system

Abstract

We provide the system. [Solution] A wearable device for collecting user health data, A terminal that receives and temporarily stores data from the wearable device, A server that receives data from the aforementioned terminal, analyzes it, and evaluates the health status, A display means that provides health advice generated by the server, A communication means for notifying the family of the aforementioned health data and analysis results, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Elderly people, especially those living alone or living away from their children in rural areas, often have difficulty in performing appropriate health management in their daily lives. As a result, the risk of overlooking their health conditions and delays in taking appropriate measures is increasing. Also, it is difficult for family members living away to grasp the health conditions of the elderly in real time and provide appropriate support. There is a need for a system that can solve these problems and enable the elderly to live their daily lives with peace of mind.

Means for Solving the Problems

[0005] The present invention provides a system comprising a wearable device for collecting user health data, a terminal for receiving and temporarily storing data from the wearable device, a server for receiving data from the terminal, analyzing it, and evaluating the user's health status, a display means for providing health advice generated by the server, and a communication means for notifying family members of the health data and analysis results. This system allows elderly individuals to easily manage their daily health, and enables family members to understand and support the user's health status in real time. Furthermore, a support function for three-way calls using generative AI enables smoother and more effective communication.

[0006] A "wearable device" is a device that a user wears to monitor their health data, and specifically includes devices such as smart bands and smartwatches.

[0007] A "terminal" is an electronic device used to temporarily store data received from a wearable device and transmit it to a server; specifically, this includes smartphones and tablets.

[0008] A "server" is a central processing unit that analyzes data received from terminals and evaluates the user's health status, and has the function of generating health advice based on the analysis results.

[0009] "Display means" refers to a device for providing health advice generated by the server to the user visually or audibly, and specifically includes displays and speakers that show avatars.

[0010] "Communication methods" refer to functions for sending user health data and analysis results to family members living separately, and specifically include internet connectivity, email, and notifications via dedicated applications.

[0011] A "three-way call" is a call session involving the user, family members, and a generative AI, in which the generative AI provides real-time assistance with conversation and health-related advice.

[0012] "Generative AI" refers to artificial intelligence technology that analyzes users' health data and call content to provide appropriate health advice and support in real time. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Modes for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the 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.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0027] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a system for supporting user health management, and mainly consists of a wearable device, a terminal, a server, and a program that links them together.

[0035] System Configuration

[0036] Wearable devices: This includes smart bands and smartwatches, which have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, and so on.

[0037] Terminal: This refers to the user's smartphone or tablet, which receives and temporarily stores data transmitted from wearable devices.

[0038] Server: Analyzes data received from terminals to evaluate and monitor the user's health status. It also has the function to generate health advice based on the analysis results and notify the user and their family.

[0039] Display means: A device for providing users with health advice generated by a server in a visual and auditory way. For example, an avatar delivers advice via voice and video through a smartphone's display or speaker.

[0040] Program processing flow

[0041] 1. Data collection:

[0042] Users wear wearable devices while going about their daily lives.

[0043] Wearable devices (terminals) monitor the user's health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[0044] 2. Data transfer and temporary storage:

[0045] The wearable device (terminal) periodically transmits the collected data to the user's smartphone via Bluetooth or Wi-Fi.

[0046] This function temporarily stores data received by a smartphone (device).

[0047] 3. Data transmission and analysis:

[0048] The smartphone (device) sends the stored data to the server via the internet.

[0049] The server analyzes the received data and assesses the user's health status. Based on the analysis results, it also generates appropriate health advice (such as exercise plans and dietary advice).

[0050] 4. Providing advice:

[0051] The server generates health advice, which is then sent to the smartphone for display.

[0052] The smartphone (device) displays the advice it receives within the application, and an avatar communicates it to the user via voice or video.

[0053] 5. Data notification:

[0054] The server notifies pre-registered family contacts of the user's health data and the generated advice and analysis results. For example, the data is sent to family members' smartphones or email addresses.

[0055] 6. Three-way calls using generative AI:

[0056] The user or a family member (user) requests a three-way call using a smartphone app.

[0057] The server activates the generative AI and configures it to allow communication between the user, family, and the generative AI.

[0058] The generative AI (server) analyzes the call content and provides appropriate supplementary information and advice in real time.

[0059] Specific example

[0060] One morning, I will explain in detail how an elderly user, Mr. A, uses the system.

[0061] Data collection:

[0062] User A: Every morning I put on my smartwatch and go for a walk.

[0063] Smartwatches (wearable devices): Continuously monitor heart rate, steps taken, and calories burned, including while walking.

[0064] Data transfer and temporary storage:

[0065] Smartwatch (wearable device): After returning home from a walk, it transmits health data to Person A's smartphone via Bluetooth.

[0066] Smartphone (device): Temporarily stores received data.

[0067] Data transmission and analysis:

[0068] Smartphone (device): Sends stored data to a server via the internet.

[0069] Server: Analyzes the received data and determines that Person A's blood pressure is slightly elevated. It also generates advice on appropriate dietary habits for managing their health.

[0070] Providing advice:

[0071] Server: Generates the advice, "Today, try to eat a low-salt meal," and sends it to Person A's smartphone.

[0072] Smartphone (device): The application displays advice and conveys it to person A through an avatar.

[0073] Data notification:

[0074] Server: Sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[0075] Son (family member / user): Check the received information.

[0076] Three-way calls using generative AI:

[0077] Son (family member / user): I need to call Person A urgently, so I request a three-way call through the app.

[0078] User A: Accepts the call request and joins the conversation.

[0079] Server: Activates a generative AI to supplement the call with health-related questions and confirmations in real time.

[0080] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[0081] The following describes the processing flow.

[0082] Step 1:

[0083] The user wears a wearable device (such as a smart band or smartwatch).

[0084] Step 2:

[0085] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0086] Step 3:

[0087] The wearable device periodically transmits the data it collects to the user's smartphone (device) via Bluetooth or Wi-Fi.

[0088] Step 4:

[0089] This function temporarily stores data received by the smartphone (device).

[0090] Step 5:

[0091] The smartphone (device) periodically transmits accumulated health data to a server via the internet.

[0092] Step 6:

[0093] The server saves the received data to the database.

[0094] Step 7:

[0095] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[0096] Step 8:

[0097] The server generates appropriate health advice (e.g., exercise plans and dietary advice) based on the analysis results.

[0098] Step 9:

[0099] The server sends the generated health advice to the user's smartphone (device).

[0100] Step 10:

[0101] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[0102] Step 11:

[0103] An avatar, acting as a display device, conveys advice to the user using voice and video.

[0104] Step 12:

[0105] The server notifies the user's health data and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[0106] Step 13:

[0107] Family members (users) review the notified information and send feedback to the server as needed.

[0108] Step 14:

[0109] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[0110] Step 15:

[0111] The user accepts the request for a three-way call.

[0112] Step 16:

[0113] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[0114] Step 17:

[0115] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[0116] Step 18:

[0117] The user and their family (user) end the call, and the server's generative AI saves or logs the call content.

[0118] (Example 1)

[0119] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0120] In modern times, health management is a crucial issue, and many people are required to understand their own health status and take appropriate measures. However, for the elderly and those with chronic diseases, collecting and analyzing their own data is difficult, making it challenging to receive appropriate health advice. Furthermore, it is difficult for family members living separately to understand the situation and provide support. To solve this problem, a system is needed that collects and analyzes health data in real time, provides appropriate advice, and allows information to be shared with family members.

[0121] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0122] In this invention, the server includes synchronization means for periodically transmitting data temporarily stored in the communication device to the information processing device; means for generating health advice based on the analysis results of the information processing device using a generative AI model; and means for the information processing device to support three-way communication between the user, family, and generative AI. This enables real-time collection and analysis of the user's health data, provision of appropriate advice, and data notification to family members.

[0123] A "measuring device" refers to a wearable device that collects user health data and has functions to monitor heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[0124] "Communication equipment" refers to a device that temporarily stores health data received from the aforementioned measuring device, and includes mobile information terminals such as smartphones and tablets.

[0125] An "information processing device" is a device that receives health data transmitted from the aforementioned communication device, analyzes it, and evaluates the user's health status, and refers to a server or cloud computer.

[0126] "Display means" refers to means for providing health advice generated by the information processing device to the user, and includes a smartphone display and an audio output device.

[0127] "Data transmission means" refers to means for notifying family members of the aforementioned health data and analysis results, and includes email and push notifications via the internet.

[0128] "Synchronization means" refers to a function for periodically transmitting data temporarily stored in the communication device to the information processing device.

[0129] A "generative AI model" is an artificial intelligence model that generates health advice based on the analysis of a user's health data, and refers to a generative AI that utilizes natural language processing technology.

[0130] A "virtual character" refers to a character used to display health advice generated by the aforementioned information processing device, and is an avatar that provides advice using voice and video.

[0131] "Means to support three-way calls" refers to features that allow users, family members, and generative AI to participate in a call simultaneously.

[0132] This invention is a system for supporting user health management, and consists of a wearable device, a terminal, a server, and a program that links them together. The specific components of the system and their functions are described below.

[0133] System Configuration

[0134] 1. Wearable devices

[0135] Measurement devices (wearable devices) have the function of monitoring the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[0136] Examples include smart bands and smartwatches.

[0137] 2. Terminal

[0138] Communication devices (smartphones and tablets) play the role of receiving and temporarily storing data transmitted from wearable devices.

[0139] Specific examples include smartphones running iOS or Android®.

[0140] 3. Server

[0141] The information processing device (server) analyzes data received from the terminal and evaluates the user's health status. Based on the analysis results, it generates health advice using a generative AI model and transmits it to the display device.

[0142] Examples include cloud servers and on-premises servers.

[0143] 4. Display means

[0144] The display means is a device for providing users with health advice generated by the server in a visual and auditory way.

[0145] Specific example: An avatar uses the smartphone's display and speakers to provide advice via voice and video.

[0146] 5. Data transmission means

[0147] The data transmission means is a means of notifying family members of health data and analysis results.

[0148] Specific example: Sending emails and push notifications over the internet.

[0149] 6. Synchronization means

[0150] The synchronization mechanism has the function of periodically transmitting data temporarily stored in the communication device to an information processing device.

[0151] 7. Generative AI Models

[0152] Generative AI models are artificial intelligence models designed to generate appropriate health advice based on the analysis of a user's health data.

[0153] Specific example: Use natural language processing technologies such as GPT-4 (registered trademark).

[0154] 8. Virtual Character

[0155] The virtual character is a character used to display health advice generated by the server, providing advice through voice and video.

[0156] 9. Means to support three-way calls

[0157] The means of supporting three-way calls provides the ability for the user, family members, and generative AI to talk simultaneously.

[0158] Specific example

[0159] The case of elderly person A one day

[0160] 1. Data collection:

[0161] User A puts on their smartwatch every morning and goes for a walk.

[0162] Smartwatches continuously monitor heart rate, steps taken, and calories burned.

[0163] 2. Data transfer and temporary storage:

[0164] The smartwatch transmits health data to Person A's smartphone via Bluetooth after returning home from a walk.

[0165] Smartphones temporarily store received data in a database within the app.

[0166] 3. Data transmission and analysis:

[0167] Smartphones transmit stored data to servers via the internet.

[0168] The server executes Python scripts and analyzes data using Scikit-learn models.

[0169] 4. Providing advice:

[0170] The server generates advice such as, "Today, try to eat a low-salt meal," and sends it to the smartphone.

[0171] The smartphone displays advice within the app and communicates it to person A via voice using the Google® Assistant API.

[0172] 5. Data notification:

[0173] The server sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[0174] The son (family member / user) checks the received information.

[0175] 6. Three-way calls using generative AI models:

[0176] The son (family member / user) requests a three-way call through the app.

[0177] User A accepts the call request.

[0178] The server sets up a call session using WebRTC and starts the generative AI model.

[0179] The generative AI model analyzes the content of the call and supplements it with health-related questions and confirmations in real time.

[0180] Example of a prompt

[0181] 1. "Mr. / Ms. A would like to check their health data for today. What is their current health status?"

[0182] 2. "What are some recent health concerns regarding Mr. / Ms. A?"

[0183] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[0184] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0185] Step 1:

[0186] Data collection

[0187] Users wear wearable devices on a daily basis while going about their daily lives.

[0188] Specific action: Every morning, the user puts on a smartwatch on their wrist.

[0189] Wearable devices collect health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[0190] Input: User's biometric information.

[0191] Data processing: Measurement using sensors.

[0192] Output: Raw health data.

[0193] Step 2:

[0194] Data transfer and temporary storage

[0195] The wearable device collects data and transmits it to the user's device via Bluetooth or Wi-Fi.

[0196] Specific operation: The wearable device synchronizes with the terminal periodically or at the user's request.

[0197] The application temporarily stores the data received by the device.

[0198] Input: Health data transmitted from a wearable device.

[0199] Data processing: Data storage within the device.

[0200] Output: Temporarily stored health data.

[0201] Step 3:

[0202] Data transmission and analysis

[0203] The device sends temporarily stored data to the server via the internet.

[0204] Specific operation: The app sends data periodically or in response to user actions.

[0205] The server analyzes the received data and evaluates the user's health status.

[0206] Input: Health data sent from the device.

[0207] Data processing: Preprocessing and analysis using Python scripts.

[0208] Output: Health assessment report.

[0209] The server generates health advice using a generative AI model.

[0210] Input: Health assessment report.

[0211] Data processing: Generating advice using generative AI models such as GPT-4.

[0212] Output: Health advice.

[0213] Step 4:

[0214] Providing advice

[0215] The server generates health advice and sends it to the device.

[0216] Specific operation: Sending data via a REST API.

[0217] The application displays the advice received by the device, and an avatar communicates it to the user via voice or video.

[0218] Input: Health advice sent from the server.

[0219] Data processing: Conversion to in-app display format and speech synthesis.

[0220] Output: Display of advice to the user and audio output.

[0221] Step 5:

[0222] Data notification

[0223] The server notifies the family of their health data and generated advice.

[0224] Specific action: Send emails and push notifications using the notification service.

[0225] Family members receive notifications and check on the user's health status.

[0226] Input: Notification data sent from the server.

[0227] Data processing: Display via email or push notification.

[0228] Output: Notification displayed to family members.

[0229] Step 6:

[0230] Three-way calls using a generative AI model

[0231] The user or a family member requests a three-way call using a smartphone app.

[0232] Specific action: Press the "3-way call" button within the app.

[0233] The server activates the generated AI model and configures it to allow calls between the user, family members, and the generated AI model.

[0234] Input: Call request.

[0235] Data processing: Session setup and activation of the generated AI model using WebRTC technology.

[0236] Output: Call session started.

[0237] The generative AI model analyzes the call content and provides appropriate supplementary information and advice in real time.

[0238] Specific operation: The system analyzes call content in real time and uses speech synthesis to provide supplementary explanations and advice.

[0239] Input: Call content.

[0240] Data processing: Real-time analysis and speech synthesis.

[0241] Output: Supplementary explanations or advice.

[0242] (Application Example 1)

[0243] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0244] This invention relates to a system for supporting users' health management. It aims to not only collect and analyze health data using wearable devices and provide health advice based on the results, but also to provide real-time, optimal guidance when implementing a fitness plan in a virtual environment, thereby enabling effective health management and fitness instruction. Furthermore, it aims to enhance communication between the user and their family through three-way calls using a generation system, making it easier for family members living separately to understand the user's health status.

[0245] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0246] In this invention, the server includes means for analyzing the user's health data and evaluating their health status, means for generating health advice and fitness plans, and means for notifying the user and their family of the generated data. This makes it possible to provide fitness plans within a virtual environment and to share information about the user's health status with their family.

[0247] A "wearable device" is a device used to collect user health data, and includes smart bands and smartwatches.

[0248] "Terminal" refers to a device that receives and temporarily stores data collected from the wearable device, and includes smartphones, tablets, and the like.

[0249] A "server" is a device that receives data transmitted from the aforementioned terminal, analyzes it, and evaluates the health status, and includes cloud servers and data processing facilities.

[0250] "Display means" refers to a device for providing health advice generated by the server to the user, and includes a smartphone display and an audio output device.

[0251] "Communication means" refers to a device for notifying family members of the aforementioned health data and analysis results, and includes internet connectivity and email systems.

[0252] "Guide data" refers to data generated by the server to provide a fitness plan within the virtual environment, and includes exercise instructions and health advice.

[0253] "Smart glasses" refers to a device that allows the terminal to display a virtual environment and provide guidance to the user, and includes head-mounted displays and augmented reality glasses.

[0254] A "virtual environment" is an environment in which users can experience and engage in activities in a virtually defined space or situation, and includes virtual fitness rooms and virtual gyms.

[0255] A "fitness plan" is an exercise guidance and exercise program generated by the server based on the user's health data, and includes individual exercise menus and exercise guidelines.

[0256] This invention relates to a system for supporting user health management, and its main components include a wearable device, a terminal, a server, and smart glasses. This system is particularly effective when applied in virtual stores.

[0257] 1. System Configuration

[0258] Wearable devices include smart bands and smartwatches that have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc. A typical smartwatch is an example.

[0259] Terminal: This refers to the user's smartphone or tablet, which receives data transmitted from wearable devices via Bluetooth or Wi-Fi and temporarily stores it.

[0260] Server: Analyzes data received from terminals and assesses the user's health status. Based on the analysis results, it generates health advice and fitness plans and notifies the user and their family.

[0261] Smart glasses: Devices that display a virtual environment and provide virtual fitness guidance. Examples include head-mounted displays (HMDs) and augmented reality (AR) glasses.

[0262] 2. Program Processing

[0263] 2.1 Data Collection

[0264] While the user wears the smartwatch and goes about their daily life, the wearable device monitors health data such as heart rate, steps taken, calories burned, and blood pressure in real time.

[0265] 2.2 Data Transfer and Temporary Storage

[0266] The smartwatch periodically transmits monitored data to the user's smartphone via Bluetooth or Wi-Fi. The smartphone temporarily stores the received data.

[0267] 2.3 Data Transmission and Analysis

[0268] Smartphones transmit stored data to servers via the internet. The servers analyze the received data and assess the user's health status. They also generate appropriate health advice and fitness plans.

[0269] 2.4 Providing Guides

[0270] The server generates a fitness plan, which is then sent to the smartphone for display. Within the virtual environment, the smart glasses convey the generated fitness guide to the user via voice and visual means through an avatar. Specifically, when the user performs a squat, animations and avatar guides are displayed on the smart glasses to instruct them on correct form.

[0271] 2.5 Data Notification

[0272] The server notifies the family of the user's health data and the generated advice and analysis results. This allows the family to understand the user's health status in real time.

[0273] 3. Specific examples

[0274] On a given morning, when a user uses the system, they would go through the following steps:

[0275] Data collection from wearable devices: Users wear smartwatches while exercising or engaging in daily activities.

[0276] Data transfer: The smartwatch transfers collected data to the smartphone.

[0277] Data analysis: The smartphone sends data to the server, and the server performs the analysis.

[0278] Fitness plan delivery: A server generates a fitness plan and sends it to smart glasses, allowing the user to receive guidance within a virtual environment.

[0279] Example of a prompt:

[0280] Let's begin today's fitness plan. I've read your heart rate data. Next, please do 5 squats.

[0281] As a result, the user can effectively execute a fitness plan in a virtual environment and manage their health in real time. Additionally, it strengthens the cooperation with family members and enables efficient management of the user's health status.

[0282] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0283] Step 1:

[0284] The user wears a smartwatch and goes through daily life. The smartwatch monitors health data such as heart rate, steps, calories burned, and blood pressure in real time. The input is the user's motion data, and the output is the monitored health data.

[0285] Step 2:

[0286] The smartwatch transmits the health data collected to the user's smartphone via Bluetooth or Wi-Fi. The input is the health data stored in the smartwatch, and the output is the data transferred to the smartphone.

[0287] Step 3:

[0288] The smartphone temporarily stores the received health data. The input is the health data transferred from the smartwatch, and the output is the temporarily stored data.

[0289] Step 4:

[0290] The smartphone transmits the temporarily stored data to the server via the Internet. The input is the data stored in the smartphone, and the output is the data transmitted to the server.

[0291] Step 5:

[0292] The server analyzes the received data and evaluates the user's health status. The input is health data sent to the server, and the output is the analysis results and health evaluation.

