.
  • the lifestyle information is information about the subject's lifestyle (for example, at least one of information obtained from a questionnaire survey of the subject and information measured by a wearable device worn by the subject).
  • the lifestyle includes, for example, at least one of the following: ⁇ Sleep habits ⁇ Eating habits ⁇ Exercise habits ⁇ Work habits
  • the "medical interview” field stores medical interview information.
  • the medical interview information is information on the results of a medical interview conducted on the subject regarding the urinary nutritional status.
  • the medical interview information includes, for example, at least one of the following: Feeling tired (e.g., feeling easily fatigued) Psychological states (e.g., stress or anxiety) Physical condition (for example, at least one of headache and concentration) Smoking status (e.g., whether or not or how often) - Pregnancy status - Menstrual status (for example, menstrual cycle) - Presence or absence of allergies - Food preferences (for example, frequency of eating fish)
  • the "blood” field stores blood information.
  • the blood information is information about blood.
  • the blood information includes, for example, at least one of the following: Vitamins (for example, vitamin D) ⁇ mineral
  • Measurement result information is stored in the measurement result database in Fig. 4.
  • the measurement result information is information relating to the results of measurements performed on subjects.
  • the measurement result information database includes a "measurement result ID” field, a "time stamp” field, a "urinary minerals” field, and a “urinary vitamins” field. Each field is associated with the others.
  • the measurement database is associated with subject identification information.
  • the "measurement result ID" field stores measurement result identification information.
  • the measurement result identification information is information that identifies the measurement result.
  • the "Timestamp” field stores timestamp information.
  • the timestamp information is information about the date and time when the measurement was performed.
  • the "urinary minerals” field stores urinary mineral information.
  • the urinary mineral information is information about mineral components in urine obtained from a urine test performed on a subject.
  • the measurement result information includes, for example, at least one of the following: ⁇ Potassium content ⁇ Magnesium content ⁇ Phosphorus content ⁇ Zinc content
  • the "urinary vitamins" field stores urinary vitamin information.
  • Urinary vitamin information is information about vitamin components in urine obtained from a urine test performed on a subject.
  • the measurement result information includes, for example, at least one of the following: Vitamin D
  • a skin model is used to estimate the skin condition.
  • the skin model includes a future skin model and a current skin model.
  • the future skin model describes the correlation between urinary components and future skin condition.
  • the future skin condition refers to the skin condition at a time point beyond the time point at which the components in the urine are measured.
  • the explanatory variables of the future skin model are the components in urine.
  • the objective variable of the future skin model is the future skin condition.
  • the future skin model differs for each index of the future skin condition.
  • the indicators of future skin condition include, for example, at least one of the following indicators: Skin moisture (e.g., the amount or level of moisture in the dermis) ⁇ Skin barrier function ⁇ Skin firmness (i.e. viscoelasticity) Skin tone (for example, transparency, yellowness, or yellowness of the skin) ⁇ Amount of hemoglobin in the skin ⁇ Amount of melanin in the skin ⁇ Skin turnover cycle
  • urinary potassium is weighted highly among the explanatory variables.
  • the future skin model predicts that the more potassium in the urine, the more moisture there is in the skin.
  • the skin barrier function is the objective variable
  • the skin barrier function for example, at least one of the explanatory variables, urinary phosphorus and urinary vitamin D
  • the future skin model predicts that the higher the amount of phosphorus in urine, the worse the skin's barrier function.
  • the future skin model predicts that the more vitamin D excreted in urine, the better the skin's barrier function.
  • a future skin model in which skin tone is the objective variable for example, urinary vitamin D is weighted heavily among the explanatory variables.
  • the future skin model predicts that the more vitamin D in the urine, the less yellowing there will be.
  • the amount of hemoglobin in the skin is the response variable
  • at least one of urinary vitamin D and urinary zinc among the explanatory variables has a large weight.
  • the future skin model predicts that the more vitamin D in urine, the higher the hemoglobin content.
  • the future skin model predicts that the more zinc in the urine, the higher the hemoglobin content.
