system

Abstract

We provide the system. [Solution] A means of receiving user information and generating individual health profiles, A means for generating health advice based on the aforementioned health profile, A means for notifying the user of the aforementioned health advice, A means of matching users with other users based on their interests and location, and forming a community. A means of monitoring user activity and sending a confirmation message if an anomaly is detected, 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 method for controlling a persona chatbot, which is 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] In an aging society, maintaining the health of the elderly and reducing medical costs are important issues. However, conventional health management systems cannot fully meet the individual needs of the elderly, and the lack of social connection is also regarded as a problem. In addition, the opportunities to effectively utilize health-related services provided by companies are limited. In such a situation, there is a need for a new method to enable the elderly to maintain a healthy and active life, promote social communication, and reduce medical costs.

Means for Solving the Problems

[0005] This invention provides a system that generates individual health profiles based on user information and notifies users of appropriate health advice. This system promotes community building through matching based on user interests and location, and supports health maintenance by providing guides on preventive medicine and online medical consultation information. Furthermore, it monitors user activity, sends confirmation messages in case of abnormalities, and effectively provides health-related services in collaboration with third-party companies. This enables improved quality of life for the elderly and reduction of social costs.

[0006] "User information" refers to data that users provide to the system, such as their age, gender, health status, exercise habits, and dietary preferences.

[0007] A "health profile" is a profile representing an individual's health status, created based on user information.

[0008] "Health advice" refers to personalized exercise and dietary recommendations generated based on a health profile.

[0009] "Matching" is the process of forming optimal groups to facilitate interaction between users based on their interests and location.

[0010] A "community" is a group of users who have been matched with each other and share common interests and goals.

[0011] "Activity" refers to actions and activities performed by a user using the system, as well as records thereof.

[0012] A "confirmation message" is a notification sent when an anomaly is detected in the user's activity status.

[0013] A "Preventive Healthcare Guide" is information on preventive healthcare provided to maintain and improve the user's health.

[0014] "Online medical treatment information" refers to information on medical services received by users through the Internet.

[0015] "Third-party company" refers to an external company that provides health-related services through a system by collaborating.

Brief Description of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It 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 combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a labeled 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.

[0020] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. %

[0021] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention describes an embodiment of a system aimed at promoting health and community building for the elderly. This system collects and analyzes user health data, provides personalized health advice, and fosters social connections. The system's program and processing overview are described below.

[0038] System Configuration

[0039] 1. Server Role

[0040] The server generates individual health profiles based on information provided by users and creates health advice based on these profiles. Furthermore, it matches users with other users based on their interests and activity levels, forming communities. It also uses data analyzed by a generative AI model to provide guides on preventive medicine and information on online medical consultations.

[0041] 2. The role of the terminal

[0042] The device displays health advice and community participation information sent from the server to the user. Through the device, users can update their health status and activity logs at any time and receive wellness messages.

[0043] 3. User Interaction

[0044] Users first install the app on their device and register their personal information, health status, and lifestyle habits. This allows them to receive health advice and exercise programs generated by the system, enabling them to manage their daily health accordingly. Furthermore, users can participate in community activities presented through matching, fostering interaction with other participants.

[0045] Specific example

[0046] Case 1: User B (68 years old, female) wants to improve her chronic lack of exercise:

[0047] Based on the information registered by user B, the server creates a program that combines light aerobic exercise and strength training. The terminal displays information about walking events that encourage participation, and users are naturally integrated into the community simply by registering.

[0048] Case 2: User C (72 years old, male) wants to learn about preventive medicine using online medical consultations:

[0049] The server uses AI generation to provide online medical information tailored to user C. Users can also select a service from the list of medical institutions displayed on their terminal and make a reservation directly.

[0050] In this way, the system addresses individual health needs, helps promote the health and maintain social relationships of the elderly, and contributes to the creation of new consumer activities.

[0051] The following describes the processing flow.

[0052] Step 1:

[0053] The user enters personal information into the application using their device. This includes age, gender, health status, exercise habits, and dietary preferences. The device then sends this information to the server.

[0054] Step 2:

[0055] The server receives information sent by the user and creates an individual health profile. This profile serves as the basis for analyzing the user's health status according to their characteristics.

[0056] Step 3:

[0057] The server uses an AI model to generate health advice based on the user's health profile. This advice includes recommended exercise plans and dietary suggestions.

[0058] Step 4:

[0059] The server generates health advice and sends it to the device. The device receives it and displays the advice to the user.

[0060] Step 5:

[0061] The user checks the display on the device and incorporates the recommended health plan into their daily life. The device periodically records the user's activity and sends feedback to the server.

[0062] Step 6:

[0063] The server matches users with other users based on their interests, location, and activity time. This ensures that users with common interests are connected.

[0064] Step 7:

[0065] The server sends the matching results to the device, and the device notifies the user of community events and group information that they can participate in.

[0066] Step 8:

[0067] Users participate in community activities and interact with other users. The server monitors these activities and periodically collects activity data.

[0068] Step 9:

[0069] If an abnormal activity pattern is detected, the server sends a confirmation message to the terminal, prompting the user to follow up.

[0070] Step 10:

[0071] The server collaborates with third-party companies to analyze collected data and provide health-related services. The terminal displays service information from partner companies to the user, encouraging their use.

[0072] (Example 1)

[0073] 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."

[0074] In systems aimed at promoting health and community building for the elderly, there is a lack of technological means to analyze individual health conditions in real time, provide appropriate health advice, and facilitate social interaction. In particular, there is a need for immediate feedback tailored to the user's health status and efficient provision of information on preventive medicine.

[0075] 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.

[0076] In this invention, the server includes means for generating a health profile based on individual health information received from a user, means for creating health advice using a generated AI model based on the health profile, and means for receiving feedback from the user and continuously updating the health profile. This enables the provision of individual health advice to the user and immediate reflection of the user's health status through continuous feedback.

[0077] "Health information" refers to data related to the user's physical condition, lifestyle, and past medical records.

[0078] A "health profile" refers to a dataset generated from health information collected from users to evaluate their individual health status.

[0079] A "generative AI model" refers to an algorithm that uses artificial intelligence technology to perform data analysis and prediction, and is used to create health advice.

[0080] "Health advice" refers to specific guidance aimed at maintaining or improving health, created based on the user's health profile.

[0081] "Communication equipment" refers to devices used to send and receive information via the internet or other digital means.

[0082] "Matching" refers to pairing users with other users based on their interests and activity times, taking into account mutual compatibility.

[0083] A "community" refers to a group of users who share common interests or activities and interact with each other and exchange information.

[0084] "Activity history" refers to past data records related to exercise and health management activities performed by the user.

[0085] "Abnormal" refers to a condition that deviates from normal health activities and may pose a risk to the user.

[0086] The "preventive field" refers to the medical field that aims to prevent the onset of disease through activities and information provision.

[0087] This system is designed for the elderly and aims to promote health and community building. It collects and analyzes users' health information and provides personalized health advice based on that information. It also has functions to support the building of social networks.

[0088] The server receives health information transmitted by the user through their device. This information includes physical condition, lifestyle, and medical history. Based on this, the server generates a health profile using a generative AI model. The generative AI model is an algorithm with data analysis and predictive capabilities that creates specific health advice tailored to the user's condition. This advice is provided, for example, as an exercise plan or dietary guidance.

[0089] The server also matches users with other users based on their interests and activity times, promoting community participation. Within this community, users can share health-related knowledge and engage in collaborative activities, strengthening their social connections.

[0090] The device displays information sent from the server to the user. Health advice and community event information are displayed on the device, and the user can check this at any time. Based on the advice, the user practices daily health management and sends feedback to the server via the device. Based on this feedback, the server updates the health profile and provides further advice.

