System

Abstract

A system is provided.SOLUTION: A system comprising: sensing means for sensing a user standing in front of a mirror; scanning means for non-invasively scanning the user's skin condition, expression, and posture; analyzing means for analyzing the scan data and assessing the user's health condition; suggestion generating means for generating nutrition suggestions, exercise program suggestions based on the analysis results; and relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In today's world, an increasing number of individuals and families, including the elderly and those with chronic diseases, want to easily manage their health in their daily lives. However, these individuals find it difficult to monitor and manage their health on a daily basis. Furthermore, there is a lack of specific guidance for conveniently checking and improving their health at home, regardless of time or location. Therefore, there is a need for a system that can non-invasively analyze daily health status in a user-friendly manner and instantly provide optimal health improvement suggestions to users. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by the means described in the claims. That is, the present invention includes the following means.

[0006] The system includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, and a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques. This allows users to easily and effectively monitor their health condition in their daily lives and receive personalized advice for improving their health.

[0007] "Detection means for detecting that a user is standing in front of a mirror" refers to a sensor or technology for detecting that a user is standing in front of a mirror and notifying the system.

[0008] "Scanning means for non-invasively scanning a user's skin condition, facial expression, and posture" refers to a camera or scanning technology for acquiring data on a user's skin condition, facial expression, and body posture without physical contact or impact.

[0009] "Analysis means for analyzing scan data and assessing the health status of a user" refers to an algorithm or software for processing the acquired scan data and assessing and determining the health status of a user.

[0010] "Proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results" refers to a system or software for automatically suggesting appropriate nutritional intake methods and exercise programs to users based on the analyzed data.

[0011] "A relaxation suggestion tool for monitoring stress levels and suggesting relaxation techniques" refers to a system or algorithm that periodically monitors a user's stress level and suggests appropriate relaxation methods based on the results. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0013] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0016] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0017] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0018] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0025] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0032] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0033] This invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, it generates and provides users with nutritional intake and exercise program suggestions. It also has a function to monitor stress levels and suggest relaxation techniques based on the results.

[0034] System configuration overview

[0035] 1. User Device:

[0036] It includes a mirror section and an integrated scanning device.

[0037] It has a built-in integrated AI system that analyzes data and generates recommendations.

[0038] 2. Server:

[0039] It provides powerful computational resources for analyzing data.

[0040] A learning model and database are put into operation to manage user data over the long term.

[0041] 3. Cloud Services:

[0042] It works in conjunction with the server to perform data backups and real-time analysis.

[0043] System Operation

[0044] 1. Initial Setup and User Registration

[0045] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[0046] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0047] 2. Daily Health Check

[0048] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[0049] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results to the user's device.

[0050] 3. Nutrition and exercise program suggestions

[0051] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may suggest daily intake of foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[0052] The user reviews the suggestions and implements them as needed.

[0053] 4. Stress level monitoring and relaxation suggestions

[0054] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[0055] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[0056] The user performs suggested relaxation techniques to reduce stress.

[0057] Specific examples

[0058] 1. Initial Setup and User Registration

[0059] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[0060] Tanaka enters his name, age, gender, and past medical history and saves it.

[0061] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[0062] 2. Daily Health Check

[0063] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[0064] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[0065] The mirror displays the analysis results to Tanaka.

[0066] 3. Nutrition and exercise program suggestions

[0067] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[0068] Tanaka implements the suggestions and works to improve his health.

[0069] 4. Stress level monitoring and relaxation suggestions

[0070] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[0071] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[0072] Tanaka does deep breathing exercises to reduce stress.

[0073] The above is a description of the mode for carrying out the invention. This system allows users to easily monitor their health status at home and obtain and implement specific measures for improvement.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] The user stands in front of the mirror. The user device detects the user's presence using a sensor that detects the user's movement.

[0077] Step 2:

[0078] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[0079] Step 3:

[0080] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[0081] Step 4:

[0082] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[0083] Step 5:

[0084] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[0085] Step 6:

[0086] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[0087] Step 7:

[0088] The user's device generates nutritional intake and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (e.g., yoga, stretching, etc.).

[0089] Step 8:

[0090] The user can check the suggestions and implement them as necessary. Support such as a guide and timer is also provided for the user device to implement the suggestions.

[0091] Step 9:

[0092] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[0093] Step 10:

[0094] The server suggests relaxation techniques based on stress levels, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[0095] Step 11:

[0096] The user terminal presents the received relaxation techniques to the user, provides specific guidance, and assists the user in carrying out the suggested relaxation techniques.

[0097] Step 12:

[0098] The user performs relaxation techniques to reduce stress, and the user device monitors the progress of the techniques and provides feedback as needed.

[0099] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health status and provide suggestions for improvement.

[0100] Example 1

[0101] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0102] Conventional health management systems struggled to provide completely non-invasive scans, real-time data analysis, and health improvement recommendations. Furthermore, insufficient analysis of scan data meant that users were unable to receive appropriate nutritional and exercise recommendations. Furthermore, the lack of real-time monitoring of stress levels and appropriate relaxation recommendations meant that users were unable to adequately manage stress in their daily lives.

[0103] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0104] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, a data transmission means for transmitting the scanned data to the server in real time, an analysis means for analyzing the scanned data using a machine learning model and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a result return means for returning the analysis results from the server to a user terminal, and a means for the user to execute the suggested nutritional intake suggestions and exercise program and transmit the feedback to the server. This enables the user to non-invasively manage their daily health and obtain appropriate health improvement measures and stress management measures in real time.

[0105] The following are definitions of key terms included in the rewritten claims:

[0106] "Detection means" refers to a sensor or device for detecting when a user stands in front of a mirror.

[0107] "Scanning means" refers to a device or system for non-invasively scanning a user's skin condition, facial expression, and posture.

[0108] "Data transmission means" refers to a communication device or protocol for transmitting scan data from a user terminal to a server in real time.

[0109] "Analysis means" refers to software or algorithms used to analyze scan data and assess the user's health status.

[0110] "Suggestion generation means" refers to a device or algorithm for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[0111] "Relaxation suggestion tools" refer to devices or algorithms that monitor stress levels and suggest appropriate relaxation techniques.

[0112] "Result return means" refers to a communication device or protocol for returning analysis results from the server to the user terminal.

[0113] "Machine Learning Model" refers to the trained algorithm or model used to analyze scan data.

[0114] "Feedback means" refers to a device or system that allows the user to carry out the suggested nutritional intake suggestions and exercise program and transmit the results to the server.

[0115] The present invention provides a system that allows users to easily manage their health in their daily lives. The system operates using the following hardware and software.

[0116] Hardware and software used

[0117] 1. User Device:

[0118] Mirror part: The mirror part used when standing in front of the user.

[0119] Scanning device: Equipped with a high-resolution camera and infrared sensors for non-invasively scanning skin condition, facial expressions, and posture.

[0120] Motion detection sensor: Used to detect when a user stands in front of the mirror.

[0121] Integrated AI system: Includes a built-in software system that analyzes data and generates recommendations.

[0122] 2. Server:

[0123] Computing resources: High-performance computing devices for analyzing data, including GPUs and high-performance CPUs.

[0124] Database: A data storage system for long-term management of user data.

[0125] Machine learning models: Operate trained deep learning models to analyze user data.

[0126] 3. Cloud Services:

[0127] Data Backup: Cloud storage for safe storage of data.

[0128] Real-time analytics: Cloud computing resources for analyzing data in real time.

[0129] System Operation Overview

[0130] 1. User Device:

[0131] When the user's device is started for the first time, it welcomes the user and displays a screen for entering basic information. The user enters basic information such as name, age, gender, and medical history. The basic information is encrypted using AES (Advanced Encryption Standard) and sent to the server. The server creates a user profile based on the received information and stores it in a database.

[0132] 2. Daily Health Check:

[0133] The next morning, when the user stands in front of the mirror, the motion detection sensor detects this and the scanning device begins a non-invasive scan. Skin condition, facial expression, and posture are scanned using a high-resolution camera and infrared sensor, and the scanned data is sent in real time to a server. The server then analyzes the received data using machine learning models to assess the user's health status. For example, it evaluates the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results back to the user's device.

[0134] 3. Analysis results and proposals:

[0135] The user device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, which are then provided to the user. For example, the system may suggest "eating foods containing vitamin E and doing 20 minutes of stretching." The user can then carry out the recommendations and send their feedback to the server.

[0136] 4. Stress level monitoring and relaxation suggestions:

[0137] The user device analyzes facial expression data to estimate the stress level in real time. The server then suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user device. The user can then perform the suggested relaxation techniques to reduce stress.

[0138] Specific examples and examples of prompts for generative AI models

[0139] Examples:

[0140] 1. Initial setup and user registration:

[0141] When Tanaka uses the system for the first time, a screen for entering basic information appears.

[0142] Tanaka enters his name, age, gender, and past medical history and saves it.

[0143] The server creates a profile for Tanaka and sends a notification back to the device that the profile has been saved.

[0144] 2. Daily Health Check:

[0145] The next morning, when Tanaka stands in front of the mirror, the device starts an automatic scan and sends the scanned data to the server.

[0146] The server analyzes the data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the device.

[0147] The terminal displays the analysis results to Tanaka.

[0148] 3. Nutrition and exercise program suggestions:

[0149] The device suggests to Tanaka, "Eat foods containing vitamin E and do 20 minutes of stretching."

[0150] Tanaka implements the suggestions and works to improve his health.

[0151] 4. Stress level monitoring and relaxation suggestions:

[0152] The device analyzes Tanaka's facial expression and assesses his stress level as "high."

[0153] The server suggests "10 minutes of deep breathing exercises" and displays it on the device.

[0154] Tanaka does deep breathing exercises to reduce stress.

[0155] Example prompt for a generative AI model:

[0156] "Please explain the process flow of a system that non-invasively scans a user's health status while they stand in front of a mirror and generates health improvement suggestions based on the analysis results."

[0157] This system allows users to non-invasively manage their daily health and provide appropriate health improvement and stress management strategies in real time.

[0158] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0159] Step 1: Enter basic user information

[0160] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information. The input screen includes items such as name, age, gender, and medical history. For example, the user might enter information such as "Ichiro Tanaka, 30 years old, male, no allergies." Input is done using a touch panel or voice recognition.

[0161] Input: Basic information entered by the user.

[0162] Output: The user's input information is saved in the system and used in the next step.

[0163] Step 2: Submit your input

[0164] The user terminal encrypts the input basic information and sends it to the server, using AES (Advanced Encryption Standard) to ensure data security.

[0165] Input: Basic information entered in step 1.

[0166] Output: The encrypted basic information is sent to the server.

[0167] Step 3: Create and save a profile

[0168] The server stores the received user information in a database and creates a user profile. After the profile is created, a completion notification is sent to the user's device.

[0169] Input: Encrypted basic information.

[0170] Output: The user profile is saved in the database and a completion notification is sent back to the user terminal.

[0171] Step 4: Detecting the user standing in front of a mirror

[0172] The user device detects when the user stands in front of the mirror using a built-in motion detection sensor, which can be an infrared sensor or a camera.

[0173] Input: Motion detection sensor data.

[0174] Output: The user is detected as standing in front of a mirror and the next scanning step is initiated.

[0175] Step 5: Run a scan

[0176] The user device activates a built-in non-invasive scanning device that scans the user's skin condition, facial expression, and posture. The scanning device uses a high-resolution camera and infrared sensor to record, in detail, the degree of skin moisture, abnormal posture, and subtle changes in facial expression.

[0177] Input: Sensory data of a user standing in front of a mirror.

[0178] Output: Scan data on skin condition, facial expression, and posture is generated.

[0179] Step 6: Send the scan data

[0180] The user device sends the scanned data to the server in real time, and the data is encrypted and sent over the network.

[0181] Input: Scan data.

[0182] Output: The encrypted scan data is sent to the server.

[0183] Step 7: Analyze your health status

[0184] The server then analyzes the received scan data using machine learning models, such as deep learning algorithms, to assess stress levels based on skin dryness, posture, and facial expressions.

[0185] Input: Encrypted scan data.

[0186] Output: The analysis results may include, for example, "skin is becoming increasingly dry," "posture is slightly distorted," and "stress level: high."

[0187] Step 8: Returning the analysis results

[0188] The server returns the analysis results to the user's terminal. The data is also encrypted here. The user's terminal displays the analysis results on its screen.

[0189] Input: Analysis results.

[0190] Output: The encrypted analysis results are sent to the user's terminal and displayed to the user.

[0191] Step 9: Generate proposals

[0192] Based on the health analysis results, the server generates optimal nutritional recommendations and exercise programs, such as "daily intake of foods containing vitamin C" and "specific exercise (yoga, stretching, etc.)."

[0193] Input: Analysis results.

[0194] Output: Proposals are generated and sent to the user device in the next step.

[0195] Step 10: Submit and view your proposal

[0196] The server transmits the generated proposal to the user terminal, which displays the proposal on its screen.

[0197] Input: Proposal content.

[0198] Output: The proposal is sent to the user's terminal and displayed to the user.

[0199] Step 11: Implementing the proposal

[0200] The user confirms the suggestions and implements them, for example, purchasing food supplements for vitamin E and stretching every morning.

[0201] Input: Proposal content.

[0202] Output: User performance feedback is generated and sent to the server in the next step.

[0203] Step 12: Submit your feedback

[0204] The user terminal transmits to the server the results of the user's implementation of the suggested nutritional intake suggestions and exercise program.

[0205] Input: User's performance feedback.

[0206] Output: The feedback data is sent to the server and stored in a database.

[0207] The above is a detailed description of the processing steps of the system and the specific operations at each step.

[0208] (Application example 1)

[0209] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0210] Conventional health management systems have difficulty monitoring the health status of individual users in real time and providing appropriate advice. In particular, in industrial environments, real-time understanding of workers' health status and immediate response are required, but current systems lack intelligent support for appropriately assessing and responding to workers' health risks.

[0211] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0212] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a means for non-invasively monitoring health in a wearable device worn by a worker, and a means for generating break and stretching suggestions based on the worker's health condition. This enables real-time monitoring of the health condition of workers in an industrial environment, enabling prompt and appropriate health management and improvement of the working environment.

[0213] The "detection means" is a device or technology for detecting that a user is standing in a specific position (for example, in front of a mirror).

[0214] "Scanning means" refers to a device or technology for non-invasively scanning a user's skin condition, facial expression, and posture.

[0215] "Analysis means" refers to functions and algorithms for analyzing scan data and assessing the user's health condition.

[0216] The "suggestion generation means" is a device or system for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[0217] "Relaxation suggestion means" refers to technologies or systems that monitor stress levels and suggest relaxation techniques.

[0218] A "wearable device" is a device that can be worn by workers and is used to monitor their health status in real time.

[0219] "Health monitoring means" refers to technologies and equipment for non-invasively monitoring workers' health using wearable devices.

[0220] A "rest suggestion means" is a function or system that suggests appropriate rest times and stretching timings based on the worker's health condition.

[0221] This invention is a system that monitors workers' health in real time and suggests appropriate breaks and stretching. The system consists of a wearable device, a server, and a cloud service.

[0222] System configuration overview

[0223] 1. Wearable devices:

[0224] It can be worn by workers and contains cameras and sensors to scan skin condition, facial expressions, and posture.

[0225] Data is collected non-invasively and transmitted to a server in real time.

[0226] 2. Server:

[0227] It provides powerful computational resources for analyzing the received data.

[0228] Evaluate the user's health status and generate appropriate suggestions.

[0229] Use databases to manage longitudinal health data.

[0230] 3. Cloud Services:

[0231] It works in conjunction with the server to back up data and perform real-time data analysis.

[0232] System Operation

[0233] 1. Initial Setup and Worker Registration:

[0234] When the wearable device is first turned on, it recognizes the worker and displays a screen for entering basic information, such as name, age, gender, and past medical history.

[0235] The server receives the input, creates a worker profile, stores it in a database, and sends a notification back to the wearable device once the profile is complete.

[0236] 2. Real-time monitoring:

[0237] The wearable device scans the worker's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time.

[0238] The server analyzes the data and evaluates the user's health status. For example, it calculates stress levels, posture distortion, and fatigue levels based on the level of dryness of the skin and facial expressions. The results are then sent to the wearable device.

[0239] 3. Proposal generation and notification:

[0240] Based on the analysis results, the server generates nutritional intake suggestions, exercise program suggestions, and rest suggestions, such as suggesting vitamin intake, short rest periods, and specific stretching exercises.

[0241] The wearable device can display these suggestions to the worker for confirmation, and if high stress levels are detected, the server will suggest appropriate relaxation techniques (e.g., deep breathing exercises) and display them on the device.

[0242] Hardware and software used

[0243] Wearable devices: smart glasses, smart watches, etc. with built-in cameras, sensors, and displays.

[0244] Server: High-performance analysis hardware (e.g., GPU server), database system (e.g., MySQL).

[0245] Cloud services: Real-time data analysis and backup capabilities, such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[0246] Analysis software: Use Python libraries (e.g., TensorFlow, Scikit-learn) to build machine learning models and perform data analysis.

[0247] Specific examples

[0248] Everyday use examples

[0249] 1. When worker A puts on the smart glasses for the first time, a basic information entry screen appears. After worker A enters the necessary information, the server receives the information and creates a profile.

[0250] 2. When the task begins, the smart glasses scan A's facial expressions and posture in real time and send the data to the server. The server analyzes the data and evaluates A's stress level and posture.

[0251] 3. If your stress level is determined to be high, you will be suggested to do 10 minutes of deep breathing exercises. If your posture is poor, a notification will appear on the glasses display urging you to correct your posture.

[0252] Example prompts for generative AI models

[0253] Text format:

[0254] A factory worker is wearing smart glasses. The camera built into the glasses captures facial expressions, posture, and fatigue levels while working, and we want to monitor his health condition in real time. Please write a program using Python to analyze the health data.

[0255] If stress levels are high, deep breathing exercises are suggested

[0256] If your posture is bad, we suggest correcting it.

[0257] If fatigue is high, a short rest is suggested

[0258] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0259] Step 1:

[0260] The user puts on the wearable device and performs the initial setup. When the device is first started up, a basic information entry screen is displayed, and the user enters information such as name, age, gender, and past medical history. This is the input, and user profile data is generated as the output and sent to the server. The server receives this data and stores it in a database for long-term management.

[0261] Step 2:

[0262] The wearable device collects data in real time. The device non-invasively scans the wearer's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time. The scan data is provided as input, and the server receives it as output and prepares it for analysis.

[0263] Step 3:

[0264] The server analyzes the received scan data. Specifically, it processes the data using machine learning models (e.g., TensorFlow) to evaluate the user's stress level, posture accuracy, and skin condition. The input is the scan data, and the output is the analysis results.