  • the skin turnover cycle is the objective variable
  • urinary zinc is weighted heavily among the explanatory variables.
  • the future skin model predicts that the more zinc there is in the urine, the more regular the turnover cycle will be.
  • the current skin model describes the correlation between urinary components and current skin condition.
  • the current skin condition refers to the skin condition at the time when the components in the urine are measured.
  • the explanatory variables for the skin model are the components in urine.
  • the objective variable of the current skin model is the current skin condition.
  • the current skin model differs for each index of the current skin condition. Indicators of current skin condition are similar to future skin condition.
  • Fig. 5 is a flowchart of the skin condition estimation processing of this embodiment.
  • Fig. 6 is a diagram showing an example of a screen displayed in the information processing of Fig. 5.
  • the user launches a specific application (e.g., an application for estimating a skin condition) of the skin condition estimating device 10.
  • the user uses the skin condition estimating device 10 to access a specific website (for example, a website that provides a service for estimating a skin condition).
  • the skin condition estimating device 10 acquires measurement results (S1110). Specifically, the processor 12 displays screen P1110 (FIG. 6) on the display. Screen P1110 includes an operation object B1110 and field objects F1110a to F1110b.
  • Operation object B1110 is an object that accepts user instructions to confirm input to field objects F1110a to F1110b.
  • Field object F1110a is an object that accepts input of subject identification information.
  • Field object F1110b is an object that accepts input of the subject's measurement result information.
  • the processor 12 stores the subject identification information and the measurement result information in the storage device 11.
  • the skin condition estimating device 10 executes estimation of a future skin condition (S1111). Specifically, the storage device 11 stores a future skin model.
  • the processor 12 estimates the future skin condition according to the components in the subject's urine by providing the measurement results input to the field object F1110b in step S1110 to the future skin model.
  • the skin condition estimating device 10 executes estimation of the current skin condition (S1112). Specifically, the storage device 11 stores a current skin model.
  • the processor 12 estimates the current skin condition (i.e., the time when step S1112 is executed) according to the components in the subject's urine by applying the measurement results input to the field object F1110b in step S1110 to the current skin model.
  • the skin condition estimating device 10 updates the database (S1113). Specifically, the processor 12 adds a new record to the measurement result database (FIG. 4) associated with the subject identification information obtained in step S1110. The following information is stored in each field of the new record.
  • Urine vitamins” field measurement result information obtained in step S1110
  • the skin condition estimating device 10 displays the estimation result (S1114).
  • the processor 12 displays screen P1111 (FIG. 6) on the display.
  • Screen P1111 includes display objects A1111a to A1111b.
  • Display object A1111a is an object that displays the estimated future skin condition obtained in step S1111.
  • Display object A1111b is an object that displays the estimation result of the current skin condition obtained in step S1112.
  • the future skin condition is estimated based on the components in urine, which can improve the accuracy of estimating the skin condition.
  • the current skin condition may be estimated based on the measurement results. This can further improve the accuracy of estimating the skin condition.
  • the first modification is an example in which recommendations are provided based on the estimation result of the skin condition.
  • the subject hands over their urine sample to the user.
  • the user performs a test on the collected urine sample and measures the components in the subject's urine.
  • a user inputs the measurement results of components in the subject's urine to the skin condition estimating device 10.
  • the skin condition estimation device 10 estimates the subject's future skin condition based on the input measurement results, and determines recommendations according to the future skin condition.
  • Fig. 8 is a flowchart of the skin condition estimation processing of this embodiment.
  • Fig. 9 is a diagram showing an example of a screen displayed in the information processing of Fig. 8.
  • the first example of the recommendation model describes the correlation between future skin conditions and recommendations.
  • the explanatory variable of the recommendation model is the future skin condition.
  • the target variable of the recommendation model is a recommendation.
  • the processor 12 generates recommendations according to the future skin condition by applying the future skin condition obtained in step S1111 to the recommendation model.
  • the second example of the recommendation model describes the correlation between the current skin condition and the recommendation.