[0091] For example, if a user wants to improve chronic lack of exercise, the generative AI model will create a mild aerobic exercise plan tailored to the user. For instance, by entering a prompt such as, "A 68-year-old woman is seeking health advice. Please generate a program to address mild lack of exercise," the server will suggest a suitable plan. Similarly, if the user is interested in preventive medicine, they can use a prompt such as, "A 72-year-old man is seeking online medical information regarding preventive medicine. Please provide a list of the best medical institutions," and the system will provide relevant information.

[0092] With the system configuration described above, users can receive information and support tailored to their individual health needs, thereby promoting the health and maintaining social relationships of the elderly.

[0093] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0094] Step 1:

[0095] The user installs and launches a dedicated application on their device. Next, the user enters personal information, health status, and lifestyle data. This data includes the user's age, gender, weight, medical history, and daily exercise habits. The device packages this information and sends it to the server.

[0096] Step 2:

[0097] The server receives health information from the terminal and stores it within the system. A generative AI model is used to analyze this data and generate a health profile for each user. Data processing includes algorithmic analysis based on the input volume. Specifically, health indicators are calculated and areas for improvement are identified. The output is a profile that quantifies the user's health status.

[0098] Step 3:

[0099] The server uses a generative AI model to create optimal health advice based on the generated health profile. The model generates advice based on prompts such as, "Suggest the best exercise program for the user." This process considers the user's past data and current health information. The output is specific health advice provided to the user.

[0100] Step 4:

[0101] The server sends health advice to the user's device. The device receives this information and displays it in a format that the user can review. The device's role is to attract the user's attention when health advice is notified, using methods such as audio or pop-up notifications. The advice is displayed to the user in text or visual format.

[0102] Step 5:

[0103] Users review health advice provided via their device and manage their health accordingly. This includes implementing suggested exercise programs and reviewing their eating habits. Users can input their results as feedback on the device. This feedback is sent to the server and used to update their health profile in the future.

[0104] Step 6:

[0105] The server receives feedback from the user and uses a generative AI model to re-adjust the health profile. This process involves analysis based on new data, updating the profile. As a result, more refined health advice is generated and provided to the user. This allows the system to continuously and dynamically support individual health management.

[0106] (Application Example 1)

[0107] 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."

[0108] There is a need to effectively manage the health status of the elderly, provide appropriate advice based on health information, and offer means to promote social connections through emergency safety checks and community building. Furthermore, the challenge is to realize a safe and secure living environment through a system that combines these functions.

[0109] 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.

[0110] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, means for monitoring user activity and sending confirmation messages if abnormalities are detected, means for generating safety confirmation information in emergencies and notifying designated contacts, and means for providing advice using an AI model generated based on the user's health data. This enables real-time management of the user's health status and the provision of services tailored to individual needs.

[0111] "User information" refers to basic personal data about the user, such as their health status, hobbies, and preferences.

[0112] A "health profile" is a dataset that represents an individual's health status and characteristics, generated based on collected user information.

[0113] "Health advice" refers to guidelines and recommended actions for maintaining or improving health, provided based on the user's health profile.

[0114] "Activity" refers to all forms of exercise, behavior, and activity that users engage in in their daily lives.

[0115] A "confirmation message" is a means of communication sent to a user for notification or confirmation, and is particularly used in the event of an abnormal situation.

[0116] A "generative AI model" is an artificial intelligence technology used to analyze a user's health data and provide personalized advice and suggestions.

[0117] A "community" is a place or group of people that connects users with common interests or concerns, fostering social interaction.

[0118] "Means for generating safety confirmation information in emergencies" refers to a mechanism that creates information for safety confirmation when the user's condition changes and promptly notifies relevant parties.

[0119] The system that realizes this application is a health promotion platform for the elderly. It consists of a server, terminals, and user interaction.

[0120] The server receives user information and uses that data to generate individual health profiles. Based on the generated health profiles, it uses an AI model to create health advice and sends it to the user's device. The server uses Python's Scikit-learn, TENSORFLOW®, GPT-3®, and other tools to perform data analysis and operate the AI ​​models. Furthermore, it has a function to match users with other users based on their interests and location, supporting community building. If an anomaly is detected, it sends a confirmation message and takes emergency action as needed.

[0121] The device consists of smartphones and smartwatches, and displays health advice and community participation information received from the server to the user. Users can update their health status and activities via the device and manage their daily health accordingly. The device monitors the user's activities and, in emergencies, collaborates with the server to generate safety confirmation information.

[0122] Users begin by registering their personal information and lifestyle habits with the system using the app. They then receive generated health advice and can get quick support in case of abnormalities. For example, if a user's heart rate is higher than normal, the AI ​​model can immediately generate a suggestion to take deep breaths and send an alert to emergency contacts.

[0123] An example of a prompt message is: "User A's heart rate has reached 110 beats per minute, which is extremely high compared to the normal 70. Please create advice for immediate action." In this way, the platform comprehensively manages the user's health and safety, providing an environment where they can live with peace of mind.

[0124] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0125] Step 1:

[0126] Users input personal information, health status, and lifestyle habits via their device. The device then collects this information and generates data packets to send to the server. Input includes registering information using the smartphone's touchscreen. Output is the transmission of user information to the server.

[0127] Step 2:

[0128] The server generates a health profile based on the received user information. The server's data analysis module comprehensively analyzes the user's health data using statistical analysis and machine learning. Data organization and profile generation are performed using Python's Scikit-learn and Pandas libraries. The output is a personalized health profile.

[0129] Step 3:

[0130] The server utilizes the generated health profile and uses a generative AI model to create health advice tailored to the user. In this process, the profile data is used as input, and the generative AI model predicts specific health advice. The output includes a generated prompt and the specific text in which the generative AI model provides advice.

[0131] Step 4:

[0132] The server generates community matching information for users based on their location and interests, along with health advice. Input includes user interest data and geographical information, and the server runs a data matching algorithm. Output includes community invitations and event information.

[0133] Step 5:

[0134] The server generates health advice and matching information, which is then sent to the terminal. The terminal receives this information and displays a notification to the user. The input is data packets from the server, and the output is the notification displayed on the terminal screen.

[0135] Step 6:

[0136] The user follows the advice and records their daily health status on the device. This causes the device to generate update data packets to send new health data to the server. The input is the user's new health data, and the output is the update information sent to the server.

[0137] Step 7:

[0138] When the server detects an anomaly, it generates a confirmation message and sends a notification to the relevant contact. Inputs are real-time user data and warnings from the anomaly detection algorithm. Outputs are warning messages regarding the anomaly. This enables rapid safety confirmation.

[0139] 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.

[0140] This invention describes an embodiment of a health promotion and community-building system for the elderly that combines an emotional engine. This system analyzes user information, health data, and emotional data to provide users with optimal health advice while promoting participation in diverse social activities. The system's program and its processing overview are outlined below.

[0141] System Configuration

[0142] 1. Server Role

[0143] The server generates individual health profiles based on information from the user. It also analyzes the user's emotional state using an emotion engine and adjusts health advice accordingly. By combining the health profile and emotional information, the server provides users with advice and suggests appropriate ways to participate in community activities.

[0144] 2. The role of the terminal

[0145] The device displays health advice and emotionally-based plan adjustments sent from the server to the user. Through the device, users can input their daily health status and emotional changes, receiving timely advice and suggestions.

[0146] 3. User Interaction

[0147] Users register information about their health, lifestyle, and emotions using their devices. The system detects changes in the user's emotions and adjusts health advice in real time. It also facilitates effective social interaction by recommending events and community activities that match the user's emotional state.

[0148] Specific example

[0149] Case 1: When User D (70 years old, female) is experiencing emotional distress:

[0150] The server analyzes user D's emotions using an emotion engine and recommends a yoga plan that promotes relaxation. The terminal displays information about online yoga events that contribute to emotional improvement, encouraging easy participation.

[0151] Case 2: When User E (75 years old, male) is experiencing increased anxiety:

[0152] The server recommends deep breathing exercises to reduce anxiety and notifies users via their devices. Furthermore, it recommends group chat sessions that contribute to emotional stability, allowing users to receive support from other participants.