[0265] Step 4:

[0266] The server generates suggestions based on the analysis results. These suggestions include nutritional intake suggestions, exercise program suggestions, and rest suggestions based on the user's health condition. For example, if the stress level is high, a suggestion for deep breathing exercises is generated. The input is the analysis results, and the output is the generated suggestions.

[0267] Step 5:

[0268] The server notifies the wearable device of the proposed content. The server sends the generated proposed content to the wearable device and displays it on the device's display. The user can check it and implement the proposed content as necessary. The input is the proposed content, and the output is a notification to the user.

[0269] Step 6:

[0270] Suggesting and implementing relaxation techniques: If the user's stress level is high, the server generates a suggestion for an appropriate relaxation technique (e.g., deep breathing exercises) and notifies the wearable device. The user then sees this and performs the relaxation technique, thereby reducing stress. The input is the analysis result, and the output is the relaxation suggestion.

[0271] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0272] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when the user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, the system generates and provides nutritional intake and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining this system with an emotion engine, the system can recognize the user's emotions and more precisely adjust the suggestions.

[0273] System configuration overview

[0274] 1. User Device:

[0275] It includes a mirror section and an integrated scanning device.

[0276] It has a built-in integrated AI system that analyzes data and generates recommendations.

[0277] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[0278] 2. Server:

[0279] It provides powerful computational resources for analyzing data.

[0280] A learning model and database are put into operation to manage user data over the long term.

[0281] 3. Cloud Services:

[0282] It works in conjunction with the server to perform data backups and real-time analysis.

[0283] System Operation

[0284] 1. Initial Setup and User Registration

[0285] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[0286] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0287] 2. Daily Health Check

[0288] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[0289] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[0290] 3. Nutrition and exercise program suggestions

[0291] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may recommend foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[0292] The emotion engine adjusts the suggestions based on the user's emotions. For example, if the user expresses fatigue, it will suggest relaxing exercises and meals.

[0293] The user reviews the suggestions and implements them as needed.

[0294] 4. Stress level monitoring and relaxation suggestions

[0295] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[0296] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[0297] The emotion engine also adjusts relaxation techniques based on the user's emotions, suggesting more effective relaxation methods if the user is showing high levels of stress, for example.

[0298] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[0299] Specific examples

[0300] 1. Initial Setup and User Registration

[0301] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[0302] Tanaka enters his name, age, gender, and past medical history and saves it.

[0303] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[0304] 2. Daily Health Check

[0305] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[0306] The server analyzes the scan data, assesses whether the skin is becoming increasingly dry and whether the posture is slightly distorted, and sends the results back to the user's device.

[0307] The mirror displays the analysis results to Tanaka, and the emotion engine determines that he is currently feeling stressed.

[0308] 3. Nutrition and exercise program suggestions

[0309] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[0310] The emotion engine analyzes Tanaka's emotional data and determines that she is feeling very tired, so it adds a suggestion for a relaxing yoga class.

[0311] Tanaka implements the suggestions and works to improve his health.

[0312] 4. Stress level monitoring and relaxation suggestions

[0313] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[0314] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[0315] Taking into account the "high level of stress" recognized by the emotion engine, the system further suggests "listening to relaxation music."

[0316] Tanaka performs deep breathing exercises and listens to music to reduce stress.

[0317] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating an emotion engine, more personalized suggestions can be made that reflect the user's emotional state.

[0318] The processing flow will be explained below.

[0319] Step 1:

[0320] The user stands in front of the mirror. The user device uses a sensor to detect the user's presence.

[0321] Step 2:

[0322] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[0323] Step 3:

[0324] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[0325] Step 4:

[0326] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[0327] Step 5:

[0328] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[0329] Step 6:

[0330] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[0331] Step 7:

[0332] The user's device generates nutritional and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[0333] Step 8:

[0334] The user device uses an emotion engine to analyze the scan data (especially facial expression data) and recognize the user's emotions, including joy, sadness, surprise, anger, etc.

[0335] Step 9:

[0336] The user device uses the recognition results of the emotion engine to further adjust nutritional intake suggestions and exercise program suggestions. For example, if the user feels very tired, the device will suggest relaxing exercises and meal plans.

[0337] Step 10:

[0338] The user can check the suggestions and implement them as necessary. The user device also provides support such as a guide and timer for implementing the suggestions.

[0339] Step 11:

[0340] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[0341] Step 12:

[0342] The server suggests appropriate relaxation techniques based on the user's stress level, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[0343] Step 13:

[0344] The user device further adjusts the relaxation techniques based on the recognition results of the emotion engine, for example, suggesting listening to relaxation music if the user shows high stress levels.

[0345] Step 14:

[0346] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[0347] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health and emotional state and provide suggestions for improvement.

[0348] Example 2

[0349] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0350] In today's modern living environment, it is difficult to efficiently manage one's health amidst busy daily lives. In particular, it is not easy to comprehensively grasp the condition of one's skin, posture, facial expressions, etc., and then provide appropriate health recommendations and relaxation methods based on that information. In addition, there is a lack of health management systems that take into account the impact of stress and emotional changes on health.

[0351] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0352] In this invention, the server includes a detection means for detecting when a user stands in front of a reflective surface, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, and an emotion analysis means for recognizing the user's emotional state and adjusting the suggestions. This enables users to easily monitor their health condition at home and obtain and implement specific improvement measures tailored to their individual conditions.

[0353] "Reflective surface" refers to a mirror or display on which a user can see their own reflection.

[0354] "Detection means" refers to a sensor or device that detects when a user stands in front of a reflective surface.

[0355] "Non-invasive" refers to a method of obtaining data without placing a physical burden on the user's body.

[0356] "Skin condition" refers to the dryness, moisture level, color, etc. of the user's skin.

[0357] "Facial expressions" refer to movements and changes in the user's face that indicate emotions and states.

[0358] "Posture" refers to the user's body position, balance, and standing style.

[0359] "Scanning means" refers to a camera or sensor used to capture the user's skin condition, facial expression, and posture.

[0360] "Analysis means" refers to software or hardware for analyzing the acquired scan data and assessing the user's health condition.

[0361] The "suggestion generation means" refers to a system for suggesting nutritional intake and exercise programs to the user based on the analysis results.

[0362] "Relaxation suggestion means" refers to a system for monitoring a user's stress level and suggesting appropriate relaxation methods.

[0363] "Emotion analysis means" refers to an analysis system that recognizes the user's emotional state and adjusts suggestions accordingly.

[0364] "Computing device" refers to a computer or server used to analyze data.

[0365] A "machine learning model" refers to an algorithm or system that uses large amounts of data to recognize and predict specific patterns.

[0366] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a reflective surface (e.g., a mirror), non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health condition. Furthermore, based on the analysis results, the system generates and provides nutritional intake suggestions and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining emotion analysis means, the present invention can recognize the user's emotions and more precisely adjust the suggestions.

[0367] System configuration overview

[0368] 1. User Device:

[0369] The mirror includes a scanning device integrated with it, specifically hardware such as a camera and infrared sensor to capture the user's skin condition, facial expression, and posture.

[0370] It has an integrated AI system that analyzes data and generates recommendations, including machine learning models for data analysis.

[0371] It is equipped with an emotion analysis tool that recognizes the user's emotions based on the scan data.

[0372] 2. Server:

[0373] Powerful computing equipment will be provided for analyzing the data, specifically a high-performance server equipped with a GPU.

[0374] The learning models and databases are operated to manage user data over time, using machine learning frameworks such as TensorFlow and PyTorch.

[0375] 3. Cloud Services:

[0376] It works in conjunction with servers to back up data and perform real-time analysis, using cloud services such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[0377] How to use

[0378] Initial Setup and User Registration

[0379] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[0380] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0381] Daily Health Check

[0382] The user device detects when the user stands in front of a reflective surface and automatically initiates a non-invasive scan, capturing information about skin condition, facial expression, and posture, with the data transmitted in real time to a server.

[0383] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[0384] Nutrition and exercise program suggestions

[0385] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, such as suggesting foods rich in vitamin E or doing 20 minutes of yoga.

[0386] The suggestion content is adjusted based on the user's emotions as recognized by the emotion analysis means. For example, if the user expresses fatigue, the suggestion of relaxing yoga will be added.

[0387] The user reviews the suggestions and implements them as needed.

[0388] Stress level monitoring and relaxation suggestions

[0389] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[0390] The server suggests appropriate relaxation techniques (e.g., 10 minutes of deep breathing exercises) based on the stress level and sends them to the user's terminal.

[0391] The system also adjusts relaxation techniques based on the user's emotions as detected by the emotion analysis means, suggesting listening to relaxation music if the user is showing signs of high stress, for example.

[0392] The user performs suggested relaxation techniques to reduce stress.

[0393] Specific examples

[0394] 1. Initial Setup and User Registration

[0395] When a user stands in front of the mirror for the first time, the mirror displays a basic information entry screen for the user: name, age, gender, and past medical history, and saves the information.

[0396] The server receives the information, creates a profile for the user, and notifies them that "registration is complete."

[0397] 2. Daily Health Check

[0398] The next morning, when the user stands in front of the mirror, the mirror automatically begins scanning and detects the condition of the skin and posture.

[0399] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[0400] The mirror displays the analysis results to the user, and the emotion analysis means determines that the user is currently feeling stressed.

[0401] 3. Nutrition and exercise program suggestions

[0402] Miller suggests users "eat foods containing vitamin E and do 20 minutes of stretching."

[0403] The emotion analysis means analyzes the user's emotion data and determines that the user is "feeling very tired," so a relaxing yoga suggestion is added.

[0404] Users implement the suggestions and work to improve their health.

[0405] 4. Stress level monitoring and relaxation suggestions

[0406] The mirror analyzes the user's facial expressions and assesses their stress level as "high."

[0407] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[0408] Taking into account the "high level of stress" recognized by the emotion analysis means, the system further suggests "listening to relaxation music."

[0409] The user performs deep breathing exercises and music to reduce stress.

[0410] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating emotion analysis means, more personalized suggestions that reflect the user's emotional state can be realized.

[0411] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0412] Step 1: User detection

[0413] The user device detects when the user stands in front of a reflective surface. Specifically, the sensor built into the user device detects the user's movement.

[0414] Input: Movement data from sensors

[0415] Data processing / calculation: The sensor analyzes movement in the area in front of the reflective surface to confirm the user's presence.

[0416] Output: Information that the user is in front of a reflective surface

[0417] Specific operation: The user device will issue a voice notification saying, "A user has been detected. Scanning will begin."

[0418] Step 2: Start Scan

[0419] The user device non-invasively scans the user's skin condition, facial expression, and posture using a camera and infrared sensor.

[0420] Input: Real-time video and infrared data of the user

[0421] Data processing / calculation: Preprocess the acquired data and extract features of skin condition, facial expression, and posture.

[0422] Output: Scan data (skin condition, facial expression, posture characteristics)

[0423] Specific operation: The user device displays "Scanning, please wait."

[0424] Step 3: Send data

[0425] The user terminal transmits the scan data to the server in real time.

[0426] Input: Scan data

[0427] Data processing / calculation: Data is divided into packets and sent securely over the Internet.

[0428] Output: Scan data sent to the server

[0429] Specific operation: The user device displays "Data is being sent."

[0430] Step 4: Data analysis

[0431] The server analyzes the received data using a machine learning model (generative AI model), specifically assessing the user's health status and analyzing their emotions.

[0432] Input: Scan data

[0433] Data processing / computation: Using machine learning models, estimate skin dryness, posture distortion, and emotions and health status from facial expressions.

[0434] Output: Health status assessment results and emotion analysis results

[0435] Specific operation: The server updates the status to "Data analysis in progress."

[0436] Step 5: Receive and display analysis results

[0437] The user terminal receives the analysis results from the server and displays them to the user.

[0438] Input: Analysis results sent from the server

[0439] Data processing / calculation: Receives analysis results and displays them in a format that is easy for users to understand.

[0440] Output: Analysis result screen

[0441] Specific operation: The user device notifies the user that "Analysis results are being displayed" and displays specific evaluation results such as "Skin dryness: Medium, Stress level: High" on the screen.

[0442] Step 6: Suggested nutrition and exercise program

[0443] The user's device will suggest optimal nutritional intake and exercise programs based on the analysis results.

[0444] Input: Health status assessment results and emotion analysis results

[0445] Data processing / calculation: Taking into account the user's current health and emotional state, suggestions are generated using a generative AI model.

[0446] Output: Suggested nutrition and exercise program

[0447] Specific actions: The user device displays the message "Eat foods containing vitamin E and do 20 minutes of yoga."

[0448] Step 7: Relaxation Suggestions

[0449] The user device will suggest appropriate relaxation techniques based on the stress level from the scan data.

[0450] Input: Sentiment analysis results

[0451] Data processing / computation: Generate suggestions for deep breathing exercises or relaxation music based on data indicating high stress levels.

[0452] Output: Suggested relaxation techniques

[0453] Specific actions: The user device displays the message, "We recommend that you practice deep breathing exercises for 10 minutes and listen to relaxation music."

[0454] Step 8: Implementation and Feedback

[0455] The user carries out the suggested nutritional intake, exercise program, and relaxation techniques, and the results are fed back to the user's terminal.

[0456] Input: User execution status data

[0457] Data processing / calculation: Collect execution data, store it in a database for the next proposal, and use it to retrain the model.

[0458] Output: Feedback data on execution status

[0459] Specific operation: The user terminal asks the user for feedback, saying, "Did you execute the suggestion? Please enter the result."

[0460] (Application example 2)

[0461] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0462] Until now, it has been difficult for users to understand their own health condition in detail and take appropriate measures based on that information. It has also been difficult for users to consciously manage their emotional state and stress level in their daily lives. Furthermore, physical stores such as cosmetics stores and wellness centers have had limited means of suggesting appropriate products to customers based on their individual skin condition and emotional state.

[0463] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a detection means for detecting when a user stands in front of a mirror; a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture; an analysis means for analyzing the scan data and evaluating the user's health status; a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results; a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques; and a product suggestion means for making optimal product suggestions based on the analysis results. This allows users to understand their health and emotional status in detail and take appropriate measures based on that information. Furthermore, it also enables physical stores such as cosmetics stores and wellness centers to individually suggest optimal products to customers.

[0464] A "user" is someone who uses the system to receive assessments of their health and emotional state and receive recommendations.

[0465] "Detection means" refers to a device such as a sensor or camera that detects when a user stands in front of a mirror.

[0466] "Scanning means" refers to technologies such as cameras and near-infrared sensors that non-invasively scan a user's skin condition, facial expression, and posture.

[0467] "Analysis Means" refers to the algorithms and machine learning models used to assess the health and emotional state of the User based on the data obtained by the Scanning Means.

[0468] "Suggestion generation means" refers to software or a system that has the function of generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[0469] "Relaxation suggestion tool" refers to software or a system that has the functionality to monitor a user's stress level and suggest relaxation techniques based on that level.

[0470] "Product suggestion means" refers to software or a system that has the function of suggesting optimal products based on the analysis results.

[0471] "Server" refers to a device that provides computing resources on a network for analyzing data, generating recommendations, managing user profiles, and so on.

[0472] "Non-invasive" refers to a method that obtains information without direct contact or damage to the body.

[0473] "Real-time" means that processing occurs immediately at the moment data is collected.

[0474] A "machine learning model" is an algorithm used in data analysis, and refers to a technology that makes predictions and classifications by learning from past data.

[0475] This invention is a system that non-invasively assesses a user's health and emotional state and makes appropriate product suggestions based on that assessment in order to improve customer service in brick-and-mortar stores.

[0476] System configuration overview

[0477] 1. User Device:

[0478] It includes cameras and sensors integrated into the mirror.

[0479] It has an integrated AI system built in that scans and performs initial analysis of data.

[0480] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[0481] 2. Server:

[0482] It provides high-performance computing resources to perform detailed analysis of scan data.

[0483] Manages learning models and databases, and stores and analyzes long-term user data.

[0484] 3. Cloud Services:

[0485] It works in conjunction with the server to perform data backups and real-time analysis.

[0486] System Operation

[0487] 1. Initial Setup and User Registration

[0488] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, and gender.

[0489] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0490] 2. Health Check and Sentiment Analysis

[0491] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[0492] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, emotions and stress levels from facial expressions, and sending the results to the user's device.

[0493] 3. Product proposal

[0494] The user terminal receives the analysis results from the server and generates optimal product proposals based on them.

[0495] The system uses an emotion engine to generate suggestions and suggests optimal products (e.g., moisturizing cream, relaxation oil, etc.) taking into account the user's emotional data.

[0496] Hardware and software used

[0497] Hardware: High-resolution cameras, sensors, smart mirrors

[0498] Software: OpenCV, Dlib, Keras (TensorFlow backend)

[0499] Specifically, the system scans the user's face using a camera and detects facial landmarks using OpenCV and Dlib. It then applies emotion and skin condition models using Keras to evaluate the user's emotion and skin health, which then leads to optimal product recommendations.

[0500] Specific examples

[0501] Here are some examples of prompts to input to a generative AI model:

[0502] "Create a program that suggests the best cosmetics and relaxation products based on the customer's skin condition and emotions. The program should include the following steps: 1) Scan the face using a camera, 2) Recognize facial landmarks, 3) Predict emotions and skin health, 4) Recommend products based on the prediction results."

[0503] This system allows users in physical stores to gain detailed information about their health and emotional state and receive personalized product recommendations based on that information.

[0504] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0505] Step 1:

[0506] When a user stands in front of a smart mirror in a store, the device detects this. The input here is data from sensors that detect the user's position and movement. The output is a signal that recognizes the user is in front of the mirror, which automatically starts the next scanning process.

[0507] Step 2:

[0508] The device scans the user's skin condition, facial expression, and posture. The input is image data obtained from high-resolution cameras and sensors. The device receives this scan data and performs initial data processing. The output is scanned image data, which is used as input for the next step.

[0509] Step 3:

[0510] The device sends the scan data to the server in real time. The input is the scan data acquired in the previous step. The device sends it to the server over the network. The output is the image data sent to the server. This data is then ready to be analyzed by the server.

[0511] Step 4:

[0512] The server analyzes the scan data and evaluates the health and emotional state. The input is the scan data sent from the device. The server extracts facial landmarks using OpenCV and Dlib, and inputs the data into the Keras model. The output is the health and emotional state assessment results. This output data is used to generate proposals.

[0513] Step 5:

[0514] The server generates optimal product suggestions based on the analysis results. The inputs are the health status assessment results and emotional status assessment results obtained in step 4. Based on this data, the server refers to pre-set rules and past data to generate appropriate product suggestions. The output is a specific product list. This list is sent to the terminal.

[0515] Step 6:

[0516] The terminal displays product suggestions to the user. The input is a list of product suggestions sent from the server. The terminal visually displays this list to the user. The output is a display screen where the user can review the product suggestions. The user can select a product based on the suggestions.

[0517] Through these steps, users can understand their own health and emotional state through the smart mirror and receive optimal product recommendations based on that information.