  • the explanatory variable of the recommendation model is the current skin condition.
  • the target variable of the recommendation model is a recommendation.
  • the processor 12 generates recommendations according to the current skin condition by applying the current skin condition obtained in step S1112 to the recommendation model.
  • the explanatory variables of the recommendation model are the future skin condition and the current skin condition.
  • the target variable of the recommendation model is a recommendation.
  • the processor 12 generates a recommendation according to the combination of the future skin condition obtained in step S1111 and the current skin condition obtained in step S1112 by providing the recommendation model with the future skin condition obtained in step S1111 and the current skin condition obtained in step S1112.
  • the processor 12 generates a recommendation according to the current skin condition by applying the current skin condition obtained in step S1112 to the recommendation model.
  • the fourth example of the recommendation model describes the correlation between changes in the measurement results of components in urine and recommendations.
  • the explanatory variables of the recommendation model are changes in the measurement results of components in urine.
  • the target variable of the recommendation model is a recommendation.
  • the processor 12 obtains measurement result information (i.e., past measurement result information) from the "urinary minerals" field and the "urinary vitamins” field of the measurement result database ( Figure 4) associated with the subject identification information obtained in step S1110.
  • the processor 12 identifies differences in the components in the urine by comparing the measurement result information (i.e., past measurement result information) with the measurement result information obtained in step S1110 (i.e., the latest measurement result information).
  • the processor 12 applies the identified difference (i.e., the change in the components in the urine) to a recommendation model to generate a recommendation according to the change.
  • the skin condition estimation device 10 After step S2110, the skin condition estimation device 10 performs database update (S1113) in the same manner as in FIG. 5.
  • the skin condition estimating device 10 displays the estimation result (S2111). Specifically, the processor 12 displays screen P2110 (FIG. 9) on the display after screen P1111 (FIG. 6). Screen P2110 includes display object A2110.
  • Display object A2110 displays the recommendations obtained in step S2110.
  • a recommendation may be generated based on the estimation result of the skin condition. This makes it possible to encourage improvement according to the skin condition.
  • recommendations may be generated based on the results of a comparison between past measurement results and the latest measurement results. This makes it possible to encourage improvements while taking into account the tendency of changes in the subject's skin condition.
  • the second modification is an example in which the skin condition is estimated based on a combination of the measurement results of components in urine and information other than the components in urine (hereinafter referred to as "non-urine information").
  • the extra-urinary information may include, for example, at least one of the following: - Lifestyle habits (for example, at least one of sleep quality and fatigue) - Results of questionnaire regarding nutritional status of urine - Results of blood tests
  • the user performs a test on the collected urine sample and measures the components in the subject's urine.
  • a user inputs the measurement results of components in the subject's urine to the skin condition estimating device 10.
  • the skin condition estimating device 10 acquires extra-urinary information of the subject.
  • the skin condition estimating device 10 estimates the subject's future skin condition based on a combination of the input measurement results and the extra-urinary information.
  • a first example of the future skin model of variant example 2 describes the correlation between a combination of urine components and lifestyle habits and a future skin condition.
  • the explanatory variables of the future skin model are urinary components and lifestyle habits.
  • the objective variable of the future skin model is the future skin condition.
  • a third example of the future skin model of variant example 2 describes the correlation between a combination of the results of a medical interview regarding urinary components and urinary nutritional status, and the future skin condition.
  • the explanatory variables of the future skin model are the components in urine and the results of a questionnaire regarding the nutritional status of urine.
  • the objective variable of the future skin model is the future skin condition. For example, if the result of the interview regarding "psychological condition" is "stressed” or "anxious,” it is presumed that the subject is deficient in magnesium. For example, if the result of a question about "food preferences" is "I don't eat much fish,” it is presumed that the patient is deficient in vitamin D.
  • the fourth example of the future skin model of variant example 2 describes the correlation between a combination of urine components and blood test results and a future skin condition.
  • the explanatory variables of the future skin model are the components in urine and the results of blood tests.