[0153] In this way, this system takes into account the user's emotional state and provides more personalized health management and social interaction opportunities, thereby improving the quality of life (QOL) of the elderly.

[0154] The following describes the processing flow.

[0155] Step 1:

[0156] Users input information about their health, lifestyle, and emotions into their device. They record daily changes in their mood and emotions through a simple questionnaire.

[0157] Step 2:

[0158] The device sends the user's input information to the server. The transmitted data includes health information and emotional state.

[0159] Step 3:

[0160] The server analyzes the user information it receives and generates individual health profiles. It uses a generative AI model and an emotion engine to comprehensively evaluate health and emotional states.

[0161] Step 4:

[0162] The server utilizes an emotion engine to analyze the user's emotional state. Specifically, it captures changes in emotions and evaluates how they affect the user's health profile.

[0163] Step 5:

[0164] The server generates optimal health advice for the user based on the emotion analysis results. For example, if stress levels are high, it will recommend activities that are effective for relaxation.

[0165] Step 6:

[0166] The device receives health advice from the server and notifies the user. This advice is customized to take into account the user's emotional state.

[0167] Step 7:

[0168] The user incorporates the provided health advice into their daily life and records their activity levels again on the device. The device continuously transmits this activity data to the server.

[0169] Step 8:

[0170] The server continuously monitors the user's emotional state and activity data, and if an abnormal pattern is detected, it sends a confirmation message to the terminal.

[0171] Step 9:

[0172] The server takes into account the user's emotions and health status to suggest appropriate community activities and events. The terminal displays this information to the user and encourages participation.

[0173] Step 10:

[0174] Users participate in recommended community events and interact with other attendees. The server then re-evaluates the emotional changes resulting from these events and incorporates them into future advice.

[0175] (Example 2)

[0176] 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".

[0177] Maintaining and improving the health of users, including the elderly, requires personalized health guidance and flexible responses to changes in their emotional state. However, current health management systems are generally templated and lack sufficient personalization to address the emotions and social needs of individual users. To solve this problem, a system is needed that can analyze the user's condition in real time and provide appropriate health guidance and suggestions for social activities based on that analysis.

[0178] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0179] In this invention, the server includes means for receiving user information and generating individual health plans, means for analyzing emotional information and adjusting health guidance, and means for suggesting social activities with other users and notifying the user of the suggested activities. This makes it possible to provide users with personalized and situation-appropriate health guidance and opportunities for social interaction.

[0180] "User information" refers to basic personal data provided by system users, as well as information regarding their health status, lifestyle, emotional state, etc.

[0181] A "health plan" is a specific plan or goal set based on a user's individual health data, with the aim of maintaining or improving their health.

[0182] "Health guidance" refers to advice and recommended actions provided based on the user's health status and emotional analysis results.

[0183] "Emotional information" refers to data about emotions that is entered by the user or collected by the system, and it represents the user's emotional state.

[0184] "Social activities" refer to community events and gatherings that users participate in through interaction with other users.

[0185] "Feedback" refers to the opinions and evaluations that users provide regarding the guidance and suggestions offered by the system, and these are used to improve future guidance.

[0186] This invention is a system that analyzes a user's health status and emotional information to provide personalized health guidance and suggestions for social activities. This system consists of three main elements: a server, a terminal, and a user.

[0187] The server generates individualized health plans based on information received from users. This plan utilizes diverse data, including the user's basic information, lifestyle, and health status. Emotional information is analyzed using a generative AI model to adjust health guidance according to the user's emotional state. This analysis utilizes natural language processing software and a cloud-based AI platform.

[0188] The terminal serves to notify the user of health guidance and suggestions for social activities transmitted from the server. The terminal provides a visual interface using hardware such as a smartphone, tablet, or personal computer. This allows the user to receive guidance tailored to their daily health status and emotional changes.

[0189] Users input their health status and emotional information through their device and view the resulting health guidance. The system collects user feedback and uses it to improve the quality of future guidance. For example, if a user inputs "I've been feeling stressed lately," the system can suggest relaxation plans and opportunities for social interaction to reduce stress.

[0190] An example of a prompt might be, "We would like to offer health guidance and interaction suggestions based on emotion analysis for elderly individuals." Based on this prompt, the generating AI model provides the user with the most suitable health management and interaction methods.

[0191] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0192] Step 1:

[0193] The user uses a device to input data about their health status, lifestyle, and emotional state. This data is used as basic information to create the user's health plan. The entered information is sent from the device to the server to prepare for the next processing step.

[0194] Step 2:

[0195] The server analyzes the received user information and generates an individualized health plan. In this process, the server uses a generation AI model to analyze the user's health data and identify the health plan best suited to the user's needs. Specifically, it sets health goals considering past health history and current condition, and incorporates these into the plan. The output is a customized health plan for each user.

[0196] Step 3:

[0197] The server generates health guidance based on the health plan and further adjusts it to match the user's current emotional state by analyzing emotional information. The server specifically analyzes emotional data using natural language processing techniques to understand stress levels and emotional tendencies. This results in the generation and output of more effective and personalized guidance.

[0198] Step 4:

[0199] Health guidance and social activity suggestions generated from the server are sent to the device. The device displays the guidance content in an easy-to-understand format for the user and provides it in a way that allows for real-time action. Specifically, the device can notify the user of the date and time through push notifications and automatic addition to the calendar.

[0200] Step 5:

[0201] Users conduct instruction and input the results and feedback via their terminals. This feedback includes the effectiveness of the instruction and areas for improvement for future sessions. This information is then sent back to the server, contributing to the overall improvement of instruction quality within the system.

[0202] Step 6:

[0203] The server analyzes feedback data collected from users and incorporates it into future health guidance and suggestions. Using a generative AI model, feedback is analyzed to reconstruct more suitable guidance and social interaction opportunities for the user. This step allows the system to continuously improve and provide better services to users.

[0204] (Application Example 2)

[0205] 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".

[0206] To simultaneously promote health management and social interaction among the elderly, thereby reducing isolation and health anxieties associated with these changes. Furthermore, to provide a comfortable, real-time in-store experience by suggesting appropriate products and services that respond to the user's emotions.

[0207] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0208] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, and means for analyzing the user's emotions and suggesting products or services based on a specific state. This makes it possible to increase opportunities for user health promotion and social interaction, and to provide products and services that correspond to specific emotional states in real time.

[0209] "User information" refers to individual data collected by the system for each user, including information about their health status, lifestyle, and emotional state.

[0210] A "health profile" is a comprehensive collection of data about a user's health status and lifestyle, generated based on their individual information.

[0211] "Health advice" refers to specific guidance and suggestions generated based on the user's health profile to help promote and maintain their health.

[0212] "Means of forming communities" refers to a function that facilitates cooperation and interaction between users based on their interests and location.

[0213] "Methods for analyzing emotions" refer to technologies that use user emotional data to determine and analyze their emotional state.

[0214] "Means of suggesting products or services" refers to a function that presents appropriate products or services based on the results of user sentiment analysis.

[0215] "Activity monitoring systems" are systems that observe various activities performed by users and notify them of warnings if any abnormalities are detected.

[0216] This system configuration is designed to support user health promotion and social interaction. The server receives user information and generates an individual health profile. Based on the health profile, appropriate health advice is automatically generated and notified from the server to the terminal. The emotion engine analyzes the user's emotional data and determines their state in real time. Specifically, it performs emotion analysis based on data registered by the user using the terminal and makes suggestions for specific products and services.

[0217] In this system, wearable devices such as smart glasses function as terminals to monitor user activity. If an anomaly is detected, a confirmation message is immediately sent from the server to notify the user. Furthermore, users are matched with other users based on their interests and current location, forming a community.