[0518] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0519] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0520] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0521] [Second embodiment]

[0522] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0523] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0524] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0525] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0526] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0527] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0528] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0529] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0530] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0531] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0532] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0533] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0534] This invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, it generates and provides users with nutritional intake and exercise program suggestions. It also has a function to monitor stress levels and suggest relaxation techniques based on the results.

[0535] System configuration overview

[0536] 1. User Device:

[0537] It includes a mirror section and an integrated scanning device.

[0538] It has a built-in integrated AI system that analyzes data and generates recommendations.

[0539] 2. Server:

[0540] It provides powerful computational resources for analyzing data.

[0541] A learning model and database are put into operation to manage user data over the long term.

[0542] 3. Cloud Services:

[0543] It works in conjunction with the server to perform data backups and real-time analysis.

[0544] System Operation

[0545] 1. Initial Setup and User Registration

[0546] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[0547] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0548] 2. Daily Health Check

[0549] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[0550] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results to the user's device.

[0551] 3. Nutrition and exercise program suggestions

[0552] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may suggest daily intake of foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[0553] The user reviews the suggestions and implements them as needed.

[0554] 4. Stress level monitoring and relaxation suggestions

[0555] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[0556] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[0557] The user performs suggested relaxation techniques to reduce stress.

[0558] Specific examples

[0559] 1. Initial Setup and User Registration

[0560] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[0561] Tanaka enters his name, age, gender, and past medical history and saves it.

[0562] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[0563] 2. Daily Health Check

[0564] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[0565] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[0566] The mirror displays the analysis results to Tanaka.

[0567] 3. Nutrition and exercise program suggestions

[0568] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[0569] Tanaka implements the suggestions and works to improve his health.

[0570] 4. Stress level monitoring and relaxation suggestions

[0571] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[0572] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[0573] Tanaka does deep breathing exercises to reduce stress.

[0574] The above is a description of the mode for carrying out the invention. This system allows users to easily monitor their health status at home and obtain and implement specific measures for improvement.

[0575] The processing flow will be explained below.

[0576] Step 1:

[0577] The user stands in front of the mirror. The user device detects the user's presence using a sensor that detects the user's movement.

[0578] Step 2:

[0579] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[0580] Step 3:

[0581] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[0582] Step 4:

[0583] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[0584] Step 5:

[0585] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[0586] Step 6:

[0587] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[0588] Step 7:

[0589] The user's device generates nutritional intake and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (e.g., yoga, stretching, etc.).

[0590] Step 8:

[0591] The user can check the suggestions and implement them as necessary. Support such as a guide and timer is also provided for the user device to implement the suggestions.

[0592] Step 9:

[0593] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[0594] Step 10:

[0595] The server suggests relaxation techniques based on stress levels, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[0596] Step 11:

[0597] The user terminal presents the received relaxation techniques to the user, provides specific guidance, and assists the user in carrying out the suggested relaxation techniques.

[0598] Step 12:

[0599] The user performs relaxation techniques to reduce stress, and the user device monitors the progress of the techniques and provides feedback as needed.

[0600] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health status and provide suggestions for improvement.

[0601] Example 1

[0602] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0603] Conventional health management systems struggled to provide completely non-invasive scans, real-time data analysis, and health improvement recommendations. Furthermore, insufficient analysis of scan data meant that users were unable to receive appropriate nutritional and exercise recommendations. Furthermore, the lack of real-time monitoring of stress levels and appropriate relaxation recommendations meant that users were unable to adequately manage stress in their daily lives.

[0604] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0605] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, a data transmission means for transmitting the scanned data to the server in real time, an analysis means for analyzing the scanned data using a machine learning model and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a result return means for returning the analysis results from the server to a user terminal, and a means for the user to execute the suggested nutritional intake suggestions and exercise program and transmit the feedback to the server. This enables the user to non-invasively manage their daily health and obtain appropriate health improvement measures and stress management measures in real time.

[0606] The following are definitions of key terms included in the rewritten claims:

[0607] "Detection means" refers to a sensor or device for detecting when a user stands in front of a mirror.

[0608] "Scanning means" refers to a device or system for non-invasively scanning a user's skin condition, facial expression, and posture.

[0609] "Data transmission means" refers to a communication device or protocol for transmitting scan data from a user terminal to a server in real time.

[0610] "Analysis means" refers to software or algorithms used to analyze scan data and assess the user's health status.

[0611] "Suggestion generation means" refers to a device or algorithm for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[0612] "Relaxation suggestion tools" refer to devices or algorithms that monitor stress levels and suggest appropriate relaxation techniques.

[0613] "Result return means" refers to a communication device or protocol for returning analysis results from the server to the user terminal.

[0614] "Machine Learning Model" refers to the trained algorithm or model used to analyze scan data.

[0615] "Feedback means" refers to a device or system that allows the user to carry out the suggested nutritional intake suggestions and exercise program and transmit the results to the server.

[0616] The present invention provides a system that allows users to easily manage their health in their daily lives. The system operates using the following hardware and software.

[0617] Hardware and software used

[0618] 1. User Device:

[0619] Mirror part: The mirror part used when standing in front of the user.

[0620] Scanning device: Equipped with a high-resolution camera and infrared sensors for non-invasively scanning skin condition, facial expressions, and posture.

[0621] Motion detection sensor: Used to detect when a user stands in front of the mirror.

[0622] Integrated AI system: Includes a built-in software system that analyzes data and generates recommendations.

[0623] 2. Server:

[0624] Computing resources: High-performance computing devices for analyzing data, including GPUs and high-performance CPUs.

[0625] Database: A data storage system for long-term management of user data.

[0626] Machine learning models: Operate trained deep learning models to analyze user data.

[0627] 3. Cloud Services:

[0628] Data Backup: Cloud storage for safe storage of data.

[0629] Real-time analytics: Cloud computing resources for analyzing data in real time.

[0630] System Operation Overview

[0631] 1. User Device:

[0632] When the user's device is started for the first time, it welcomes the user and displays a screen for entering basic information. The user enters basic information such as name, age, gender, and medical history. The basic information is encrypted using AES (Advanced Encryption Standard) and sent to the server. The server creates a user profile based on the received information and stores it in a database.

[0633] 2. Daily Health Check:

[0634] The next morning, when the user stands in front of the mirror, the motion detection sensor detects this and the scanning device begins a non-invasive scan. Skin condition, facial expression, and posture are scanned using a high-resolution camera and infrared sensor, and the scanned data is sent in real time to a server. The server then analyzes the received data using machine learning models to assess the user's health status. For example, it evaluates the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results back to the user's device.

[0635] 3. Analysis results and proposals:

[0636] The user device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, which are then provided to the user. For example, the system may suggest "eating foods containing vitamin E and doing 20 minutes of stretching." The user can then carry out the recommendations and send their feedback to the server.

[0637] 4. Stress level monitoring and relaxation suggestions:

[0638] The user device analyzes facial expression data to estimate the stress level in real time. The server then suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user device. The user can then perform the suggested relaxation techniques to reduce stress.

[0639] Specific examples and examples of prompts for generative AI models

[0640] Examples:

[0641] 1. Initial setup and user registration:

[0642] When Tanaka uses the system for the first time, a screen for entering basic information appears.

[0643] Tanaka enters his name, age, gender, and past medical history and saves it.

[0644] The server creates a profile for Tanaka and sends a notification back to the device that the profile has been saved.

[0645] 2. Daily Health Check:

[0646] The next morning, when Tanaka stands in front of the mirror, the device starts an automatic scan and sends the scanned data to the server.

[0647] The server analyzes the data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the device.

[0648] The terminal displays the analysis results to Tanaka.

[0649] 3. Nutrition and exercise program suggestions:

[0650] The device suggests to Tanaka, "Eat foods containing vitamin E and do 20 minutes of stretching."

[0651] Tanaka implements the suggestions and works to improve his health.

[0652] 4. Stress level monitoring and relaxation suggestions:

[0653] The device analyzes Tanaka's facial expression and assesses his stress level as "high."

[0654] The server suggests "10 minutes of deep breathing exercises" and displays it on the device.

[0655] Tanaka does deep breathing exercises to reduce stress.

[0656] Example prompt for a generative AI model:

[0657] "Please explain the process flow of a system that non-invasively scans a user's health status while they stand in front of a mirror and generates health improvement suggestions based on the analysis results."

[0658] This system allows users to non-invasively manage their daily health and provide appropriate health improvement and stress management strategies in real time.

[0659] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0660] Step 1: Enter basic user information

[0661] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information. The input screen includes items such as name, age, gender, and medical history. For example, the user might enter information such as "Ichiro Tanaka, 30 years old, male, no allergies." Input is done using a touch panel or voice recognition.

[0662] Input: Basic information entered by the user.

[0663] Output: The user's input information is saved in the system and used in the next step.

[0664] Step 2: Submit your input

[0665] The user terminal encrypts the input basic information and sends it to the server, using AES (Advanced Encryption Standard) to ensure data security.

[0666] Input: Basic information entered in step 1.

[0667] Output: The encrypted basic information is sent to the server.

[0668] Step 3: Create and save a profile

[0669] The server stores the received user information in a database and creates a user profile. After the profile is created, a completion notification is sent to the user's device.

[0670] Input: Encrypted basic information.

[0671] Output: The user profile is saved in the database and a completion notification is sent back to the user terminal.

[0672] Step 4: Detecting the user standing in front of a mirror

[0673] The user device detects when the user stands in front of the mirror using a built-in motion detection sensor, which can be an infrared sensor or a camera.

[0674] Input: Motion detection sensor data.

[0675] Output: The user is detected as standing in front of a mirror and the next scanning step is initiated.

[0676] Step 5: Run a scan

[0677] The user device activates a built-in non-invasive scanning device that scans the user's skin condition, facial expression, and posture. The scanning device uses a high-resolution camera and infrared sensor to record, in detail, the degree of skin moisture, abnormal posture, and subtle changes in facial expression.

[0678] Input: Sensory data of a user standing in front of a mirror.

[0679] Output: Scan data on skin condition, facial expression, and posture is generated.

[0680] Step 6: Send the scan data

[0681] The user device sends the scanned data to the server in real time, and the data is encrypted and sent over the network.

[0682] Input: Scan data.

[0683] Output: The encrypted scan data is sent to the server.

[0684] Step 7: Analyze your health status

[0685] The server then analyzes the received scan data using machine learning models, such as deep learning algorithms, to assess stress levels based on skin dryness, posture, and facial expressions.

[0686] Input: Encrypted scan data.

[0687] Output: The analysis results may include, for example, "skin is becoming increasingly dry," "posture is slightly distorted," and "stress level: high."

[0688] Step 8: Returning the analysis results

[0689] The server returns the analysis results to the user's terminal. The data is also encrypted here. The user's terminal displays the analysis results on its screen.

[0690] Input: Analysis results.

[0691] Output: The encrypted analysis results are sent to the user's terminal and displayed to the user.

[0692] Step 9: Generate proposals

[0693] Based on the health analysis results, the server generates optimal nutritional recommendations and exercise programs, such as "daily intake of foods containing vitamin C" and "specific exercise (yoga, stretching, etc.)."

[0694] Input: Analysis results.

[0695] Output: Proposals are generated and sent to the user device in the next step.

[0696] Step 10: Submit and view your proposal

[0697] The server transmits the generated proposal to the user terminal, which displays the proposal on its screen.

[0698] Input: Proposal content.

[0699] Output: The proposal is sent to the user's terminal and displayed to the user.

[0700] Step 11: Implementing the proposal

[0701] The user confirms the suggestions and implements them, for example, purchasing food supplements for vitamin E and stretching every morning.

[0702] Input: Proposal content.

[0703] Output: User performance feedback is generated and sent to the server in the next step.

[0704] Step 12: Submit your feedback

[0705] The user terminal transmits to the server the results of the user's implementation of the suggested nutritional intake suggestions and exercise program.

[0706] Input: User's performance feedback.

[0707] Output: The feedback data is sent to the server and stored in a database.

[0708] The above is a detailed description of the processing steps of the system and the specific operations at each step.

[0709] (Application example 1)

[0710] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0711] Conventional health management systems have difficulty monitoring the health status of individual users in real time and providing appropriate advice. In particular, in industrial environments, real-time understanding of workers' health status and immediate response are required, but current systems lack intelligent support for appropriately assessing and responding to workers' health risks.

[0712] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0713] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a means for non-invasively monitoring health in a wearable device worn by a worker, and a means for generating break and stretching suggestions based on the worker's health condition. This enables real-time monitoring of the health condition of workers in an industrial environment, enabling prompt and appropriate health management and improvement of the working environment.

[0714] The "detection means" is a device or technology for detecting that a user is standing in a specific position (for example, in front of a mirror).

[0715] "Scanning means" refers to a device or technology for non-invasively scanning a user's skin condition, facial expression, and posture.

[0716] "Analysis means" refers to functions and algorithms for analyzing scan data and assessing the user's health condition.

[0717] The "suggestion generation means" is a device or system for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[0718] "Relaxation suggestion means" refers to technologies or systems that monitor stress levels and suggest relaxation techniques.

[0719] A "wearable device" is a device that can be worn by workers and is used to monitor their health status in real time.

[0720] "Health monitoring means" refers to technologies and equipment for non-invasively monitoring workers' health using wearable devices.

[0721] A "rest suggestion means" is a function or system that suggests appropriate rest times and stretching timings based on the worker's health condition.

[0722] This invention is a system that monitors workers' health in real time and suggests appropriate breaks and stretching. The system consists of a wearable device, a server, and a cloud service.

[0723] System configuration overview

[0724] 1. Wearable devices:

[0725] It can be worn by workers and contains cameras and sensors to scan skin condition, facial expressions, and posture.

[0726] Data is collected non-invasively and transmitted to a server in real time.

[0727] 2. Server:

[0728] It provides powerful computational resources for analyzing the received data.

[0729] Evaluate the user's health status and generate appropriate suggestions.

[0730] Use databases to manage longitudinal health data.

[0731] 3. Cloud Services:

[0732] It works in conjunction with the server to back up data and perform real-time data analysis.

[0733] System Operation

[0734] 1. Initial Setup and Worker Registration:

[0735] When the wearable device is first turned on, it recognizes the worker and displays a screen for entering basic information, such as name, age, gender, and past medical history.

[0736] The server receives the input, creates a worker profile, stores it in a database, and sends a notification back to the wearable device once the profile is complete.

[0737] 2. Real-time monitoring:

[0738] The wearable device scans the worker's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time.

[0739] The server analyzes the data and evaluates the user's health status. For example, it calculates stress levels, posture distortion, and fatigue levels based on the level of dryness of the skin and facial expressions. The results are then sent to the wearable device.

[0740] 3. Proposal generation and notification:

[0741] Based on the analysis results, the server generates nutritional intake suggestions, exercise program suggestions, and rest suggestions, such as suggesting vitamin intake, short rest periods, and specific stretching exercises.

[0742] The wearable device can display these suggestions to the worker for confirmation, and if high stress levels are detected, the server will suggest appropriate relaxation techniques (e.g., deep breathing exercises) and display them on the device.

[0743] Hardware and software used

[0744] Wearable devices: smart glasses, smart watches, etc. with built-in cameras, sensors, and displays.

[0745] Server: High-performance analysis hardware (e.g., GPU server), database system (e.g., MySQL).

[0746] Cloud services: Real-time data analysis and backup capabilities, such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[0747] Analysis software: Use Python libraries (e.g., TensorFlow, Scikit-learn) to build machine learning models and perform data analysis.

[0748] Specific examples

[0749] Everyday use examples

[0750] 1. When worker A puts on the smart glasses for the first time, a basic information entry screen appears. After worker A enters the necessary information, the server receives the information and creates a profile.

[0751] 2. When the task begins, the smart glasses scan A's facial expressions and posture in real time and send the data to the server. The server analyzes the data and evaluates A's stress level and posture.

[0752] 3. If your stress level is determined to be high, you will be suggested to do 10 minutes of deep breathing exercises. If your posture is poor, a notification will appear on the glasses display urging you to correct your posture.

[0753] Example prompts for generative AI models

[0754] Text format:

[0755] A factory worker is wearing smart glasses. The camera built into the glasses captures facial expressions, posture, and fatigue levels while working, and we want to monitor his health condition in real time. Please write a program using Python to analyze the health data.

[0756] If stress levels are high, deep breathing exercises are suggested

[0757] If your posture is bad, we suggest correcting it.

[0758] If fatigue is high, a short rest is suggested

[0759] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0760] Step 1:

[0761] The user puts on the wearable device and performs the initial setup. When the device is first started up, a basic information entry screen is displayed, and the user enters information such as name, age, gender, and past medical history. This is the input, and user profile data is generated as the output and sent to the server. The server receives this data and stores it in a database for long-term management.

[0762] Step 2:

[0763] The wearable device collects data in real time. The device non-invasively scans the wearer's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time. The scan data is provided as input, and the server receives it as output and prepares it for analysis.

[0764] Step 3:

[0765] The server analyzes the received scan data. Specifically, it processes the data using machine learning models (e.g., TensorFlow) to evaluate the user's stress level, posture accuracy, and skin condition. The input is the scan data, and the output is the analysis results.

[0766] Step 4:

[0767] The server generates suggestions based on the analysis results. These suggestions include nutritional intake suggestions, exercise program suggestions, and rest suggestions based on the user's health condition. For example, if the stress level is high, a suggestion for deep breathing exercises is generated. The input is the analysis results, and the output is the generated suggestions.

[0768] Step 5:

[0769] The server notifies the wearable device of the proposed content. The server sends the generated proposed content to the wearable device and displays it on the device's display. The user can check it and implement the proposed content as necessary. The input is the proposed content, and the output is a notification to the user.

[0770] Step 6:

[0771] Suggesting and implementing relaxation techniques: If the user's stress level is high, the server generates a suggestion for an appropriate relaxation technique (e.g., deep breathing exercises) and notifies the wearable device. The user then sees this and performs the relaxation technique, thereby reducing stress. The input is the analysis result, and the output is the relaxation suggestion.

[0772] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0773] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when the user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, the system generates and provides nutritional intake and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining this system with an emotion engine, the system can recognize the user's emotions and more precisely adjust the suggestions.

[0774] System configuration overview

[0775] 1. User Device:

[0776] It includes a mirror section and an integrated scanning device.

[0777] It has a built-in integrated AI system that analyzes data and generates recommendations.

[0778] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[0779] 2. Server:

[0780] It provides powerful computational resources for analyzing data.

[0781] A learning model and database are put into operation to manage user data over the long term.

[0782] 3. Cloud Services:

[0783] It works in conjunction with the server to perform data backups and real-time analysis.