[0293] Step 6:

[0294] The server generates appropriate health advice and fitness plans based on the analysis results. The input is health assessment data, and the output is health advice and fitness plans.

[0295] Step 7:

[0296] The server generates a fitness plan and sends it to the smartphone, which then displays it. The input is the generated fitness plan, and the output is the fitness plan displayed on the smartphone.

[0297] Step 8:

[0298] Smart glasses display a fitness plan in a virtual environment and provide guidance to the user. The input is the fitness plan displayed on a smartphone, and the output is the guidance displayed on the smart glasses. This may include exercise instruction using animations or avatars.

[0299] Step 9:

[0300] The server notifies the family of the user's health data and analysis results. The input is the generated analysis results and health data, and the output is the notification sent to the family.

[0301] Step 10:

[0302] The smart phone displays the generated prompt text to the user, and the user starts exercising according to the instructions. The input is the generated prompt text, and the output is the execution of the exercise by the user. Examples of prompt text: "Start today's fitness plan. Heart rate data has been read. Next, please do 5 squats."

[0303] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform specific processing using the user's emotion.

[0304] The present invention is a system for supporting the health management of users, mainly composed of a wearable device, a terminal, a server, an emotion engine, and a program for linking them.

[0305] Configuration of the system

[0306] Wearable device: A smart band or a smart watch corresponds to this, and it has a function of monitoring the user's heart rate, number of steps, calories consumed, blood pressure, blood sugar level, etc.

[0307] Terminal: It is the user's smart phone or tablet, which receives the data transmitted from the wearable device and temporarily stores it.

[0308] Server: Analyzes the data received from the terminal, evaluates and monitors the user's health status. It also has a function of generating health advice based on the analysis results and notifying the user and family members.

[0309] Display means: A device for visually and auditorily providing the health advice generated by the server to the user. For example, an avatar conveys advice in voice or video through the display and speaker of the smart phone.

[0310] Emotion Engine: It has an algorithm that recognizes the user's emotions and analyzes their emotional state based on collected health data.

[0311] Program processing flow

[0312] 1. Data collection:

[0313] Users wear wearable devices while going about their daily lives.

[0314] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0315] 2. Data transfer and temporary storage:

[0316] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[0317] This function temporarily stores data received by a smartphone (device).

[0318] 3. Data transmission and analysis:

[0319] The smartphone (device) sends the stored data to the server via the internet.

[0320] The server saves the received data to the database and begins analysis.

[0321] The emotion engine (device) analyzes the user's emotional state based on the collected data.

[0322] 4. Generating advice:

[0323] The server generates personalized health advice based on the analyzed health and emotional data.

[0324] The server sends the generated health advice to the user's smartphone (device).

[0325] 5. Providing advice:

[0326] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[0327] An avatar, acting as a display device, conveys advice to the user using voice and video.

[0328] 6. Data notification:

[0329] The server notifies pre-registered family contacts of the user's health data, emotional data, and analysis results.

[0330] Family members (users) review the notified information and send feedback as needed.

[0331] 7. Three-way calls using generative AI:

[0332] The user or a family member (user) requests a three-way call through a smartphone application.

[0333] The server activates a generative AI and sets up a three-way call. During the call, the generative AI supplements the conversation between the user and their family, providing real-time health-related questions and advice.

[0334] Specific example

[0335] One morning, I will explain in detail how an elderly person, Mr. B, uses the system.

[0336] 1. Data collection:

[0337] User B puts on their smartwatch and goes for a walk.

[0338] A smartwatch (wearable device) monitors your heart rate, steps taken, and calories burned while you're out for a walk.

[0339] 2. Data transfer and temporary storage:

[0340] The smartwatch (wearable device) transmits the collected data to Person B's smartphone via Bluetooth.

[0341] This function temporarily stores data received by the smartphone (device).

[0342] 3. Data transmission and analysis:

[0343] The smartphone (device) sends the stored data to the server.

[0344] The server analyzes the data and determines that Person B's blood pressure is on the higher side. Additionally, the emotion engine analyzes Person B's emotional state as "high stress."

[0345] 4. Generating advice:

[0346] The server generates advice such as, "Today, try to eat a low-salt diet," and based on the emotion engine, it also generates additional advice such as, "I recommend listening to relaxing music."

[0347] The smartphone (device) receives the advice, and the avatar relays it to person B along with a voice message.

[0348] 5. Data notification:

[0349] The server notifies B's family of their health and emotional data.

[0350] The family member (user) checks the notification and sends feedback to the server about Person B's health condition.

[0351] 6. Three-way calls using generative AI:

[0352] A family member (user) requests a call, and person B accepts.

[0353] The server activates a generative AI, providing real-time health-related questions and advice during the call.

[0354] In this way, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind. In particular, by integrating an emotion engine, it is possible to provide personalized advice that takes into account the user's mental state, not just monitoring health data. Furthermore, it becomes easier for family members living separately to understand the health status in real time and provide necessary support.

[0355] The following describes the processing flow.

[0356] Step 1:

[0357] The user wears a wearable device (such as a smart band or smartwatch).

[0358] Step 2:

[0359] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0360] Step 3:

[0361] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[0362] Step 4:

[0363] This function temporarily stores data received by the smartphone (device).

[0364] Step 5:

[0365] An emotion engine (located on the device or on a server) analyzes additional information such as the user's voice, facial expressions, and text input based on data from wearable devices and smartphones to identify the user's emotional state.

[0366] Step 6:

[0367] The smartphone (device) transmits accumulated health data and emotional data to a server via the internet.

[0368] Step 7:

[0369] The server saves the received data to the database.

[0370] Step 8:

[0371] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[0372] Step 9:

[0373] The server evaluates the user's emotional state based on the results from the emotion engine and generates personalized health advice.

[0374] Step 10:

[0375] The server sends the generated health advice to the user's smartphone (device).

[0376] Step 11:

[0377] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[0378] Step 12:

[0379] An avatar, acting as a display device, conveys advice to the user using voice and video.

[0380] Step 13:

[0381] The server notifies the user's health data, emotional data, and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[0382] Step 14:

[0383] Family members (users) review the notified information and send feedback to the server as needed.

[0384] Step 15:

[0385] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[0386] Step 16:

[0387] The user accepts the request for a three-way call.

[0388] Step 17:

[0389] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[0390] Step 18:

[0391] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[0392] Step 19:

[0393] The user and their family (user) end the call, and the server saves or logs the call content using a generative AI.

[0394] (Example 2)

[0395] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0396] In modern society, there is a need for systems that can monitor both a user's health and emotional state in real time and provide appropriate advice. Collecting and analyzing health data in daily life is particularly important for the elderly and those with unstable health conditions. However, there is a lack of technology that not only monitors health data but also provides personalized advice that takes emotional states into account. Furthermore, there are limited means for family members living separately to monitor a user's health in real time and provide necessary support.

[0397] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an emotion engine that analyzes the user's emotional state using an emotion algorithm, means for supporting a three-way call between the user, family, and a generating AI model, a measurement device for collecting the user's health data, a terminal that receives and temporarily stores data from the measurement device, means for receiving data from the terminal, analyzing it, and evaluating the health state, display means for providing health advice generated by the server, and communication means for notifying the family of the health data and analysis results. This makes it possible to grasp the user's health state and emotional state in real time and provide personalized advice. In addition, family members can grasp the health state in real time from a remote location and provide appropriate support.

[0398] A "measurement device" is a device used to collect a user's health data, monitoring physical data such as heart rate, steps taken, calories burned, blood pressure, and blood glucose levels.

[0399] A "terminal" is a device that receives and temporarily stores health data transmitted from a measurement device, and includes smartphones and tablets.

[0400] A "server" is a computing system that receives data transmitted from a terminal, performs analysis, and evaluates the user's health status. Its role is to generate and notify users of health advice based on the analysis results.

[0401] "Display means" refers to a device that provides the user with health advice generated by the server, either visually or audibly, and includes smartphone displays, speakers, avatars, and other similar devices.

[0402] "Means of communication" refers to the method by which the server analyzes health data and analysis results and notifies family members of these methods, including the internet, email, and text messages.

[0403] An "emotion engine" is an algorithm and system that analyzes a user's emotional state based on their health data and behavioral patterns.

[0404] A "generative AI model" is an artificial intelligence system designed to support communication with users and their families, providing real-time answers to health-related questions and advice.

[0405] A "three-way call" refers to a call between the user, their family, and a generative AI model, allowing the user and their family to exchange health-related information and receive advice in real time.

[0406] "Health advice" refers to specific instructions and suggestions generated by the server based on an analysis of the user's health and emotional data, providing information necessary to improve and maintain the user's health.

[0407] The present invention is a system for supporting user health management and emotion analysis, and consists of a measurement device, a terminal, a server, an emotion engine, a generative AI model, and a program that links these together.

[0408] System Configuration

[0409] Measurement devices

[0410] Measurement devices such as smart bands and smartwatches are used. These devices have the function of continuously monitoring the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels. For example, a smartwatch measures the user's heart rate every minute and stores that data in its internal memory.

[0411] terminal

[0412] The terminal is the user's smartphone or tablet, and its role is to receive and temporarily store data transmitted from the measurement device. For example, the smartphone receives data transmitted from a smartwatch via Bluetooth and temporarily stores it in local storage.

[0413] server

[0414] The server is a computing system located in the cloud that analyzes data received from terminals and evaluates the user's health status. The server utilizes multiple algorithms to analyze trends in heart rate data, for example, and detect anomalies. Based on the analysis results, it generates personalized health advice and notifies the user and their family.

[0415] Emotional Engine

[0416] The emotion engine is a software component integrated within the server that analyzes the user's emotional state based on health data and behavioral patterns. For example, if the user has a low step count and a high heart rate, the emotion engine detects the user's stress level and incorporates that information into the analysis results.

[0417] Generative AI Models

[0418] The Generative AI Model is an artificial intelligence system that supports three-way calls between the user and their family, providing real-time health-related questions and advice. For example, if a user enters a prompt such as, "My blood pressure is high today, and I'm feeling stressed. Could you give me some advice on how to relax?", the Generative AI Model will provide appropriate advice in real time.

[0419] means of communication

[0420] The system uses the internet, email, and text messages as communication methods to notify family members of the health data and analysis results analyzed by the server. For example, if a user's heart rate remains elevated, a notification will be sent to their family via email.

[0421] Display means

[0422] The display methods used include smartphone displays, speakers, and avatars. Health advice generated by the server is provided to the user visually or audibly. For example, a smartphone app might display the advice, "We recommend you go to bed early tonight," while an avatar delivers the advice verbally.

[0423] Specific example

[0424] Let's take an example of an elderly user using this system one morning. The user puts on a smartwatch and goes for a walk. The smartwatch monitors heart rate, steps taken, and calories burned during the walk. The collected data is transmitted to the user's smartphone via Bluetooth, where it is temporarily stored.

[0425] The smartphone then sends the saved data to the server. The server analyzes the received data and determines that the user has high blood pressure and is under high stress. The server generates health advice such as "Try to eat a low-salt diet today" and emotional data-based advice such as "We recommend listening to relaxing music," and sends these to the user's smartphone.

[0426] A smartphone app receives advice, and an avatar conveys it to the user via voice. The server also notifies the user's family of the analysis data, and the family sends feedback to the server about the user's health.

[0427] The user or their family can request a three-way call through a generative AI model and receive real-time health-related questions and advice during the call. In this way, the system of the present invention can provide integrated support for the user's health management and emotional state.

[0428] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0429] Step 1: Data Collection

[0430] The user wears a measurement device (e.g., a smartwatch). The smartwatch monitors health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0431] Input: User's biometric information

[0432] Data processing: The smartwatch senses biometric information in real time, collects the necessary data, and stores it in its internal memory.

[0433] Output: Collected health data (heart rate, steps, etc.)

[0434] Step 2: Data Transfer and Temporary Storage

[0435] The wearable device transmits the data it collects via Bluetooth to the user's smartphone.

[0436] Input: Health data from smartwatch

[0437] Data processing: The smartphone receives data via Bluetooth, converts it to an appropriate format for temporary storage, and saves it to its internal storage.

[0438] Output: Health data stored on the smartphone

[0439] Step 3: Data transmission and analysis

[0440] The smartphone sends the stored data to the server via the internet.

[0441] Input: Health data on your smartphone

[0442] Data transfer: The smartphone uploads data to the server using the appropriate protocol (e.g., HTTPS).

[0443] Output: Health data sent to the server

[0444] Step 4: Data analysis and emotional state analysis

[0445] The server stores the received data in a database and performs initial analysis. The server analyzes trends and anomalies in the health data, and the emotion engine evaluates the emotional state.

[0446] Input: Received health data

[0447] Data processing: The server uses algorithms to perform analysis, and the emotion engine performs sentiment analysis based on user behavior data and health data.

[0448] Output: Analysis results (health assessment, emotional assessment)

[0449] Step 5: Generate and send advice

[0450] The server generates personalized health advice based on the analysis results. The emotion engine also generates advice that reflects emotional assessments.

[0451] Input: Analysis results

[0452] Data processing: The server generates text advice based on health and emotional states.

[0453] Output: Generated health advice

[0454] Step 6: Providing advice

[0455] The smartphone displays advice received from the server within the application. An interactive avatar provides advice via voice and video.

[0456] Input: Advice from the server

[0457] Data processing: A smartphone app displays advice in a format suitable for the user interface, and an avatar provides voice output.

[0458] Output: Advice that users receive visually and aurally.

[0459] Step 7: Notification of health data and analysis results

[0460] The server notifies the family of the user's health data and analysis results.

[0461] Input: Analysis results

[0462] Data communication: The server sends the analysis results to pre-registered family contacts (e.g., email, text message).

[0463] Output: Health data and analysis results notified to the family.

[0464] Step 8: Support for three-way calls using generative AI models

[0465] The user or a family member requests a three-way call through a smartphone app. The server activates a generated AI model and sets up the call.

[0466] Input: Call request

[0467] Data processing: Generative AI models supplement user and family conversations, providing real-time health-related questions and advice.

[0468] Output: Health advice provided in real time

[0469] (Application Example 2)

[0470] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0471] Modern users are expected not only to monitor their health data but also to take concrete actions based on that data. However, current systems do not adequately support users in choosing appropriate products and services based on their health data, and furthermore, they lack advice that takes into account the user's emotional state. In addition, it is difficult to grasp health and emotional states in a unified manner and translate that into actual actions.

[0472] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for having an avatar for displaying health advice and product suggestions generated by analyzing the user's health data, means for supporting three-way communication between the user, family, and the generated AI, and means for suggesting health products suitable for the user. As a result, the user can receive personalized advice and product suggestions according to their health and emotional state and take appropriate health actions.

[0473] A "wearable device" is a device that is worn on the body to continuously monitor the user's health data.

[0474] A "terminal" is a device that receives and temporarily stores data transmitted from a wearable device.

[0475] A "server" is a device that analyzes data received from terminals and generates health advice and product suggestions based on that analysis.

[0476] A "display means" is a device that provides users with health advice and product suggestions generated by a server, both visually and audibly.

[0477] "Communication means" refers to the means of notifying the user's family of health data and analysis results.

[0478] "Suggestion methods" refer to methods for suggesting health products suitable for the user based on collected health data and emotional data.

[0479] "Means of having an avatar" refers to a virtual character used to display health advice and product suggestions generated by the server.

[0480] This section describes the specific system configuration and operation for implementing this invention. This system collects and analyzes user health data and suggests suitable health products based on the results. The hardware and software used and their processing are described below.

[0481] 1. Hardware Usage Configuration

[0482] Wearable devices: such as smartwatches and smart bands.

[0483] Device: Smartphones and tablets

[0484] Server: A server used for data analysis.

[0485] Display devices: Smartphones, smart glasses (AR glasses)

[0486] 2. Software Usage Configuration

[0487] Health data collection app: Transfers data collected by wearable devices to your device.

[0488] Data analysis system: A program that runs on the server side and evaluates and analyzes health status.

[0489] Emotion Engine: An algorithm that analyzes the user's emotional state.

[0490] Generative AI models: Suggest products based on user health and emotional data.

[0491] Virtual Avatar Generation Engine: A program for generating virtual characters to present product suggestions to users.

[0492] 3. System Operation

[0493] This system operates using the following processing flow:

[0494] Wearable devices monitor the user's health data in real time, including heart rate, steps taken, calories burned, blood pressure, and blood sugar levels, and transmit this data to the device.

[0495] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[0496] The server analyzes the received health data and evaluates the user's health status. The emotion engine also analyzes the user's emotional state.

[0497] The data analysis system and emotion engine use generative AI models based on the analysis results to generate health products and advice tailored to the user.

[0498] The display device uses a smartphone or smart glasses, and an avatar provides product suggestions and health advice to the user via voice and video. It also supports three-way calls based on a generative AI model, allowing the user, family, and AI to communicate in real time.

[0499] 4. Specific Examples

[0500] One afternoon, User A finished jogging while wearing a wearable device. Afterward, the following data was sent to their smartphone:

[0501] Heart rate: 120 bpm

[0502] Steps: 10,000 steps

[0503] Calories burned: 450 kcal

[0504] Blood pressure: 130 / 85

[0505] Blood glucose level: 95 mg / dL

[0506] Emotional state: Stressed

[0507] The server analyzed this data and generated the following product suggestions:

[0508] Supplements: "Vitamin C supplements effective for relieving fatigue"

[0509] Fitness equipment: "Yoga mat"

[0510] Health foods: "Low-calorie protein bars"

[0511] Stress relief item: "Aromatherapy candle for meditation"

[0512] Using smart glasses as a display device, a virtual avatar presents these products to person A using voice and video. The avatar then suggests an additional option, saying, "We can also provide relaxing music," and person A purchases the products within the app.

[0513] 5. Example of a prompt statement

[0514] The following are examples of prompts for generative AI models:

[0515] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[0516] This system allows users to easily take specific actions tailored to their health condition and receive support in selecting appropriate products and services.

[0517] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0518] Step 1:

[0519] Users wear wearable devices that collect health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels in real time.

[0520] Input: User's health data (heart rate, steps, calories burned, blood pressure, blood sugar level)

[0521] Output: Collected health data

[0522] Specific operation: The wearable device uses sensors to measure health data and stores the data in its internal memory.

[0523] Step 2:

[0524] Data collected from wearable devices is transmitted to a terminal (smartphone) via Bluetooth or Wi-Fi.

[0525] Input: Health data stored on a wearable device

[0526] Output: Health data transferred to smartphone

[0527] Specific operation: The wearable device uses Bluetooth or Wi-Fi to send data to a smartphone app.

[0528] Step 3:

[0529] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[0530] Input: Temporary data stored on a smartphone (health data)

[0531] Output: Health data sent to the server

[0532] Specific operation: The smartphone temporarily stores the received data in its memory, and then uploads the data to the server via the internet.

[0533] Step 4:

[0534] The server analyzes the health data it receives and evaluates the user's health and emotional state.

[0535] Input: Health data sent to the server

[0536] Output: Analyzed health and emotional state

[0537] Specific operation: The server uses a data analysis system and an emotion engine to analyze health data and evaluate the user's physical condition and stress level.

[0538] Step 5:

[0539] The server uses a generative AI model based on the analysis results to generate health products and advice tailored to the user.

[0540] Input: Analyzed health and emotional state

[0541] Output: Health advice and product suggestions

[0542] Specific operation: The server references a generative AI model and makes product suggestions using the following prompts:

[0543] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[0544] Step 6:

[0545] Virtual avatars provide users with health advice and product recommendations via smartphones and smart glasses.

[0546] Input: Health advice and product suggestions

[0547] Output: Advice and product information provided to the user.

[0548] Specific operation: Smartphones and smart glasses display devices use virtual avatars to provide information to users through audio and video.

[0549] Step 7:

[0550] The server uses a generative AI model to support three-way calls involving the user, family members, and the AI.

[0551] Input: User and family requests, generative AI model

[0552] Output: Three-way call session and real-time health advice

[0553] Specific operation: The server activates a generative AI model and provides health-related questions and advice in real time during the call.

[0554] This allows users to easily take specific actions based on their health data and receive support in choosing appropriate products and services.