  • the objective variable of the future skin model is the future skin condition.
  • the explanatory variables of the current skin model are urinary components and lifestyle habits.
  • the objective variable of the current skin model is the current skin condition.
  • a third example of the current skin model of the second modified example describes the correlation between a combination of the results of a medical interview regarding the components in urine and the nutritional status of urine, and the current skin condition.
  • the explanatory variables for the current skin model are the components in urine and the results of a questionnaire regarding the nutritional status of urine.
  • the objective variable of the current skin model is the current skin condition. For example, if the result of a medical interview regarding "fatigue” is "you get tired easily,” it is presumed that you have a vitamin B deficiency. For example, if the result of the interview regarding "psychological condition" is "stressed” or "anxious,” it is presumed that the subject is deficient in magnesium.
  • the fourth example of the current skin model of variant example 2 describes the correlation between a combination of urine components and blood test results and the current skin condition.
  • the explanatory variables of the current skin model are the components in urine and the results of blood tests.
  • the objective variable of the current skin model is the current skin condition.
  • the skin condition estimation device 10 acquires the measurement results (S1110) in the same manner as in FIG. 5.
  • the skin condition estimating device 10 acquires non-urine information (S3110).
  • the processor 12 refers to the subject database (FIG. 3) to obtain extra-urinary information associated with the subject identification information obtained in step S1110.
  • the skin condition estimating device 10 executes estimation of a future skin condition (S3111). Specifically, the storage device 11 stores a future skin model.
  • the processor 12 provides the measurement result information obtained in step S1110 and the non-urinary information obtained in step S3110 to a future skin model, and estimates a future skin condition according to the combination of the measurement result information and the non-urinary information.
  • the skin condition estimating device 10 executes estimation of the current skin condition (S3112).
  • the storage device 11 currently stores a skin model.
  • the processor 12 provides the measurement result information obtained in step S1110 and the non-urinary information obtained in step S3110 to the current skin model, and estimates the current skin condition according to the combination of the measurement result information and the non-urinary information.
  • the skin condition estimation device 10 After step S3112, the skin condition estimation device 10 performs the steps from updating the database (S1113) to displaying the estimation results (S1114), similar to FIG. 5.
  • the skin condition of a subject may be estimated based on a combination of urinary components and extra-urinary information (for example, at least one of the results of a questionnaire regarding lifestyle habits and urinary nutritional status). This can further improve the accuracy of estimating the skin condition.
  • Modification 3 is an example of a skin condition estimating system that includes the skin condition estimating device 10.
  • a subject hands over his or her urine specimen to a user.
  • the subject transmits subject identification information to the skin condition estimating device 10 via the client device 30 .
  • the user performs a test on the collected urine sample and measures the components in the subject's urine.
  • a user inputs the measurement results of components in the subject's urine and the subject identification information to the skin condition estimating device 10.
  • the skin condition estimating device 10 stores the input measurement results and subject identification information in association with each other.
  • the skin condition estimating device 10 estimates the future skin condition of the subject based on the input measurement results, and presents the estimation result to the subject via the client device 30.
  • FIG. 13 is a functional block diagram of the skin condition estimation system of Modification 3.
  • the skin condition estimation system 1 of variant example 3 includes a skin condition estimation device 10 and a client device 30.
  • the configuration of the skin condition estimation device 10 is the same as that shown in Figure 1.
  • the client device 30 is, for example, a smartphone, a tablet terminal, or a personal computer. As shown in FIG. 1, the client device 30 includes a storage device 31, a processor 32, an input/output interface 33, and a communication interface .
  • the storage device 31 is configured to store programs and data.
  • the storage device 31 is, for example, a combination of ROM, RAM, and storage (for example, flash memory or a hard disk).
  • the programs include, for example, the following programs: - OS (Operating System) programs - Parameters, functions, and models used in information processing - Programs of applications (e.g., web browsers) that execute information processing
  • OS Operating System
  • Programs of applications e.g., web browsers
  • the data includes, for example, the following data: - Databases referenced in information processing - Data obtained by executing information processing (i.e., the results of executing information processing)
  • the processor 32 is configured to realize the functions of the client device 30 by starting the programs stored in the storage device 31.