[0218] For example, if a user visits a store and is wearing smart glasses, the glasses' cameras and sensors detect the user's emotional state and physical condition in real time, and appropriate products or events are suggested. Based on the generated emotional data, the generative AI model outputs prompt sentences related to specific emotions and provides the user with a corresponding experience.

[0219] An example of a prompt message is: "Jane's smart glasses analyzed her smile. The emotion engine determined that her emotional state was stable, and displayed information about a healthy salad sale." In this way, the system operates by integrating various functions that improve the user experience.

[0220] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0221] Step 1:

[0222] The server receives user information and generates individual health profiles. The input consists of data collected from the user regarding their health status, lifestyle, and emotional state, which is used to create the health profile. A database management system is used to integrate different data and calculate metrics related to the user's health.

[0223] Step 2:

[0224] The server generates health advice based on the health profile and sends it to the terminal. The input is health profile data; a generation AI model is used to perform trend analysis and edit appropriate health advice. As output, specific health management suggestions are generated and notified to the terminal.

[0225] Step 3:

[0226] The user inputs emotional data using a device. This input is feedback indicating the user's emotional state and is collected via sensors in smart glasses, etc. An emotional analysis algorithm analyzes this data and generates an output to determine the user's emotional state.

[0227] Step 4:

[0228] The server analyzes the user's emotional data and suggests products or services based on their specific state. The input is the analysis results from step 3, and it utilizes an AI-based inference engine to select highly relevant products or events in real time. As output, specific suggestions are generated and displayed on the terminal.

[0229] Step 5:

[0230] The device notifies the user of suggested products or services and encourages purchase or participation. Input is the suggested content received from the server, and output includes the presentation of suggestions to the user and tracking information of their response. Voice guidance and visual displays are used to guide the user's actions.

[0231] Step 6:

[0232] Users decide to participate in or purchase products or services they are interested in. In this step, user feedback is recorded as new input for re-analysis in the next step. The user's selected actions are collected in a database, contributing to improving the accuracy of future recommendations.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] [Second Embodiment]

[0237] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0238] 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.

[0239] 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).

[0240] 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.

[0241] 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.

[0242] 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).

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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".

[0249] This invention describes an embodiment of a system aimed at promoting health and community building for the elderly. This system collects and analyzes user health data, provides personalized health advice, and fosters social connections. The system's program and processing overview are described below.

[0250] System Configuration

[0251] 1. Server Role

[0252] The server generates individual health profiles based on information provided by users and creates health advice based on these profiles. Furthermore, it matches users with other users based on their interests and activity levels, forming communities. It also uses data analyzed by a generative AI model to provide guides on preventive medicine and information on online medical consultations.

[0253] 2. The role of the terminal

[0254] The device displays health advice and community participation information sent from the server to the user. Through the device, users can update their health status and activity logs at any time and receive wellness messages.

[0255] 3. User Interaction

[0256] Users first install the app on their device and register their personal information, health status, and lifestyle habits. This allows them to receive health advice and exercise programs generated by the system, enabling them to manage their daily health accordingly. Furthermore, users can participate in community activities presented through matching, fostering interaction with other participants.

[0257] Specific example

[0258] Case 1: User B (68 years old, female) wants to improve her chronic lack of exercise:

[0259] Based on the information registered by user B, the server creates a program that combines light aerobic exercise and strength training. The terminal displays information about walking events that encourage participation, and users are naturally integrated into the community simply by registering.

[0260] Case 2: User C (72 years old, male) wants to learn about preventive medicine using online medical consultations:

[0261] The server uses AI generation to provide online medical information tailored to user C. Users can also select a service from the list of medical institutions displayed on their terminal and make a reservation directly.

[0262] In this way, the system addresses individual health needs, helps promote the health and maintain social relationships of the elderly, and contributes to the creation of new consumer activities.

[0263] The following describes the processing flow.

[0264] Step 1:

[0265] The user enters personal information into the application using their device. This includes age, gender, health status, exercise habits, and dietary preferences. The device then sends this information to the server.

[0266] Step 2:

[0267] The server receives information sent by the user and creates an individual health profile. This profile serves as the basis for analyzing the user's health status according to their characteristics.

[0268] Step 3:

[0269] The server uses an AI model to generate health advice based on the user's health profile. This advice includes recommended exercise plans and dietary suggestions.

[0270] Step 4:

[0271] The server generates health advice and sends it to the device. The device receives it and displays the advice to the user.

[0272] Step 5:

[0273] The user checks the display of the terminal and incorporates the recommended health plan into daily life. The terminal periodically records the user's activity status and sends feedback to the server.

[0274] Step 6:

[0275] The server matches the user with other users based on the user's interests, location, and activity time. As a result, users with common interests are matched.

[0276] Step 7:

[0277] The server sends the matching result to the terminal, and the terminal notifies the user of community events and group information that the user can participate in.

[0278] Step 8:

[0279] The user participates in community activities and communicates with other users. The server monitors this activity and periodically collects activity data.

[0280] Step 9:

[0281] If an abnormal activity pattern is detected, the server sends a confirmation message to the terminal to prompt the user for follow-up.

[0282] Step 10:

[0283] The server collaborates with third-party companies, analyzes the collected data, and provides health-related services. The terminal shows the user service information from the partnering companies and promotes utilization.

[0284] (Example 1)

[0285] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0286] In a system aimed at promoting health and forming communities for the elderly, there is a lack of technical means to analyze individual health conditions in real time, provide appropriate health advice, and promote social interaction. In particular, there is a need to efficiently provide immediate feedback according to the user's health condition and information on preventive medicine.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0288] In this invention, the server includes means for generating a health profile based on individual health information received from a user, means for creating health advice using an AI model generated based on the health profile, and means for receiving feedback from the user and continuously updating the health profile. As a result, it becomes possible to provide individual health advice to the user and immediately reflect the health condition by continuous feedback.

[0289] "Health information" refers to data related to the user's physical condition, lifestyle, and past medical records.

[0290] "Health profile" refers to a dataset for evaluating individual health conditions generated based on health information collected from a user.

[0291] "Generated AI model" refers to an algorithm that uses artificial intelligence technology for data analysis and prediction and is used to create health advice.

[0292] "Health advice" refers to specific guidance content for maintaining and improving health created based on the user's health profile.

[0293] "Communication device" refers to a device for transmitting and receiving information through the Internet or other digital means.

[0294] "Matching" refers to pairing users with other users based on their interests and activity times, taking into account mutual compatibility.

[0295] A "community" refers to a group of users who share common interests or activities and interact with each other and exchange information.

[0296] "Activity history" refers to past data records related to exercise and health management activities performed by the user.

[0297] "Abnormal" refers to a condition that deviates from normal health activities and may pose a risk to the user.

[0298] The "preventive field" refers to the medical field that aims to prevent the onset of disease through activities and information provision.

[0299] This system is designed for the elderly and aims to promote health and community building. It collects and analyzes users' health information and provides personalized health advice based on that information. It also has functions to support the building of social networks.

[0300] The server receives health information transmitted by the user through their device. This information includes physical condition, lifestyle, and medical history. Based on this, the server generates a health profile using a generative AI model. The generative AI model is an algorithm with data analysis and predictive capabilities that creates specific health advice tailored to the user's condition. This advice is provided, for example, as an exercise plan or dietary guidance.

[0301] The server also matches users with other users based on their interests and activity times, promoting community participation. Within this community, users can share health-related knowledge and engage in collaborative activities, strengthening their social connections.

[0302] The terminal displays the information sent from the server to the user. Information such as health advice and community event information is displayed on the terminal, and the user can check this at any time. The user practices daily health management based on the advice and sends feedback to the server via the terminal. Based on this feedback, the server updates the health profile and provides further advice.

[0303] As a specific example, when a user wants to improve chronic lack of exercise, the generative AI model creates a light aerobic exercise plan suitable for the user. For example, by inputting a prompt sentence such as "A 68-year-old woman is seeking health advice. Please generate a program to eliminate mild lack of exercise.", the server proposes an appropriate plan. Also, when interested in preventive medicine, relevant information can be provided using a prompt sentence such as "A 72-year-old man is seeking online medical consultation information regarding preventive medicine. Please provide a list of optimal medical institutions."