[0555] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0556] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0557] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0558] [Second Embodiment]

[0559] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0560] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0561] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0562] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0563] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0564] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0565] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0566] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0567] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0568] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0569] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0570] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0571] This invention is a system for supporting user health management, and mainly consists of a wearable device, a terminal, a server, and a program that links them together.

[0572] System Configuration

[0573] Wearable devices: This includes smart bands and smartwatches, which have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, and so on.

[0574] Terminal: This refers to the user's smartphone or tablet, which receives and temporarily stores data transmitted from wearable devices.

[0575] Server: Analyzes data received from terminals to evaluate and monitor the user's health status. It also has the function to generate health advice based on the analysis results and notify the user and their family.

[0576] Display means: A device for providing users with health advice generated by a server in a visual and auditory way. For example, an avatar delivers advice via voice and video through a smartphone's display or speaker.

[0577] Program processing flow

[0578] 1. Data collection:

[0579] Users wear wearable devices while going about their daily lives.

[0580] Wearable devices (terminals) monitor the user's health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[0581] 2. Data transfer and temporary storage:

[0582] The wearable device (terminal) periodically transmits the collected data to the user's smartphone via Bluetooth or Wi-Fi.

[0583] This function temporarily stores data received by a smartphone (device).

[0584] 3. Data transmission and analysis:

[0585] The smartphone (device) sends the stored data to the server via the internet.

[0586] The server analyzes the received data and assesses the user's health status. Based on the analysis results, it also generates appropriate health advice (such as exercise plans and dietary advice).

[0587] 4. Providing advice:

[0588] The server generates health advice, which is then sent to the smartphone for display.

[0589] The smartphone (device) displays the advice it receives within the application, and an avatar communicates it to the user via voice or video.

[0590] 5. Data notification:

[0591] The server notifies pre-registered family contacts of the user's health data and the generated advice and analysis results. For example, the data is sent to family members' smartphones or email addresses.

[0592] 6. Three-way calls using generative AI:

[0593] The user or a family member (user) requests a three-way call using a smartphone app.

[0594] The server activates the generative AI and configures it to allow communication between the user, family, and the generative AI.

[0595] The generative AI (server) analyzes the call content and provides appropriate supplementary information and advice in real time.

[0596] Specific example

[0597] One morning, I will explain in detail how an elderly user, Mr. A, uses the system.

[0598] Data collection:

[0599] User A: Every morning I put on my smartwatch and go for a walk.

[0600] Smartwatches (wearable devices): Continuously monitor heart rate, steps taken, and calories burned, including while walking.

[0601] Data transfer and temporary storage:

[0602] Smartwatch (wearable device): After returning home from a walk, it transmits health data to Person A's smartphone via Bluetooth.

[0603] Smartphone (device): Temporarily stores received data.

[0604] Data transmission and analysis:

[0605] Smartphone (device): Sends stored data to a server via the internet.

[0606] Server: Analyzes the received data and determines that Person A's blood pressure is slightly elevated. It also generates advice on appropriate dietary habits for managing their health.

[0607] Providing advice:

[0608] Server: Generates the advice, "Today, try to eat a low-salt meal," and sends it to Person A's smartphone.

[0609] Smartphone (device): The application displays advice and conveys it to person A through an avatar.

[0610] Data notification:

[0611] Server: Sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[0612] Son (family member / user): Check the received information.

[0613] Three-way calls using generative AI:

[0614] Son (family member / user): I need to call Person A urgently, so I request a three-way call through the app.

[0615] User A: Accepts the call request and joins the conversation.

[0616] Server: Activates a generative AI to supplement the call with health-related questions and confirmations in real time.

[0617] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[0618] The following describes the processing flow.

[0619] Step 1:

[0620] The user wears a wearable device (such as a smart band or smartwatch).

[0621] Step 2:

[0622] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0623] Step 3:

[0624] The wearable device periodically transmits the data it collects to the user's smartphone (device) via Bluetooth or Wi-Fi.

[0625] Step 4:

[0626] This function temporarily stores data received by the smartphone (device).

[0627] Step 5:

[0628] The smartphone (device) periodically transmits accumulated health data to a server via the internet.

[0629] Step 6:

[0630] The server saves the received data to the database.

[0631] Step 7:

[0632] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[0633] Step 8:

[0634] The server generates appropriate health advice (e.g., exercise plans and dietary advice) based on the analysis results.

[0635] Step 9:

[0636] The server sends the generated health advice to the user's smartphone (device).

[0637] Step 10:

[0638] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[0639] Step 11:

[0640] An avatar, acting as a display device, conveys advice to the user using voice and video.

[0641] Step 12:

[0642] The server notifies the user's health data and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[0643] Step 13:

[0644] Family members (users) review the notified information and send feedback to the server as needed.

[0645] Step 14:

[0646] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[0647] Step 15:

[0648] The user accepts the request for a three-way call.

[0649] Step 16:

[0650] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[0651] Step 17:

[0652] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[0653] Step 18:

[0654] The user and their family (user) end the call, and the server's generative AI saves or logs the call content.

[0655] (Example 1)

[0656] Next, we will describe Example 1. 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."

[0657] In modern times, health management is a crucial issue, and many people are required to understand their own health status and take appropriate measures. However, for the elderly and those with chronic diseases, collecting and analyzing their own data is difficult, making it challenging to receive appropriate health advice. Furthermore, it is difficult for family members living separately to understand the situation and provide support. To solve this problem, a system is needed that collects and analyzes health data in real time, provides appropriate advice, and allows information to be shared with family members.

[0658] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0659] In this invention, the server includes synchronization means for periodically transmitting data temporarily stored in the communication device to the information processing device; means for generating health advice based on the analysis results of the information processing device using a generative AI model; and means for the information processing device to support three-way communication between the user, family, and generative AI. This enables real-time collection and analysis of the user's health data, provision of appropriate advice, and data notification to family members.

[0660] A "measuring device" refers to a wearable device that collects user health data and has functions to monitor heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[0661] "Communication equipment" refers to a device that temporarily stores health data received from the aforementioned measuring device, and includes mobile information terminals such as smartphones and tablets.

[0662] An "information processing device" is a device that receives health data transmitted from the aforementioned communication device, analyzes it, and evaluates the user's health status, and refers to a server or cloud computer.

[0663] "Display means" refers to means for providing health advice generated by the information processing device to the user, and includes a smartphone display and an audio output device.

[0664] "Data transmission means" refers to means for notifying family members of the aforementioned health data and analysis results, and includes email and push notifications via the internet.

[0665] "Synchronization means" refers to a function for periodically transmitting data temporarily stored in the communication device to the information processing device.

[0666] A "generative AI model" is an artificial intelligence model that generates health advice based on the analysis of a user's health data, and refers to a generative AI that utilizes natural language processing technology.

[0667] A "virtual character" refers to a character used to display health advice generated by the aforementioned information processing device, and is an avatar that provides advice using voice and video.

[0668] "Means to support three-way calls" refers to features that allow users, family members, and generative AI to participate in a call simultaneously.

[0669] This invention is a system for supporting user health management, and consists of a wearable device, a terminal, a server, and a program that links them together. The specific components of the system and their functions are described below.

[0670] System Configuration

[0671] 1. Wearable devices

[0672] Measurement devices (wearable devices) have the function of monitoring the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[0673] Examples include smart bands and smartwatches.

[0674] 2. Terminal

[0675] Communication devices (smartphones and tablets) play the role of receiving and temporarily storing data transmitted from wearable devices.

[0676] Specific examples include smartphones running iOS or Android.

[0677] 3. Server

[0678] The information processing device (server) analyzes data received from the terminal and evaluates the user's health status. Based on the analysis results, it generates health advice using a generative AI model and transmits it to the display device.

[0679] Examples include cloud servers and on-premises servers.

[0680] 4. Display means

[0681] The display means is a device for providing users with health advice generated by the server in a visual and auditory way.

[0682] Specific example: An avatar uses the smartphone's display and speakers to provide advice via voice and video.

[0683] 5. Data transmission means

[0684] The data transmission means is a means of notifying family members of health data and analysis results.

[0685] Specific example: Sending emails and push notifications over the internet.

[0686] 6. Synchronization means

[0687] The synchronization mechanism has the function of periodically transmitting data temporarily stored in the communication device to an information processing device.

[0688] 7. Generative AI Models

[0689] Generative AI models are artificial intelligence models designed to generate appropriate health advice based on the analysis of a user's health data.

[0690] Specific example: Use natural language processing techniques such as GPT-4.

[0691] 8. Virtual Character

[0692] The virtual character is a character used to display health advice generated by the server, providing advice through voice and video.

[0693] 9. Means to support three-way calls

[0694] The means of supporting three-way calls provides the ability for the user, family members, and generative AI to talk simultaneously.

[0695] Specific example

[0696] The case of elderly person A one day

[0697] 1. Data collection:

[0698] User A puts on their smartwatch every morning and goes for a walk.

[0699] Smartwatches continuously monitor heart rate, steps taken, and calories burned.

[0700] 2. Data transfer and temporary storage:

[0701] The smartwatch transmits health data to Person A's smartphone via Bluetooth after returning home from a walk.

[0702] Smartphones temporarily store received data in a database within the app.

[0703] 3. Data transmission and analysis:

[0704] Smartphones transmit stored data to servers via the internet.

[0705] The server executes Python scripts and analyzes data using Scikit-learn models.

[0706] 4. Providing advice:

[0707] The server generates advice such as, "Today, try to eat a low-salt meal," and sends it to the smartphone.

[0708] The smartphone displays advice within the app and communicates it to person A via voice using the Google Assistant API.

[0709] 5. Data notification:

[0710] The server sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[0711] The son (family member / user) checks the received information.

[0712] 6. Three-way calls using generative AI models:

[0713] The son (family member / user) requests a three-way call through the app.

[0714] User A accepts the call request.

[0715] The server sets up a call session using WebRTC and starts the generative AI model.

[0716] The generative AI model analyzes the content of the call and supplements it with health-related questions and confirmations in real time.

[0717] Example of a prompt

[0718] 1. "Mr. / Ms. A would like to check their health data for today. What is their current health status?"

[0719] 2. "What are some recent health concerns regarding Mr. / Ms. A?"

[0720] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[0721] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0722] Step 1:

[0723] Data collection

[0724] Users wear wearable devices on a daily basis while going about their daily lives.

[0725] Specific action: Every morning, the user puts on a smartwatch on their wrist.

[0726] Wearable devices collect health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[0727] Input: User's biometric information.

[0728] Data processing: Measurement using sensors.

[0729] Output: Raw health data.

[0730] Step 2:

[0731] Data transfer and temporary storage

[0732] The wearable device collects data and transmits it to the user's device via Bluetooth or Wi-Fi.

[0733] Specific operation: The wearable device synchronizes with the terminal periodically or at the user's request.

[0734] The application temporarily stores the data received by the device.

[0735] Input: Health data transmitted from a wearable device.

[0736] Data processing: Data storage within the device.

[0737] Output: Temporarily stored health data.

[0738] Step 3:

[0739] Data transmission and analysis

[0740] The device sends temporarily stored data to the server via the internet.

[0741] Specific operation: The app sends data periodically or in response to user actions.

[0742] The server analyzes the received data and evaluates the user's health status.

[0743] Input: Health data sent from the device.

[0744] Data processing: Preprocessing and analysis using Python scripts.

[0745] Output: Health assessment report.

[0746] The server generates health advice using a generative AI model.

[0747] Input: Health assessment report.

[0748] Data processing: Generating advice using generative AI models such as GPT-4.

[0749] Output: Health advice.

[0750] Step 4:

[0751] Providing advice

[0752] The server generates health advice and sends it to the device.

[0753] Specific operation: Sending data via a REST API.

[0754] The application displays the advice received by the device, and an avatar communicates it to the user via voice or video.

[0755] Input: Health advice sent from the server.

[0756] Data processing: Conversion to in-app display format and speech synthesis.

[0757] Output: Display of advice to the user and audio output.

[0758] Step 5:

[0759] Data notification

[0760] The server notifies the family of their health data and generated advice.

[0761] Specific action: Send emails and push notifications using the notification service.

[0762] Family members receive notifications and check on the user's health status.

[0763] Input: Notification data sent from the server.

[0764] Data processing: Display via email or push notification.

[0765] Output: Notification displayed to family members.

[0766] Step 6:

[0767] Three-way calls using a generative AI model

[0768] The user or a family member requests a three-way call using a smartphone app.

[0769] Specific action: Press the "3-way call" button within the app.

[0770] The server activates the generated AI model and configures it to allow calls between the user, family members, and the generated AI model.

[0771] Input: Call request.

[0772] Data processing: Session setup and activation of the generated AI model using WebRTC technology.

[0773] Output: Call session started.

[0774] The generative AI model analyzes the call content and provides appropriate supplementary information and advice in real time.

[0775] Specific operation: The system analyzes call content in real time and uses speech synthesis to provide supplementary explanations and advice.

[0776] Input: Call content.

[0777] Data processing: Real-time analysis and speech synthesis.

[0778] Output: Supplementary explanations or advice.

[0779] (Application Example 1)

[0780] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0781] This invention relates to a system for supporting users' health management. It aims to not only collect and analyze health data using wearable devices and provide health advice based on the results, but also to provide real-time, optimal guidance when implementing a fitness plan in a virtual environment, thereby enabling effective health management and fitness instruction. Furthermore, it aims to enhance communication between the user and their family through three-way calls using a generation system, making it easier for family members living separately to understand the user's health status.

[0782] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0783] In this invention, the server includes means for analyzing the user's health data and evaluating their health status, means for generating health advice and fitness plans, and means for notifying the user and their family of the generated data. This makes it possible to provide fitness plans within a virtual environment and to share information about the user's health status with their family.

[0784] A "wearable device" is a device used to collect user health data, and includes smart bands and smartwatches.

[0785] "Terminal" refers to a device that receives and temporarily stores data collected from the wearable device, and includes smartphones, tablets, and the like.

[0786] A "server" is a device that receives data transmitted from the aforementioned terminal, analyzes it, and evaluates the health status, and includes cloud servers and data processing facilities.

[0787] "Display means" refers to a device for providing health advice generated by the server to the user, and includes a smartphone display and an audio output device.

[0788] "Communication means" refers to a device for notifying family members of the aforementioned health data and analysis results, and includes internet connectivity and email systems.

[0789] "Guide data" refers to data generated by the server to provide a fitness plan within the virtual environment, and includes exercise instructions and health advice.

[0790] "Smart glasses" refers to a device that allows the terminal to display a virtual environment and provide guidance to the user, and includes head-mounted displays and augmented reality glasses.

[0791] A "virtual environment" is an environment in which users can experience and engage in activities in a virtually defined space or situation, and includes virtual fitness rooms and virtual gyms.

[0792] A "fitness plan" is an exercise guidance and exercise program generated by the server based on the user's health data, and includes individual exercise menus and exercise guidelines.

[0793] This invention relates to a system for supporting user health management, and its main components include a wearable device, a terminal, a server, and smart glasses. This system is particularly effective when applied in virtual stores.

[0794] 1. System Configuration

[0795] Wearable devices include smart bands and smartwatches that have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc. A typical smartwatch is an example.

[0796] Terminal: This refers to the user's smartphone or tablet, which receives data transmitted from wearable devices via Bluetooth or Wi-Fi and temporarily stores it.

[0797] Server: Analyzes data received from terminals and assesses the user's health status. Based on the analysis results, it generates health advice and fitness plans and notifies the user and their family.

[0798] Smart glasses: Devices that display a virtual environment and provide virtual fitness guidance. Examples include head-mounted displays (HMDs) and augmented reality (AR) glasses.

[0799] 2. Program Processing

[0800] 2.1 Data Collection

[0801] While the user wears the smartwatch and goes about their daily life, the wearable device monitors health data such as heart rate, steps taken, calories burned, and blood pressure in real time.

[0802] 2.2 Data Transfer and Temporary Storage

[0803] The smartwatch periodically transmits monitored data to the user's smartphone via Bluetooth or Wi-Fi. The smartphone temporarily stores the received data.

[0804] 2.3 Data Transmission and Analysis

[0805] Smartphones transmit stored data to servers via the internet. The servers analyze the received data and assess the user's health status. They also generate appropriate health advice and fitness plans.

[0806] 2.4 Providing Guides

[0807] The server generates a fitness plan, which is then sent to the smartphone for display. Within the virtual environment, the smart glasses convey the generated fitness guide to the user via voice and visual means through an avatar. Specifically, when the user performs a squat, animations and avatar guides are displayed on the smart glasses to instruct them on correct form.

[0808] 2.5 Data Notification

[0809] The server notifies the family of the user's health data and the generated advice and analysis results. This allows the family to understand the user's health status in real time.

[0810] 3. Specific examples

[0811] On a given morning, when a user uses the system, they would go through the following steps:

[0812] Data collection from wearable devices: Users wear smartwatches while exercising or engaging in daily activities.

[0813] Data transfer: The smartwatch transfers collected data to the smartphone.

[0814] Data analysis: The smartphone sends data to the server, and the server performs the analysis.

[0815] Fitness plan delivery: A server generates a fitness plan and sends it to smart glasses, allowing the user to receive guidance within a virtual environment.

[0816] Example of a prompt:

[0817] Let's begin today's fitness plan. I've read your heart rate data. Next, please do 5 squats.

[0818] This allows users to effectively execute fitness plans in a virtual environment and manage their health in real time. It also strengthens family collaboration and enables efficient management of the user's health status.

[0819] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0820] Step 1:

[0821] The user wears a smartwatch while going about their daily life. The smartwatch monitors health data such as heart rate, steps taken, calories burned, and blood pressure in real time. The input is the user's activity data, and the output is the monitored health data.

[0822] Step 2:

[0823] The smartwatch collects health data and transmits it to the user's smartphone via Bluetooth or Wi-Fi. The input is the health data stored on the smartwatch, and the output is the data transferred to the smartphone.

[0824] Step 3:

[0825] The smartphone temporarily stores the health data it receives. The input is the health data transferred from the smartwatch, and the output is the temporarily stored data.

[0826] Step 4:

[0827] A smartphone sends temporarily stored data to a server via the internet. The input is the data stored on the smartphone, and the output is the data sent to the server.

[0828] Step 5:

[0829] The server analyzes the received data and evaluates the user's health status. The input is health data sent to the server, and the output is the analysis results and health evaluation.

[0830] Step 6:

[0831] The server generates appropriate health advice and fitness plans based on the analysis results. The input is health assessment data, and the output is health advice and fitness plans.

[0832] Step 7:

[0833] The server generates a fitness plan and sends it to the smartphone, which then displays it. The input is the generated fitness plan, and the output is the fitness plan displayed on the smartphone.

[0834] Step 8:

[0835] Smart glasses display a fitness plan in a virtual environment and provide guidance to the user. The input is the fitness plan displayed on a smartphone, and the output is the guidance displayed on the smart glasses. This may include exercise instruction using animations or avatars.

[0836] Step 9:

[0837] The server notifies the family of the user's health data and analysis results. The input is the generated analysis results and health data, and the output is the notification sent to the family.

[0838] Step 10:

[0839] The smartphone displays a generated prompt message to the user, who then follows the instructions to begin exercising. The input is the generated prompt message, and the output is the user's exercise performance. Example prompt message: "Starting today's fitness plan. Heart rate data read. Now, please do 5 squats."

[0840] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0841] This invention is a system that supports user health management and mainly consists of a wearable device, a terminal, a server, an emotion engine, and a program that coordinates these components.

[0842] System Configuration

[0843] Wearable devices: This includes smart bands and smartwatches, which have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, and so on.

[0844] Terminal: This refers to the user's smartphone or tablet, which receives and temporarily stores data transmitted from wearable devices.

[0845] Server: Analyzes data received from terminals to evaluate and monitor the user's health status. It also has the function to generate health advice based on the analysis results and notify the user and their family.

[0846] Display means: A device for providing users with health advice generated by a server in a visual and auditory way. For example, an avatar delivers advice via voice and video through a smartphone's display or speaker.

[0847] Emotion Engine: It has an algorithm that recognizes the user's emotions and analyzes their emotional state based on collected health data.

[0848] Program processing flow

[0849] 1. Data collection:

[0850] Users wear wearable devices while going about their daily lives.