[0784] System Operation

[0785] 1. Initial Setup and User Registration

[0786] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[0787] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0788] 2. Daily Health Check

[0789] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[0790] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[0791] 3. Nutrition and exercise program suggestions

[0792] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may recommend foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[0793] The emotion engine adjusts the suggestions based on the user's emotions. For example, if the user expresses fatigue, it will suggest relaxing exercises and meals.

[0794] The user reviews the suggestions and implements them as needed.

[0795] 4. Stress level monitoring and relaxation suggestions

[0796] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[0797] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[0798] The emotion engine also adjusts relaxation techniques based on the user's emotions, suggesting more effective relaxation methods if the user is showing high levels of stress, for example.

[0799] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[0800] Specific examples

[0801] 1. Initial Setup and User Registration

[0802] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[0803] Tanaka enters his name, age, gender, and past medical history and saves it.

[0804] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[0805] 2. Daily Health Check

[0806] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[0807] The server analyzes the scan data, assesses whether the skin is becoming increasingly dry and whether the posture is slightly distorted, and sends the results back to the user's device.

[0808] The mirror displays the analysis results to Tanaka, and the emotion engine determines that he is currently feeling stressed.

[0809] 3. Nutrition and exercise program suggestions

[0810] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[0811] The emotion engine analyzes Tanaka's emotional data and determines that she is feeling very tired, so it adds a suggestion for a relaxing yoga class.

[0812] Tanaka implements the suggestions and works to improve his health.

[0813] 4. Stress level monitoring and relaxation suggestions

[0814] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[0815] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[0816] Taking into account the "high level of stress" recognized by the emotion engine, the system further suggests "listening to relaxation music."

[0817] Tanaka performs deep breathing exercises and listens to music to reduce stress.

[0818] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating an emotion engine, more personalized suggestions can be made that reflect the user's emotional state.

[0819] The processing flow will be explained below.

[0820] Step 1:

[0821] The user stands in front of the mirror. The user device uses a sensor to detect the user's presence.

[0822] Step 2:

[0823] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[0824] Step 3:

[0825] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[0826] Step 4:

[0827] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[0828] Step 5:

[0829] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[0830] Step 6:

[0831] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[0832] Step 7:

[0833] The user's device generates nutritional and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[0834] Step 8:

[0835] The user device uses an emotion engine to analyze the scan data (especially facial expression data) and recognize the user's emotions, including joy, sadness, surprise, anger, etc.

[0836] Step 9:

[0837] The user device uses the recognition results of the emotion engine to further adjust nutritional intake suggestions and exercise program suggestions. For example, if the user feels very tired, the device will suggest relaxing exercises and meal plans.

[0838] Step 10:

[0839] The user can check the suggestions and implement them as necessary. The user device also provides support such as a guide and timer for implementing the suggestions.

[0840] Step 11:

[0841] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[0842] Step 12:

[0843] The server suggests appropriate relaxation techniques based on the user's stress level, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[0844] Step 13:

[0845] The user device further adjusts the relaxation techniques based on the recognition results of the emotion engine, for example, suggesting listening to relaxation music if the user shows high stress levels.

[0846] Step 14:

[0847] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[0848] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health and emotional state and provide suggestions for improvement.

[0849] Example 2

[0850] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0851] In today's modern living environment, it is difficult to efficiently manage one's health amidst busy daily lives. In particular, it is not easy to comprehensively grasp the condition of one's skin, posture, facial expressions, etc., and then provide appropriate health recommendations and relaxation methods based on that information. In addition, there is a lack of health management systems that take into account the impact of stress and emotional changes on health.

[0852] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0853] In this invention, the server includes a detection means for detecting when a user stands in front of a reflective surface, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, and an emotion analysis means for recognizing the user's emotional state and adjusting the suggestions. This enables users to easily monitor their health condition at home and obtain and implement specific improvement measures tailored to their individual conditions.

[0854] "Reflective surface" refers to a mirror or display on which a user can see their own reflection.

[0855] "Detection means" refers to a sensor or device that detects when a user stands in front of a reflective surface.

[0856] "Non-invasive" refers to a method of obtaining data without placing a physical burden on the user's body.

[0857] "Skin condition" refers to the dryness, moisture level, color, etc. of the user's skin.

[0858] "Facial expressions" refer to movements and changes in the user's face that indicate emotions and states.

[0859] "Posture" refers to the user's body position, balance, and standing style.

[0860] "Scanning means" refers to a camera or sensor used to capture the user's skin condition, facial expression, and posture.

[0861] "Analysis means" refers to software or hardware for analyzing the acquired scan data and assessing the user's health condition.

[0862] The "suggestion generation means" refers to a system for suggesting nutritional intake and exercise programs to the user based on the analysis results.

[0863] "Relaxation suggestion means" refers to a system for monitoring a user's stress level and suggesting appropriate relaxation methods.

[0864] "Emotion analysis means" refers to an analysis system that recognizes the user's emotional state and adjusts suggestions accordingly.

[0865] "Computing device" refers to a computer or server used to analyze data.

[0866] A "machine learning model" refers to an algorithm or system that uses large amounts of data to recognize and predict specific patterns.

[0867] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a reflective surface (e.g., a mirror), non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health condition. Furthermore, based on the analysis results, the system generates and provides nutritional intake suggestions and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining emotion analysis means, the present invention can recognize the user's emotions and more precisely adjust the suggestions.

[0868] System configuration overview

[0869] 1. User Device:

[0870] The mirror includes a scanning device integrated with it, specifically hardware such as a camera and infrared sensor to capture the user's skin condition, facial expression, and posture.

[0871] It has an integrated AI system that analyzes data and generates recommendations, including machine learning models for data analysis.

[0872] It is equipped with an emotion analysis tool that recognizes the user's emotions based on the scan data.

[0873] 2. Server:

[0874] Powerful computing equipment will be provided for analyzing the data, specifically a high-performance server equipped with a GPU.

[0875] The learning models and databases are operated to manage user data over time, using machine learning frameworks such as TensorFlow and PyTorch.

[0876] 3. Cloud Services:

[0877] It works in conjunction with servers to back up data and perform real-time analysis, using cloud services such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[0878] How to use

[0879] Initial Setup and User Registration

[0880] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[0881] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0882] Daily Health Check

[0883] The user device detects when the user stands in front of a reflective surface and automatically initiates a non-invasive scan, capturing information about skin condition, facial expression, and posture, with the data transmitted in real time to a server.

[0884] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[0885] Nutrition and exercise program suggestions

[0886] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, such as suggesting foods rich in vitamin E or doing 20 minutes of yoga.

[0887] The suggestion content is adjusted based on the user's emotions as recognized by the emotion analysis means. For example, if the user expresses fatigue, the suggestion of relaxing yoga will be added.

[0888] The user reviews the suggestions and implements them as needed.

[0889] Stress level monitoring and relaxation suggestions

[0890] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[0891] The server suggests appropriate relaxation techniques (e.g., 10 minutes of deep breathing exercises) based on the stress level and sends them to the user's terminal.

[0892] The system also adjusts relaxation techniques based on the user's emotions as detected by the emotion analysis means, suggesting listening to relaxation music if the user is showing signs of high stress, for example.

[0893] The user performs suggested relaxation techniques to reduce stress.

[0894] Specific examples

[0895] 1. Initial Setup and User Registration

[0896] When a user stands in front of the mirror for the first time, the mirror displays a basic information entry screen for the user: name, age, gender, and past medical history, and saves the information.

[0897] The server receives the information, creates a profile for the user, and notifies them that "registration is complete."

[0898] 2. Daily Health Check

[0899] The next morning, when the user stands in front of the mirror, the mirror automatically begins scanning and detects the condition of the skin and posture.

[0900] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[0901] The mirror displays the analysis results to the user, and the emotion analysis means determines that the user is currently feeling stressed.

[0902] 3. Nutrition and exercise program suggestions

[0903] Miller suggests users "eat foods containing vitamin E and do 20 minutes of stretching."

[0904] The emotion analysis means analyzes the user's emotion data and determines that the user is "feeling very tired," so a relaxing yoga suggestion is added.

[0905] Users implement the suggestions and work to improve their health.

[0906] 4. Stress level monitoring and relaxation suggestions

[0907] The mirror analyzes the user's facial expressions and assesses their stress level as "high."

[0908] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[0909] Taking into account the "high level of stress" recognized by the emotion analysis means, the system further suggests "listening to relaxation music."

[0910] The user performs deep breathing exercises and music to reduce stress.

[0911] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating emotion analysis means, more personalized suggestions that reflect the user's emotional state can be realized.

[0912] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0913] Step 1: User detection

[0914] The user device detects when the user stands in front of a reflective surface. Specifically, the sensor built into the user device detects the user's movement.

[0915] Input: Movement data from sensors

[0916] Data processing / calculation: The sensor analyzes movement in the area in front of the reflective surface to confirm the user's presence.

[0917] Output: Information that the user is in front of a reflective surface

[0918] Specific operation: The user device will issue a voice notification saying, "A user has been detected. Scanning will begin."

[0919] Step 2: Start Scan

[0920] The user device non-invasively scans the user's skin condition, facial expression, and posture using a camera and infrared sensor.

[0921] Input: Real-time video and infrared data of the user

[0922] Data processing / calculation: Preprocess the acquired data and extract features of skin condition, facial expression, and posture.

[0923] Output: Scan data (skin condition, facial expression, posture characteristics)

[0924] Specific operation: The user device displays "Scanning, please wait."

[0925] Step 3: Send data

[0926] The user terminal transmits the scan data to the server in real time.

[0927] Input: Scan data

[0928] Data processing / calculation: Data is divided into packets and sent securely over the Internet.

[0929] Output: Scan data sent to the server

[0930] Specific operation: The user device displays "Data is being sent."

[0931] Step 4: Data analysis

[0932] The server analyzes the received data using a machine learning model (generative AI model), specifically assessing the user's health status and analyzing their emotions.

[0933] Input: Scan data

[0934] Data processing / computation: Using machine learning models, estimate skin dryness, posture distortion, and emotions and health status from facial expressions.

[0935] Output: Health status assessment results and emotion analysis results

[0936] Specific operation: The server updates the status to "Data analysis in progress."

[0937] Step 5: Receive and display analysis results

[0938] The user terminal receives the analysis results from the server and displays them to the user.

[0939] Input: Analysis results sent from the server

[0940] Data processing / calculation: Receives analysis results and displays them in a format that is easy for users to understand.

[0941] Output: Analysis result screen

[0942] Specific operation: The user device notifies the user that "Analysis results are being displayed" and displays specific evaluation results such as "Skin dryness: Medium, Stress level: High" on the screen.

[0943] Step 6: Suggested nutrition and exercise program

[0944] The user's device will suggest optimal nutritional intake and exercise programs based on the analysis results.

[0945] Input: Health status assessment results and emotion analysis results

[0946] Data processing / calculation: Taking into account the user's current health and emotional state, suggestions are generated using a generative AI model.

[0947] Output: Suggested nutrition and exercise program

[0948] Specific actions: The user device displays the message "Eat foods containing vitamin E and do 20 minutes of yoga."

[0949] Step 7: Relaxation Suggestions

[0950] The user device will suggest appropriate relaxation techniques based on the stress level from the scan data.

[0951] Input: Sentiment analysis results

[0952] Data processing / computation: Generate suggestions for deep breathing exercises or relaxation music based on data indicating high stress levels.

[0953] Output: Suggested relaxation techniques

[0954] Specific actions: The user device displays the message, "We recommend that you practice deep breathing exercises for 10 minutes and listen to relaxation music."

[0955] Step 8: Implementation and Feedback

[0956] The user carries out the suggested nutritional intake, exercise program, and relaxation techniques, and the results are fed back to the user's terminal.

[0957] Input: User execution status data

[0958] Data processing / calculation: Collect execution data, store it in a database for the next proposal, and use it to retrain the model.

[0959] Output: Feedback data on execution status

[0960] Specific operation: The user terminal asks the user for feedback, saying, "Did you execute the suggestion? Please enter the result."

[0961] (Application example 2)

[0962] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0963] Until now, it has been difficult for users to understand their own health condition in detail and take appropriate measures based on that information. It has also been difficult for users to consciously manage their emotional state and stress level in their daily lives. Furthermore, physical stores such as cosmetics stores and wellness centers have had limited means of suggesting appropriate products to customers based on their individual skin condition and emotional state.

[0964] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a detection means for detecting when a user stands in front of a mirror; a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture; an analysis means for analyzing the scan data and evaluating the user's health status; a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results; a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques; and a product suggestion means for making optimal product suggestions based on the analysis results. This allows users to understand their health and emotional status in detail and take appropriate measures based on that information. Furthermore, it also enables physical stores such as cosmetics stores and wellness centers to individually suggest optimal products to customers.

[0965] A "user" is someone who uses the system to receive assessments of their health and emotional state and receive recommendations.

[0966] "Detection means" refers to a device such as a sensor or camera that detects when a user stands in front of a mirror.

[0967] "Scanning means" refers to technologies such as cameras and near-infrared sensors that non-invasively scan a user's skin condition, facial expression, and posture.

[0968] "Analysis Means" refers to the algorithms and machine learning models used to assess the health and emotional state of the User based on the data obtained by the Scanning Means.

[0969] "Suggestion generation means" refers to software or a system that has the function of generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[0970] "Relaxation suggestion tool" refers to software or a system that has the functionality to monitor a user's stress level and suggest relaxation techniques based on that level.

[0971] "Product suggestion means" refers to software or a system that has the function of suggesting optimal products based on the analysis results.

[0972] "Server" refers to a device that provides computing resources on a network for analyzing data, generating recommendations, managing user profiles, and so on.

[0973] "Non-invasive" refers to a method that obtains information without direct contact or damage to the body.

[0974] "Real-time" means that processing occurs immediately at the moment data is collected.

[0975] A "machine learning model" is an algorithm used in data analysis, and refers to a technology that makes predictions and classifications by learning from past data.

[0976] This invention is a system that non-invasively assesses a user's health and emotional state and makes appropriate product suggestions based on that assessment in order to improve customer service in brick-and-mortar stores.

[0977] System configuration overview

[0978] 1. User Device:

[0979] It includes cameras and sensors integrated into the mirror.

[0980] It has an integrated AI system built in that scans and performs initial analysis of data.

[0981] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[0982] 2. Server:

[0983] It provides high-performance computing resources to perform detailed analysis of scan data.

[0984] Manages learning models and databases, and stores and analyzes long-term user data.

[0985] 3. Cloud Services:

[0986] It works in conjunction with the server to perform data backups and real-time analysis.

[0987] System Operation

[0988] 1. Initial Setup and User Registration

[0989] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, and gender.

[0990] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[0991] 2. Health Check and Sentiment Analysis

[0992] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[0993] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, emotions and stress levels from facial expressions, and sending the results to the user's device.

[0994] 3. Product proposal

[0995] The user terminal receives the analysis results from the server and generates optimal product proposals based on them.

[0996] The system uses an emotion engine to generate suggestions and suggests optimal products (e.g., moisturizing cream, relaxation oil, etc.) taking into account the user's emotional data.

[0997] Hardware and software used

[0998] Hardware: High-resolution cameras, sensors, smart mirrors

[0999] Software: OpenCV, Dlib, Keras (TensorFlow backend)

[1000] Specifically, the system scans the user's face using a camera and detects facial landmarks using OpenCV and Dlib. It then applies emotion and skin condition models using Keras to evaluate the user's emotion and skin health, which then leads to optimal product recommendations.

[1001] Specific examples

[1002] Here are some examples of prompts to input to a generative AI model:

[1003] "Create a program that suggests the best cosmetics and relaxation products based on the customer's skin condition and emotions. The program should include the following steps: 1) Scan the face using a camera, 2) Recognize facial landmarks, 3) Predict emotions and skin health, 4) Recommend products based on the prediction results."

[1004] This system allows users in physical stores to gain detailed information about their health and emotional state and receive personalized product recommendations based on that information.

[1005] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1006] Step 1:

[1007] When a user stands in front of a smart mirror in a store, the device detects this. The input here is data from sensors that detect the user's position and movement. The output is a signal that recognizes the user is in front of the mirror, which automatically starts the next scanning process.

[1008] Step 2:

[1009] The device scans the user's skin condition, facial expression, and posture. The input is image data obtained from high-resolution cameras and sensors. The device receives this scan data and performs initial data processing. The output is scanned image data, which is used as input for the next step.

[1010] Step 3:

[1011] The device sends the scan data to the server in real time. The input is the scan data acquired in the previous step. The device sends it to the server over the network. The output is the image data sent to the server. This data is then ready to be analyzed by the server.

[1012] Step 4:

[1013] The server analyzes the scan data and evaluates the health and emotional state. The input is the scan data sent from the device. The server extracts facial landmarks using OpenCV and Dlib, and inputs the data into the Keras model. The output is the health and emotional state assessment results. This output data is used to generate proposals.

[1014] Step 5:

[1015] The server generates optimal product suggestions based on the analysis results. The inputs are the health status assessment results and emotional status assessment results obtained in step 4. Based on this data, the server refers to pre-set rules and past data to generate appropriate product suggestions. The output is a specific product list. This list is sent to the terminal.

[1016] Step 6:

[1017] The terminal displays product suggestions to the user. The input is a list of product suggestions sent from the server. The terminal visually displays this list to the user. The output is a display screen where the user can review the product suggestions. The user can select a product based on the suggestions.

[1018] Through these steps, users can understand their own health and emotional state through the smart mirror and receive optimal product recommendations based on that information.

[1019] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1020] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1021] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1022] [Third embodiment]

[1023] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1024] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1026] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1027] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1028] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1030] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1031] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1033] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1034] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1035] This invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, it generates and provides users with nutritional intake and exercise program suggestions. It also has a function to monitor stress levels and suggest relaxation techniques based on the results.

[1036] System configuration overview

[1037] 1. User Device:

[1038] It includes a mirror section and an integrated scanning device.

[1039] It has a built-in integrated AI system that analyzes data and generates recommendations.

[1040] 2. Server:

[1041] It provides powerful computational resources for analyzing data.

[1042] A learning model and database are put into operation to manage user data over the long term.

[1043] 3. Cloud Services:

[1044] It works in conjunction with the server to perform data backups and real-time analysis.

[1045] System Operation

[1046] 1. Initial Setup and User Registration

[1047] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[1048] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1049] 2. Daily Health Check

[1050] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[1051] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results to the user's device.

[1052] 3. Nutrition and exercise program suggestions

[1053] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may suggest daily intake of foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[1054] The user reviews the suggestions and implements them as needed.

[1055] 4. Stress level monitoring and relaxation suggestions

[1056] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[1057] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[1058] The user performs suggested relaxation techniques to reduce stress.

[1059] Specific examples

[1060] 1. Initial Setup and User Registration

[1061] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[1062] Tanaka enters his name, age, gender, and past medical history and saves it.

[1063] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[1064] 2. Daily Health Check

[1065] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[1066] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[1067] The mirror displays the analysis results to Tanaka.