[0304] With the system configuration as described above, the user can receive information and support corresponding to individual health needs, and health promotion and maintenance of social relationships for the elderly can be achieved.

[0305] The flow of the specific process in Example 1 will be described using FIG. 11.

[0306] Step 1:

[0307] The user installs and launches a dedicated application on the terminal. Next, the user inputs data regarding personal information, health status, and lifestyle habits. These input data include the user's age, gender, weight, medical history, daily exercise habits, etc. The terminal packages this information and sends it to the server.

[0308] Step 2:

[0309] The server receives health information from the terminal and stores it within the system. A generative AI model is used to analyze this data and generate a health profile for each user. Data processing includes algorithmic analysis based on the input volume. Specifically, health indicators are calculated and areas for improvement are identified. The output is a profile that quantifies the user's health status.

[0310] Step 3:

[0311] The server uses a generative AI model to create optimal health advice based on the generated health profile. The model generates advice based on prompts such as, "Suggest the best exercise program for the user." This process considers the user's past data and current health information. The output is specific health advice provided to the user.

[0312] Step 4:

[0313] The server sends health advice to the user's device. The device receives this information and displays it in a format that the user can review. The device's role is to attract the user's attention when health advice is notified, using methods such as audio or pop-up notifications. The advice is displayed to the user in text or visual format.

[0314] Step 5:

[0315] Users review health advice provided via their device and manage their health accordingly. This includes implementing suggested exercise programs and reviewing their eating habits. Users can input their results as feedback on the device. This feedback is sent to the server and used to update their health profile in the future.

[0316] Step 6:

[0317] The server receives feedback from the user and uses a generative AI model to re-adjust the health profile. This process involves analysis based on new data, updating the profile. As a result, more refined health advice is generated and provided to the user. This allows the system to continuously and dynamically support individual health management.

[0318] (Application Example 1)

[0319] 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."

[0320] There is a need to effectively manage the health status of the elderly, provide appropriate advice based on health information, and offer means to promote social connections through emergency safety checks and community building. Furthermore, the challenge is to realize a safe and secure living environment through a system that combines these functions.

[0321] 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.

[0322] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, means for monitoring user activity and sending confirmation messages if abnormalities are detected, means for generating safety confirmation information in emergencies and notifying designated contacts, and means for providing advice using an AI model generated based on the user's health data. This enables real-time management of the user's health status and the provision of services tailored to individual needs.

[0323] "User information" refers to basic personal data about the user, such as their health status, hobbies, and preferences.

[0324] A "health profile" is a dataset that represents an individual's health status and characteristics, generated based on collected user information.

[0325] "Health advice" refers to guidelines and recommended actions for maintaining or improving health, provided based on the user's health profile.

[0326] "Activity" refers to all forms of exercise, behavior, and activity that users engage in in their daily lives.

[0327] A "confirmation message" is a means of communication sent to a user for notification or confirmation, and is particularly used in the event of an abnormal situation.

[0328] A "generative AI model" is an artificial intelligence technology used to analyze a user's health data and provide personalized advice and suggestions.

[0329] A "community" is a place or group of people that connects users with common interests or concerns, fostering social interaction.

[0330] "Means for generating safety confirmation information in emergencies" refers to a mechanism that creates information for safety confirmation when the user's condition changes and promptly notifies relevant parties.

[0331] The system that realizes this application is a health promotion platform for the elderly. It consists of a server, terminals, and user interaction.

[0332] The server receives user information and uses that data to generate individual health profiles. Based on the generated health profiles, it uses an AI model to create health advice and sends it to the user's device. The server uses Python's Scikit-learn, TensorFlow, GPT-3, etc., for data analysis and AI model operation. Furthermore, it has a function to match users with other users based on their interests and location, supporting community building. If an anomaly is detected, it sends a confirmation message and takes emergency action as needed.

[0333] The device consists of smartphones and smartwatches, and displays health advice and community participation information received from the server to the user. Users can update their health status and activities via the device and manage their daily health accordingly. The device monitors the user's activities and, in emergencies, collaborates with the server to generate safety confirmation information.

[0334] Users begin by registering their personal information and lifestyle habits with the system using the app. They then receive generated health advice and can get quick support in case of abnormalities. For example, if a user's heart rate is higher than normal, the AI ​​model can immediately generate a suggestion to take deep breaths and send an alert to emergency contacts.

[0335] An example of a prompt message is: "User A's heart rate has reached 110 beats per minute, which is extremely high compared to the normal 70. Please create advice for immediate action." In this way, the platform comprehensively manages the user's health and safety, providing an environment where they can live with peace of mind.

[0336] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0337] Step 1:

[0338] Users input personal information, health status, and lifestyle habits via their device. The device then collects this information and generates data packets to send to the server. Input includes registering information using the smartphone's touchscreen. Output is the transmission of user information to the server.

[0339] Step 2:

[0340] The server generates a health profile based on the received user information. The server's data analysis module comprehensively analyzes the user's health data using statistical analysis and machine learning. Data organization and profile generation are performed using Python's Scikit-learn and Pandas libraries. The output is a personalized health profile.

[0341] Step 3:

[0342] The server utilizes the generated health profile and uses a generative AI model to create health advice tailored to the user. In this process, the profile data is used as input, and the generative AI model predicts specific health advice. The output includes a generated prompt and the specific text in which the generative AI model provides advice.

[0343] Step 4:

[0344] The server generates community matching information for users based on their location and interests, along with health advice. Input includes user interest data and geographical information, and the server runs a data matching algorithm. Output includes community invitations and event information.

[0345] Step 5:

[0346] The server generates health advice and matching information, which is then sent to the terminal. The terminal receives this information and displays a notification to the user. The input is data packets from the server, and the output is the notification displayed on the terminal screen.

[0347] Step 6:

[0348] The user follows the advice and records their daily health status on the device. This causes the device to generate update data packets to send new health data to the server. The input is the user's new health data, and the output is the update information sent to the server.

[0349] Step 7:

[0350] When the server detects an anomaly, it generates a confirmation message and sends a notification to the relevant contact. Inputs are real-time user data and warnings from the anomaly detection algorithm. Outputs are warning messages regarding the anomaly. This enables rapid safety confirmation.

[0351] 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.

[0352] This invention describes an embodiment of a health promotion and community-building system for the elderly that combines an emotional engine. This system analyzes user information, health data, and emotional data to provide users with optimal health advice while promoting participation in diverse social activities. The system's program and its processing overview are outlined below.

[0353] System Configuration

[0354] 1. Server Role

[0355] The server generates individual health profiles based on information from the user. It also analyzes the user's emotional state using an emotion engine and adjusts health advice accordingly. By combining the health profile and emotional information, the server provides users with advice and suggests appropriate ways to participate in community activities.

[0356] 2. The role of the terminal

[0357] The device displays health advice and emotionally-based plan adjustments sent from the server to the user. Through the device, users can input their daily health status and emotional changes, receiving timely advice and suggestions.

[0358] 3. User Interaction

[0359] Users register information about their health, lifestyle, and emotions using their devices. The system detects changes in the user's emotions and adjusts health advice in real time. It also facilitates effective social interaction by recommending events and community activities that match the user's emotional state.

[0360] Specific example

[0361] Case 1: When User D (70 years old, female) is experiencing emotional distress:

[0362] The server analyzes user D's emotions using an emotion engine and recommends a yoga plan that promotes relaxation. The terminal displays information about online yoga events that contribute to emotional improvement, encouraging easy participation.

[0363] Case 2: When User E (75 years old, male) is experiencing increased anxiety:

[0364] The server recommends deep breathing exercises to reduce anxiety and notifies users via their devices. Furthermore, it recommends group chat sessions that contribute to emotional stability, allowing users to receive support from other participants.