[0851] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0852] 2. Data transfer and temporary storage:

[0853] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[0854] This function temporarily stores data received by a smartphone (device).

[0855] 3. Data transmission and analysis:

[0856] The smartphone (device) sends the stored data to the server via the internet.

[0857] The server saves the received data to the database and begins analysis.

[0858] The emotion engine (device) analyzes the user's emotional state based on the collected data.

[0859] 4. Generating advice:

[0860] The server generates personalized health advice based on the analyzed health and emotional data.

[0861] The server sends the generated health advice to the user's smartphone (device).

[0862] 5. Providing advice:

[0863] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[0864] An avatar, acting as a display device, conveys advice to the user using voice and video.

[0865] 6. Data notification:

[0866] The server notifies pre-registered family contacts of the user's health data, emotional data, and analysis results.

[0867] Family members (users) review the notified information and send feedback as needed.

[0868] 7. Three-way calls using generative AI:

[0869] The user or a family member (user) requests a three-way call through a smartphone application.

[0870] The server activates a generative AI and sets up a three-way call. During the call, the generative AI supplements the conversation between the user and their family, providing real-time health-related questions and advice.

[0871] Specific example

[0872] One morning, I will explain in detail how an elderly person, Mr. B, uses the system.

[0873] 1. Data collection:

[0874] User B puts on their smartwatch and goes for a walk.

[0875] A smartwatch (wearable device) monitors your heart rate, steps taken, and calories burned while you're out for a walk.

[0876] 2. Data transfer and temporary storage:

[0877] The smartwatch (wearable device) transmits the collected data to Person B's smartphone via Bluetooth.

[0878] This function temporarily stores data received by the smartphone (device).

[0879] 3. Data transmission and analysis:

[0880] The smartphone (device) sends the stored data to the server.

[0881] The server analyzes the data and determines that Person B's blood pressure is on the higher side. Additionally, the emotion engine analyzes Person B's emotional state as "high stress."

[0882] 4. Generating advice:

[0883] The server generates advice such as, "Today, try to eat a low-salt diet," and based on the emotion engine, it also generates additional advice such as, "I recommend listening to relaxing music."

[0884] The smartphone (device) receives the advice, and the avatar relays it to person B along with a voice message.

[0885] 5. Data notification:

[0886] The server notifies B's family of their health and emotional data.

[0887] The family member (user) checks the notification and sends feedback to the server about Person B's health condition.

[0888] 6. Three-way calls using generative AI:

[0889] A family member (user) requests a call, and person B accepts.

[0890] The server activates a generative AI, providing real-time health-related questions and advice during the call.

[0891] In this way, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind. In particular, by integrating an emotion engine, it is possible to provide personalized advice that takes into account the user's mental state, not just monitoring health data. Furthermore, it becomes easier for family members living separately to understand the health status in real time and provide necessary support.

[0892] The following describes the processing flow.

[0893] Step 1:

[0894] The user wears a wearable device (such as a smart band or smartwatch).

[0895] Step 2:

[0896] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0897] Step 3:

[0898] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[0899] Step 4:

[0900] This function temporarily stores data received by the smartphone (device).

[0901] Step 5:

[0902] An emotion engine (located on the device or on a server) analyzes additional information such as the user's voice, facial expressions, and text input based on data from wearable devices and smartphones to identify the user's emotional state.

[0903] Step 6:

[0904] The smartphone (device) transmits accumulated health data and emotional data to a server via the internet.

[0905] Step 7:

[0906] The server saves the received data to the database.

[0907] Step 8:

[0908] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[0909] Step 9:

[0910] The server evaluates the user's emotional state based on the results from the emotion engine and generates personalized health advice.

[0911] Step 10:

[0912] The server sends the generated health advice to the user's smartphone (device).

[0913] Step 11:

[0914] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[0915] Step 12:

[0916] An avatar, acting as a display device, conveys advice to the user using voice and video.

[0917] Step 13:

[0918] The server notifies the user's health data, emotional data, and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[0919] Step 14:

[0920] Family members (users) review the notified information and send feedback to the server as needed.

[0921] Step 15:

[0922] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[0923] Step 16:

[0924] The user accepts the request for a three-way call.

[0925] Step 17:

[0926] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[0927] Step 18:

[0928] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[0929] Step 19:

[0930] The user and their family (user) end the call, and the server saves or logs the call content using a generative AI.

[0931] (Example 2)

[0932] Next, we will describe Example 2. 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".

[0933] In modern society, there is a need for systems that can monitor both a user's health and emotional state in real time and provide appropriate advice. Collecting and analyzing health data in daily life is particularly important for the elderly and those with unstable health conditions. However, there is a lack of technology that not only monitors health data but also provides personalized advice that takes emotional states into account. Furthermore, there are limited means for family members living separately to monitor a user's health in real time and provide necessary support.

[0934] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an emotion engine that analyzes the user's emotional state using an emotion algorithm, means for supporting a three-way call between the user, family, and a generating AI model, a measurement device for collecting the user's health data, a terminal that receives and temporarily stores data from the measurement device, means for receiving data from the terminal, analyzing it, and evaluating the health state, display means for providing health advice generated by the server, and communication means for notifying the family of the health data and analysis results. This makes it possible to grasp the user's health state and emotional state in real time and provide personalized advice. In addition, family members can grasp the health state in real time from a remote location and provide appropriate support.

[0935] A "measurement device" is a device used to collect a user's health data, monitoring physical data such as heart rate, steps taken, calories burned, blood pressure, and blood glucose levels.

[0936] A "terminal" is a device that receives and temporarily stores health data transmitted from a measurement device, and includes smartphones and tablets.

[0937] A "server" is a computing system that receives data transmitted from a terminal, performs analysis, and evaluates the user's health status. Its role is to generate and notify users of health advice based on the analysis results.

[0938] "Display means" refers to a device that provides the user with health advice generated by the server, either visually or audibly, and includes smartphone displays, speakers, avatars, and other similar devices.

[0939] "Means of communication" refers to the method by which the server analyzes health data and analysis results and notifies family members of these methods, including the internet, email, and text messages.

[0940] An "emotion engine" is an algorithm and system that analyzes a user's emotional state based on their health data and behavioral patterns.

[0941] A "generative AI model" is an artificial intelligence system designed to support communication with users and their families, providing real-time answers to health-related questions and advice.

[0942] A "three-way call" refers to a call between the user, their family, and a generative AI model, allowing the user and their family to exchange health-related information and receive advice in real time.

[0943] "Health advice" refers to specific instructions and suggestions generated by the server based on an analysis of the user's health and emotional data, providing information necessary to improve and maintain the user's health.

[0944] The present invention is a system for supporting user health management and emotion analysis, and consists of a measurement device, a terminal, a server, an emotion engine, a generative AI model, and a program that links these together.

[0945] System Configuration

[0946] Measurement devices

[0947] Measurement devices such as smart bands and smartwatches are used. These devices have the function of continuously monitoring the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels. For example, a smartwatch measures the user's heart rate every minute and stores that data in its internal memory.

[0948] terminal

[0949] The terminal is the user's smartphone or tablet, and its role is to receive and temporarily store data transmitted from the measurement device. For example, the smartphone receives data transmitted from a smartwatch via Bluetooth and temporarily stores it in local storage.

[0950] server

[0951] The server is a computing system located in the cloud that analyzes data received from terminals and evaluates the user's health status. The server utilizes multiple algorithms to analyze trends in heart rate data, for example, and detect anomalies. Based on the analysis results, it generates personalized health advice and notifies the user and their family.

[0952] Emotional Engine

[0953] The emotion engine is a software component integrated within the server that analyzes the user's emotional state based on health data and behavioral patterns. For example, if the user has a low step count and a high heart rate, the emotion engine detects the user's stress level and incorporates that information into the analysis results.

[0954] Generative AI Models

[0955] The Generative AI Model is an artificial intelligence system that supports three-way calls between the user and their family, providing real-time health-related questions and advice. For example, if a user enters a prompt such as, "My blood pressure is high today, and I'm feeling stressed. Could you give me some advice on how to relax?", the Generative AI Model will provide appropriate advice in real time.

[0956] means of communication

[0957] The system uses the internet, email, and text messages as communication methods to notify family members of the health data and analysis results analyzed by the server. For example, if a user's heart rate remains elevated, a notification will be sent to their family via email.

[0958] Display means

[0959] The display methods used include smartphone displays, speakers, and avatars. Health advice generated by the server is provided to the user visually or audibly. For example, a smartphone app might display the advice, "We recommend you go to bed early tonight," while an avatar delivers the advice verbally.

[0960] Specific example

[0961] Let's take an example of an elderly user using this system one morning. The user puts on a smartwatch and goes for a walk. The smartwatch monitors heart rate, steps taken, and calories burned during the walk. The collected data is transmitted to the user's smartphone via Bluetooth, where it is temporarily stored.

[0962] The smartphone then sends the saved data to the server. The server analyzes the received data and determines that the user has high blood pressure and is under high stress. The server generates health advice such as "Try to eat a low-salt diet today" and emotional data-based advice such as "We recommend listening to relaxing music," and sends these to the user's smartphone.

[0963] A smartphone app receives advice, and an avatar conveys it to the user via voice. The server also notifies the user's family of the analysis data, and the family sends feedback to the server about the user's health.

[0964] The user or their family can request a three-way call through a generative AI model and receive real-time health-related questions and advice during the call. In this way, the system of the present invention can provide integrated support for the user's health management and emotional state.

[0965] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0966] Step 1: Data Collection

[0967] The user wears a measurement device (e.g., a smartwatch). The smartwatch monitors health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[0968] Input: User's biometric information

[0969] Data processing: The smartwatch senses biometric information in real time, collects the necessary data, and stores it in its internal memory.

[0970] Output: Collected health data (heart rate, steps, etc.)

[0971] Step 2: Data Transfer and Temporary Storage

[0972] The wearable device transmits the data it collects via Bluetooth to the user's smartphone.

[0973] Input: Health data from smartwatch

[0974] Data processing: The smartphone receives data via Bluetooth, converts it to an appropriate format for temporary storage, and saves it to its internal storage.

[0975] Output: Health data stored on the smartphone

[0976] Step 3: Data transmission and analysis

[0977] The smartphone sends the stored data to the server via the internet.

[0978] Input: Health data on your smartphone

[0979] Data transfer: The smartphone uploads data to the server using the appropriate protocol (e.g., HTTPS).

[0980] Output: Health data sent to the server

[0981] Step 4: Data analysis and emotional state analysis

[0982] The server stores the received data in a database and performs initial analysis. The server analyzes trends and anomalies in the health data, and the emotion engine evaluates the emotional state.

[0983] Input: Received health data

[0984] Data processing: The server uses algorithms to perform analysis, and the emotion engine performs sentiment analysis based on user behavior data and health data.

[0985] Output: Analysis results (health assessment, emotional assessment)

[0986] Step 5: Generate and send advice

[0987] The server generates personalized health advice based on the analysis results. The emotion engine also generates advice that reflects emotional assessments.

[0988] Input: Analysis results

[0989] Data processing: The server generates text advice based on health and emotional states.

[0990] Output: Generated health advice

[0991] Step 6: Providing advice

[0992] The smartphone displays advice received from the server within the application. An interactive avatar provides advice via voice and video.

[0993] Input: Advice from the server

[0994] Data processing: A smartphone app displays advice in a format suitable for the user interface, and an avatar provides voice output.

[0995] Output: Advice that users receive visually and aurally.

[0996] Step 7: Notification of health data and analysis results

[0997] The server notifies the family of the user's health data and analysis results.

[0998] Input: Analysis results

[0999] Data communication: The server sends the analysis results to pre-registered family contacts (e.g., email, text message).

[1000] Output: Health data and analysis results notified to the family.

[1001] Step 8: Support for three-way calls using generative AI models

[1002] The user or a family member requests a three-way call through a smartphone app. The server activates a generated AI model and sets up the call.

[1003] Input: Call request

[1004] Data processing: Generative AI models supplement user and family conversations, providing real-time health-related questions and advice.

[1005] Output: Health advice provided in real time

[1006] (Application Example 2)

[1007] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1008] Modern users are expected not only to monitor their health data but also to take concrete actions based on that data. However, current systems do not adequately support users in choosing appropriate products and services based on their health data, and furthermore, they lack advice that takes into account the user's emotional state. In addition, it is difficult to grasp health and emotional states in a unified manner and translate that into actual actions.

[1009] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for having an avatar for displaying health advice and product suggestions generated by analyzing the user's health data, means for supporting three-way communication between the user, family, and the generated AI, and means for suggesting health products suitable for the user. As a result, the user can receive personalized advice and product suggestions according to their health and emotional state and take appropriate health actions.

[1010] A "wearable device" is a device that is worn on the body to continuously monitor the user's health data.

[1011] A "terminal" is a device that receives and temporarily stores data transmitted from a wearable device.

[1012] A "server" is a device that analyzes data received from terminals and generates health advice and product suggestions based on that analysis.

[1013] A "display means" is a device that provides users with health advice and product suggestions generated by a server, both visually and audibly.

[1014] "Communication means" refers to the means of notifying the user's family of health data and analysis results.

[1015] "Suggestion methods" refer to methods for suggesting health products suitable for the user based on collected health data and emotional data.

[1016] "Means of having an avatar" refers to a virtual character used to display health advice and product suggestions generated by the server.

[1017] This section describes the specific system configuration and operation for implementing this invention. This system collects and analyzes user health data and suggests suitable health products based on the results. The hardware and software used and their processing are described below.

[1018] 1. Hardware Usage Configuration

[1019] Wearable devices: such as smartwatches and smart bands.

[1020] Device: Smartphones and tablets

[1021] Server: A server used for data analysis.

[1022] Display devices: Smartphones, smart glasses (AR glasses)

[1023] 2. Software Usage Configuration

[1024] Health data collection app: Transfers data collected by wearable devices to your device.

[1025] Data analysis system: A program that runs on the server side and evaluates and analyzes health status.

[1026] Emotion Engine: An algorithm that analyzes the user's emotional state.

[1027] Generative AI models: Suggest products based on user health and emotional data.

[1028] Virtual Avatar Generation Engine: A program for generating virtual characters to present product suggestions to users.

[1029] 3. System Operation

[1030] This system operates using the following processing flow:

[1031] Wearable devices monitor the user's health data in real time, including heart rate, steps taken, calories burned, blood pressure, and blood sugar levels, and transmit this data to the device.

[1032] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[1033] The server analyzes the received health data and evaluates the user's health status. The emotion engine also analyzes the user's emotional state.

[1034] The data analysis system and emotion engine use generative AI models based on the analysis results to generate health products and advice tailored to the user.

[1035] The display device uses a smartphone or smart glasses, and an avatar provides product suggestions and health advice to the user via voice and video. It also supports three-way calls based on a generative AI model, allowing the user, family, and AI to communicate in real time.

[1036] 4. Specific Examples

[1037] One afternoon, User A finished jogging while wearing a wearable device. Afterward, the following data was sent to their smartphone:

[1038] Heart rate: 120 bpm

[1039] Steps: 10,000 steps

[1040] Calories burned: 450 kcal

[1041] Blood pressure: 130 / 85

[1042] Blood glucose level: 95 mg / dL

[1043] Emotional state: Stressed

[1044] The server analyzed this data and generated the following product suggestions:

[1045] Supplements: "Vitamin C supplements effective for relieving fatigue"

[1046] Fitness equipment: "Yoga mat"

[1047] Health foods: "Low-calorie protein bars"

[1048] Stress relief item: "Aromatherapy candle for meditation"

[1049] Using smart glasses as a display device, a virtual avatar presents these products to person A using voice and video. The avatar then suggests an additional option, saying, "We can also provide relaxing music," and person A purchases the products within the app.

[1050] 5. Example of a prompt statement

[1051] The following are examples of prompts for generative AI models:

[1052] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[1053] This system allows users to easily take specific actions tailored to their health condition and receive support in selecting appropriate products and services.

[1054] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1055] Step 1:

[1056] Users wear wearable devices that collect health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels in real time.

[1057] Input: User's health data (heart rate, steps, calories burned, blood pressure, blood sugar level)

[1058] Output: Collected health data

[1059] Specific operation: The wearable device uses sensors to measure health data and stores the data in its internal memory.

[1060] Step 2:

[1061] Data collected from wearable devices is transmitted to a terminal (smartphone) via Bluetooth or Wi-Fi.

[1062] Input: Health data stored on a wearable device

[1063] Output: Health data transferred to smartphone

[1064] Specific operation: The wearable device uses Bluetooth or Wi-Fi to send data to a smartphone app.

[1065] Step 3:

[1066] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[1067] Input: Temporary data stored on a smartphone (health data)

[1068] Output: Health data sent to the server

[1069] Specific operation: The smartphone temporarily stores the received data in its memory, and then uploads the data to the server via the internet.

[1070] Step 4:

[1071] The server analyzes the health data it receives and evaluates the user's health and emotional state.

[1072] Input: Health data sent to the server

[1073] Output: Analyzed health and emotional state

[1074] Specific operation: The server uses a data analysis system and an emotion engine to analyze health data and evaluate the user's physical condition and stress level.

[1075] Step 5:

[1076] The server uses a generative AI model based on the analysis results to generate health products and advice tailored to the user.

[1077] Input: Analyzed health and emotional state

[1078] Output: Health advice and product suggestions

[1079] Specific operation: The server references a generative AI model and makes product suggestions using the following prompts:

[1080] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[1081] Step 6:

[1082] Virtual avatars provide users with health advice and product recommendations via smartphones and smart glasses.

[1083] Input: Health advice and product suggestions

[1084] Output: Advice and product information provided to the user.

[1085] Specific operation: Smartphones and smart glasses display devices use virtual avatars to provide information to users through audio and video.

[1086] Step 7:

[1087] The server uses a generative AI model to support three-way calls involving the user, family members, and the AI.

[1088] Input: User and family requests, generative AI model

[1089] Output: Three-way call session and real-time health advice

[1090] Specific operation: The server activates a generative AI model and provides health-related questions and advice in real time during the call.

[1091] This allows users to easily take specific actions based on their health data and receive support in choosing appropriate products and services.

[1092] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1093] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1094] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1095] [Third Embodiment]

[1096] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1097] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1098] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1099] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1100] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1101] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1102] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1103] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1104] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1105] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1106] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1107] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1108] This invention is a system for supporting user health management, and mainly consists of a wearable device, a terminal, a server, and a program that links them together.

[1109] System Configuration

[1110] Wearable devices: This includes smart bands and smartwatches, which have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, and so on.

[1111] Terminal: This refers to the user's smartphone or tablet, which receives and temporarily stores data transmitted from wearable devices.

[1112] Server: Analyzes data received from terminals to evaluate and monitor the user's health status. It also has the function to generate health advice based on the analysis results and notify the user and their family.

[1113] Display means: A device for providing users with health advice generated by a server in a visual and auditory way. For example, an avatar delivers advice via voice and video through a smartphone's display or speaker.

[1114] Program processing flow

[1115] 1. Data collection:

[1116] Users wear wearable devices while going about their daily lives.

[1117] Wearable devices (terminals) monitor the user's health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[1118] 2. Data transfer and temporary storage:

[1119] The wearable device (terminal) periodically transmits the collected data to the user's smartphone via Bluetooth or Wi-Fi.

[1120] This function temporarily stores data received by a smartphone (device).

[1121] 3. Data transmission and analysis:

[1122] The smartphone (device) sends the stored data to the server via the internet.

[1123] The server analyzes the received data and assesses the user's health status. Based on the analysis results, it also generates appropriate health advice (such as exercise plans and dietary advice).

[1124] 4. Providing advice:

[1125] The server generates health advice, which is then sent to the smartphone for display.

[1126] The smartphone (device) displays the advice it receives within the application, and an avatar communicates it to the user via voice or video.

[1127] 5. Data notification:

[1128] The server notifies pre-registered family contacts of the user's health data and the generated advice and analysis results. For example, the data is sent to family members' smartphones or email addresses.

[1129] 6. Three-way calls using generative AI:

[1130] The user or a family member (user) requests a three-way call using a smartphone app.

[1131] The server activates the generative AI and configures it to allow communication between the user, family, and the generative AI.

[1132] The generative AI (server) analyzes the call content and provides appropriate supplementary information and advice in real time.