[1068] 3. Nutrition and exercise program suggestions

[1069] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[1070] Tanaka implements the suggestions and works to improve his health.

[1071] 4. Stress level monitoring and relaxation suggestions

[1072] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[1073] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[1074] Tanaka does deep breathing exercises to reduce stress.

[1075] The above is a description of the mode for carrying out the invention. This system allows users to easily monitor their health status at home and obtain and implement specific measures for improvement.

[1076] The processing flow will be explained below.

[1077] Step 1:

[1078] The user stands in front of the mirror. The user device detects the user's presence using a sensor that detects the user's movement.

[1079] Step 2:

[1080] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[1081] Step 3:

[1082] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[1083] Step 4:

[1084] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[1085] Step 5:

[1086] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[1087] Step 6:

[1088] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[1089] Step 7:

[1090] The user's device generates nutritional intake and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (e.g., yoga, stretching, etc.).

[1091] Step 8:

[1092] The user can check the suggestions and implement them as necessary. Support such as a guide and timer is also provided for the user device to implement the suggestions.

[1093] Step 9:

[1094] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[1095] Step 10:

[1096] The server suggests relaxation techniques based on stress levels, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[1097] Step 11:

[1098] The user terminal presents the received relaxation techniques to the user, provides specific guidance, and assists the user in carrying out the suggested relaxation techniques.

[1099] Step 12:

[1100] The user performs relaxation techniques to reduce stress, and the user device monitors the progress of the techniques and provides feedback as needed.

[1101] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health status and provide suggestions for improvement.

[1102] Example 1

[1103] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1104] Conventional health management systems struggled to provide completely non-invasive scans, real-time data analysis, and health improvement recommendations. Furthermore, insufficient analysis of scan data meant that users were unable to receive appropriate nutritional and exercise recommendations. Furthermore, the lack of real-time monitoring of stress levels and appropriate relaxation recommendations meant that users were unable to adequately manage stress in their daily lives.

[1105] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1106] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, a data transmission means for transmitting the scanned data to the server in real time, an analysis means for analyzing the scanned data using a machine learning model and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a result return means for returning the analysis results from the server to a user terminal, and a means for the user to execute the suggested nutritional intake suggestions and exercise program and transmit the feedback to the server. This enables the user to non-invasively manage their daily health and obtain appropriate health improvement measures and stress management measures in real time.

[1107] The following are definitions of key terms included in the rewritten claims:

[1108] "Detection means" refers to a sensor or device for detecting when a user stands in front of a mirror.

[1109] "Scanning means" refers to a device or system for non-invasively scanning a user's skin condition, facial expression, and posture.

[1110] "Data transmission means" refers to a communication device or protocol for transmitting scan data from a user terminal to a server in real time.

[1111] "Analysis means" refers to software or algorithms used to analyze scan data and assess the user's health status.

[1112] "Suggestion generation means" refers to a device or algorithm for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[1113] "Relaxation suggestion tools" refer to devices or algorithms that monitor stress levels and suggest appropriate relaxation techniques.

[1114] "Result return means" refers to a communication device or protocol for returning analysis results from the server to the user terminal.

[1115] "Machine Learning Model" refers to the trained algorithm or model used to analyze scan data.

[1116] "Feedback means" refers to a device or system that allows the user to carry out the suggested nutritional intake suggestions and exercise program and transmit the results to the server.

[1117] The present invention provides a system that allows users to easily manage their health in their daily lives. The system operates using the following hardware and software.

[1118] Hardware and software used

[1119] 1. User Device:

[1120] Mirror part: The mirror part used when standing in front of the user.

[1121] Scanning device: Equipped with a high-resolution camera and infrared sensors for non-invasively scanning skin condition, facial expressions, and posture.

[1122] Motion detection sensor: Used to detect when a user stands in front of the mirror.

[1123] Integrated AI system: Includes a built-in software system that analyzes data and generates recommendations.

[1124] 2. Server:

[1125] Computing resources: High-performance computing devices for analyzing data, including GPUs and high-performance CPUs.

[1126] Database: A data storage system for long-term management of user data.

[1127] Machine learning models: Operate trained deep learning models to analyze user data.

[1128] 3. Cloud Services:

[1129] Data Backup: Cloud storage for safe storage of data.

[1130] Real-time analytics: Cloud computing resources for analyzing data in real time.

[1131] System Operation Overview

[1132] 1. User Device:

[1133] When the user's device is started for the first time, it welcomes the user and displays a screen for entering basic information. The user enters basic information such as name, age, gender, and medical history. The basic information is encrypted using AES (Advanced Encryption Standard) and sent to the server. The server creates a user profile based on the received information and stores it in a database.

[1134] 2. Daily Health Check:

[1135] The next morning, when the user stands in front of the mirror, the motion detection sensor detects this and the scanning device begins a non-invasive scan. Skin condition, facial expression, and posture are scanned using a high-resolution camera and infrared sensor, and the scanned data is sent in real time to a server. The server then analyzes the received data using machine learning models to assess the user's health status. For example, it evaluates the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results back to the user's device.

[1136] 3. Analysis results and proposals:

[1137] The user device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, which are then provided to the user. For example, the system may suggest "eating foods containing vitamin E and doing 20 minutes of stretching." The user can then carry out the recommendations and send their feedback to the server.

[1138] 4. Stress level monitoring and relaxation suggestions:

[1139] The user device analyzes facial expression data to estimate the stress level in real time. The server then suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user device. The user can then perform the suggested relaxation techniques to reduce stress.

[1140] Specific examples and examples of prompts for generative AI models

[1141] Examples:

[1142] 1. Initial setup and user registration:

[1143] When Tanaka uses the system for the first time, a screen for entering basic information appears.

[1144] Tanaka enters his name, age, gender, and past medical history and saves it.

[1145] The server creates a profile for Tanaka and sends a notification back to the device that the profile has been saved.

[1146] 2. Daily Health Check:

[1147] The next morning, when Tanaka stands in front of the mirror, the device starts an automatic scan and sends the scanned data to the server.

[1148] The server analyzes the data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the device.

[1149] The terminal displays the analysis results to Tanaka.

[1150] 3. Nutrition and exercise program suggestions:

[1151] The device suggests to Tanaka, "Eat foods containing vitamin E and do 20 minutes of stretching."

[1152] Tanaka implements the suggestions and works to improve his health.

[1153] 4. Stress level monitoring and relaxation suggestions:

[1154] The device analyzes Tanaka's facial expression and assesses his stress level as "high."

[1155] The server suggests "10 minutes of deep breathing exercises" and displays it on the device.

[1156] Tanaka does deep breathing exercises to reduce stress.

[1157] Example prompt for a generative AI model:

[1158] "Please explain the process flow of a system that non-invasively scans a user's health status while they stand in front of a mirror and generates health improvement suggestions based on the analysis results."

[1159] This system allows users to non-invasively manage their daily health and provide appropriate health improvement and stress management strategies in real time.

[1160] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1161] Step 1: Enter basic user information

[1162] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information. The input screen includes items such as name, age, gender, and medical history. For example, the user might enter information such as "Ichiro Tanaka, 30 years old, male, no allergies." Input is done using a touch panel or voice recognition.

[1163] Input: Basic information entered by the user.

[1164] Output: The user's input information is saved in the system and used in the next step.

[1165] Step 2: Submit your input

[1166] The user terminal encrypts the input basic information and sends it to the server, using AES (Advanced Encryption Standard) to ensure data security.

[1167] Input: Basic information entered in step 1.

[1168] Output: The encrypted basic information is sent to the server.

[1169] Step 3: Create and save a profile

[1170] The server stores the received user information in a database and creates a user profile. After the profile is created, a completion notification is sent to the user's device.

[1171] Input: Encrypted basic information.

[1172] Output: The user profile is saved in the database and a completion notification is sent back to the user terminal.

[1173] Step 4: Detecting the user standing in front of a mirror

[1174] The user device detects when the user stands in front of the mirror using a built-in motion detection sensor, which can be an infrared sensor or a camera.

[1175] Input: Motion detection sensor data.

[1176] Output: The user is detected as standing in front of a mirror and the next scanning step is initiated.

[1177] Step 5: Run a scan

[1178] The user device activates a built-in non-invasive scanning device that scans the user's skin condition, facial expression, and posture. The scanning device uses a high-resolution camera and infrared sensor to record, in detail, the degree of skin moisture, abnormal posture, and subtle changes in facial expression.

[1179] Input: Sensory data of a user standing in front of a mirror.

[1180] Output: Scan data on skin condition, facial expression, and posture is generated.

[1181] Step 6: Send the scan data

[1182] The user device sends the scanned data to the server in real time, and the data is encrypted and sent over the network.

[1183] Input: Scan data.

[1184] Output: The encrypted scan data is sent to the server.

[1185] Step 7: Analyze your health status

[1186] The server then analyzes the received scan data using machine learning models, such as deep learning algorithms, to assess stress levels based on skin dryness, posture, and facial expressions.

[1187] Input: Encrypted scan data.

[1188] Output: The analysis results may include, for example, "skin is becoming increasingly dry," "posture is slightly distorted," and "stress level: high."

[1189] Step 8: Returning the analysis results

[1190] The server returns the analysis results to the user's terminal. The data is also encrypted here. The user's terminal displays the analysis results on its screen.

[1191] Input: Analysis results.

[1192] Output: The encrypted analysis results are sent to the user's terminal and displayed to the user.

[1193] Step 9: Generate proposals

[1194] Based on the health analysis results, the server generates optimal nutritional recommendations and exercise programs, such as "daily intake of foods containing vitamin C" and "specific exercise (yoga, stretching, etc.)."

[1195] Input: Analysis results.

[1196] Output: Proposals are generated and sent to the user device in the next step.

[1197] Step 10: Submit and view your proposal

[1198] The server transmits the generated proposal to the user terminal, which displays the proposal on its screen.

[1199] Input: Proposal content.

[1200] Output: The proposal is sent to the user's terminal and displayed to the user.

[1201] Step 11: Implementing the proposal

[1202] The user confirms the suggestions and implements them, for example, purchasing food supplements for vitamin E and stretching every morning.

[1203] Input: Proposal content.

[1204] Output: User performance feedback is generated and sent to the server in the next step.

[1205] Step 12: Submit your feedback

[1206] The user terminal transmits to the server the results of the user's implementation of the suggested nutritional intake suggestions and exercise program.

[1207] Input: User's performance feedback.

[1208] Output: The feedback data is sent to the server and stored in a database.

[1209] The above is a detailed description of the processing steps of the system and the specific operations at each step.

[1210] (Application example 1)

[1211] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1212] Conventional health management systems have difficulty monitoring the health status of individual users in real time and providing appropriate advice. In particular, in industrial environments, real-time understanding of workers' health status and immediate response are required, but current systems lack intelligent support for appropriately assessing and responding to workers' health risks.

[1213] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1214] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a means for non-invasively monitoring health in a wearable device worn by a worker, and a means for generating break and stretching suggestions based on the worker's health condition. This enables real-time monitoring of the health condition of workers in an industrial environment, enabling prompt and appropriate health management and improvement of the working environment.

[1215] The "detection means" is a device or technology for detecting that a user is standing in a specific position (for example, in front of a mirror).

[1216] "Scanning means" refers to a device or technology for non-invasively scanning a user's skin condition, facial expression, and posture.

[1217] "Analysis means" refers to functions and algorithms for analyzing scan data and assessing the user's health condition.

[1218] The "suggestion generation means" is a device or system for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[1219] "Relaxation suggestion means" refers to technologies or systems that monitor stress levels and suggest relaxation techniques.

[1220] A "wearable device" is a device that can be worn by workers and is used to monitor their health status in real time.

[1221] "Health monitoring means" refers to technologies and equipment for non-invasively monitoring workers' health using wearable devices.

[1222] A "rest suggestion means" is a function or system that suggests appropriate rest times and stretching timings based on the worker's health condition.

[1223] This invention is a system that monitors workers' health in real time and suggests appropriate breaks and stretching. The system consists of a wearable device, a server, and a cloud service.

[1224] System configuration overview

[1225] 1. Wearable devices:

[1226] It can be worn by workers and contains cameras and sensors to scan skin condition, facial expressions, and posture.

[1227] Data is collected non-invasively and transmitted to a server in real time.

[1228] 2. Server:

[1229] It provides powerful computational resources for analyzing the received data.

[1230] Evaluate the user's health status and generate appropriate suggestions.

[1231] Use databases to manage longitudinal health data.

[1232] 3. Cloud Services:

[1233] It works in conjunction with the server to back up data and perform real-time data analysis.

[1234] System Operation

[1235] 1. Initial Setup and Worker Registration:

[1236] When the wearable device is first turned on, it recognizes the worker and displays a screen for entering basic information, such as name, age, gender, and past medical history.

[1237] The server receives the input, creates a worker profile, stores it in a database, and sends a notification back to the wearable device once the profile is complete.

[1238] 2. Real-time monitoring:

[1239] The wearable device scans the worker's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time.

[1240] The server analyzes the data and evaluates the user's health status. For example, it calculates stress levels, posture distortion, and fatigue levels based on the level of dryness of the skin and facial expressions. The results are then sent to the wearable device.

[1241] 3. Proposal generation and notification:

[1242] Based on the analysis results, the server generates nutritional intake suggestions, exercise program suggestions, and rest suggestions, such as suggesting vitamin intake, short rest periods, and specific stretching exercises.

[1243] The wearable device can display these suggestions to the worker for confirmation, and if high stress levels are detected, the server will suggest appropriate relaxation techniques (e.g., deep breathing exercises) and display them on the device.

[1244] Hardware and software used

[1245] Wearable devices: smart glasses, smart watches, etc. with built-in cameras, sensors, and displays.

[1246] Server: High-performance analysis hardware (e.g., GPU server), database system (e.g., MySQL).

[1247] Cloud services: Real-time data analysis and backup capabilities, such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[1248] Analysis software: Use Python libraries (e.g., TensorFlow, Scikit-learn) to build machine learning models and perform data analysis.

[1249] Specific examples

[1250] Everyday use examples

[1251] 1. When worker A puts on the smart glasses for the first time, a basic information entry screen appears. After worker A enters the necessary information, the server receives the information and creates a profile.

[1252] 2. When the task begins, the smart glasses scan A's facial expressions and posture in real time and send the data to the server. The server analyzes the data and evaluates A's stress level and posture.

[1253] 3. If your stress level is determined to be high, you will be suggested to do 10 minutes of deep breathing exercises. If your posture is poor, a notification will appear on the glasses display urging you to correct your posture.

[1254] Example prompts for generative AI models

[1255] Text format:

[1256] A factory worker is wearing smart glasses. The camera built into the glasses captures facial expressions, posture, and fatigue levels while working, and we want to monitor his health condition in real time. Please write a program using Python to analyze the health data.

[1257] If stress levels are high, deep breathing exercises are suggested

[1258] If your posture is bad, we suggest correcting it.

[1259] If fatigue is high, a short rest is suggested

[1260] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1261] Step 1:

[1262] The user puts on the wearable device and performs the initial setup. When the device is first started up, a basic information entry screen is displayed, and the user enters information such as name, age, gender, and past medical history. This is the input, and user profile data is generated as the output and sent to the server. The server receives this data and stores it in a database for long-term management.

[1263] Step 2:

[1264] The wearable device collects data in real time. The device non-invasively scans the wearer's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time. The scan data is provided as input, and the server receives it as output and prepares it for analysis.

[1265] Step 3:

[1266] The server analyzes the received scan data. Specifically, it processes the data using machine learning models (e.g., TensorFlow) to evaluate the user's stress level, posture accuracy, and skin condition. The input is the scan data, and the output is the analysis results.

[1267] Step 4:

[1268] The server generates suggestions based on the analysis results. These suggestions include nutritional intake suggestions, exercise program suggestions, and rest suggestions based on the user's health condition. For example, if the stress level is high, a suggestion for deep breathing exercises is generated. The input is the analysis results, and the output is the generated suggestions.

[1269] Step 5:

[1270] The server notifies the wearable device of the proposed content. The server sends the generated proposed content to the wearable device and displays it on the device's display. The user can check it and implement the proposed content as necessary. The input is the proposed content, and the output is a notification to the user.

[1271] Step 6:

[1272] Suggesting and implementing relaxation techniques: If the user's stress level is high, the server generates a suggestion for an appropriate relaxation technique (e.g., deep breathing exercises) and notifies the wearable device. The user then sees this and performs the relaxation technique, thereby reducing stress. The input is the analysis result, and the output is the relaxation suggestion.

[1273] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1274] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when the user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, the system generates and provides nutritional intake and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining this system with an emotion engine, the system can recognize the user's emotions and more precisely adjust the suggestions.

[1275] System configuration overview

[1276] 1. User Device:

[1277] It includes a mirror section and an integrated scanning device.

[1278] It has a built-in integrated AI system that analyzes data and generates recommendations.

[1279] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[1280] 2. Server:

[1281] It provides powerful computational resources for analyzing data.

[1282] A learning model and database are put into operation to manage user data over the long term.

[1283] 3. Cloud Services:

[1284] It works in conjunction with the server to perform data backups and real-time analysis.

[1285] System Operation

[1286] 1. Initial Setup and User Registration

[1287] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[1288] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1289] 2. Daily Health Check

[1290] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[1291] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[1292] 3. Nutrition and exercise program suggestions

[1293] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may recommend foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[1294] The emotion engine adjusts the suggestions based on the user's emotions. For example, if the user expresses fatigue, it will suggest relaxing exercises and meals.

[1295] The user reviews the suggestions and implements them as needed.

[1296] 4. Stress level monitoring and relaxation suggestions

[1297] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[1298] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[1299] The emotion engine also adjusts relaxation techniques based on the user's emotions, suggesting more effective relaxation methods if the user is showing high levels of stress, for example.

[1300] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[1301] Specific examples

[1302] 1. Initial Setup and User Registration

[1303] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[1304] Tanaka enters his name, age, gender, and past medical history and saves it.

[1305] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[1306] 2. Daily Health Check

[1307] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[1308] The server analyzes the scan data, assesses whether the skin is becoming increasingly dry and whether the posture is slightly distorted, and sends the results back to the user's device.

[1309] The mirror displays the analysis results to Tanaka, and the emotion engine determines that he is currently feeling stressed.

[1310] 3. Nutrition and exercise program suggestions

[1311] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[1312] The emotion engine analyzes Tanaka's emotional data and determines that she is feeling very tired, so it adds a suggestion for a relaxing yoga class.

[1313] Tanaka implements the suggestions and works to improve his health.

[1314] 4. Stress level monitoring and relaxation suggestions

[1315] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[1316] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[1317] Taking into account the "high level of stress" recognized by the emotion engine, the system further suggests "listening to relaxation music."

[1318] Tanaka performs deep breathing exercises and listens to music to reduce stress.