[0365] In this way, this system takes into account the user's emotional state and provides more personalized health management and social interaction opportunities, thereby improving the quality of life (QOL) of the elderly.

[0366] The following describes the processing flow.

[0367] Step 1:

[0368] Users input information about their health, lifestyle, and emotions into their device. They record daily changes in their mood and emotions through a simple questionnaire.

[0369] Step 2:

[0370] The device sends the user's input information to the server. The transmitted data includes health information and emotional state.

[0371] Step 3:

[0372] The server analyzes the user information it receives and generates individual health profiles. It uses a generative AI model and an emotion engine to comprehensively evaluate health and emotional states.

[0373] Step 4:

[0374] The server utilizes an emotion engine to analyze the user's emotional state. Specifically, it captures changes in emotions and evaluates how they affect the user's health profile.

[0375] Step 5:

[0376] The server generates optimal health advice for the user based on the emotion analysis results. For example, if stress levels are high, it will recommend activities that are effective for relaxation.

[0377] Step 6:

[0378] The device receives health advice from the server and notifies the user. This advice is customized to take into account the user's emotional state.

[0379] Step 7:

[0380] The user incorporates the provided health advice into their daily life and records their activity levels again on the device. The device continuously transmits this activity data to the server.

[0381] Step 8:

[0382] The server continuously monitors the user's emotional state and activity data, and if an abnormal pattern is detected, it sends a confirmation message to the terminal.

[0383] Step 9:

[0384] The server takes into account the user's emotions and health status to suggest appropriate community activities and events. The terminal displays this information to the user and encourages participation.

[0385] Step 10:

[0386] Users participate in recommended community events and interact with other attendees. The server then re-evaluates the emotional changes resulting from these events and incorporates them into future advice.

[0387] (Example 2)

[0388] 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".

[0389] Maintaining and improving the health of users, including the elderly, requires personalized health guidance and flexible responses to changes in their emotional state. However, current health management systems are generally templated and lack sufficient personalization to address the emotions and social needs of individual users. To solve this problem, a system is needed that can analyze the user's condition in real time and provide appropriate health guidance and suggestions for social activities based on that analysis.

[0390] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0391] In this invention, the server includes means for receiving user information and generating individual health plans, means for analyzing emotional information and adjusting health guidance, and means for suggesting social activities with other users and notifying the user of the suggested activities. This makes it possible to provide users with personalized and situation-appropriate health guidance and opportunities for social interaction.

[0392] "User information" refers to basic personal data provided by system users, as well as information regarding their health status, lifestyle, emotional state, etc.

[0393] A "health plan" is a specific plan or goal set based on a user's individual health data, with the aim of maintaining or improving their health.

[0394] "Health guidance" refers to advice and recommended actions provided based on the user's health status and emotional analysis results.

[0395] "Emotional information" refers to data about emotions that is entered by the user or collected by the system, and it represents the user's emotional state.

[0396] "Social activities" refer to community events and gatherings that users participate in through interaction with other users.

[0397] "Feedback" refers to the opinions and evaluations that users provide regarding the guidance and suggestions offered by the system, and these are used to improve future guidance.

[0398] This invention is a system that analyzes a user's health status and emotional information to provide personalized health guidance and suggestions for social activities. This system consists of three main elements: a server, a terminal, and a user.

[0399] The server generates individualized health plans based on information received from users. This plan utilizes diverse data, including the user's basic information, lifestyle, and health status. Emotional information is analyzed using a generative AI model to adjust health guidance according to the user's emotional state. This analysis utilizes natural language processing software and a cloud-based AI platform.

[0400] The terminal serves to notify the user of health guidance and suggestions for social activities transmitted from the server. The terminal provides a visual interface using hardware such as a smartphone, tablet, or personal computer. This allows the user to receive guidance tailored to their daily health status and emotional changes.

[0401] Users input their health status and emotional information through their device and view the resulting health guidance. The system collects user feedback and uses it to improve the quality of future guidance. For example, if a user inputs "I've been feeling stressed lately," the system can suggest relaxation plans and opportunities for social interaction to reduce stress.

[0402] An example of a prompt might be, "We would like to offer health guidance and interaction suggestions based on emotion analysis for elderly individuals." Based on this prompt, the generating AI model provides the user with the most suitable health management and interaction methods.

[0403] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0404] Step 1:

[0405] The user uses a device to input data about their health status, lifestyle, and emotional state. This data is used as basic information to create the user's health plan. The entered information is sent from the device to the server to prepare for the next processing step.

[0406] Step 2:

[0407] The server analyzes the received user information and generates an individualized health plan. In this process, the server uses a generation AI model to analyze the user's health data and identify the health plan best suited to the user's needs. Specifically, it sets health goals considering past health history and current condition, and incorporates these into the plan. The output is a customized health plan for each user.

[0408] Step 3:

[0409] The server generates health guidance based on the health plan and further adjusts it to match the user's current emotional state by analyzing emotional information. The server specifically analyzes emotional data using natural language processing techniques to understand stress levels and emotional tendencies. This results in the generation and output of more effective and personalized guidance.

[0410] Step 4:

[0411] Health guidance and social activity suggestions generated from the server are sent to the device. The device displays the guidance content in an easy-to-understand format for the user and provides it in a way that allows for real-time action. Specifically, the device can notify the user of the date and time through push notifications and automatic addition to the calendar.

[0412] Step 5:

[0413] Users conduct instruction and input the results and feedback via their terminals. This feedback includes the effectiveness of the instruction and areas for improvement for future sessions. This information is then sent back to the server, contributing to the overall improvement of instruction quality within the system.

[0414] Step 6:

[0415] The server analyzes feedback data collected from users and incorporates it into future health guidance and suggestions. Using a generative AI model, feedback is analyzed to reconstruct more suitable guidance and social interaction opportunities for the user. This step allows the system to continuously improve and provide better services to users.

[0416] (Application Example 2)

[0417] 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."

[0418] To simultaneously promote health management and social interaction among the elderly, thereby reducing isolation and health anxieties associated with these changes. Furthermore, to provide a comfortable, real-time in-store experience by suggesting appropriate products and services that respond to the user's emotions.

[0419] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0420] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, and means for analyzing the user's emotions and suggesting products or services based on a specific state. This makes it possible to increase opportunities for user health promotion and social interaction, and to provide products and services that correspond to specific emotional states in real time.

[0421] "User information" refers to individual data collected by the system for each user, including information about their health status, lifestyle, and emotional state.

[0422] A "health profile" is a comprehensive collection of data about a user's health status and lifestyle, generated based on their individual information.

[0423] "Health advice" refers to specific guidance and suggestions generated based on the user's health profile to help promote and maintain their health.

[0424] "Means of forming communities" refers to a function that facilitates cooperation and interaction between users based on their interests and location.

[0425] "Methods for analyzing emotions" refer to technologies that use user emotional data to determine and analyze their emotional state.

[0426] "Means of suggesting products or services" refers to a function that presents appropriate products or services based on the results of user sentiment analysis.

[0427] "Activity monitoring systems" are systems that observe various activities performed by users and notify them of warnings if any abnormalities are detected.

[0428] This system configuration is designed to support user health promotion and social interaction. The server receives user information and generates an individual health profile. Based on the health profile, appropriate health advice is automatically generated and notified from the server to the terminal. The emotion engine analyzes the user's emotional data and determines their state in real time. Specifically, it performs emotion analysis based on data registered by the user using the terminal and makes suggestions for specific products and services.

[0429] In this system, wearable devices such as smart glasses function as terminals to monitor user activity. If an anomaly is detected, a confirmation message is immediately sent from the server to notify the user. Furthermore, users are matched with other users based on their interests and current location, forming a community.

[0430] For example, if a user visits a store and is wearing smart glasses, the glasses' cameras and sensors detect the user's emotional state and physical condition in real time, and appropriate products or events are suggested. Based on the generated emotional data, the generative AI model outputs prompt sentences related to specific emotions and provides the user with a corresponding experience.