[1133] Specific example

[1134] One morning, I will explain in detail how an elderly user, Mr. A, uses the system.

[1135] Data collection:

[1136] User A: Every morning I put on my smartwatch and go for a walk.

[1137] Smartwatches (wearable devices): Continuously monitor heart rate, steps taken, and calories burned, including while walking.

[1138] Data transfer and temporary storage:

[1139] Smartwatch (wearable device): After returning home from a walk, it transmits health data to Person A's smartphone via Bluetooth.

[1140] Smartphone (device): Temporarily stores received data.

[1141] Data transmission and analysis:

[1142] Smartphone (device): Sends stored data to a server via the internet.

[1143] Server: Analyzes the received data and determines that Person A's blood pressure is slightly elevated. It also generates advice on appropriate dietary habits for managing their health.

[1144] Providing advice:

[1145] Server: Generates the advice, "Today, try to eat a low-salt meal," and sends it to Person A's smartphone.

[1146] Smartphone (device): The application displays advice and conveys it to person A through an avatar.

[1147] Data notification:

[1148] Server: Sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[1149] Son (family member / user): Check the received information.

[1150] Three-way calls using generative AI:

[1151] Son (family member / user): I need to call Person A urgently, so I request a three-way call through the app.

[1152] User A: Accepts the call request and joins the conversation.

[1153] Server: Activates a generative AI to supplement the call with health-related questions and confirmations in real time.

[1154] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[1155] The following describes the processing flow.

[1156] Step 1:

[1157] The user wears a wearable device (such as a smart band or smartwatch).

[1158] Step 2:

[1159] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[1160] Step 3:

[1161] The wearable device periodically transmits the data it collects to the user's smartphone (device) via Bluetooth or Wi-Fi.

[1162] Step 4:

[1163] This function temporarily stores data received by the smartphone (device).

[1164] Step 5:

[1165] The smartphone (device) periodically transmits accumulated health data to a server via the internet.

[1166] Step 6:

[1167] The server saves the received data to the database.

[1168] Step 7:

[1169] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[1170] Step 8:

[1171] The server generates appropriate health advice (e.g., exercise plans and dietary advice) based on the analysis results.

[1172] Step 9:

[1173] The server sends the generated health advice to the user's smartphone (device).

[1174] Step 10:

[1175] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[1176] Step 11:

[1177] An avatar, acting as a display device, conveys advice to the user using voice and video.

[1178] Step 12:

[1179] The server notifies the user's health data and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[1180] Step 13:

[1181] Family members (users) review the notified information and send feedback to the server as needed.

[1182] Step 14:

[1183] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[1184] Step 15:

[1185] The user accepts the request for a three-way call.

[1186] Step 16:

[1187] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[1188] Step 17:

[1189] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[1190] Step 18:

[1191] The user and their family (user) end the call, and the server's generative AI saves or logs the call content.

[1192] (Example 1)

[1193] Next, we will describe Example 1. 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."

[1194] In modern times, health management is a crucial issue, and many people are required to understand their own health status and take appropriate measures. However, for the elderly and those with chronic diseases, collecting and analyzing their own data is difficult, making it challenging to receive appropriate health advice. Furthermore, it is difficult for family members living separately to understand the situation and provide support. To solve this problem, a system is needed that collects and analyzes health data in real time, provides appropriate advice, and allows information to be shared with family members.

[1195] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1196] In this invention, the server includes synchronization means for periodically transmitting data temporarily stored in the communication device to the information processing device; means for generating health advice based on the analysis results of the information processing device using a generative AI model; and means for the information processing device to support three-way communication between the user, family, and generative AI. This enables real-time collection and analysis of the user's health data, provision of appropriate advice, and data notification to family members.

[1197] A "measuring device" refers to a wearable device that collects user health data and has functions to monitor heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[1198] "Communication equipment" refers to a device that temporarily stores health data received from the aforementioned measuring device, and includes mobile information terminals such as smartphones and tablets.

[1199] An "information processing device" is a device that receives health data transmitted from the aforementioned communication device, analyzes it, and evaluates the user's health status, and refers to a server or cloud computer.

[1200] "Display means" refers to means for providing health advice generated by the information processing device to the user, and includes a smartphone display and an audio output device.

[1201] "Data transmission means" refers to means for notifying family members of the aforementioned health data and analysis results, and includes email and push notifications via the internet.

[1202] "Synchronization means" refers to a function for periodically transmitting data temporarily stored in the communication device to the information processing device.

[1203] A "generative AI model" is an artificial intelligence model that generates health advice based on the analysis of a user's health data, and refers to a generative AI that utilizes natural language processing technology.

[1204] A "virtual character" refers to a character used to display health advice generated by the aforementioned information processing device, and is an avatar that provides advice using voice and video.

[1205] "Means to support three-way calls" refers to features that allow users, family members, and generative AI to participate in a call simultaneously.

[1206] This invention is a system for supporting user health management, and consists of a wearable device, a terminal, a server, and a program that links them together. The specific components of the system and their functions are described below.

[1207] System Configuration

[1208] 1. Wearable devices

[1209] Measurement devices (wearable devices) have the function of monitoring the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[1210] Examples include smart bands and smartwatches.

[1211] 2. Terminal

[1212] Communication devices (smartphones and tablets) play the role of receiving and temporarily storing data transmitted from wearable devices.

[1213] Specific examples include smartphones running iOS or Android.

[1214] 3. Server

[1215] The information processing device (server) analyzes data received from the terminal and evaluates the user's health status. Based on the analysis results, it generates health advice using a generative AI model and transmits it to the display device.

[1216] Examples include cloud servers and on-premises servers.

[1217] 4. Display means

[1218] The display means is a device for providing users with health advice generated by the server in a visual and auditory way.

[1219] Specific example: An avatar uses the smartphone's display and speakers to provide advice via voice and video.

[1220] 5. Data transmission means

[1221] The data transmission means is a means of notifying family members of health data and analysis results.

[1222] Specific example: Sending emails and push notifications over the internet.

[1223] 6. Synchronization means

[1224] The synchronization mechanism has the function of periodically transmitting data temporarily stored in the communication device to an information processing device.

[1225] 7. Generative AI Models

[1226] Generative AI models are artificial intelligence models designed to generate appropriate health advice based on the analysis of a user's health data.

[1227] Specific example: Use natural language processing techniques such as GPT-4.

[1228] 8. Virtual Character

[1229] The virtual character is a character used to display health advice generated by the server, providing advice through voice and video.

[1230] 9. Means to support three-way calls

[1231] The means of supporting three-way calls provides the ability for the user, family members, and generative AI to talk simultaneously.

[1232] Specific example

[1233] The case of elderly person A one day

[1234] 1. Data collection:

[1235] User A puts on their smartwatch every morning and goes for a walk.

[1236] Smartwatches continuously monitor heart rate, steps taken, and calories burned.

[1237] 2. Data transfer and temporary storage:

[1238] The smartwatch transmits health data to Person A's smartphone via Bluetooth after returning home from a walk.

[1239] Smartphones temporarily store received data in a database within the app.

[1240] 3. Data transmission and analysis:

[1241] Smartphones transmit stored data to servers via the internet.

[1242] The server executes Python scripts and analyzes data using Scikit-learn models.

[1243] 4. Providing advice:

[1244] The server generates advice such as, "Today, try to eat a low-salt meal," and sends it to the smartphone.

[1245] The smartphone displays advice within the app and communicates it to person A via voice using the Google Assistant API.

[1246] 5. Data notification:

[1247] The server sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[1248] The son (family member / user) checks the received information.

[1249] 6. Three-way calls using generative AI models:

[1250] The son (family member / user) requests a three-way call through the app.

[1251] User A accepts the call request.

[1252] The server sets up a call session using WebRTC and starts the generative AI model.

[1253] The generative AI model analyzes the content of the call and supplements it with health-related questions and confirmations in real time.

[1254] Example of a prompt

[1255] 1. "Mr. / Ms. A would like to check their health data for today. What is their current health status?"

[1256] 2. "What are some recent health concerns regarding Mr. / Ms. A?"

[1257] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[1258] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1259] Step 1:

[1260] Data collection

[1261] Users wear wearable devices on a daily basis while going about their daily lives.

[1262] Specific action: Every morning, the user puts on a smartwatch on their wrist.

[1263] Wearable devices collect health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[1264] Input: User's biometric information.

[1265] Data processing: Measurement using sensors.

[1266] Output: Raw health data.

[1267] Step 2:

[1268] Data transfer and temporary storage

[1269] The wearable device collects data and transmits it to the user's device via Bluetooth or Wi-Fi.

[1270] Specific operation: The wearable device synchronizes with the terminal periodically or at the user's request.

[1271] The application temporarily stores the data received by the device.

[1272] Input: Health data transmitted from a wearable device.

[1273] Data processing: Data storage within the device.

[1274] Output: Temporarily stored health data.

[1275] Step 3:

[1276] Data transmission and analysis

[1277] The device sends temporarily stored data to the server via the internet.

[1278] Specific operation: The app sends data periodically or in response to user actions.

[1279] The server analyzes the received data and evaluates the user's health status.

[1280] Input: Health data sent from the device.

[1281] Data processing: Preprocessing and analysis using Python scripts.

[1282] Output: Health assessment report.

[1283] The server generates health advice using a generative AI model.

[1284] Input: Health assessment report.

[1285] Data processing: Generating advice using generative AI models such as GPT-4.

[1286] Output: Health advice.

[1287] Step 4:

[1288] Providing advice

[1289] The server generates health advice and sends it to the device.

[1290] Specific operation: Sending data via a REST API.

[1291] The application displays the advice received by the device, and an avatar communicates it to the user via voice or video.

[1292] Input: Health advice sent from the server.

[1293] Data processing: Conversion to in-app display format and speech synthesis.

[1294] Output: Display of advice to the user and audio output.

[1295] Step 5:

[1296] Data notification

[1297] The server notifies the family of their health data and generated advice.

[1298] Specific action: Send emails and push notifications using the notification service.

[1299] Family members receive notifications and check on the user's health status.

[1300] Input: Notification data sent from the server.

[1301] Data processing: Display via email or push notification.

[1302] Output: Notification displayed to family members.

[1303] Step 6:

[1304] Three-way calls using a generative AI model

[1305] The user or a family member requests a three-way call using a smartphone app.

[1306] Specific action: Press the "3-way call" button within the app.

[1307] The server activates the generated AI model and configures it to allow calls between the user, family members, and the generated AI model.

[1308] Input: Call request.

[1309] Data processing: Session setup and activation of the generated AI model using WebRTC technology.

[1310] Output: Call session started.

[1311] The generative AI model analyzes the call content and provides appropriate supplementary information and advice in real time.

[1312] Specific operation: The system analyzes call content in real time and uses speech synthesis to provide supplementary explanations and advice.

[1313] Input: Call content.

[1314] Data processing: Real-time analysis and speech synthesis.

[1315] Output: Supplementary explanations or advice.

[1316] (Application Example 1)

[1317] Next, we will explain Application Example 1. In the following explanation, 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."

[1318] This invention relates to a system for supporting users' health management. It aims to not only collect and analyze health data using wearable devices and provide health advice based on the results, but also to provide real-time, optimal guidance when implementing a fitness plan in a virtual environment, thereby enabling effective health management and fitness instruction. Furthermore, it aims to enhance communication between the user and their family through three-way calls using a generation system, making it easier for family members living separately to understand the user's health status.

[1319] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1320] In this invention, the server includes means for analyzing the user's health data and evaluating their health status, means for generating health advice and fitness plans, and means for notifying the user and their family of the generated data. This makes it possible to provide fitness plans within a virtual environment and to share information about the user's health status with their family.

[1321] A "wearable device" is a device used to collect user health data, and includes smart bands and smartwatches.

[1322] "Terminal" refers to a device that receives and temporarily stores data collected from the wearable device, and includes smartphones, tablets, and the like.

[1323] A "server" is a device that receives data transmitted from the aforementioned terminal, analyzes it, and evaluates the health status, and includes cloud servers and data processing facilities.

[1324] "Display means" refers to a device for providing health advice generated by the server to the user, and includes a smartphone display and an audio output device.

[1325] "Communication means" refers to a device for notifying family members of the aforementioned health data and analysis results, and includes internet connectivity and email systems.

[1326] "Guide data" refers to data generated by the server to provide a fitness plan within the virtual environment, and includes exercise instructions and health advice.

[1327] "Smart glasses" refers to a device that allows the terminal to display a virtual environment and provide guidance to the user, and includes head-mounted displays and augmented reality glasses.

[1328] A "virtual environment" is an environment in which users can experience and engage in activities in a virtually defined space or situation, and includes virtual fitness rooms and virtual gyms.

[1329] A "fitness plan" is an exercise guidance and exercise program generated by the server based on the user's health data, and includes individual exercise menus and exercise guidelines.

[1330] This invention relates to a system for supporting user health management, and its main components include a wearable device, a terminal, a server, and smart glasses. This system is particularly effective when applied in virtual stores.

[1331] 1. System Configuration

[1332] Wearable devices include smart bands and smartwatches that have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc. A typical smartwatch is an example.

[1333] Terminal: This refers to the user's smartphone or tablet, which receives data transmitted from wearable devices via Bluetooth or Wi-Fi and temporarily stores it.

[1334] Server: Analyzes data received from terminals and assesses the user's health status. Based on the analysis results, it generates health advice and fitness plans and notifies the user and their family.

[1335] Smart glasses: Devices that display a virtual environment and provide virtual fitness guidance. Examples include head-mounted displays (HMDs) and augmented reality (AR) glasses.

[1336] 2. Program Processing

[1337] 2.1 Data Collection

[1338] While the user wears the smartwatch and goes about their daily life, the wearable device monitors health data such as heart rate, steps taken, calories burned, and blood pressure in real time.

[1339] 2.2 Data Transfer and Temporary Storage

[1340] The smartwatch periodically transmits monitored data to the user's smartphone via Bluetooth or Wi-Fi. The smartphone temporarily stores the received data.

[1341] 2.3 Data Transmission and Analysis

[1342] Smartphones transmit stored data to servers via the internet. The servers analyze the received data and assess the user's health status. They also generate appropriate health advice and fitness plans.

[1343] 2.4 Providing Guides

[1344] The server generates a fitness plan, which is then sent to the smartphone for display. Within the virtual environment, the smart glasses convey the generated fitness guide to the user via voice and visual means through an avatar. Specifically, when the user performs a squat, animations and avatar guides are displayed on the smart glasses to instruct them on correct form.

[1345] 2.5 Data Notification

[1346] The server notifies the family of the user's health data and the generated advice and analysis results. This allows the family to understand the user's health status in real time.

[1347] 3. Specific examples

[1348] On a given morning, when a user uses the system, they would go through the following steps:

[1349] Data collection from wearable devices: Users wear smartwatches while exercising or engaging in daily activities.

[1350] Data transfer: The smartwatch transfers collected data to the smartphone.

[1351] Data analysis: The smartphone sends data to the server, and the server performs the analysis.

[1352] Fitness plan delivery: A server generates a fitness plan and sends it to smart glasses, allowing the user to receive guidance within a virtual environment.

[1353] Example of a prompt:

[1354] Let's begin today's fitness plan. I've read your heart rate data. Next, please do 5 squats.

[1355] This allows users to effectively execute fitness plans in a virtual environment and manage their health in real time. It also strengthens family collaboration and enables efficient management of the user's health status.

[1356] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1357] Step 1:

[1358] The user wears a smartwatch while going about their daily life. The smartwatch monitors health data such as heart rate, steps taken, calories burned, and blood pressure in real time. The input is the user's activity data, and the output is the monitored health data.

[1359] Step 2:

[1360] The smartwatch collects health data and transmits it to the user's smartphone via Bluetooth or Wi-Fi. The input is the health data stored on the smartwatch, and the output is the data transferred to the smartphone.

[1361] Step 3:

[1362] The smartphone temporarily stores the health data it receives. The input is the health data transferred from the smartwatch, and the output is the temporarily stored data.

[1363] Step 4:

[1364] A smartphone sends temporarily stored data to a server via the internet. The input is the data stored on the smartphone, and the output is the data sent to the server.

[1365] Step 5:

[1366] The server analyzes the received data and evaluates the user's health status. The input is health data sent to the server, and the output is the analysis results and health evaluation.

[1367] Step 6:

[1368] The server generates appropriate health advice and fitness plans based on the analysis results. The input is health assessment data, and the output is health advice and fitness plans.

[1369] Step 7:

[1370] The server generates a fitness plan and sends it to the smartphone, which then displays it. The input is the generated fitness plan, and the output is the fitness plan displayed on the smartphone.

[1371] Step 8:

[1372] Smart glasses display a fitness plan in a virtual environment and provide guidance to the user. The input is the fitness plan displayed on a smartphone, and the output is the guidance displayed on the smart glasses. This may include exercise instruction using animations or avatars.

[1373] Step 9:

[1374] The server notifies the family of the user's health data and analysis results. The input is the generated analysis results and health data, and the output is the notification sent to the family.

[1375] Step 10:

[1376] The smartphone displays a generated prompt message to the user, who then follows the instructions to begin exercising. The input is the generated prompt message, and the output is the user's exercise performance. Example prompt message: "Starting today's fitness plan. Heart rate data read. Now, please do 5 squats."

[1377] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1378] This invention is a system that supports user health management and mainly consists of a wearable device, a terminal, a server, an emotion engine, and a program that coordinates these components.

[1379] System Configuration

[1380] Wearable devices: This includes smart bands and smartwatches, which have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, and so on.

[1381] Terminal: This refers to the user's smartphone or tablet, which receives and temporarily stores data transmitted from wearable devices.

[1382] Server: Analyzes data received from terminals to evaluate and monitor the user's health status. It also has the function to generate health advice based on the analysis results and notify the user and their family.

[1383] Display means: A device for providing users with health advice generated by a server in a visual and auditory way. For example, an avatar delivers advice via voice and video through a smartphone's display or speaker.

[1384] Emotion Engine: It has an algorithm that recognizes the user's emotions and analyzes their emotional state based on collected health data.

[1385] Program processing flow

[1386] 1. Data collection:

[1387] Users wear wearable devices while going about their daily lives.

[1388] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[1389] 2. Data transfer and temporary storage:

[1390] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[1391] This function temporarily stores data received by a smartphone (device).

[1392] 3. Data transmission and analysis:

[1393] The smartphone (device) sends the stored data to the server via the internet.

[1394] The server saves the received data to the database and begins analysis.

[1395] The emotion engine (device) analyzes the user's emotional state based on the collected data.

[1396] 4. Generating advice:

[1397] The server generates personalized health advice based on the analyzed health and emotional data.

[1398] The server sends the generated health advice to the user's smartphone (device).

[1399] 5. Providing advice:

[1400] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[1401] An avatar, acting as a display device, conveys advice to the user using voice and video.

[1402] 6. Data notification:

[1403] The server notifies pre-registered family contacts of the user's health data, emotional data, and analysis results.

[1404] Family members (users) review the notified information and send feedback as needed.

[1405] 7. Three-way calls using generative AI:

[1406] The user or a family member (user) requests a three-way call through a smartphone application.

[1407] The server activates a generative AI and sets up a three-way call. During the call, the generative AI supplements the conversation between the user and their family, providing real-time health-related questions and advice.

[1408] Specific example

[1409] One morning, I will explain in detail how an elderly person, Mr. B, uses the system.

[1410] 1. Data collection:

[1411] User B puts on their smartwatch and goes for a walk.

[1412] A smartwatch (wearable device) monitors your heart rate, steps taken, and calories burned while you're out for a walk.

[1413] 2. Data transfer and temporary storage:

[1414] The smartwatch (wearable device) transmits the collected data to Person B's smartphone via Bluetooth.

[1415] This function temporarily stores data received by the smartphone (device).

[1416] 3. Data transmission and analysis:

[1417] The smartphone (device) sends the stored data to the server.

[1418] The server analyzes the data and determines that Person B's blood pressure is on the higher side. Additionally, the emotion engine analyzes Person B's emotional state as "high stress."

[1419] 4. Generating advice:

[1420] The server generates advice such as, "Today, try to eat a low-salt diet," and based on the emotion engine, it also generates additional advice such as, "I recommend listening to relaxing music."