[1319] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating an emotion engine, more personalized suggestions can be made that reflect the user's emotional state.

[1320] The processing flow will be explained below.

[1321] Step 1:

[1322] The user stands in front of the mirror. The user device uses a sensor to detect the user's presence.

[1323] Step 2:

[1324] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[1325] Step 3:

[1326] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[1327] Step 4:

[1328] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[1329] Step 5:

[1330] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[1331] Step 6:

[1332] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[1333] Step 7:

[1334] The user's device generates nutritional and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[1335] Step 8:

[1336] The user device uses an emotion engine to analyze the scan data (especially facial expression data) and recognize the user's emotions, including joy, sadness, surprise, anger, etc.

[1337] Step 9:

[1338] The user device uses the recognition results of the emotion engine to further adjust nutritional intake suggestions and exercise program suggestions. For example, if the user feels very tired, the device will suggest relaxing exercises and meal plans.

[1339] Step 10:

[1340] The user can check the suggestions and implement them as necessary. The user device also provides support such as a guide and timer for implementing the suggestions.

[1341] Step 11:

[1342] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[1343] Step 12:

[1344] The server suggests appropriate relaxation techniques based on the user's stress level, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[1345] Step 13:

[1346] The user device further adjusts the relaxation techniques based on the recognition results of the emotion engine, for example, suggesting listening to relaxation music if the user shows high stress levels.

[1347] Step 14:

[1348] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[1349] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health and emotional state and provide suggestions for improvement.

[1350] Example 2

[1351] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1352] In today's modern living environment, it is difficult to efficiently manage one's health amidst busy daily lives. In particular, it is not easy to comprehensively grasp the condition of one's skin, posture, facial expressions, etc., and then provide appropriate health recommendations and relaxation methods based on that information. In addition, there is a lack of health management systems that take into account the impact of stress and emotional changes on health.

[1353] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1354] In this invention, the server includes a detection means for detecting when a user stands in front of a reflective surface, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, and an emotion analysis means for recognizing the user's emotional state and adjusting the suggestions. This enables users to easily monitor their health condition at home and obtain and implement specific improvement measures tailored to their individual conditions.

[1355] "Reflective surface" refers to a mirror or display on which a user can see their own reflection.

[1356] "Detection means" refers to a sensor or device that detects when a user stands in front of a reflective surface.

[1357] "Non-invasive" refers to a method of obtaining data without placing a physical burden on the user's body.

[1358] "Skin condition" refers to the dryness, moisture level, color, etc. of the user's skin.

[1359] "Facial expressions" refer to movements and changes in the user's face that indicate emotions and states.

[1360] "Posture" refers to the user's body position, balance, and standing style.

[1361] "Scanning means" refers to a camera or sensor used to capture the user's skin condition, facial expression, and posture.

[1362] "Analysis means" refers to software or hardware for analyzing the acquired scan data and assessing the user's health condition.

[1363] The "suggestion generation means" refers to a system for suggesting nutritional intake and exercise programs to the user based on the analysis results.

[1364] "Relaxation suggestion means" refers to a system for monitoring a user's stress level and suggesting appropriate relaxation methods.

[1365] "Emotion analysis means" refers to an analysis system that recognizes the user's emotional state and adjusts suggestions accordingly.

[1366] "Computing device" refers to a computer or server used to analyze data.

[1367] A "machine learning model" refers to an algorithm or system that uses large amounts of data to recognize and predict specific patterns.

[1368] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a reflective surface (e.g., a mirror), non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health condition. Furthermore, based on the analysis results, the system generates and provides nutritional intake suggestions and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining emotion analysis means, the present invention can recognize the user's emotions and more precisely adjust the suggestions.

[1369] System configuration overview

[1370] 1. User Device:

[1371] The mirror includes a scanning device integrated with it, specifically hardware such as a camera and infrared sensor to capture the user's skin condition, facial expression, and posture.

[1372] It has an integrated AI system that analyzes data and generates recommendations, including machine learning models for data analysis.

[1373] It is equipped with an emotion analysis tool that recognizes the user's emotions based on the scan data.

[1374] 2. Server:

[1375] Powerful computing equipment will be provided for analyzing the data, specifically a high-performance server equipped with a GPU.

[1376] The learning models and databases are operated to manage user data over time, using machine learning frameworks such as TensorFlow and PyTorch.

[1377] 3. Cloud Services:

[1378] It works in conjunction with servers to back up data and perform real-time analysis, using cloud services such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[1379] How to use

[1380] Initial Setup and User Registration

[1381] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[1382] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1383] Daily Health Check

[1384] The user device detects when the user stands in front of a reflective surface and automatically initiates a non-invasive scan, capturing information about skin condition, facial expression, and posture, with the data transmitted in real time to a server.

[1385] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[1386] Nutrition and exercise program suggestions

[1387] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, such as suggesting foods rich in vitamin E or doing 20 minutes of yoga.

[1388] The suggestion content is adjusted based on the user's emotions as recognized by the emotion analysis means. For example, if the user expresses fatigue, the suggestion of relaxing yoga will be added.

[1389] The user reviews the suggestions and implements them as needed.

[1390] Stress level monitoring and relaxation suggestions

[1391] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[1392] The server suggests appropriate relaxation techniques (e.g., 10 minutes of deep breathing exercises) based on the stress level and sends them to the user's terminal.

[1393] The system also adjusts relaxation techniques based on the user's emotions as detected by the emotion analysis means, suggesting listening to relaxation music if the user is showing signs of high stress, for example.

[1394] The user performs suggested relaxation techniques to reduce stress.

[1395] Specific examples

[1396] 1. Initial Setup and User Registration

[1397] When a user stands in front of the mirror for the first time, the mirror displays a basic information entry screen for the user: name, age, gender, and past medical history, and saves the information.

[1398] The server receives the information, creates a profile for the user, and notifies them that "registration is complete."

[1399] 2. Daily Health Check

[1400] The next morning, when the user stands in front of the mirror, the mirror automatically begins scanning and detects the condition of the skin and posture.

[1401] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[1402] The mirror displays the analysis results to the user, and the emotion analysis means determines that the user is currently feeling stressed.

[1403] 3. Nutrition and exercise program suggestions

[1404] Miller suggests users "eat foods containing vitamin E and do 20 minutes of stretching."

[1405] The emotion analysis means analyzes the user's emotion data and determines that the user is "feeling very tired," so a relaxing yoga suggestion is added.

[1406] Users implement the suggestions and work to improve their health.

[1407] 4. Stress level monitoring and relaxation suggestions

[1408] The mirror analyzes the user's facial expressions and assesses their stress level as "high."

[1409] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[1410] Taking into account the "high level of stress" recognized by the emotion analysis means, the system further suggests "listening to relaxation music."

[1411] The user performs deep breathing exercises and music to reduce stress.

[1412] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating emotion analysis means, more personalized suggestions that reflect the user's emotional state can be realized.

[1413] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1414] Step 1: User detection

[1415] The user device detects when the user stands in front of a reflective surface. Specifically, the sensor built into the user device detects the user's movement.

[1416] Input: Movement data from sensors

[1417] Data processing / calculation: The sensor analyzes movement in the area in front of the reflective surface to confirm the user's presence.

[1418] Output: Information that the user is in front of a reflective surface

[1419] Specific operation: The user device will issue a voice notification saying, "A user has been detected. Scanning will begin."

[1420] Step 2: Start Scan

[1421] The user device non-invasively scans the user's skin condition, facial expression, and posture using a camera and infrared sensor.

[1422] Input: Real-time video and infrared data of the user

[1423] Data processing / calculation: Preprocess the acquired data and extract features of skin condition, facial expression, and posture.

[1424] Output: Scan data (skin condition, facial expression, posture characteristics)

[1425] Specific operation: The user device displays "Scanning, please wait."

[1426] Step 3: Send data

[1427] The user terminal transmits the scan data to the server in real time.

[1428] Input: Scan data

[1429] Data processing / calculation: Data is divided into packets and sent securely over the Internet.

[1430] Output: Scan data sent to the server

[1431] Specific operation: The user device displays "Data is being sent."

[1432] Step 4: Data analysis

[1433] The server analyzes the received data using a machine learning model (generative AI model), specifically assessing the user's health status and analyzing their emotions.

[1434] Input: Scan data

[1435] Data processing / computation: Using machine learning models, estimate skin dryness, posture distortion, and emotions and health status from facial expressions.

[1436] Output: Health status assessment results and emotion analysis results

[1437] Specific operation: The server updates the status to "Data analysis in progress."

[1438] Step 5: Receive and display analysis results

[1439] The user terminal receives the analysis results from the server and displays them to the user.

[1440] Input: Analysis results sent from the server

[1441] Data processing / calculation: Receives analysis results and displays them in a format that is easy for users to understand.

[1442] Output: Analysis result screen

[1443] Specific operation: The user device notifies the user that "Analysis results are being displayed" and displays specific evaluation results such as "Skin dryness: Medium, Stress level: High" on the screen.

[1444] Step 6: Suggested nutrition and exercise program

[1445] The user's device will suggest optimal nutritional intake and exercise programs based on the analysis results.

[1446] Input: Health status assessment results and emotion analysis results

[1447] Data processing / calculation: Taking into account the user's current health and emotional state, suggestions are generated using a generative AI model.

[1448] Output: Suggested nutrition and exercise program

[1449] Specific actions: The user device displays the message "Eat foods containing vitamin E and do 20 minutes of yoga."

[1450] Step 7: Relaxation Suggestions

[1451] The user device will suggest appropriate relaxation techniques based on the stress level from the scan data.

[1452] Input: Sentiment analysis results

[1453] Data processing / computation: Generate suggestions for deep breathing exercises or relaxation music based on data indicating high stress levels.

[1454] Output: Suggested relaxation techniques

[1455] Specific actions: The user device displays the message, "We recommend that you practice deep breathing exercises for 10 minutes and listen to relaxation music."

[1456] Step 8: Implementation and Feedback

[1457] The user carries out the suggested nutritional intake, exercise program, and relaxation techniques, and the results are fed back to the user's terminal.

[1458] Input: User execution status data

[1459] Data processing / calculation: Collect execution data, store it in a database for the next proposal, and use it to retrain the model.

[1460] Output: Feedback data on execution status

[1461] Specific operation: The user terminal asks the user for feedback, saying, "Did you execute the suggestion? Please enter the result."

[1462] (Application example 2)

[1463] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1464] Until now, it has been difficult for users to understand their own health condition in detail and take appropriate measures based on that information. It has also been difficult for users to consciously manage their emotional state and stress level in their daily lives. Furthermore, physical stores such as cosmetics stores and wellness centers have had limited means of suggesting appropriate products to customers based on their individual skin condition and emotional state.

[1465] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a detection means for detecting when a user stands in front of a mirror; a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture; an analysis means for analyzing the scan data and evaluating the user's health status; a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results; a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques; and a product suggestion means for making optimal product suggestions based on the analysis results. This allows users to understand their health and emotional status in detail and take appropriate measures based on that information. Furthermore, it also enables physical stores such as cosmetics stores and wellness centers to individually suggest optimal products to customers.

[1466] A "user" is someone who uses the system to receive assessments of their health and emotional state and receive recommendations.

[1467] "Detection means" refers to a device such as a sensor or camera that detects when a user stands in front of a mirror.

[1468] "Scanning means" refers to technologies such as cameras and near-infrared sensors that non-invasively scan a user's skin condition, facial expression, and posture.

[1469] "Analysis Means" refers to the algorithms and machine learning models used to assess the health and emotional state of the User based on the data obtained by the Scanning Means.

[1470] "Suggestion generation means" refers to software or a system that has the function of generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[1471] "Relaxation suggestion tool" refers to software or a system that has the functionality to monitor a user's stress level and suggest relaxation techniques based on that level.

[1472] "Product suggestion means" refers to software or a system that has the function of suggesting optimal products based on the analysis results.

[1473] "Server" refers to a device that provides computing resources on a network for analyzing data, generating recommendations, managing user profiles, and so on.

[1474] "Non-invasive" refers to a method that obtains information without direct contact or damage to the body.

[1475] "Real-time" means that processing occurs immediately at the moment data is collected.

[1476] A "machine learning model" is an algorithm used in data analysis, and refers to a technology that makes predictions and classifications by learning from past data.

[1477] This invention is a system that non-invasively assesses a user's health and emotional state and makes appropriate product suggestions based on that assessment in order to improve customer service in brick-and-mortar stores.

[1478] System configuration overview

[1479] 1. User Device:

[1480] It includes cameras and sensors integrated into the mirror.

[1481] It has an integrated AI system built in that scans and performs initial analysis of data.

[1482] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[1483] 2. Server:

[1484] It provides high-performance computing resources to perform detailed analysis of scan data.

[1485] Manages learning models and databases, and stores and analyzes long-term user data.

[1486] 3. Cloud Services:

[1487] It works in conjunction with the server to perform data backups and real-time analysis.

[1488] System Operation

[1489] 1. Initial Setup and User Registration

[1490] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, and gender.

[1491] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1492] 2. Health Check and Sentiment Analysis

[1493] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[1494] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, emotions and stress levels from facial expressions, and sending the results to the user's device.

[1495] 3. Product proposal

[1496] The user terminal receives the analysis results from the server and generates optimal product proposals based on them.

[1497] The system uses an emotion engine to generate suggestions and suggests optimal products (e.g., moisturizing cream, relaxation oil, etc.) taking into account the user's emotional data.

[1498] Hardware and software used

[1499] Hardware: High-resolution cameras, sensors, smart mirrors

[1500] Software: OpenCV, Dlib, Keras (TensorFlow backend)

[1501] Specifically, the system scans the user's face using a camera and detects facial landmarks using OpenCV and Dlib. It then applies emotion and skin condition models using Keras to evaluate the user's emotion and skin health, which then leads to optimal product recommendations.

[1502] Specific examples

[1503] Here are some examples of prompts to input to a generative AI model:

[1504] "Create a program that suggests the best cosmetics and relaxation products based on the customer's skin condition and emotions. The program should include the following steps: 1) Scan the face using a camera, 2) Recognize facial landmarks, 3) Predict emotions and skin health, 4) Recommend products based on the prediction results."

[1505] This system allows users in physical stores to gain detailed information about their health and emotional state and receive personalized product recommendations based on that information.

[1506] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1507] Step 1:

[1508] When a user stands in front of a smart mirror in a store, the device detects this. The input here is data from sensors that detect the user's position and movement. The output is a signal that recognizes the user is in front of the mirror, which automatically starts the next scanning process.

[1509] Step 2:

[1510] The device scans the user's skin condition, facial expression, and posture. The input is image data obtained from high-resolution cameras and sensors. The device receives this scan data and performs initial data processing. The output is scanned image data, which is used as input for the next step.

[1511] Step 3:

[1512] The device sends the scan data to the server in real time. The input is the scan data acquired in the previous step. The device sends it to the server over the network. The output is the image data sent to the server. This data is then ready to be analyzed by the server.

[1513] Step 4:

[1514] The server analyzes the scan data and evaluates the health and emotional state. The input is the scan data sent from the device. The server extracts facial landmarks using OpenCV and Dlib, and inputs the data into the Keras model. The output is the health and emotional state assessment results. This output data is used to generate proposals.

[1515] Step 5:

[1516] The server generates optimal product suggestions based on the analysis results. The inputs are the health status assessment results and emotional status assessment results obtained in step 4. Based on this data, the server refers to pre-set rules and past data to generate appropriate product suggestions. The output is a specific product list. This list is sent to the terminal.

[1517] Step 6:

[1518] The terminal displays product suggestions to the user. The input is a list of product suggestions sent from the server. The terminal visually displays this list to the user. The output is a display screen where the user can review the product suggestions. The user can select a product based on the suggestions.

[1519] Through these steps, users can understand their own health and emotional state through the smart mirror and receive optimal product recommendations based on that information.

[1520] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1521] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1522] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1523] [Fourth embodiment]

[1524] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1525] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1526] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1527] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1528] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1529] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1530] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1531] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1532] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1533] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1534] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1535] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1536] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1537] This invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, it generates and provides users with nutritional intake and exercise program suggestions. It also has a function to monitor stress levels and suggest relaxation techniques based on the results.

[1538] System configuration overview

[1539] 1. User Device:

[1540] It includes a mirror section and an integrated scanning device.

[1541] It has a built-in integrated AI system that analyzes data and generates recommendations.

[1542] 2. Server:

[1543] It provides powerful computational resources for analyzing data.

[1544] A learning model and database are put into operation to manage user data over the long term.

[1545] 3. Cloud Services:

[1546] It works in conjunction with the server to perform data backups and real-time analysis.

[1547] System Operation

[1548] 1. Initial Setup and User Registration

[1549] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[1550] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1551] 2. Daily Health Check

[1552] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[1553] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results to the user's device.

[1554] 3. Nutrition and exercise program suggestions

[1555] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may suggest daily intake of foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[1556] The user reviews the suggestions and implements them as needed.

[1557] 4. Stress level monitoring and relaxation suggestions

[1558] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[1559] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[1560] The user performs suggested relaxation techniques to reduce stress.

[1561] Specific examples

[1562] 1. Initial Setup and User Registration

[1563] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[1564] Tanaka enters his name, age, gender, and past medical history and saves it.

[1565] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[1566] 2. Daily Health Check

[1567] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[1568] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[1569] The mirror displays the analysis results to Tanaka.

[1570] 3. Nutrition and exercise program suggestions

[1571] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[1572] Tanaka implements the suggestions and works to improve his health.

[1573] 4. Stress level monitoring and relaxation suggestions

[1574] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[1575] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[1576] Tanaka does deep breathing exercises to reduce stress.

[1577] The above is a description of the mode for carrying out the invention. This system allows users to easily monitor their health status at home and obtain and implement specific measures for improvement.

[1578] The processing flow will be explained below.

[1579] Step 1:

[1580] The user stands in front of the mirror. The user device detects the user's presence using a sensor that detects the user's movement.

[1581] Step 2:

[1582] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[1583] Step 3:

[1584] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[1585] Step 4:

[1586] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[1587] Step 5:

[1588] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[1589] Step 6:

[1590] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[1591] Step 7:

[1592] The user's device generates nutritional intake and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (e.g., yoga, stretching, etc.).

[1593] Step 8:

[1594] The user can check the suggestions and implement them as necessary. Support such as a guide and timer is also provided for the user device to implement the suggestions.

[1595] Step 9:

[1596] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[1597] Step 10:

[1598] The server suggests relaxation techniques based on stress levels, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[1599] Step 11:

[1600] The user terminal presents the received relaxation techniques to the user, provides specific guidance, and assists the user in carrying out the suggested relaxation techniques.

[1601] Step 12:

[1602] The user performs relaxation techniques to reduce stress, and the user device monitors the progress of the techniques and provides feedback as needed.

[1603] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health status and provide suggestions for improvement.