[0431] An example of a prompt message is: "Jane's smart glasses analyzed her smile. The emotion engine determined that her emotional state was stable, and displayed information about a healthy salad sale." In this way, the system operates by integrating various functions that improve the user experience.

[0432] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0433] Step 1:

[0434] The server receives user information and generates individual health profiles. The input consists of data collected from the user regarding their health status, lifestyle, and emotional state, which is used to create the health profile. A database management system is used to integrate different data and calculate metrics related to the user's health.

[0435] Step 2:

[0436] The server generates health advice based on the health profile and sends it to the terminal. The input is health profile data; a generation AI model is used to perform trend analysis and edit appropriate health advice. As output, specific health management suggestions are generated and notified to the terminal.

[0437] Step 3:

[0438] The user inputs emotional data using a device. This input is feedback indicating the user's emotional state and is collected via sensors in smart glasses, etc. An emotional analysis algorithm analyzes this data and generates an output to determine the user's emotional state.

[0439] Step 4:

[0440] The server analyzes the user's emotional data and suggests products or services based on their specific state. The input is the analysis results from step 3, and it utilizes an AI-based inference engine to select highly relevant products or events in real time. As output, specific suggestions are generated and displayed on the terminal.

[0441] Step 5:

[0442] The device notifies the user of suggested products or services and encourages purchase or participation. Input is the suggested content received from the server, and output includes the presentation of suggestions to the user and tracking information of their response. Voice guidance and visual displays are used to guide the user's actions.

[0443] Step 6:

[0444] Users decide to participate in or purchase products or services they are interested in. In this step, user feedback is recorded as new input for re-analysis in the next step. The user's selected actions are collected in a database, contributing to improving the accuracy of future recommendations.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] [Third Embodiment]

[0449] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0450] 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.

[0451] 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).

[0452] 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.

[0453] 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.

[0454] 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).

[0455] 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.

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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".

[0461] This invention describes an embodiment of a system aimed at promoting health and community building for the elderly. This system collects and analyzes user health data, provides personalized health advice, and fosters social connections. The system's program and processing overview are described below.

[0462] System Configuration

[0463] 1. Server Role

[0464] The server generates individual health profiles based on information provided by users and creates health advice based on these profiles. Furthermore, it matches users with other users based on their interests and activity levels, forming communities. It also uses data analyzed by a generative AI model to provide guides on preventive medicine and information on online medical consultations.

[0465] 2. The role of the terminal

[0466] The device displays health advice and community participation information sent from the server to the user. Through the device, users can update their health status and activity logs at any time and receive wellness messages.

[0467] 3. User Interaction

[0468] Users first install the app on their device and register their personal information, health status, and lifestyle habits. This allows them to receive health advice and exercise programs generated by the system, enabling them to manage their daily health accordingly. Furthermore, users can participate in community activities presented through matching, fostering interaction with other participants.

[0469] Specific example

[0470] Case 1: User B (68 years old, female) wants to improve her chronic lack of exercise:

[0471] Based on the information registered by user B, the server creates a program that combines light aerobic exercise and strength training. The terminal displays information about walking events that encourage participation, and users are naturally integrated into the community simply by registering.

[0472] Case 2: User C (72 years old, male) wants to learn about preventive medicine using online medical consultations:

[0473] The server uses AI generation to provide online medical information tailored to user C. Users can also select a service from the list of medical institutions displayed on their terminal and make a reservation directly.

[0474] In this way, the system addresses individual health needs, helps promote the health and maintain social relationships of the elderly, and contributes to the creation of new consumer activities.

[0475] The following describes the processing flow.

[0476] Step 1:

[0477] The user enters personal information into the application using their device. This includes age, gender, health status, exercise habits, and dietary preferences. The device then sends this information to the server.

[0478] Step 2:

[0479] The server receives information sent by the user and creates an individual health profile. This profile serves as the basis for analyzing the user's health status according to their characteristics.

[0480] Step 3:

[0481] The server uses an AI model to generate health advice based on the user's health profile. This advice includes recommended exercise plans and dietary suggestions.

[0482] Step 4:

[0483] The server generates health advice and sends it to the device. The device receives it and displays the advice to the user.

[0484] Step 5:

[0485] The user checks the display on the device and incorporates the recommended health plan into their daily life. The device periodically records the user's activity and sends feedback to the server.

[0486] Step 6:

[0487] The server matches users with other users based on their interests, location, and activity time. This ensures that users with common interests are connected.

[0488] Step 7:

[0489] The server sends the matching results to the device, and the device notifies the user of community events and group information that they can participate in.

[0490] Step 8:

[0491] Users participate in community activities and interact with other users. The server monitors these activities and periodically collects activity data.

[0492] Step 9:

[0493] If an abnormal activity pattern is detected, the server sends a confirmation message to the terminal, prompting the user to follow up.

[0494] Step 10:

[0495] The server collaborates with third-party companies to analyze collected data and provide health-related services. The terminal displays service information from partner companies to the user, encouraging their use.

[0496] (Example 1)

[0497] 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."

[0498] In systems aimed at promoting health and community building for the elderly, there is a lack of technological means to analyze individual health conditions in real time, provide appropriate health advice, and facilitate social interaction. In particular, there is a need for immediate feedback tailored to the user's health status and efficient provision of information on preventive medicine.

[0499] 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.

[0500] In this invention, the server includes means for generating a health profile based on individual health information received from a user, means for creating health advice using a generated AI model based on the health profile, and means for receiving feedback from the user and continuously updating the health profile. This enables the provision of individual health advice to the user and immediate reflection of the user's health status through continuous feedback.

[0501] "Health information" refers to data related to the user's physical condition, lifestyle, and past medical records.

[0502] A "health profile" refers to a dataset generated from health information collected from users to evaluate their individual health status.

[0503] A "generative AI model" refers to an algorithm that uses artificial intelligence technology to perform data analysis and prediction, and is used to create health advice.

[0504] "Health advice" refers to specific guidance aimed at maintaining or improving health, created based on the user's health profile.

[0505] "Communication equipment" refers to devices used to send and receive information via the internet or other digital means.

[0506] "Matching" refers to pairing users with other users based on their interests and activity times, taking into account mutual compatibility.

[0507] A "community" refers to a group of users who share common interests or activities and interact with each other and exchange information.

[0508] "Activity history" refers to past data records related to exercise and health management activities performed by the user.

[0509] "Abnormal" refers to a condition that deviates from normal health activities and may pose a risk to the user.

[0510] The "preventive field" refers to the medical field that aims to prevent the onset of disease through activities and information provision.

[0511] This system is designed for the elderly and aims to promote health and community building. It collects and analyzes users' health information and provides personalized health advice based on that information. It also has functions to support the building of social networks.

[0512] The server receives health information transmitted by the user through their device. This information includes physical condition, lifestyle, and medical history. Based on this, the server generates a health profile using a generative AI model. The generative AI model is an algorithm with data analysis and predictive capabilities that creates specific health advice tailored to the user's condition. This advice is provided, for example, as an exercise plan or dietary guidance.

[0513] The server also matches users with other users based on their interests and activity times, promoting community participation. Within this community, users can share health-related knowledge and engage in collaborative activities, strengthening their social connections.

[0514] The device displays information sent from the server to the user. Health advice and community event information are displayed on the device, and the user can check this at any time. Based on the advice, the user practices daily health management and sends feedback to the server via the device. Based on this feedback, the server updates the health profile and provides further advice.

[0515] For example, if a user wants to improve chronic lack of exercise, the generative AI model will create a mild aerobic exercise plan tailored to the user. For instance, by entering a prompt such as, "A 68-year-old woman is seeking health advice. Please generate a program to address mild lack of exercise," the server will suggest a suitable plan. Similarly, if the user is interested in preventive medicine, they can use a prompt such as, "A 72-year-old man is seeking online medical information regarding preventive medicine. Please provide a list of the best medical institutions," and the system will provide relevant information.