[1421] The smartphone (device) receives the advice, and the avatar relays it to person B along with a voice message.

[1422] 5. Data notification:

[1423] The server notifies B's family of their health and emotional data.

[1424] The family member (user) checks the notification and sends feedback to the server about Person B's health condition.

[1425] 6. Three-way calls using generative AI:

[1426] A family member (user) requests a call, and person B accepts.

[1427] The server activates a generative AI, providing real-time health-related questions and advice during the call.

[1428] In this way, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind. In particular, by integrating an emotion engine, it is possible to provide personalized advice that takes into account the user's mental state, not just monitoring health data. Furthermore, it becomes easier for family members living separately to understand the health status in real time and provide necessary support.

[1429] The following describes the processing flow.

[1430] Step 1:

[1431] The user wears a wearable device (such as a smart band or smartwatch).

[1432] Step 2:

[1433] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[1434] Step 3:

[1435] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[1436] Step 4:

[1437] This function temporarily stores data received by the smartphone (device).

[1438] Step 5:

[1439] An emotion engine (located on the device or on a server) analyzes additional information such as the user's voice, facial expressions, and text input based on data from wearable devices and smartphones to identify the user's emotional state.

[1440] Step 6:

[1441] The smartphone (device) transmits accumulated health data and emotional data to a server via the internet.

[1442] Step 7:

[1443] The server saves the received data to the database.

[1444] Step 8:

[1445] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[1446] Step 9:

[1447] The server evaluates the user's emotional state based on the results from the emotion engine and generates personalized health advice.

[1448] Step 10:

[1449] The server sends the generated health advice to the user's smartphone (device).

[1450] Step 11:

[1451] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[1452] Step 12:

[1453] An avatar, acting as a display device, conveys advice to the user using voice and video.

[1454] Step 13:

[1455] The server notifies the user's health data, emotional data, and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[1456] Step 14:

[1457] Family members (users) review the notified information and send feedback to the server as needed.

[1458] Step 15:

[1459] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[1460] Step 16:

[1461] The user accepts the request for a three-way call.

[1462] Step 17:

[1463] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[1464] Step 18:

[1465] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[1466] Step 19:

[1467] The user and their family (user) end the call, and the server saves or logs the call content using a generative AI.

[1468] (Example 2)

[1469] Next, we will describe Example 2. 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."

[1470] In modern society, there is a need for systems that can monitor both a user's health and emotional state in real time and provide appropriate advice. Collecting and analyzing health data in daily life is particularly important for the elderly and those with unstable health conditions. However, there is a lack of technology that not only monitors health data but also provides personalized advice that takes emotional states into account. Furthermore, there are limited means for family members living separately to monitor a user's health in real time and provide necessary support.

[1471] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an emotion engine that analyzes the user's emotional state using an emotion algorithm, means for supporting a three-way call between the user, family, and a generating AI model, a measurement device for collecting the user's health data, a terminal that receives and temporarily stores data from the measurement device, means for receiving data from the terminal, analyzing it, and evaluating the health state, display means for providing health advice generated by the server, and communication means for notifying the family of the health data and analysis results. This makes it possible to grasp the user's health state and emotional state in real time and provide personalized advice. In addition, family members can grasp the health state in real time from a remote location and provide appropriate support.

[1472] A "measurement device" is a device used to collect a user's health data, monitoring physical data such as heart rate, steps taken, calories burned, blood pressure, and blood glucose levels.

[1473] A "terminal" is a device that receives and temporarily stores health data transmitted from a measurement device, and includes smartphones and tablets.

[1474] A "server" is a computing system that receives data transmitted from a terminal, performs analysis, and evaluates the user's health status. Its role is to generate and notify users of health advice based on the analysis results.

[1475] "Display means" refers to a device that provides the user with health advice generated by the server, either visually or audibly, and includes smartphone displays, speakers, avatars, and other similar devices.

[1476] "Means of communication" refers to the method by which the server analyzes health data and analysis results and notifies family members of these methods, including the internet, email, and text messages.

[1477] An "emotion engine" is an algorithm and system that analyzes a user's emotional state based on their health data and behavioral patterns.

[1478] A "generative AI model" is an artificial intelligence system designed to support communication with users and their families, providing real-time answers to health-related questions and advice.

[1479] A "three-way call" refers to a call between the user, their family, and a generative AI model, allowing the user and their family to exchange health-related information and receive advice in real time.

[1480] "Health advice" refers to specific instructions and suggestions generated by the server based on an analysis of the user's health and emotional data, providing information necessary to improve and maintain the user's health.

[1481] The present invention is a system for supporting user health management and emotion analysis, and consists of a measurement device, a terminal, a server, an emotion engine, a generative AI model, and a program that links these together.

[1482] System Configuration

[1483] Measurement devices

[1484] Measurement devices such as smart bands and smartwatches are used. These devices have the function of continuously monitoring the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels. For example, a smartwatch measures the user's heart rate every minute and stores that data in its internal memory.

[1485] terminal

[1486] The terminal is the user's smartphone or tablet, and its role is to receive and temporarily store data transmitted from the measurement device. For example, the smartphone receives data transmitted from a smartwatch via Bluetooth and temporarily stores it in local storage.

[1487] server

[1488] The server is a computing system located in the cloud that analyzes data received from terminals and evaluates the user's health status. The server utilizes multiple algorithms to analyze trends in heart rate data, for example, and detect anomalies. Based on the analysis results, it generates personalized health advice and notifies the user and their family.

[1489] Emotional Engine

[1490] The emotion engine is a software component integrated within the server that analyzes the user's emotional state based on health data and behavioral patterns. For example, if the user has a low step count and a high heart rate, the emotion engine detects the user's stress level and incorporates that information into the analysis results.

[1491] Generative AI Models

[1492] The Generative AI Model is an artificial intelligence system that supports three-way calls between the user and their family, providing real-time health-related questions and advice. For example, if a user enters a prompt such as, "My blood pressure is high today, and I'm feeling stressed. Could you give me some advice on how to relax?", the Generative AI Model will provide appropriate advice in real time.

[1493] means of communication

[1494] The system uses the internet, email, and text messages as communication methods to notify family members of the health data and analysis results analyzed by the server. For example, if a user's heart rate remains elevated, a notification will be sent to their family via email.

[1495] Display means

[1496] The display methods used include smartphone displays, speakers, and avatars. Health advice generated by the server is provided to the user visually or audibly. For example, a smartphone app might display the advice, "We recommend you go to bed early tonight," while an avatar delivers the advice verbally.

[1497] Specific example

[1498] Let's take an example of an elderly user using this system one morning. The user puts on a smartwatch and goes for a walk. The smartwatch monitors heart rate, steps taken, and calories burned during the walk. The collected data is transmitted to the user's smartphone via Bluetooth, where it is temporarily stored.

[1499] The smartphone then sends the saved data to the server. The server analyzes the received data and determines that the user has high blood pressure and is under high stress. The server generates health advice such as "Try to eat a low-salt diet today" and emotional data-based advice such as "We recommend listening to relaxing music," and sends these to the user's smartphone.

[1500] A smartphone app receives advice, and an avatar conveys it to the user via voice. The server also notifies the user's family of the analysis data, and the family sends feedback to the server about the user's health.

[1501] The user or their family can request a three-way call through a generative AI model and receive real-time health-related questions and advice during the call. In this way, the system of the present invention can provide integrated support for the user's health management and emotional state.

[1502] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1503] Step 1: Data Collection

[1504] The user wears a measurement device (e.g., a smartwatch). The smartwatch monitors health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[1505] Input: User's biometric information

[1506] Data processing: The smartwatch senses biometric information in real time, collects the necessary data, and stores it in its internal memory.

[1507] Output: Collected health data (heart rate, steps, etc.)

[1508] Step 2: Data Transfer and Temporary Storage

[1509] The wearable device transmits the data it collects via Bluetooth to the user's smartphone.

[1510] Input: Health data from smartwatch

[1511] Data processing: The smartphone receives data via Bluetooth, converts it to an appropriate format for temporary storage, and saves it to its internal storage.

[1512] Output: Health data stored on the smartphone

[1513] Step 3: Data transmission and analysis

[1514] The smartphone sends the stored data to the server via the internet.

[1515] Input: Health data on your smartphone

[1516] Data transfer: The smartphone uploads data to the server using the appropriate protocol (e.g., HTTPS).

[1517] Output: Health data sent to the server

[1518] Step 4: Data analysis and emotional state analysis

[1519] The server stores the received data in a database and performs initial analysis. The server analyzes trends and anomalies in the health data, and the emotion engine evaluates the emotional state.

[1520] Input: Received health data

[1521] Data processing: The server uses algorithms to perform analysis, and the emotion engine performs sentiment analysis based on user behavior data and health data.

[1522] Output: Analysis results (health assessment, emotional assessment)

[1523] Step 5: Generate and send advice

[1524] The server generates personalized health advice based on the analysis results. The emotion engine also generates advice that reflects emotional assessments.

[1525] Input: Analysis results

[1526] Data processing: The server generates text advice based on health and emotional states.

[1527] Output: Generated health advice

[1528] Step 6: Providing advice

[1529] The smartphone displays advice received from the server within the application. An interactive avatar provides advice via voice and video.

[1530] Input: Advice from the server

[1531] Data processing: A smartphone app displays advice in a format suitable for the user interface, and an avatar provides voice output.

[1532] Output: Advice that users receive visually and aurally.

[1533] Step 7: Notification of health data and analysis results

[1534] The server notifies the family of the user's health data and analysis results.

[1535] Input: Analysis results

[1536] Data communication: The server sends the analysis results to pre-registered family contacts (e.g., email, text message).

[1537] Output: Health data and analysis results notified to the family.

[1538] Step 8: Support for three-way calls using generative AI models

[1539] The user or a family member requests a three-way call through a smartphone app. The server activates a generated AI model and sets up the call.

[1540] Input: Call request

[1541] Data processing: Generative AI models supplement user and family conversations, providing real-time health-related questions and advice.

[1542] Output: Health advice provided in real time

[1543] (Application Example 2)

[1544] Next, we will explain application example 2. In the following explanation, 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."

[1545] Modern users are expected not only to monitor their health data but also to take concrete actions based on that data. However, current systems do not adequately support users in choosing appropriate products and services based on their health data, and furthermore, they lack advice that takes into account the user's emotional state. In addition, it is difficult to grasp health and emotional states in a unified manner and translate that into actual actions.

[1546] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for having an avatar for displaying health advice and product suggestions generated by analyzing the user's health data, means for supporting three-way communication between the user, family, and the generated AI, and means for suggesting health products suitable for the user. As a result, the user can receive personalized advice and product suggestions according to their health and emotional state and take appropriate health actions.

[1547] A "wearable device" is a device that is worn on the body to continuously monitor the user's health data.

[1548] A "terminal" is a device that receives and temporarily stores data transmitted from a wearable device.

[1549] A "server" is a device that analyzes data received from terminals and generates health advice and product suggestions based on that analysis.

[1550] A "display means" is a device that provides users with health advice and product suggestions generated by a server, both visually and audibly.

[1551] "Communication means" refers to the means of notifying the user's family of health data and analysis results.

[1552] "Suggestion methods" refer to methods for suggesting health products suitable for the user based on collected health data and emotional data.

[1553] "Means of having an avatar" refers to a virtual character used to display health advice and product suggestions generated by the server.

[1554] This section describes the specific system configuration and operation for implementing this invention. This system collects and analyzes user health data and suggests suitable health products based on the results. The hardware and software used and their processing are described below.

[1555] 1. Hardware Usage Configuration

[1556] Wearable devices: such as smartwatches and smart bands.

[1557] Device: Smartphones and tablets

[1558] Server: A server used for data analysis.

[1559] Display devices: Smartphones, smart glasses (AR glasses)

[1560] 2. Software Usage Configuration

[1561] Health data collection app: Transfers data collected by wearable devices to your device.

[1562] Data analysis system: A program that runs on the server side and evaluates and analyzes health status.

[1563] Emotion Engine: An algorithm that analyzes the user's emotional state.

[1564] Generative AI models: Suggest products based on user health and emotional data.

[1565] Virtual Avatar Generation Engine: A program for generating virtual characters to present product suggestions to users.

[1566] 3. System Operation

[1567] This system operates using the following processing flow:

[1568] Wearable devices monitor the user's health data in real time, including heart rate, steps taken, calories burned, blood pressure, and blood sugar levels, and transmit this data to the device.

[1569] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[1570] The server analyzes the received health data and evaluates the user's health status. The emotion engine also analyzes the user's emotional state.

[1571] The data analysis system and emotion engine use generative AI models based on the analysis results to generate health products and advice tailored to the user.

[1572] The display device uses a smartphone or smart glasses, and an avatar provides product suggestions and health advice to the user via voice and video. It also supports three-way calls based on a generative AI model, allowing the user, family, and AI to communicate in real time.

[1573] 4. Specific Examples

[1574] One afternoon, User A finished jogging while wearing a wearable device. Afterward, the following data was sent to their smartphone:

[1575] Heart rate: 120 bpm

[1576] Steps: 10,000 steps

[1577] Calories burned: 450 kcal

[1578] Blood pressure: 130 / 85

[1579] Blood glucose level: 95 mg / dL

[1580] Emotional state: Stressed

[1581] The server analyzed this data and generated the following product suggestions:

[1582] Supplements: "Vitamin C supplements effective for relieving fatigue"

[1583] Fitness equipment: "Yoga mat"

[1584] Health foods: "Low-calorie protein bars"

[1585] Stress relief item: "Aromatherapy candle for meditation"

[1586] Using smart glasses as a display device, a virtual avatar presents these products to person A using voice and video. The avatar then suggests an additional option, saying, "We can also provide relaxing music," and person A purchases the products within the app.

[1587] 5. Example of a prompt statement

[1588] The following are examples of prompts for generative AI models:

[1589] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[1590] This system allows users to easily take specific actions tailored to their health condition and receive support in selecting appropriate products and services.

[1591] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1592] Step 1:

[1593] Users wear wearable devices that collect health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels in real time.

[1594] Input: User's health data (heart rate, steps, calories burned, blood pressure, blood sugar level)

[1595] Output: Collected health data

[1596] Specific operation: The wearable device uses sensors to measure health data and stores the data in its internal memory.

[1597] Step 2:

[1598] Data collected from wearable devices is transmitted to a terminal (smartphone) via Bluetooth or Wi-Fi.

[1599] Input: Health data stored on a wearable device

[1600] Output: Health data transferred to smartphone

[1601] Specific operation: The wearable device uses Bluetooth or Wi-Fi to send data to a smartphone app.

[1602] Step 3:

[1603] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[1604] Input: Temporary data stored on a smartphone (health data)

[1605] Output: Health data sent to the server

[1606] Specific operation: The smartphone temporarily stores the received data in its memory, and then uploads the data to the server via the internet.

[1607] Step 4:

[1608] The server analyzes the health data it receives and evaluates the user's health and emotional state.

[1609] Input: Health data sent to the server

[1610] Output: Analyzed health and emotional state

[1611] Specific operation: The server uses a data analysis system and an emotion engine to analyze health data and evaluate the user's physical condition and stress level.

[1612] Step 5:

[1613] The server uses a generative AI model based on the analysis results to generate health products and advice tailored to the user.

[1614] Input: Analyzed health and emotional state

[1615] Output: Health advice and product suggestions

[1616] Specific operation: The server references a generative AI model and makes product suggestions using the following prompts:

[1617] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[1618] Step 6:

[1619] Virtual avatars provide users with health advice and product recommendations via smartphones and smart glasses.

[1620] Input: Health advice and product suggestions

[1621] Output: Advice and product information provided to the user.

[1622] Specific operation: Smartphones and smart glasses display devices use virtual avatars to provide information to users through audio and video.

[1623] Step 7:

[1624] The server uses a generative AI model to support three-way calls involving the user, family members, and the AI.

[1625] Input: User and family requests, generative AI model

[1626] Output: Three-way call session and real-time health advice

[1627] Specific operation: The server activates a generative AI model and provides health-related questions and advice in real time during the call.

[1628] This allows users to easily take specific actions based on their health data and receive support in choosing appropriate products and services.

[1629] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1630] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1631] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1632] [Fourth Embodiment]

[1633] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1634] As shown in Figure 7, the 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.

[1635] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1636] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1637] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1638] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1639] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1640] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1641] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1642] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1643] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1644] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1645] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1646] This invention is a system for supporting user health management, and mainly consists of a wearable device, a terminal, a server, and a program that links them together.

[1647] System Configuration

[1648] Wearable devices: This includes smart bands and smartwatches, which have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, and so on.

[1649] Terminal: This refers to the user's smartphone or tablet, which receives and temporarily stores data transmitted from wearable devices.

[1650] Server: Analyzes data received from terminals to evaluate and monitor the user's health status. It also has the function to generate health advice based on the analysis results and notify the user and their family.

[1651] Display means: A device for providing users with health advice generated by a server in a visual and auditory way. For example, an avatar delivers advice via voice and video through a smartphone's display or speaker.

[1652] Program processing flow

[1653] 1. Data collection:

[1654] Users wear wearable devices while going about their daily lives.

[1655] Wearable devices (terminals) monitor the user's health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[1656] 2. Data transfer and temporary storage:

[1657] The wearable device (terminal) periodically transmits the collected data to the user's smartphone via Bluetooth or Wi-Fi.

[1658] This function temporarily stores data received by a smartphone (device).

[1659] 3. Data transmission and analysis:

[1660] The smartphone (device) sends the stored data to the server via the internet.

[1661] The server analyzes the received data and assesses the user's health status. Based on the analysis results, it also generates appropriate health advice (such as exercise plans and dietary advice).

[1662] 4. Providing advice:

[1663] The server generates health advice, which is then sent to the smartphone for display.

[1664] The smartphone (device) displays the advice it receives within the application, and an avatar communicates it to the user via voice or video.

[1665] 5. Data notification:

[1666] The server notifies pre-registered family contacts of the user's health data and the generated advice and analysis results. For example, the data is sent to family members' smartphones or email addresses.

[1667] 6. Three-way calls using generative AI:

[1668] The user or a family member (user) requests a three-way call using a smartphone app.

[1669] The server activates the generative AI and configures it to allow communication between the user, family, and the generative AI.

[1670] The generative AI (server) analyzes the call content and provides appropriate supplementary information and advice in real time.

[1671] Specific example

[1672] One morning, I will explain in detail how an elderly user, Mr. A, uses the system.

[1673] Data collection:

[1674] User A: Every morning I put on my smartwatch and go for a walk.

[1675] Smartwatches (wearable devices): Continuously monitor heart rate, steps taken, and calories burned, including while walking.

[1676] Data transfer and temporary storage:

[1677] Smartwatch (wearable device): After returning home from a walk, it transmits health data to Person A's smartphone via Bluetooth.

[1678] Smartphone (device): Temporarily stores received data.

[1679] Data transmission and analysis:

[1680] Smartphone (device): Sends stored data to a server via the internet.

[1681] Server: Analyzes the received data and determines that Person A's blood pressure is slightly elevated. It also generates advice on appropriate dietary habits for managing their health.

[1682] Providing advice:

[1683] Server: Generates the advice, "Today, try to eat a low-salt meal," and sends it to Person A's smartphone.

[1684] Smartphone (device): The application displays advice and conveys it to person A through an avatar.

[1685] Data notification:

[1686] Server: Sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[1687] Son (family member / user): Check the received information.

[1688] Three-way calls using generative AI:

[1689] Son (family member / user): I need to call Person A urgently, so I request a three-way call through the app.

[1690] User A: Accepts the call request and joins the conversation.

[1691] Server: Activates a generative AI to supplement the call with health-related questions and confirmations in real time.

[1692] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[1693] The following describes the processing flow.

[1694] Step 1:

[1695] The user wears a wearable device (such as a smart band or smartwatch).

[1696] Step 2:

[1697] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[1698] Step 3:

[1699] The wearable device periodically transmits the data it collects to the user's smartphone (device) via Bluetooth or Wi-Fi.

[1700] Step 4:

[1701] This function temporarily stores data received by the smartphone (device).

[1702] Step 5:

[1703] The smartphone (device) periodically transmits accumulated health data to a server via the internet.

[1704] Step 6:

[1705] The server saves the received data to the database.