[1604] Example 1

[1605] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1606] Conventional health management systems struggled to provide completely non-invasive scans, real-time data analysis, and health improvement recommendations. Furthermore, insufficient analysis of scan data meant that users were unable to receive appropriate nutritional and exercise recommendations. Furthermore, the lack of real-time monitoring of stress levels and appropriate relaxation recommendations meant that users were unable to adequately manage stress in their daily lives.

[1607] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1608] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, a data transmission means for transmitting the scanned data to the server in real time, an analysis means for analyzing the scanned data using a machine learning model and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a result return means for returning the analysis results from the server to a user terminal, and a means for the user to execute the suggested nutritional intake suggestions and exercise program and transmit the feedback to the server. This enables the user to non-invasively manage their daily health and obtain appropriate health improvement measures and stress management measures in real time.

[1609] The following are definitions of key terms included in the rewritten claims:

[1610] "Detection means" refers to a sensor or device for detecting when a user stands in front of a mirror.

[1611] "Scanning means" refers to a device or system for non-invasively scanning a user's skin condition, facial expression, and posture.

[1612] "Data transmission means" refers to a communication device or protocol for transmitting scan data from a user terminal to a server in real time.

[1613] "Analysis means" refers to software or algorithms used to analyze scan data and assess the user's health status.

[1614] "Suggestion generation means" refers to a device or algorithm for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[1615] "Relaxation suggestion tools" refer to devices or algorithms that monitor stress levels and suggest appropriate relaxation techniques.

[1616] "Result return means" refers to a communication device or protocol for returning analysis results from the server to the user terminal.

[1617] "Machine Learning Model" refers to the trained algorithm or model used to analyze scan data.

[1618] "Feedback means" refers to a device or system that allows the user to carry out the suggested nutritional intake suggestions and exercise program and transmit the results to the server.

[1619] The present invention provides a system that allows users to easily manage their health in their daily lives. The system operates using the following hardware and software.

[1620] Hardware and software used

[1621] 1. User Device:

[1622] Mirror part: The mirror part used when standing in front of the user.

[1623] Scanning device: Equipped with a high-resolution camera and infrared sensors for non-invasively scanning skin condition, facial expressions, and posture.

[1624] Motion detection sensor: Used to detect when a user stands in front of the mirror.

[1625] Integrated AI system: Includes a built-in software system that analyzes data and generates recommendations.

[1626] 2. Server:

[1627] Computing resources: High-performance computing devices for analyzing data, including GPUs and high-performance CPUs.

[1628] Database: A data storage system for long-term management of user data.

[1629] Machine learning models: Operate trained deep learning models to analyze user data.

[1630] 3. Cloud Services:

[1631] Data Backup: Cloud storage for safe storage of data.

[1632] Real-time analytics: Cloud computing resources for analyzing data in real time.

[1633] System Operation Overview

[1634] 1. User Device:

[1635] When the user's device is started for the first time, it welcomes the user and displays a screen for entering basic information. The user enters basic information such as name, age, gender, and medical history. The basic information is encrypted using AES (Advanced Encryption Standard) and sent to the server. The server creates a user profile based on the received information and stores it in a database.

[1636] 2. Daily Health Check:

[1637] The next morning, when the user stands in front of the mirror, the motion detection sensor detects this and the scanning device begins a non-invasive scan. Skin condition, facial expression, and posture are scanned using a high-resolution camera and infrared sensor, and the scanned data is sent in real time to a server. The server then analyzes the received data using machine learning models to assess the user's health status. For example, it evaluates the level of dryness of the skin, posture distortion, and stress level based on facial expressions, and sends the results back to the user's device.

[1638] 3. Analysis results and proposals:

[1639] The user device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, which are then provided to the user. For example, the system may suggest "eating foods containing vitamin E and doing 20 minutes of stretching." The user can then carry out the recommendations and send their feedback to the server.

[1640] 4. Stress level monitoring and relaxation suggestions:

[1641] The user device analyzes facial expression data to estimate the stress level in real time. The server then suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user device. The user can then perform the suggested relaxation techniques to reduce stress.

[1642] Specific examples and examples of prompts for generative AI models

[1643] Examples:

[1644] 1. Initial setup and user registration:

[1645] When Tanaka uses the system for the first time, a screen for entering basic information appears.

[1646] Tanaka enters his name, age, gender, and past medical history and saves it.

[1647] The server creates a profile for Tanaka and sends a notification back to the device that the profile has been saved.

[1648] 2. Daily Health Check:

[1649] The next morning, when Tanaka stands in front of the mirror, the device starts an automatic scan and sends the scanned data to the server.

[1650] The server analyzes the data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the device.

[1651] The terminal displays the analysis results to Tanaka.

[1652] 3. Nutrition and exercise program suggestions:

[1653] The device suggests to Tanaka, "Eat foods containing vitamin E and do 20 minutes of stretching."

[1654] Tanaka implements the suggestions and works to improve his health.

[1655] 4. Stress level monitoring and relaxation suggestions:

[1656] The device analyzes Tanaka's facial expression and assesses his stress level as "high."

[1657] The server suggests "10 minutes of deep breathing exercises" and displays it on the device.

[1658] Tanaka does deep breathing exercises to reduce stress.

[1659] Example prompt for a generative AI model:

[1660] "Please explain the process flow of a system that non-invasively scans a user's health status while they stand in front of a mirror and generates health improvement suggestions based on the analysis results."

[1661] This system allows users to non-invasively manage their daily health and provide appropriate health improvement and stress management strategies in real time.

[1662] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1663] Step 1: Enter basic user information

[1664] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information. The input screen includes items such as name, age, gender, and medical history. For example, the user might enter information such as "Ichiro Tanaka, 30 years old, male, no allergies." Input is done using a touch panel or voice recognition.

[1665] Input: Basic information entered by the user.

[1666] Output: The user's input information is saved in the system and used in the next step.

[1667] Step 2: Submit your input

[1668] The user terminal encrypts the input basic information and sends it to the server, using AES (Advanced Encryption Standard) to ensure data security.

[1669] Input: Basic information entered in step 1.

[1670] Output: The encrypted basic information is sent to the server.

[1671] Step 3: Create and save a profile

[1672] The server stores the received user information in a database and creates a user profile. After the profile is created, a completion notification is sent to the user's device.

[1673] Input: Encrypted basic information.

[1674] Output: The user profile is saved in the database and a completion notification is sent back to the user terminal.

[1675] Step 4: Detecting the user standing in front of a mirror

[1676] The user device detects when the user stands in front of the mirror using a built-in motion detection sensor, which can be an infrared sensor or a camera.

[1677] Input: Motion detection sensor data.

[1678] Output: The user is detected as standing in front of a mirror and the next scanning step is initiated.

[1679] Step 5: Run a scan

[1680] The user device activates a built-in non-invasive scanning device that scans the user's skin condition, facial expression, and posture. The scanning device uses a high-resolution camera and infrared sensor to record, in detail, the degree of skin moisture, abnormal posture, and subtle changes in facial expression.

[1681] Input: Sensory data of a user standing in front of a mirror.

[1682] Output: Scan data on skin condition, facial expression, and posture is generated.

[1683] Step 6: Send the scan data

[1684] The user device sends the scanned data to the server in real time, and the data is encrypted and sent over the network.

[1685] Input: Scan data.

[1686] Output: The encrypted scan data is sent to the server.

[1687] Step 7: Analyze your health status

[1688] The server then analyzes the received scan data using machine learning models, such as deep learning algorithms, to assess stress levels based on skin dryness, posture, and facial expressions.

[1689] Input: Encrypted scan data.

[1690] Output: The analysis results may include, for example, "skin is becoming increasingly dry," "posture is slightly distorted," and "stress level: high."

[1691] Step 8: Returning the analysis results

[1692] The server returns the analysis results to the user's terminal. The data is also encrypted here. The user's terminal displays the analysis results on its screen.

[1693] Input: Analysis results.

[1694] Output: The encrypted analysis results are sent to the user's terminal and displayed to the user.

[1695] Step 9: Generate proposals

[1696] Based on the health analysis results, the server generates optimal nutritional recommendations and exercise programs, such as "daily intake of foods containing vitamin C" and "specific exercise (yoga, stretching, etc.)."

[1697] Input: Analysis results.

[1698] Output: Proposals are generated and sent to the user device in the next step.

[1699] Step 10: Submit and view your proposal

[1700] The server transmits the generated proposal to the user terminal, which displays the proposal on its screen.

[1701] Input: Proposal content.

[1702] Output: The proposal is sent to the user's terminal and displayed to the user.

[1703] Step 11: Implementing the proposal

[1704] The user confirms the suggestions and implements them, for example, purchasing food supplements for vitamin E and stretching every morning.

[1705] Input: Proposal content.

[1706] Output: User performance feedback is generated and sent to the server in the next step.

[1707] Step 12: Submit your feedback

[1708] The user terminal transmits to the server the results of the user's implementation of the suggested nutritional intake suggestions and exercise program.

[1709] Input: User's performance feedback.

[1710] Output: The feedback data is sent to the server and stored in a database.

[1711] The above is a detailed description of the processing steps of the system and the specific operations at each step.

[1712] (Application example 1)

[1713] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1714] Conventional health management systems have difficulty monitoring the health status of individual users in real time and providing appropriate advice. In particular, in industrial environments, real-time understanding of workers' health status and immediate response are required, but current systems lack intelligent support for appropriately assessing and responding to workers' health risks.

[1715] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1716] In this invention, the server includes a detection means for detecting when a user stands in front of a mirror, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, a means for non-invasively monitoring health in a wearable device worn by a worker, and a means for generating break and stretching suggestions based on the worker's health condition. This enables real-time monitoring of the health condition of workers in an industrial environment, enabling prompt and appropriate health management and improvement of the working environment.

[1717] The "detection means" is a device or technology for detecting that a user is standing in a specific position (for example, in front of a mirror).

[1718] "Scanning means" refers to a device or technology for non-invasively scanning a user's skin condition, facial expression, and posture.

[1719] "Analysis means" refers to functions and algorithms for analyzing scan data and assessing the user's health condition.

[1720] The "suggestion generation means" is a device or system for generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[1721] "Relaxation suggestion means" refers to technologies or systems that monitor stress levels and suggest relaxation techniques.

[1722] A "wearable device" is a device that can be worn by workers and is used to monitor their health status in real time.

[1723] "Health monitoring means" refers to technologies and equipment for non-invasively monitoring workers' health using wearable devices.

[1724] A "rest suggestion means" is a function or system that suggests appropriate rest times and stretching timings based on the worker's health condition.

[1725] This invention is a system that monitors workers' health in real time and suggests appropriate breaks and stretching. The system consists of a wearable device, a server, and a cloud service.

[1726] System configuration overview

[1727] 1. Wearable devices:

[1728] It can be worn by workers and contains cameras and sensors to scan skin condition, facial expressions, and posture.

[1729] Data is collected non-invasively and transmitted to a server in real time.

[1730] 2. Server:

[1731] It provides powerful computational resources for analyzing the received data.

[1732] Evaluate the user's health status and generate appropriate suggestions.

[1733] Use databases to manage longitudinal health data.

[1734] 3. Cloud Services:

[1735] It works in conjunction with the server to back up data and perform real-time data analysis.

[1736] System Operation

[1737] 1. Initial Setup and Worker Registration:

[1738] When the wearable device is first turned on, it recognizes the worker and displays a screen for entering basic information, such as name, age, gender, and past medical history.

[1739] The server receives the input, creates a worker profile, stores it in a database, and sends a notification back to the wearable device once the profile is complete.

[1740] 2. Real-time monitoring:

[1741] The wearable device scans the worker's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time.

[1742] The server analyzes the data and evaluates the user's health status. For example, it calculates stress levels, posture distortion, and fatigue levels based on the level of dryness of the skin and facial expressions. The results are then sent to the wearable device.

[1743] 3. Proposal generation and notification:

[1744] Based on the analysis results, the server generates nutritional intake suggestions, exercise program suggestions, and rest suggestions, such as suggesting vitamin intake, short rest periods, and specific stretching exercises.

[1745] The wearable device can display these suggestions to the worker for confirmation, and if high stress levels are detected, the server will suggest appropriate relaxation techniques (e.g., deep breathing exercises) and display them on the device.

[1746] Hardware and software used

[1747] Wearable devices: smart glasses, smart watches, etc. with built-in cameras, sensors, and displays.

[1748] Server: High-performance analysis hardware (e.g., GPU server), database system (e.g., MySQL).

[1749] Cloud services: Real-time data analysis and backup capabilities, such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[1750] Analysis software: Use Python libraries (e.g., TensorFlow, Scikit-learn) to build machine learning models and perform data analysis.

[1751] Specific examples

[1752] Everyday use examples

[1753] 1. When worker A puts on the smart glasses for the first time, a basic information entry screen appears. After worker A enters the necessary information, the server receives the information and creates a profile.

[1754] 2. When the task begins, the smart glasses scan A's facial expressions and posture in real time and send the data to the server. The server analyzes the data and evaluates A's stress level and posture.

[1755] 3. If your stress level is determined to be high, you will be suggested to do 10 minutes of deep breathing exercises. If your posture is poor, a notification will appear on the glasses display urging you to correct your posture.

[1756] Example prompts for generative AI models

[1757] Text format:

[1758] A factory worker is wearing smart glasses. The camera built into the glasses captures facial expressions, posture, and fatigue levels while working, and we want to monitor his health condition in real time. Please write a program using Python to analyze the health data.

[1759] If stress levels are high, deep breathing exercises are suggested

[1760] If your posture is bad, we suggest correcting it.

[1761] If fatigue is high, a short rest is suggested

[1762] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1763] Step 1:

[1764] The user puts on the wearable device and performs the initial setup. When the device is first started up, a basic information entry screen is displayed, and the user enters information such as name, age, gender, and past medical history. This is the input, and user profile data is generated as the output and sent to the server. The server receives this data and stores it in a database for long-term management.

[1765] Step 2:

[1766] The wearable device collects data in real time. The device non-invasively scans the wearer's skin condition, facial expression, posture, and fatigue level, and transmits the data to a server in real time. The scan data is provided as input, and the server receives it as output and prepares it for analysis.

[1767] Step 3:

[1768] The server analyzes the received scan data. Specifically, it processes the data using machine learning models (e.g., TensorFlow) to evaluate the user's stress level, posture accuracy, and skin condition. The input is the scan data, and the output is the analysis results.

[1769] Step 4:

[1770] The server generates suggestions based on the analysis results. These suggestions include nutritional intake suggestions, exercise program suggestions, and rest suggestions based on the user's health condition. For example, if the stress level is high, a suggestion for deep breathing exercises is generated. The input is the analysis results, and the output is the generated suggestions.

[1771] Step 5:

[1772] The server notifies the wearable device of the proposed content. The server sends the generated proposed content to the wearable device and displays it on the device's display. The user can check it and implement the proposed content as necessary. The input is the proposed content, and the output is a notification to the user.

[1773] Step 6:

[1774] Suggesting and implementing relaxation techniques: If the user's stress level is high, the server generates a suggestion for an appropriate relaxation technique (e.g., deep breathing exercises) and notifies the wearable device. The user then sees this and performs the relaxation technique, thereby reducing stress. The input is the analysis result, and the output is the relaxation suggestion.

[1775] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1776] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when the user stands in front of a mirror, non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health. Furthermore, based on the analysis results, the system generates and provides nutritional intake and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining this system with an emotion engine, the system can recognize the user's emotions and more precisely adjust the suggestions.

[1777] System configuration overview

[1778] 1. User Device:

[1779] It includes a mirror section and an integrated scanning device.

[1780] It has a built-in integrated AI system that analyzes data and generates recommendations.

[1781] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[1782] 2. Server:

[1783] It provides powerful computational resources for analyzing data.

[1784] A learning model and database are put into operation to manage user data over the long term.

[1785] 3. Cloud Services:

[1786] It works in conjunction with the server to perform data backups and real-time analysis.

[1787] System Operation

[1788] 1. Initial Setup and User Registration

[1789] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[1790] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1791] 2. Daily Health Check

[1792] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[1793] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[1794] 3. Nutrition and exercise program suggestions

[1795] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them. For example, it may recommend foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[1796] The emotion engine adjusts the suggestions based on the user's emotions. For example, if the user expresses fatigue, it will suggest relaxing exercises and meals.

[1797] The user reviews the suggestions and implements them as needed.

[1798] 4. Stress level monitoring and relaxation suggestions

[1799] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[1800] The server suggests appropriate relaxation techniques (e.g., deep breathing exercises or meditation) based on the stress level and sends them to the user's device.

[1801] The emotion engine also adjusts relaxation techniques based on the user's emotions, suggesting more effective relaxation methods if the user is showing high levels of stress, for example.

[1802] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[1803] Specific examples

[1804] 1. Initial Setup and User Registration

[1805] Tanaka stands in front of the mirror for the first time. The mirror displays a screen for Tanaka to enter basic information.

[1806] Tanaka enters his name, age, gender, and past medical history and saves it.

[1807] The server receives the information, creates a profile for Tanaka, and notifies him that the save is complete.

[1808] 2. Daily Health Check

[1809] The next morning, when Tanaka stands in front of the mirror, the mirror automatically begins scanning and detects the condition of her skin and posture.

[1810] The server analyzes the scan data, assesses whether the skin is becoming increasingly dry and whether the posture is slightly distorted, and sends the results back to the user's device.

[1811] The mirror displays the analysis results to Tanaka, and the emotion engine determines that he is currently feeling stressed.

[1812] 3. Nutrition and exercise program suggestions

[1813] Miller suggests that Tanaka "consume foods containing vitamin E and do 20 minutes of stretching."

[1814] The emotion engine analyzes Tanaka's emotional data and determines that she is feeling very tired, so it adds a suggestion for a relaxing yoga class.

[1815] Tanaka implements the suggestions and works to improve his health.

[1816] 4. Stress level monitoring and relaxation suggestions

[1817] The mirror analyzes Tanaka's facial expression and assesses his stress level as "high."

[1818] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[1819] Taking into account the "high level of stress" recognized by the emotion engine, the system further suggests "listening to relaxation music."

[1820] Tanaka performs deep breathing exercises and listens to music to reduce stress.

[1821] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating an emotion engine, more personalized suggestions can be made that reflect the user's emotional state.

[1822] The processing flow will be explained below.

[1823] Step 1:

[1824] The user stands in front of the mirror. The user device uses a sensor to detect the user's presence.

[1825] Step 2:

[1826] The user terminal automatically initiates a non-invasive scan, using a scanning means to acquire data on the user's skin condition, facial expression, and posture.

[1827] Step 3:

[1828] The scanned data acquired by the user's device is sent to a server in real time, including skin images, facial expression data, and body posture data.

[1829] Step 4:

[1830] The server analyzes the received scan data, using analytical means to calculate the level of dryness of the skin, stress level from facial expressions, posture distortion, etc.