  • the processor 32 is, for example, a CPU, a GPU, an ASIC, an FPGA, or a combination of these.
  • the input/output interface 33 is configured to obtain user instructions from an input device connected to the client device 30 , and to output information to an output device connected to the client device 30 .
  • the input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof.
  • the output device is, for example, a display.
  • the communication interface 34 is configured to control communication between the client device 30 and the skin condition estimation device 10.
  • the subject launches a specific application (e.g., an application for estimating a skin condition) of the skin condition estimating device 10.
  • the subject uses the skin condition estimating device 10 to access a specific website (e.g., a website that provides a service for estimating a skin condition).
  • the client device 30 acquires the measurement results (S1110) in the same manner as in FIG. 5.
  • the client device 30 executes an estimation request (S5310). Specifically, the processor 32 transmits the estimation request data to the skin condition estimating device 10.
  • the estimation request data includes, for example, the following information: Subject identification information input to the field object F1110a Measurement result information input to the field object F1110b
  • the skin condition estimation device 10 executes the process of estimating future skin conditions (S1111) through updating the database (S1113), similar to FIG. 5.
  • the skin condition estimating device 10 executes an estimated response (S5110). Specifically, the processor 12 transmits the estimated response data to the client device 30.
  • the estimated response data includes, for example, the following information: The estimation result of the future skin condition obtained in step S1111. The estimation result of the current skin condition obtained in step S1112.
  • the client device 30 displays the estimation result (S1114) in the same manner as in FIG. 5.
  • the storage device 11 may be connected to the skin condition estimating device 10 via a network.
  • the storage device 31 may be connected to the client device 30 via a network.
  • Skin condition estimation system 10 Skin condition estimation device 11: Storage device 12: Processor 13: Input/output interface 14: Communication interface 30: Client device 31: Storage device 32: Processor 33: Input/output interface 34: Communication interface

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Abstract

L'invention concerne une méthode d'estimation de l'état de la peau, comprenant une étape de mesure d'un composant dans l'urine d'un sujet, et une étape d'estimation d'un état futur de la peau du sujet sur la base du résultat de mesure du composant.
PCT/JP2024/029268 2023-08-23 2024-08-19 Méthode d'estimation de l'état de la peau, dispositif d'estimation de l'état de la peau, système d'estimation de l'état de la peau et programme Pending WO2025041729A1 (fr)

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JP2019528688A (ja) * 2016-08-12 2019-10-17 エムディー ヘルスケア インコーポレイテッドＭｄ Ｈｅａｌｔｈｃａｒｅ Ｉｎｃ． バチルス属細菌由来ナノ小胞およびその用途
JP2020014710A (ja) * 2018-07-26 2020-01-30 ポーラ化成工業株式会社 肌状態の鑑別法
JP2020046200A (ja) * 2018-09-14 2020-03-26 ポーラ化成工業株式会社 肌状態の鑑別法
CN114209288A (zh) * 2022-01-14 2022-03-22 平安普惠企业管理有限公司 皮肤状态预测方法、皮肤状态预测装置、设备及存储介质

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JP2019528688A (ja) * 2016-08-12 2019-10-17 エムディー ヘルスケア インコーポレイテッドＭｄ Ｈｅａｌｔｈｃａｒｅ Ｉｎｃ． バチルス属細菌由来ナノ小胞およびその用途
JP2020014710A (ja) * 2018-07-26 2020-01-30 ポーラ化成工業株式会社 肌状態の鑑別法
JP2020046200A (ja) * 2018-09-14 2020-03-26 ポーラ化成工業株式会社 肌状態の鑑別法
CN114209288A (zh) * 2022-01-14 2022-03-22 平安普惠企业管理有限公司 皮肤状态预测方法、皮肤状态预测装置、设备及存储介质

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