[1706] Step 7:

[1707] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[1708] Step 8:

[1709] The server generates appropriate health advice (e.g., exercise plans and dietary advice) based on the analysis results.

[1710] Step 9:

[1711] The server sends the generated health advice to the user's smartphone (device).

[1712] Step 10:

[1713] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[1714] Step 11:

[1715] An avatar, acting as a display device, conveys advice to the user using voice and video.

[1716] Step 12:

[1717] The server notifies the user's health data and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[1718] Step 13:

[1719] Family members (users) review the notified information and send feedback to the server as needed.

[1720] Step 14:

[1721] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[1722] Step 15:

[1723] The user accepts the request for a three-way call.

[1724] Step 16:

[1725] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[1726] Step 17:

[1727] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[1728] Step 18:

[1729] The user and their family (user) end the call, and the server's generative AI saves or logs the call content.

[1730] (Example 1)

[1731] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1732] In modern times, health management is a crucial issue, and many people are required to understand their own health status and take appropriate measures. However, for the elderly and those with chronic diseases, collecting and analyzing their own data is difficult, making it challenging to receive appropriate health advice. Furthermore, it is difficult for family members living separately to understand the situation and provide support. To solve this problem, a system is needed that collects and analyzes health data in real time, provides appropriate advice, and allows information to be shared with family members.

[1733] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1734] In this invention, the server includes synchronization means for periodically transmitting data temporarily stored in the communication device to the information processing device; means for generating health advice based on the analysis results of the information processing device using a generative AI model; and means for the information processing device to support three-way communication between the user, family, and generative AI. This enables real-time collection and analysis of the user's health data, provision of appropriate advice, and data notification to family members.

[1735] A "measuring device" refers to a wearable device that collects user health data and has functions to monitor heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[1736] "Communication equipment" refers to a device that temporarily stores health data received from the aforementioned measuring device, and includes mobile information terminals such as smartphones and tablets.

[1737] An "information processing device" is a device that receives health data transmitted from the aforementioned communication device, analyzes it, and evaluates the user's health status, and refers to a server or cloud computer.

[1738] "Display means" refers to means for providing health advice generated by the information processing device to the user, and includes a smartphone display and an audio output device.

[1739] "Data transmission means" refers to means for notifying family members of the aforementioned health data and analysis results, and includes email and push notifications via the internet.

[1740] "Synchronization means" refers to a function for periodically transmitting data temporarily stored in the communication device to the information processing device.

[1741] A "generative AI model" is an artificial intelligence model that generates health advice based on the analysis of a user's health data, and refers to a generative AI that utilizes natural language processing technology.

[1742] A "virtual character" refers to a character used to display health advice generated by the aforementioned information processing device, and is an avatar that provides advice using voice and video.

[1743] "Means to support three-way calls" refers to features that allow users, family members, and generative AI to participate in a call simultaneously.

[1744] This invention is a system for supporting user health management, and consists of a wearable device, a terminal, a server, and a program that links them together. The specific components of the system and their functions are described below.

[1745] System Configuration

[1746] 1. Wearable devices

[1747] Measurement devices (wearable devices) have the function of monitoring the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, etc.

[1748] Examples include smart bands and smartwatches.

[1749] 2. Terminal

[1750] Communication devices (smartphones and tablets) play the role of receiving and temporarily storing data transmitted from wearable devices.

[1751] Specific examples include smartphones running iOS or Android.

[1752] 3. Server

[1753] The information processing device (server) analyzes data received from the terminal and evaluates the user's health status. Based on the analysis results, it generates health advice using a generative AI model and transmits it to the display device.

[1754] Examples include cloud servers and on-premises servers.

[1755] 4. Display means

[1756] The display means is a device for providing users with health advice generated by the server in a visual and auditory way.

[1757] Specific example: An avatar uses the smartphone's display and speakers to provide advice via voice and video.

[1758] 5. Data transmission means

[1759] The data transmission means is a means of notifying family members of health data and analysis results.

[1760] Specific example: Sending emails and push notifications over the internet.

[1761] 6. Synchronization means

[1762] The synchronization mechanism has the function of periodically transmitting data temporarily stored in the communication device to an information processing device.

[1763] 7. Generative AI Models

[1764] Generative AI models are artificial intelligence models designed to generate appropriate health advice based on the analysis of a user's health data.

[1765] Specific example: Use natural language processing techniques such as GPT-4.

[1766] 8. Virtual Character

[1767] The virtual character is a character used to display health advice generated by the server, providing advice through voice and video.

[1768] 9. Means to support three-way calls

[1769] The means of supporting three-way calls provides the ability for the user, family members, and generative AI to talk simultaneously.

[1770] Specific example

[1771] The case of elderly person A one day

[1772] 1. Data collection:

[1773] User A puts on their smartwatch every morning and goes for a walk.

[1774] Smartwatches continuously monitor heart rate, steps taken, and calories burned.

[1775] 2. Data transfer and temporary storage:

[1776] The smartwatch transmits health data to Person A's smartphone via Bluetooth after returning home from a walk.

[1777] Smartphones temporarily store received data in a database within the app.

[1778] 3. Data transmission and analysis:

[1779] Smartphones transmit stored data to servers via the internet.

[1780] The server executes Python scripts and analyzes data using Scikit-learn models.

[1781] 4. Providing advice:

[1782] The server generates advice such as, "Today, try to eat a low-salt meal," and sends it to the smartphone.

[1783] The smartphone displays advice within the app and communicates it to person A via voice using the Google Assistant API.

[1784] 5. Data notification:

[1785] The server sends an email notification to Mr. A's son stating, "Mr. A's blood pressure is a little high."

[1786] The son (family member / user) checks the received information.

[1787] 6. Three-way calls using generative AI models:

[1788] The son (family member / user) requests a three-way call through the app.

[1789] User A accepts the call request.

[1790] The server sets up a call session using WebRTC and starts the generative AI model.

[1791] The generative AI model analyzes the content of the call and supplements it with health-related questions and confirmations in real time.

[1792] Example of a prompt

[1793] 1. "Mr. / Ms. A would like to check their health data for today. What is their current health status?"

[1794] 2. "What are some recent health concerns regarding Mr. / Ms. A?"

[1795] In this way, the system of the present invention provides support for elderly people to live their daily lives safely, and enables family members living separately to monitor their health status in real time and provide support.

[1796] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1797] Step 1:

[1798] Data collection

[1799] Users wear wearable devices on a daily basis while going about their daily lives.

[1800] Specific action: Every morning, the user puts on a smartwatch on their wrist.

[1801] Wearable devices collect health data (heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc.).

[1802] Input: User's biometric information.

[1803] Data processing: Measurement using sensors.

[1804] Output: Raw health data.

[1805] Step 2:

[1806] Data transfer and temporary storage

[1807] The wearable device collects data and transmits it to the user's device via Bluetooth or Wi-Fi.

[1808] Specific operation: The wearable device synchronizes with the terminal periodically or at the user's request.

[1809] The application temporarily stores the data received by the device.

[1810] Input: Health data transmitted from a wearable device.

[1811] Data processing: Data storage within the device.

[1812] Output: Temporarily stored health data.

[1813] Step 3:

[1814] Data transmission and analysis

[1815] The device sends temporarily stored data to the server via the internet.

[1816] Specific operation: The app sends data periodically or in response to user actions.

[1817] The server analyzes the received data and evaluates the user's health status.

[1818] Input: Health data sent from the device.

[1819] Data processing: Preprocessing and analysis using Python scripts.

[1820] Output: Health assessment report.

[1821] The server generates health advice using a generative AI model.

[1822] Input: Health assessment report.

[1823] Data processing: Generating advice using generative AI models such as GPT-4.

[1824] Output: Health advice.

[1825] Step 4:

[1826] Providing advice

[1827] The server generates health advice and sends it to the device.

[1828] Specific operation: Sending data via a REST API.

[1829] The application displays the advice received by the device, and an avatar communicates it to the user via voice or video.

[1830] Input: Health advice sent from the server.

[1831] Data processing: Conversion to in-app display format and speech synthesis.

[1832] Output: Display of advice to the user and audio output.

[1833] Step 5:

[1834] Data notification

[1835] The server notifies the family of their health data and generated advice.

[1836] Specific action: Send emails and push notifications using the notification service.

[1837] Family members receive notifications and check on the user's health status.

[1838] Input: Notification data sent from the server.

[1839] Data processing: Display via email or push notification.

[1840] Output: Notification displayed to family members.

[1841] Step 6:

[1842] Three-way calls using a generative AI model

[1843] The user or a family member requests a three-way call using a smartphone app.

[1844] Specific action: Press the "3-way call" button within the app.

[1845] The server activates the generated AI model and configures it to allow calls between the user, family members, and the generated AI model.

[1846] Input: Call request.

[1847] Data processing: Session setup and activation of the generated AI model using WebRTC technology.

[1848] Output: Call session started.

[1849] The generative AI model analyzes the call content and provides appropriate supplementary information and advice in real time.

[1850] Specific operation: The system analyzes call content in real time and uses speech synthesis to provide supplementary explanations and advice.

[1851] Input: Call content.

[1852] Data processing: Real-time analysis and speech synthesis.

[1853] Output: Supplementary explanations or advice.

[1854] (Application Example 1)

[1855] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1856] This invention relates to a system for supporting users' health management. It aims to not only collect and analyze health data using wearable devices and provide health advice based on the results, but also to provide real-time, optimal guidance when implementing a fitness plan in a virtual environment, thereby enabling effective health management and fitness instruction. Furthermore, it aims to enhance communication between the user and their family through three-way calls using a generation system, making it easier for family members living separately to understand the user's health status.

[1857] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1858] In this invention, the server includes means for analyzing the user's health data and evaluating their health status, means for generating health advice and fitness plans, and means for notifying the user and their family of the generated data. This makes it possible to provide fitness plans within a virtual environment and to share information about the user's health status with their family.

[1859] A "wearable device" is a device used to collect user health data, and includes smart bands and smartwatches.

[1860] "Terminal" refers to a device that receives and temporarily stores data collected from the wearable device, and includes smartphones, tablets, and the like.

[1861] A "server" is a device that receives data transmitted from the aforementioned terminal, analyzes it, and evaluates the health status, and includes cloud servers and data processing facilities.

[1862] "Display means" refers to a device for providing health advice generated by the server to the user, and includes a smartphone display and an audio output device.

[1863] "Communication means" refers to a device for notifying family members of the aforementioned health data and analysis results, and includes internet connectivity and email systems.

[1864] "Guide data" refers to data generated by the server to provide a fitness plan within the virtual environment, and includes exercise instructions and health advice.

[1865] "Smart glasses" refers to a device that allows the terminal to display a virtual environment and provide guidance to the user, and includes head-mounted displays and augmented reality glasses.

[1866] A "virtual environment" is an environment in which users can experience and engage in activities in a virtually defined space or situation, and includes virtual fitness rooms and virtual gyms.

[1867] A "fitness plan" is an exercise guidance and exercise program generated by the server based on the user's health data, and includes individual exercise menus and exercise guidelines.

[1868] This invention relates to a system for supporting user health management, and its main components include a wearable device, a terminal, a server, and smart glasses. This system is particularly effective when applied in virtual stores.

[1869] 1. System Configuration

[1870] Wearable devices include smart bands and smartwatches that have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, etc. A typical smartwatch is an example.

[1871] Terminal: This refers to the user's smartphone or tablet, which receives data transmitted from wearable devices via Bluetooth or Wi-Fi and temporarily stores it.

[1872] Server: Analyzes data received from terminals and assesses the user's health status. Based on the analysis results, it generates health advice and fitness plans and notifies the user and their family.

[1873] Smart glasses: Devices that display a virtual environment and provide virtual fitness guidance. Examples include head-mounted displays (HMDs) and augmented reality (AR) glasses.

[1874] 2. Program Processing

[1875] 2.1 Data Collection

[1876] While the user wears the smartwatch and goes about their daily life, the wearable device monitors health data such as heart rate, steps taken, calories burned, and blood pressure in real time.

[1877] 2.2 Data Transfer and Temporary Storage

[1878] The smartwatch periodically transmits monitored data to the user's smartphone via Bluetooth or Wi-Fi. The smartphone temporarily stores the received data.

[1879] 2.3 Data Transmission and Analysis

[1880] Smartphones transmit stored data to servers via the internet. The servers analyze the received data and assess the user's health status. They also generate appropriate health advice and fitness plans.

[1881] 2.4 Providing Guides

[1882] The server generates a fitness plan, which is then sent to the smartphone for display. Within the virtual environment, the smart glasses convey the generated fitness guide to the user via voice and visual means through an avatar. Specifically, when the user performs a squat, animations and avatar guides are displayed on the smart glasses to instruct them on correct form.

[1883] 2.5 Data Notification

[1884] The server notifies the family of the user's health data and the generated advice and analysis results. This allows the family to understand the user's health status in real time.

[1885] 3. Specific examples

[1886] On a given morning, when a user uses the system, they would go through the following steps:

[1887] Data collection from wearable devices: Users wear smartwatches while exercising or engaging in daily activities.

[1888] Data transfer: The smartwatch transfers collected data to the smartphone.

[1889] Data analysis: The smartphone sends data to the server, and the server performs the analysis.

[1890] Fitness plan delivery: A server generates a fitness plan and sends it to smart glasses, allowing the user to receive guidance within a virtual environment.

[1891] Example of a prompt:

[1892] Let's begin today's fitness plan. I've read your heart rate data. Next, please do 5 squats.

[1893] This allows users to effectively execute fitness plans in a virtual environment and manage their health in real time. It also strengthens family collaboration and enables efficient management of the user's health status.

[1894] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1895] Step 1:

[1896] The user wears a smartwatch while going about their daily life. The smartwatch monitors health data such as heart rate, steps taken, calories burned, and blood pressure in real time. The input is the user's activity data, and the output is the monitored health data.

[1897] Step 2:

[1898] The smartwatch collects health data and transmits it to the user's smartphone via Bluetooth or Wi-Fi. The input is the health data stored on the smartwatch, and the output is the data transferred to the smartphone.

[1899] Step 3:

[1900] The smartphone temporarily stores the health data it receives. The input is the health data transferred from the smartwatch, and the output is the temporarily stored data.

[1901] Step 4:

[1902] A smartphone sends temporarily stored data to a server via the internet. The input is the data stored on the smartphone, and the output is the data sent to the server.

[1903] Step 5:

[1904] The server analyzes the received data and evaluates the user's health status. The input is health data sent to the server, and the output is the analysis results and health evaluation.

[1905] Step 6:

[1906] The server generates appropriate health advice and fitness plans based on the analysis results. The input is health assessment data, and the output is health advice and fitness plans.

[1907] Step 7:

[1908] The server generates a fitness plan and sends it to the smartphone, which then displays it. The input is the generated fitness plan, and the output is the fitness plan displayed on the smartphone.

[1909] Step 8:

[1910] Smart glasses display a fitness plan in a virtual environment and provide guidance to the user. The input is the fitness plan displayed on a smartphone, and the output is the guidance displayed on the smart glasses. This may include exercise instruction using animations or avatars.

[1911] Step 9:

[1912] The server notifies the family of the user's health data and analysis results. The input is the generated analysis results and health data, and the output is the notification sent to the family.

[1913] Step 10:

[1914] The smartphone displays a generated prompt message to the user, who then follows the instructions to begin exercising. The input is the generated prompt message, and the output is the user's exercise performance. Example prompt message: "Starting today's fitness plan. Heart rate data read. Now, please do 5 squats."

[1915] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1916] This invention is a system that supports user health management and mainly consists of a wearable device, a terminal, a server, an emotion engine, and a program that coordinates these components.

[1917] System Configuration

[1918] Wearable devices: This includes smart bands and smartwatches, which have functions to monitor the user's heart rate, steps taken, calories burned, blood pressure, blood sugar levels, and so on.

[1919] Terminal: This refers to the user's smartphone or tablet, which receives and temporarily stores data transmitted from wearable devices.

[1920] Server: Analyzes data received from terminals to evaluate and monitor the user's health status. It also has the function to generate health advice based on the analysis results and notify the user and their family.

[1921] Display means: A device for providing users with health advice generated by a server in a visual and auditory way. For example, an avatar delivers advice via voice and video through a smartphone's display or speaker.

[1922] Emotion Engine: It has an algorithm that recognizes the user's emotions and analyzes their emotional state based on collected health data.

[1923] Program processing flow

[1924] 1. Data collection:

[1925] Users wear wearable devices while going about their daily lives.

[1926] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[1927] 2. Data transfer and temporary storage:

[1928] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[1929] This function temporarily stores data received by a smartphone (device).

[1930] 3. Data transmission and analysis:

[1931] The smartphone (device) sends the stored data to the server via the internet.

[1932] The server saves the received data to the database and begins analysis.

[1933] The emotion engine (device) analyzes the user's emotional state based on the collected data.

[1934] 4. Generating advice:

[1935] The server generates personalized health advice based on the analyzed health and emotional data.

[1936] The server sends the generated health advice to the user's smartphone (device).

[1937] 5. Providing advice:

[1938] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[1939] An avatar, acting as a display device, conveys advice to the user using voice and video.

[1940] 6. Data notification:

[1941] The server notifies pre-registered family contacts of the user's health data, emotional data, and analysis results.

[1942] Family members (users) review the notified information and send feedback as needed.

[1943] 7. Three-way calls using generative AI:

[1944] The user or a family member (user) requests a three-way call through a smartphone application.

[1945] The server activates a generative AI and sets up a three-way call. During the call, the generative AI supplements the conversation between the user and their family, providing real-time health-related questions and advice.

[1946] Specific example

[1947] One morning, I will explain in detail how an elderly person, Mr. B, uses the system.

[1948] 1. Data collection:

[1949] User B puts on their smartwatch and goes for a walk.

[1950] A smartwatch (wearable device) monitors your heart rate, steps taken, and calories burned while you're out for a walk.

[1951] 2. Data transfer and temporary storage:

[1952] The smartwatch (wearable device) transmits the collected data to Person B's smartphone via Bluetooth.

[1953] This function temporarily stores data received by the smartphone (device).

[1954] 3. Data transmission and analysis:

[1955] The smartphone (device) sends the stored data to the server.

[1956] The server analyzes the data and determines that Person B's blood pressure is on the higher side. Additionally, the emotion engine analyzes Person B's emotional state as "high stress."

[1957] 4. Generating advice:

[1958] The server generates advice such as, "Today, try to eat a low-salt diet," and based on the emotion engine, it also generates additional advice such as, "I recommend listening to relaxing music."

[1959] The smartphone (device) receives the advice, and the avatar relays it to person B along with a voice message.

[1960] 5. Data notification:

[1961] The server notifies B's family of their health and emotional data.

[1962] The family member (user) checks the notification and sends feedback to the server about Person B's health condition.

[1963] 6. Three-way calls using generative AI:

[1964] A family member (user) requests a call, and person B accepts.

[1965] The server activates a generative AI, providing real-time health-related questions and advice during the call.

[1966] In this way, the system of the present invention provides comprehensive support to enable elderly people to live their daily lives with peace of mind. In particular, by integrating an emotion engine, it is possible to provide personalized advice that takes into account the user's mental state, not just monitoring health data. Furthermore, it becomes easier for family members living separately to understand the health status in real time and provide necessary support.

[1967] The following describes the processing flow.

[1968] Step 1:

[1969] The user wears a wearable device (such as a smart band or smartwatch).

[1970] Step 2:

[1971] Wearable devices continuously monitor the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[1972] Step 3:

[1973] The wearable device (terminal) collects data and transmits it to the user's smartphone (terminal) via Bluetooth or Wi-Fi.

[1974] Step 4:

[1975] This function temporarily stores data received by the smartphone (device).

[1976] Step 5:

[1977] An emotion engine (located on the device or on a server) analyzes additional information such as the user's voice, facial expressions, and text input based on data from wearable devices and smartphones to identify the user's emotional state.

[1978] Step 6:

[1979] The smartphone (device) transmits accumulated health data and emotional data to a server via the internet.

[1980] Step 7:

[1981] The server saves the received data to the database.

[1982] Step 8:

[1983] The server analyzes the stored data and executes an algorithm to evaluate the user's health status.

[1984] Step 9:

[1985] The server evaluates the user's emotional state based on the results from the emotion engine and generates personalized health advice.