[1831] Step 5:

[1832] The server generates the analysis results and sends them back to the user's device, which contain detailed information about the user's health condition.

[1833] Step 6:

[1834] The user's device displays the analysis results it receives and notifies the user, including the evaluation results of skin dryness, stress level, and posture.

[1835] Step 7:

[1836] The user's device generates nutritional and exercise program suggestions based on the analysis results, such as recommending foods containing vitamin C or specific exercises (yoga, stretching, etc.).

[1837] Step 8:

[1838] The user device uses an emotion engine to analyze the scan data (especially facial expression data) and recognize the user's emotions, including joy, sadness, surprise, anger, etc.

[1839] Step 9:

[1840] The user device uses the recognition results of the emotion engine to further adjust nutritional intake suggestions and exercise program suggestions. For example, if the user feels very tired, the device will suggest relaxing exercises and meal plans.

[1841] Step 10:

[1842] The user can check the suggestions and implement them as necessary. The user device also provides support such as a guide and timer for implementing the suggestions.

[1843] Step 11:

[1844] The user's device analyzes facial expressions from the scanned data and monitors stress levels. Stress levels are assessed in real time based on the facial expression data for each frame.

[1845] Step 12:

[1846] The server suggests appropriate relaxation techniques based on the user's stress level, such as five minutes of deep breathing exercises or meditation, and notifies the user on their device how to do so.

[1847] Step 13:

[1848] The user device further adjusts the relaxation techniques based on the recognition results of the emotion engine, for example, suggesting listening to relaxation music if the user shows high stress levels.

[1849] Step 14:

[1850] The user performs the suggested relaxation techniques to reduce stress, and the user device monitors the progress and provides feedback as needed.

[1851] The above is the specific processing flow of the program in this system. We have explained in detail how the user, user device, and server work together at each step to monitor the user's health and emotional state and provide suggestions for improvement.

[1852] Example 2

[1853] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1854] In today's modern living environment, it is difficult to efficiently manage one's health amidst busy daily lives. In particular, it is not easy to comprehensively grasp the condition of one's skin, posture, facial expressions, etc., and then provide appropriate health recommendations and relaxation methods based on that information. In addition, there is a lack of health management systems that take into account the impact of stress and emotional changes on health.

[1855] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1856] In this invention, the server includes a detection means for detecting when a user stands in front of a reflective surface, a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture, an analysis means for analyzing the scan data and evaluating the user's health condition, a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results, a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques, and an emotion analysis means for recognizing the user's emotional state and adjusting the suggestions. This enables users to easily monitor their health condition at home and obtain and implement specific improvement measures tailored to their individual conditions.

[1857] "Reflective surface" refers to a mirror or display on which a user can see their own reflection.

[1858] "Detection means" refers to a sensor or device that detects when a user stands in front of a reflective surface.

[1859] "Non-invasive" refers to a method of obtaining data without placing a physical burden on the user's body.

[1860] "Skin condition" refers to the dryness, moisture level, color, etc. of the user's skin.

[1861] "Facial expressions" refer to movements and changes in the user's face that indicate emotions and states.

[1862] "Posture" refers to the user's body position, balance, and standing style.

[1863] "Scanning means" refers to a camera or sensor used to capture the user's skin condition, facial expression, and posture.

[1864] "Analysis means" refers to software or hardware for analyzing the acquired scan data and assessing the user's health condition.

[1865] The "suggestion generation means" refers to a system for suggesting nutritional intake and exercise programs to the user based on the analysis results.

[1866] "Relaxation suggestion means" refers to a system for monitoring a user's stress level and suggesting appropriate relaxation methods.

[1867] "Emotion analysis means" refers to an analysis system that recognizes the user's emotional state and adjusts suggestions accordingly.

[1868] "Computing device" refers to a computer or server used to analyze data.

[1869] A "machine learning model" refers to an algorithm or system that uses large amounts of data to recognize and predict specific patterns.

[1870] The present invention is a system that allows users to easily manage their health in their daily lives. This system detects when a user stands in front of a reflective surface (e.g., a mirror), non-invasively scans the user's skin condition, facial expression, and posture, and analyzes the data to evaluate their health condition. Furthermore, based on the analysis results, the system generates and provides nutritional intake suggestions and exercise program suggestions to the user. It also has a function to monitor stress levels and suggest relaxation techniques based on the results. Furthermore, by combining emotion analysis means, the present invention can recognize the user's emotions and more precisely adjust the suggestions.

[1871] System configuration overview

[1872] 1. User Device:

[1873] The mirror includes a scanning device integrated with it, specifically hardware such as a camera and infrared sensor to capture the user's skin condition, facial expression, and posture.

[1874] It has an integrated AI system that analyzes data and generates recommendations, including machine learning models for data analysis.

[1875] It is equipped with an emotion analysis tool that recognizes the user's emotions based on the scan data.

[1876] 2. Server:

[1877] Powerful computing equipment will be provided for analyzing the data, specifically a high-performance server equipped with a GPU.

[1878] The learning models and databases are operated to manage user data over time, using machine learning frameworks such as TensorFlow and PyTorch.

[1879] 3. Cloud Services:

[1880] It works in conjunction with servers to back up data and perform real-time analysis, using cloud services such as Amazon Web Services (AWS) and Google Cloud Platform (GCP).

[1881] How to use

[1882] Initial Setup and User Registration

[1883] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, gender, and medical history.

[1884] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1885] Daily Health Check

[1886] The user device detects when the user stands in front of a reflective surface and automatically initiates a non-invasive scan, capturing information about skin condition, facial expression, and posture, with the data transmitted in real time to a server.

[1887] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, stress level and emotions from facial expressions, and sends the results to the user's device.

[1888] Nutrition and exercise program suggestions

[1889] The user's device receives the analysis results from the server and generates optimal nutritional recommendations and exercise programs based on them, such as suggesting foods rich in vitamin E or doing 20 minutes of yoga.

[1890] The suggestion content is adjusted based on the user's emotions as recognized by the emotion analysis means. For example, if the user expresses fatigue, the suggestion of relaxing yoga will be added.

[1891] The user reviews the suggestions and implements them as needed.

[1892] Stress level monitoring and relaxation suggestions

[1893] The user's device analyzes facial expressions from the scan data and estimates stress levels in real time.

[1894] The server suggests appropriate relaxation techniques (e.g., 10 minutes of deep breathing exercises) based on the stress level and sends them to the user's terminal.

[1895] The system also adjusts relaxation techniques based on the user's emotions as detected by the emotion analysis means, suggesting listening to relaxation music if the user is showing signs of high stress, for example.

[1896] The user performs suggested relaxation techniques to reduce stress.

[1897] Specific examples

[1898] 1. Initial Setup and User Registration

[1899] When a user stands in front of the mirror for the first time, the mirror displays a basic information entry screen for the user: name, age, gender, and past medical history, and saves the information.

[1900] The server receives the information, creates a profile for the user, and notifies them that "registration is complete."

[1901] 2. Daily Health Check

[1902] The next morning, when the user stands in front of the mirror, the mirror automatically begins scanning and detects the condition of the skin and posture.

[1903] The server analyzes the scan data, assesses whether "skin is becoming increasingly dry" and "posture is slightly distorted," and sends the results back to the user's device.

[1904] The mirror displays the analysis results to the user, and the emotion analysis means determines that the user is currently feeling stressed.

[1905] 3. Nutrition and exercise program suggestions

[1906] Miller suggests users "eat foods containing vitamin E and do 20 minutes of stretching."

[1907] The emotion analysis means analyzes the user's emotion data and determines that the user is "feeling very tired," so a relaxing yoga suggestion is added.

[1908] Users implement the suggestions and work to improve their health.

[1909] 4. Stress level monitoring and relaxation suggestions

[1910] The mirror analyzes the user's facial expressions and assesses their stress level as "high."

[1911] The server suggests "10 minutes of deep breathing exercises" and displays it on the mirror.

[1912] Taking into account the "high level of stress" recognized by the emotion analysis means, the system further suggests "listening to relaxation music."

[1913] The user performs deep breathing exercises and music to reduce stress.

[1914] This concludes the description of the embodiment of the invention. This system allows users to easily monitor their health status at home and obtain and implement specific improvement measures. Furthermore, by integrating emotion analysis means, more personalized suggestions that reflect the user's emotional state can be realized.

[1915] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1916] Step 1: User detection

[1917] The user device detects when the user stands in front of a reflective surface. Specifically, the sensor built into the user device detects the user's movement.

[1918] Input: Movement data from sensors

[1919] Data processing / calculation: The sensor analyzes movement in the area in front of the reflective surface to confirm the user's presence.

[1920] Output: Information that the user is in front of a reflective surface

[1921] Specific operation: The user device will issue a voice notification saying, "A user has been detected. Scanning will begin."

[1922] Step 2: Start Scan

[1923] The user device non-invasively scans the user's skin condition, facial expression, and posture using a camera and infrared sensor.

[1924] Input: Real-time video and infrared data of the user

[1925] Data processing / calculation: Preprocess the acquired data and extract features of skin condition, facial expression, and posture.

[1926] Output: Scan data (skin condition, facial expression, posture characteristics)

[1927] Specific operation: The user device displays "Scanning, please wait."

[1928] Step 3: Send data

[1929] The user terminal transmits the scan data to the server in real time.

[1930] Input: Scan data

[1931] Data processing / calculation: Data is divided into packets and sent securely over the Internet.

[1932] Output: Scan data sent to the server

[1933] Specific operation: The user device displays "Data is being sent."

[1934] Step 4: Data analysis

[1935] The server analyzes the received data using a machine learning model (generative AI model), specifically assessing the user's health status and analyzing their emotions.

[1936] Input: Scan data

[1937] Data processing / computation: Using machine learning models, estimate skin dryness, posture distortion, and emotions and health status from facial expressions.

[1938] Output: Health status assessment results and emotion analysis results

[1939] Specific operation: The server updates the status to "Data analysis in progress."

[1940] Step 5: Receive and display analysis results

[1941] The user terminal receives the analysis results from the server and displays them to the user.

[1942] Input: Analysis results sent from the server

[1943] Data processing / calculation: Receives analysis results and displays them in a format that is easy for users to understand.

[1944] Output: Analysis result screen

[1945] Specific operation: The user device notifies the user that "Analysis results are being displayed" and displays specific evaluation results such as "Skin dryness: Medium, Stress level: High" on the screen.

[1946] Step 6: Suggested nutrition and exercise program

[1947] The user's device will suggest optimal nutritional intake and exercise programs based on the analysis results.

[1948] Input: Health status assessment results and emotion analysis results

[1949] Data processing / calculation: Taking into account the user's current health and emotional state, suggestions are generated using a generative AI model.

[1950] Output: Suggested nutrition and exercise program

[1951] Specific actions: The user device displays the message "Eat foods containing vitamin E and do 20 minutes of yoga."

[1952] Step 7: Relaxation Suggestions

[1953] The user device will suggest appropriate relaxation techniques based on the stress level from the scan data.

[1954] Input: Sentiment analysis results

[1955] Data processing / computation: Generate suggestions for deep breathing exercises or relaxation music based on data indicating high stress levels.

[1956] Output: Suggested relaxation techniques

[1957] Specific actions: The user device displays the message, "We recommend that you practice deep breathing exercises for 10 minutes and listen to relaxation music."

[1958] Step 8: Implementation and Feedback

[1959] The user carries out the suggested nutritional intake, exercise program, and relaxation techniques, and the results are fed back to the user's terminal.

[1960] Input: User execution status data

[1961] Data processing / calculation: Collect execution data, store it in a database for the next proposal, and use it to retrain the model.

[1962] Output: Feedback data on execution status

[1963] Specific operation: The user terminal asks the user for feedback, saying, "Did you execute the suggestion? Please enter the result."

[1964] (Application example 2)

[1965] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1966] Until now, it has been difficult for users to understand their own health condition in detail and take appropriate measures based on that information. It has also been difficult for users to consciously manage their emotional state and stress level in their daily lives. Furthermore, physical stores such as cosmetics stores and wellness centers have had limited means of suggesting appropriate products to customers based on their individual skin condition and emotional state.

[1967] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a detection means for detecting when a user stands in front of a mirror; a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture; an analysis means for analyzing the scan data and evaluating the user's health status; a proposal generation means for generating nutritional intake suggestions and exercise program suggestions based on the analysis results; a relaxation suggestion means for monitoring stress levels and suggesting relaxation techniques; and a product suggestion means for making optimal product suggestions based on the analysis results. This allows users to understand their health and emotional status in detail and take appropriate measures based on that information. Furthermore, it also enables physical stores such as cosmetics stores and wellness centers to individually suggest optimal products to customers.

[1968] A "user" is someone who uses the system to receive assessments of their health and emotional state and receive recommendations.

[1969] "Detection means" refers to a device such as a sensor or camera that detects when a user stands in front of a mirror.

[1970] "Scanning means" refers to technologies such as cameras and near-infrared sensors that non-invasively scan a user's skin condition, facial expression, and posture.

[1971] "Analysis Means" refers to the algorithms and machine learning models used to assess the health and emotional state of the User based on the data obtained by the Scanning Means.

[1972] "Suggestion generation means" refers to software or a system that has the function of generating nutritional intake suggestions and exercise program suggestions based on the analysis results.

[1973] "Relaxation suggestion tool" refers to software or a system that has the functionality to monitor a user's stress level and suggest relaxation techniques based on that level.

[1974] "Product suggestion means" refers to software or a system that has the function of suggesting optimal products based on the analysis results.

[1975] "Server" refers to a device that provides computing resources on a network for analyzing data, generating recommendations, managing user profiles, and so on.

[1976] "Non-invasive" refers to a method that obtains information without direct contact or damage to the body.

[1977] "Real-time" means that processing occurs immediately at the moment data is collected.

[1978] A "machine learning model" is an algorithm used in data analysis, and refers to a technology that makes predictions and classifications by learning from past data.

[1979] This invention is a system that non-invasively assesses a user's health and emotional state and makes appropriate product suggestions based on that assessment in order to improve customer service in brick-and-mortar stores.

[1980] System configuration overview

[1981] 1. User Device:

[1982] It includes cameras and sensors integrated into the mirror.

[1983] It has an integrated AI system built in that scans and performs initial analysis of data.

[1984] It is equipped with an emotion engine that recognizes the user's emotions based on scan data.

[1985] 2. Server:

[1986] It provides high-performance computing resources to perform detailed analysis of scan data.

[1987] Manages learning models and databases, and stores and analyzes long-term user data.

[1988] 3. Cloud Services:

[1989] It works in conjunction with the server to perform data backups and real-time analysis.

[1990] System Operation

[1991] 1. Initial Setup and User Registration

[1992] When the user terminal starts up, it welcomes the user and displays a screen for inputting basic information, such as name, age, and gender.

[1993] The server receives the input information, creates a user profile, stores it in a database, and sends a notification back to the user's device after the profile creation is complete.

[1994] 2. Health Check and Sentiment Analysis

[1995] The user device detects when the user stands in front of the mirror and automatically initiates a non-invasive scan, capturing skin condition, facial expression, and posture, with the data transmitted to a server in real time.

[1996] The server analyzes the data and evaluates the user's health condition, calculating the level of dryness of the skin, posture distortion, emotions and stress levels from facial expressions, and sending the results to the user's device.

[1997] 3. Product proposal

[1998] The user terminal receives the analysis results from the server and generates optimal product proposals based on them.

[1999] The system uses an emotion engine to generate suggestions and suggests optimal products (e.g., moisturizing cream, relaxation oil, etc.) taking into account the user's emotional data.

[2000] Hardware and software used

[2001] Hardware: High-resolution cameras, sensors, smart mirrors

[2002] Software: OpenCV, Dlib, Keras (TensorFlow backend)

[2003] Specifically, the system scans the user's face using a camera and detects facial landmarks using OpenCV and Dlib. It then applies emotion and skin condition models using Keras to evaluate the user's emotion and skin health, which then leads to optimal product recommendations.

[2004] Specific examples

[2005] Here are some examples of prompts to input to a generative AI model:

[2006] "Create a program that suggests the best cosmetics and relaxation products based on the customer's skin condition and emotions. The program should include the following steps: 1) Scan the face using a camera, 2) Recognize facial landmarks, 3) Predict emotions and skin health, 4) Recommend products based on the prediction results."

[2007] This system allows users in physical stores to gain detailed information about their health and emotional state and receive personalized product recommendations based on that information.

[2008] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2009] Step 1:

[2010] When a user stands in front of a smart mirror in a store, the device detects this. The input here is data from sensors that detect the user's position and movement. The output is a signal that recognizes the user is in front of the mirror, which automatically starts the next scanning process.

[2011] Step 2:

[2012] The device scans the user's skin condition, facial expression, and posture. The input is image data obtained from high-resolution cameras and sensors. The device receives this scan data and performs initial data processing. The output is scanned image data, which is used as input for the next step.

[2013] Step 3:

[2014] The device sends the scan data to the server in real time. The input is the scan data acquired in the previous step. The device sends it to the server over the network. The output is the image data sent to the server. This data is then ready to be analyzed by the server.

[2015] Step 4:

[2016] The server analyzes the scan data and evaluates the health and emotional state. The input is the scan data sent from the device. The server extracts facial landmarks using OpenCV and Dlib, and inputs the data into the Keras model. The output is the health and emotional state assessment results. This output data is used to generate proposals.

[2017] Step 5:

[2018] The server generates optimal product suggestions based on the analysis results. The inputs are the health status assessment results and emotional status assessment results obtained in step 4. Based on this data, the server refers to pre-set rules and past data to generate appropriate product suggestions. The output is a specific product list. This list is sent to the terminal.

[2019] Step 6:

[2020] The terminal displays product suggestions to the user. The input is a list of product suggestions sent from the server. The terminal visually displays this list to the user. The output is a display screen where the user can review the product suggestions. The user can select a product based on the suggestions.

[2021] Through these steps, users can understand their own health and emotional state through the smart mirror and receive optimal product recommendations based on that information.

[2022] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2023] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2024] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2025] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2026] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2027] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2028] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2029] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2030] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2031] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2032] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2033] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2034] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2035] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2036] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2037] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2038] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2039] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2040] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2041] The above-described description and illustrations are a detailed explana...

Claims

1. a detection means for detecting when a user stands in front of a mirror; a scanning means for non-invasively scanning the user's skin condition, facial expression, and posture; analysis means for analyzing the scan data and assessing the health status of the user; a proposal generation means for generating nutritional intake proposals and exercise program proposals based on the analysis results; A system that monitors stress levels and includes a relaxation suggestion means for suggesting relaxation techniques.

2. The data acquired by the scanning means is transmitted to a server in real time; 2. The system of claim 1, wherein the server analyzes the received data.

3. 2. The system of claim 1, wherein the analyzing means analyzes the user's scan data using a machine learning model.

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