[1986] Step 10:

[1987] The server sends the generated health advice to the user's smartphone (device).

[1988] Step 11:

[1989] The application displays advice received by the smartphone (device), allowing the user to confirm it visually or audibly.

[1990] Step 12:

[1991] An avatar, acting as a display device, conveys advice to the user using voice and video.

[1992] Step 13:

[1993] The server notifies the user's health data, emotional data, and analysis results to pre-registered family contacts (e.g., family members' smartphones or email addresses).

[1994] Step 14:

[1995] Family members (users) review the notified information and send feedback to the server as needed.

[1996] Step 15:

[1997] If a family member (user) wishes to make a three-way call, they can submit a request through a smartphone application.

[1998] Step 16:

[1999] The user accepts the request for a three-way call.

[2000] Step 17:

[2001] The server activates the generative AI and sets up a three-way call between the user, family members, and the generative AI.

[2002] Step 18:

[2003] The generative AI (server) supplements the conversation between the user and their family during a call, providing real-time health-related questions and advice.

[2004] Step 19:

[2005] The user and their family (user) end the call, and the server saves or logs the call content using a generative AI.

[2006] (Example 2)

[2007] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2008] In modern society, there is a need for systems that can monitor both a user's health and emotional state in real time and provide appropriate advice. Collecting and analyzing health data in daily life is particularly important for the elderly and those with unstable health conditions. However, there is a lack of technology that not only monitors health data but also provides personalized advice that takes emotional states into account. Furthermore, there are limited means for family members living separately to monitor a user's health in real time and provide necessary support.

[2009] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an emotion engine that analyzes the user's emotional state using an emotion algorithm, means for supporting a three-way call between the user, family, and a generating AI model, a measurement device for collecting the user's health data, a terminal that receives and temporarily stores data from the measurement device, means for receiving data from the terminal, analyzing it, and evaluating the health state, display means for providing health advice generated by the server, and communication means for notifying the family of the health data and analysis results. This makes it possible to grasp the user's health state and emotional state in real time and provide personalized advice. In addition, family members can grasp the health state in real time from a remote location and provide appropriate support.

[2010] A "measurement device" is a device used to collect a user's health data, monitoring physical data such as heart rate, steps taken, calories burned, blood pressure, and blood glucose levels.

[2011] A "terminal" is a device that receives and temporarily stores health data transmitted from a measurement device, and includes smartphones and tablets.

[2012] A "server" is a computing system that receives data transmitted from a terminal, performs analysis, and evaluates the user's health status. Its role is to generate and notify users of health advice based on the analysis results.

[2013] "Display means" refers to a device that provides the user with health advice generated by the server, either visually or audibly, and includes smartphone displays, speakers, avatars, and other similar devices.

[2014] "Means of communication" refers to the method by which the server analyzes health data and analysis results and notifies family members of these methods, including the internet, email, and text messages.

[2015] An "emotion engine" is an algorithm and system that analyzes a user's emotional state based on their health data and behavioral patterns.

[2016] A "generative AI model" is an artificial intelligence system designed to support communication with users and their families, providing real-time answers to health-related questions and advice.

[2017] A "three-way call" refers to a call between the user, their family, and a generative AI model, allowing the user and their family to exchange health-related information and receive advice in real time.

[2018] "Health advice" refers to specific instructions and suggestions generated by the server based on an analysis of the user's health and emotional data, providing information necessary to improve and maintain the user's health.

[2019] The present invention is a system for supporting user health management and emotion analysis, and consists of a measurement device, a terminal, a server, an emotion engine, a generative AI model, and a program that links these together.

[2020] System Configuration

[2021] Measurement devices

[2022] Measurement devices such as smart bands and smartwatches are used. These devices have the function of continuously monitoring the user's health data, such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels. For example, a smartwatch measures the user's heart rate every minute and stores that data in its internal memory.

[2023] terminal

[2024] The terminal is the user's smartphone or tablet, and its role is to receive and temporarily store data transmitted from the measurement device. For example, the smartphone receives data transmitted from a smartwatch via Bluetooth and temporarily stores it in local storage.

[2025] server

[2026] The server is a computing system located in the cloud that analyzes data received from terminals and evaluates the user's health status. The server utilizes multiple algorithms to analyze trends in heart rate data, for example, and detect anomalies. Based on the analysis results, it generates personalized health advice and notifies the user and their family.

[2027] Emotional Engine

[2028] The emotion engine is a software component integrated within the server that analyzes the user's emotional state based on health data and behavioral patterns. For example, if the user has a low step count and a high heart rate, the emotion engine detects the user's stress level and incorporates that information into the analysis results.

[2029] Generative AI Models

[2030] The Generative AI Model is an artificial intelligence system that supports three-way calls between the user and their family, providing real-time health-related questions and advice. For example, if a user enters a prompt such as, "My blood pressure is high today, and I'm feeling stressed. Could you give me some advice on how to relax?", the Generative AI Model will provide appropriate advice in real time.

[2031] means of communication

[2032] The system uses the internet, email, and text messages as communication methods to notify family members of the health data and analysis results analyzed by the server. For example, if a user's heart rate remains elevated, a notification will be sent to their family via email.

[2033] Display means

[2034] The display methods used include smartphone displays, speakers, and avatars. Health advice generated by the server is provided to the user visually or audibly. For example, a smartphone app might display the advice, "We recommend you go to bed early tonight," while an avatar delivers the advice verbally.

[2035] Specific example

[2036] Let's take an example of an elderly user using this system one morning. The user puts on a smartwatch and goes for a walk. The smartwatch monitors heart rate, steps taken, and calories burned during the walk. The collected data is transmitted to the user's smartphone via Bluetooth, where it is temporarily stored.

[2037] The smartphone then sends the saved data to the server. The server analyzes the received data and determines that the user has high blood pressure and is under high stress. The server generates health advice such as "Try to eat a low-salt diet today" and emotional data-based advice such as "We recommend listening to relaxing music," and sends these to the user's smartphone.

[2038] A smartphone app receives advice, and an avatar conveys it to the user via voice. The server also notifies the user's family of the analysis data, and the family sends feedback to the server about the user's health.

[2039] The user or their family can request a three-way call through a generative AI model and receive real-time health-related questions and advice during the call. In this way, the system of the present invention can provide integrated support for the user's health management and emotional state.

[2040] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2041] Step 1: Data Collection

[2042] The user wears a measurement device (e.g., a smartwatch). The smartwatch monitors health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels.

[2043] Input: User's biometric information

[2044] Data processing: The smartwatch senses biometric information in real time, collects the necessary data, and stores it in its internal memory.

[2045] Output: Collected health data (heart rate, steps, etc.)

[2046] Step 2: Data Transfer and Temporary Storage

[2047] The wearable device transmits the data it collects via Bluetooth to the user's smartphone.

[2048] Input: Health data from smartwatch

[2049] Data processing: The smartphone receives data via Bluetooth, converts it to an appropriate format for temporary storage, and saves it to its internal storage.

[2050] Output: Health data stored on the smartphone

[2051] Step 3: Data transmission and analysis

[2052] The smartphone sends the stored data to the server via the internet.

[2053] Input: Health data on your smartphone

[2054] Data transfer: The smartphone uploads data to the server using the appropriate protocol (e.g., HTTPS).

[2055] Output: Health data sent to the server

[2056] Step 4: Data analysis and emotional state analysis

[2057] The server stores the received data in a database and performs initial analysis. The server analyzes trends and anomalies in the health data, and the emotion engine evaluates the emotional state.

[2058] Input: Received health data

[2059] Data processing: The server uses algorithms to perform analysis, and the emotion engine performs sentiment analysis based on user behavior data and health data.

[2060] Output: Analysis results (health assessment, emotional assessment)

[2061] Step 5: Generate and send advice

[2062] The server generates personalized health advice based on the analysis results. The emotion engine also generates advice that reflects emotional assessments.

[2063] Input: Analysis results

[2064] Data processing: The server generates text advice based on health and emotional states.

[2065] Output: Generated health advice

[2066] Step 6: Providing advice

[2067] The smartphone displays advice received from the server within the application. An interactive avatar provides advice via voice and video.

[2068] Input: Advice from the server

[2069] Data processing: A smartphone app displays advice in a format suitable for the user interface, and an avatar provides voice output.

[2070] Output: Advice that users receive visually and aurally.

[2071] Step 7: Notification of health data and analysis results

[2072] The server notifies the family of the user's health data and analysis results.

[2073] Input: Analysis results

[2074] Data communication: The server sends the analysis results to pre-registered family contacts (e.g., email, text message).

[2075] Output: Health data and analysis results notified to the family.

[2076] Step 8: Support for three-way calls using generative AI models

[2077] The user or a family member requests a three-way call through a smartphone app. The server activates a generated AI model and sets up the call.

[2078] Input: Call request

[2079] Data processing: Generative AI models supplement user and family conversations, providing real-time health-related questions and advice.

[2080] Output: Health advice provided in real time

[2081] (Application Example 2)

[2082] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2083] Modern users are expected not only to monitor their health data but also to take concrete actions based on that data. However, current systems do not adequately support users in choosing appropriate products and services based on their health data, and furthermore, they lack advice that takes into account the user's emotional state. In addition, it is difficult to grasp health and emotional states in a unified manner and translate that into actual actions.

[2084] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes means for having an avatar for displaying health advice and product suggestions generated by analyzing the user's health data, means for supporting three-way communication between the user, family, and the generated AI, and means for suggesting health products suitable for the user. As a result, the user can receive personalized advice and product suggestions according to their health and emotional state and take appropriate health actions.

[2085] A "wearable device" is a device that is worn on the body to continuously monitor the user's health data.

[2086] A "terminal" is a device that receives and temporarily stores data transmitted from a wearable device.

[2087] A "server" is a device that analyzes data received from terminals and generates health advice and product suggestions based on that analysis.

[2088] A "display means" is a device that provides users with health advice and product suggestions generated by a server, both visually and audibly.

[2089] "Communication means" refers to the means of notifying the user's family of health data and analysis results.

[2090] "Suggestion methods" refer to methods for suggesting health products suitable for the user based on collected health data and emotional data.

[2091] "Means of having an avatar" refers to a virtual character used to display health advice and product suggestions generated by the server.

[2092] This section describes the specific system configuration and operation for implementing this invention. This system collects and analyzes user health data and suggests suitable health products based on the results. The hardware and software used and their processing are described below.

[2093] 1. Hardware Usage Configuration

[2094] Wearable devices: such as smartwatches and smart bands.

[2095] Device: Smartphones and tablets

[2096] Server: A server used for data analysis.

[2097] Display devices: Smartphones, smart glasses (AR glasses)

[2098] 2. Software Usage Configuration

[2099] Health data collection app: Transfers data collected by wearable devices to your device.

[2100] Data analysis system: A program that runs on the server side and evaluates and analyzes health status.

[2101] Emotion Engine: An algorithm that analyzes the user's emotional state.

[2102] Generative AI models: Suggest products based on user health and emotional data.

[2103] Virtual Avatar Generation Engine: A program for generating virtual characters to present product suggestions to users.

[2104] 3. System Operation

[2105] This system operates using the following processing flow:

[2106] Wearable devices monitor the user's health data in real time, including heart rate, steps taken, calories burned, blood pressure, and blood sugar levels, and transmit this data to the device.

[2107] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[2108] The server analyzes the received health data and evaluates the user's health status. The emotion engine also analyzes the user's emotional state.

[2109] The data analysis system and emotion engine use generative AI models based on the analysis results to generate health products and advice tailored to the user.

[2110] The display device uses a smartphone or smart glasses, and an avatar provides product suggestions and health advice to the user via voice and video. It also supports three-way calls based on a generative AI model, allowing the user, family, and AI to communicate in real time.

[2111] 4. Specific Examples

[2112] One afternoon, User A finished jogging while wearing a wearable device. Afterward, the following data was sent to their smartphone:

[2113] Heart rate: 120 bpm

[2114] Steps: 10,000 steps

[2115] Calories burned: 450 kcal

[2116] Blood pressure: 130 / 85

[2117] Blood glucose level: 95 mg / dL

[2118] Emotional state: Stressed

[2119] The server analyzed this data and generated the following product suggestions:

[2120] Supplements: "Vitamin C supplements effective for relieving fatigue"

[2121] Fitness equipment: "Yoga mat"

[2122] Health foods: "Low-calorie protein bars"

[2123] Stress relief item: "Aromatherapy candle for meditation"

[2124] Using smart glasses as a display device, a virtual avatar presents these products to person A using voice and video. The avatar then suggests an additional option, saying, "We can also provide relaxing music," and person A purchases the products within the app.

[2125] 5. Example of a prompt statement

[2126] The following are examples of prompts for generative AI models:

[2127] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[2128] This system allows users to easily take specific actions tailored to their health condition and receive support in selecting appropriate products and services.

[2129] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2130] Step 1:

[2131] Users wear wearable devices that collect health data such as heart rate, steps taken, calories burned, blood pressure, and blood sugar levels in real time.

[2132] Input: User's health data (heart rate, steps, calories burned, blood pressure, blood sugar level)

[2133] Output: Collected health data

[2134] Specific operation: The wearable device uses sensors to measure health data and stores the data in its internal memory.

[2135] Step 2:

[2136] Data collected from wearable devices is transmitted to a terminal (smartphone) via Bluetooth or Wi-Fi.

[2137] Input: Health data stored on a wearable device

[2138] Output: Health data transferred to smartphone

[2139] Specific operation: The wearable device uses Bluetooth or Wi-Fi to send data to a smartphone app.

[2140] Step 3:

[2141] The terminal temporarily stores data received from the wearable device and sends it to the server via the internet.

[2142] Input: Temporary data stored on a smartphone (health data)

[2143] Output: Health data sent to the server

[2144] Specific operation: The smartphone temporarily stores the received data in its memory, and then uploads the data to the server via the internet.

[2145] Step 4:

[2146] The server analyzes the health data it receives and evaluates the user's health and emotional state.

[2147] Input: Health data sent to the server

[2148] Output: Analyzed health and emotional state

[2149] Specific operation: The server uses a data analysis system and an emotion engine to analyze health data and evaluate the user's physical condition and stress level.

[2150] Step 5:

[2151] The server uses a generative AI model based on the analysis results to generate health products and advice tailored to the user.

[2152] Input: Analyzed health and emotional state

[2153] Output: Health advice and product suggestions

[2154] Specific operation: The server references a generative AI model and makes product suggestions using the following prompts:

[2155] Based on the user's heart rate, steps taken, calories burned, blood pressure, blood glucose levels, and current emotional state, suggest the most suitable health products for them. If the user is experiencing high stress levels, also suggest relaxation products.

[2156] Step 6:

[2157] Virtual avatars provide users with health advice and product recommendations via smartphones and smart glasses.

[2158] Input: Health advice and product suggestions

[2159] Output: Advice and product information provided to the user.

[2160] Specific operation: Smartphones and smart glasses display devices use virtual avatars to provide information to users through audio and video.

[2161] Step 7:

[2162] The server uses a generative AI model to support three-way calls involving the user, family members, and the AI.

[2163] Input: User and family requests, generative AI model

[2164] Output: Three-way call session and real-time health advice

[2165] Specific operation: The server activates a generative AI model and provides health-related questions and advice in real time during the call.

[2166] This allows users to easily take specific actions based on their health data and receive support in choosing appropriate products and services.

[2167] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2168] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2169] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2170] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2171] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2172] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2173] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2174] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2175] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2176] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2177] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2178] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2179] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2180] 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.

[2181] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2182] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2183] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2184] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2185] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2186] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2187] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2188] The following is further disclosed regarding the embodiments described above.

[2189] (Claim 1)

[2190] A wearable device for collecting user health data,

[2191] A terminal that receives and temporarily stores data from the wearable device,

[2192] A server that receives data from the aforementioned terminal, analyzes it, and evaluates the health status,

[2193] A display means that provides health advice generated by the server,

[2194] A communication means for notifying the family of the aforementioned health data and analysis results,

[2195] A system that includes this.

[2196] (Claim 2)

[2197] The system according to claim 1, wherein the server has an avatar for displaying health advice generated by analyzing the health data.

[2198] (Claim 3)

[2199] The system according to claim 1, wherein the server has means for supporting a three-way call between the user, family members, and a generative AI.

[2200] "Example 1"

[2201] (Claim 1)

[2202] A measuring device for collecting user health data,

[2203] A communication device that receives and temporarily stores data from the aforementioned measuring device,

[2204] An information processing device that receives data from the aforementioned communication device, analyzes it, and evaluates the health status,

[2205] A display means that provides health advice generated by the information processing device,

[2206] A data transmission means for notifying the family of the aforementioned health data and analysis results,

[2207] A synchronization means for periodically transmitting data temporarily stored in the communication device to the information processing device,

[2208] The aforementioned information processing device provides means for generating health advice based on the analysis results using a generative AI model,

[2209] A system that includes this.

[2210] (Claim 2)

[2211] The system according to claim 1, wherein the information processing device has a virtual character for displaying health advice generated by analyzing the health data.

[2212] (Claim 3)

[2213] The system according to claim 1, wherein the information processing device has means for supporting a three-way call involving a user, family, and generative AI.

[2214] "Application Example 1"

[2215] (Claim 1)

[2216] A wearable device for collecting user health data,

[2217] A terminal that receives and temporarily stores data from the wearable device,

[2218] A server that receives data from the aforementioned terminal, analyzes it, and evaluates the health status,

[2219] A display means that provides health advice generated by the server,

[2220] A communication means for notifying the family of the aforementioned health data and analysis results,

[2221] The server provides means for generating guide data to provide a fitness plan within a virtual environment,

[2222] The aforementioned terminal includes smart glasses for displaying a virtual environment and providing guidance to the user,

[2223] A system that includes this.

[2224] (Claim 2)

[2225] The system according to claim 1, wherein the server has an avatar for displaying health advice generated by analyzing the health data.

[2226] (Claim 3)

[2227] The system according to claim 1, wherein the server has means for supporting a three-way call between a user, a family member, and a generation system.

[2228] "Example 2 of combining an emotion engine"

[2229] (Claim 1)

[2230] A measurement device for collecting user health data,

[2231] A terminal that receives and temporarily stores data from the aforementioned measuring device,

[2232] A server that receives data from the aforementioned terminal, analyzes it, and evaluates the health status,

[2233] A display means that provides health advice generated by the server,

[2234] A communication means for notifying the family of the aforementioned health data and analysis results,

[2235] An emotion engine that analyzes the user's emotional state using an emotion algorithm,

[2236] A means to support three-way calls involving the user, family, and a generative AI model,

[2237] A system that includes this.

[2238] (Claim 2)

[2239] The system according to claim 1, wherein the server has an interactive avatar for displaying health advice generated by analyzing the health data and emotional data.

[2240] (Claim 3)

[2241] The system according to claim 1, wherein the server has means for supporting a three-way call between a user, a family member, and a generated AI model.

[2242] "Application example 2 when combining with an emotional engine"

[2243] (Claim 1)

[2244] A wearable device for collecting user health data,

[2245] A terminal that receives and temporarily stores data from the wearable device,

[2246] A server that receives data from the aforementioned terminal, analyzes it, and evaluates the health status,

[2247] A display means that provides health advice generated by the server,

[2248] A communication means for notifying the family of the aforementioned health data and analysis results,

[2249] A proposal means that proposes health products suitable for the user based on the aforementioned data,

[2250] A system that includes this.

[2251] (Claim 2)

[2252] The system according to claim 1, wherein the server has an avatar for displaying health advice and product suggestions generated by analyzing the health data.

[2253] (Claim 3)

[2254] The system according to claim 1, wherein the server has means for supporting a three-way call between the user, family members, and a generating AI. [Explanation of symbols]

[2255] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A wearable device for collecting user health data, A terminal that receives and temporarily stores data from the wearable device, A server that receives data from the aforementioned terminal, analyzes it, and evaluates the health status, A display means that provides health advice generated by the server, A communication means for notifying the family of the aforementioned health data and analysis results, A system that includes this.

2. The system according to claim 1, wherein the server has an avatar for displaying health advice generated by analyzing the health data.

3. The system according to claim 1, wherein the server has means for supporting a three-way call between the user, family members, and a generative AI.

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