[0516] With the system configuration described above, users can receive information and support tailored to their individual health needs, thereby promoting the health and maintaining social relationships of the elderly.

[0517] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0518] Step 1:

[0519] The user installs and launches a dedicated application on their device. Next, the user enters personal information, health status, and lifestyle data. This data includes the user's age, gender, weight, medical history, and daily exercise habits. The device packages this information and sends it to the server.

[0520] Step 2:

[0521] The server receives health information from the terminal and stores it within the system. A generative AI model is used to analyze this data and generate a health profile for each user. Data processing includes algorithmic analysis based on the input volume. Specifically, health indicators are calculated and areas for improvement are identified. The output is a profile that quantifies the user's health status.

[0522] Step 3:

[0523] The server uses a generative AI model to create optimal health advice based on the generated health profile. The model generates advice based on prompts such as, "Suggest the best exercise program for the user." This process considers the user's past data and current health information. The output is specific health advice provided to the user.

[0524] Step 4:

[0525] The server sends health advice to the user's device. The device receives this information and displays it in a format that the user can review. The device's role is to attract the user's attention when health advice is notified, using methods such as audio or pop-up notifications. The advice is displayed to the user in text or visual format.

[0526] Step 5:

[0527] Users review health advice provided via their device and manage their health accordingly. This includes implementing suggested exercise programs and reviewing their eating habits. Users can input their results as feedback on the device. This feedback is sent to the server and used to update their health profile in the future.

[0528] Step 6:

[0529] The server receives feedback from the user and uses a generative AI model to re-adjust the health profile. This process involves analysis based on new data, updating the profile. As a result, more refined health advice is generated and provided to the user. This allows the system to continuously and dynamically support individual health management.

[0530] (Application Example 1)

[0531] 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."

[0532] There is a need to effectively manage the health status of the elderly, provide appropriate advice based on health information, and offer means to promote social connections through emergency safety checks and community building. Furthermore, the challenge is to realize a safe and secure living environment through a system that combines these functions.

[0533] 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.

[0534] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, means for monitoring user activity and sending confirmation messages if abnormalities are detected, means for generating safety confirmation information in emergencies and notifying designated contacts, and means for providing advice using an AI model generated based on the user's health data. This enables real-time management of the user's health status and the provision of services tailored to individual needs.

[0535] "User information" refers to basic personal data about the user, such as their health status, hobbies, and preferences.

[0536] A "health profile" is a dataset that represents an individual's health status and characteristics, generated based on collected user information.

[0537] "Health advice" refers to guidelines and recommended actions for maintaining or improving health, provided based on the user's health profile.

[0538] "Activity" refers to all forms of exercise, behavior, and activity that users engage in in their daily lives.

[0539] A "confirmation message" is a means of communication sent to a user for notification or confirmation, and is particularly used in the event of an abnormal situation.

[0540] A "generative AI model" is an artificial intelligence technology used to analyze a user's health data and provide personalized advice and suggestions.

[0541] A "community" is a place or group of people that connects users with common interests or concerns, fostering social interaction.

[0542] "Means for generating safety confirmation information in emergencies" refers to a mechanism that creates information for safety confirmation when the user's condition changes and promptly notifies relevant parties.

[0543] The system that realizes this application is a health promotion platform for the elderly. It consists of a server, terminals, and user interaction.

[0544] The server receives user information and uses that data to generate individual health profiles. Based on the generated health profiles, it uses an AI model to create health advice and sends it to the user's device. The server uses Python's Scikit-learn, TensorFlow, GPT-3, etc., for data analysis and AI model operation. Furthermore, it has a function to match users with other users based on their interests and location, supporting community building. If an anomaly is detected, it sends a confirmation message and takes emergency action as needed.

[0545] The device consists of smartphones and smartwatches, and displays health advice and community participation information received from the server to the user. Users can update their health status and activities via the device and manage their daily health accordingly. The device monitors the user's activities and, in emergencies, collaborates with the server to generate safety confirmation information.

[0546] Users begin by registering their personal information and lifestyle habits with the system using the app. They then receive generated health advice and can get quick support in case of abnormalities. For example, if a user's heart rate is higher than normal, the AI ​​model can immediately generate a suggestion to take deep breaths and send an alert to emergency contacts.

[0547] An example of a prompt message is: "User A's heart rate has reached 110 beats per minute, which is extremely high compared to the normal 70. Please create advice for immediate action." In this way, the platform comprehensively manages the user's health and safety, providing an environment where they can live with peace of mind.

[0548] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0549] Step 1:

[0550] Users input personal information, health status, and lifestyle habits via their device. The device then collects this information and generates data packets to send to the server. Input includes registering information using the smartphone's touchscreen. Output is the transmission of user information to the server.

[0551] Step 2:

[0552] The server generates a health profile based on the received user information. The server's data analysis module comprehensively analyzes the user's health data using statistical analysis and machine learning. Data organization and profile generation are performed using Python's Scikit-learn and Pandas libraries. The output is a personalized health profile.

[0553] Step 3:

[0554] The server utilizes the generated health profile and uses a generative AI model to create health advice tailored to the user. In this process, the profile data is used as input, and the generative AI model predicts specific health advice. The output includes a generated prompt and the specific text in which the generative AI model provides advice.

[0555] Step 4:

[0556] The server generates community matching information for users based on their location and interests, along with health advice. Input includes user interest data and geographical information, and the server runs a data matching algorithm. Output includes community invitations and event information.

[0557] Step 5:

[0558] The server generates health advice and matching information, which is then sent to the terminal. The terminal receives this information and displays a notification to the user. The input is data packets from the server, and the output is the notification displayed on the terminal screen.

[0559] Step 6:

[0560] The user follows the advice and records their daily health status on the device. This causes the device to generate update data packets to send new health data to the server. The input is the user's new health data, and the output is the update information sent to the server.

[0561] Step 7:

[0562] When the server detects an anomaly, it generates a confirmation message and sends a notification to the relevant contact. Inputs are real-time user data and warnings from the anomaly detection algorithm. Outputs are warning messages regarding the anomaly. This enables rapid safety confirmation.

[0563] 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.

[0564] This invention describes an embodiment of a health promotion and community-building system for the elderly that combines an emotional engine. This system analyzes user information, health data, and emotional data to provide users with optimal health advice while promoting participation in diverse social activities. The system's program and its processing overview are outlined below.

[0565] System Configuration

[0566] 1. Server Role

[0567] The server generates individual health profiles based on information from the user. It also analyzes the user's emotional state using an emotion engine and adjusts health advice accordingly. By combining the health profile and emotional information, the server provides users with advice and suggests appropriate ways to participate in community activities.

[0568] 2. The role of the terminal

[0569] The device displays health advice and emotionally-based plan adjustments sent from the server to the user. Through the device, users can input their daily health status and emotional changes, receiving timely advice and suggestions.

[0570] 3. User Interaction

[0571] Users register information about their health, lifestyle, and emotions using their devices. The system detects changes in the user's emotions and adjusts health advice in real time. It also facilitates effective social interaction by recommending events and community activities that match the user's emotional state.

[0572] Specific example

[0573] Case 1: When User D (70 years old, female) is experiencing emotional distress:

[0574] The server analyzes user D's emotions using an emotion engine and recommends a yoga plan that promotes relaxation. The terminal displays information about online yoga events that contribute to emotional improvement, encouraging easy participation.

[0575] Case 2: When User E (75 years old, male) is experiencing increased anxiety:

[0576] The server recommends deep breathing exercises to reduce anxiety and notifies users via their devices. Furthermore, it recommends group chat sessions that contribute to emotional stability, allowing users to receive support from other participants.

[0577] In this way, this system takes into account the user's emotional state and provides more personalized health management and social interaction opportunities, thereby improving the quality of life (QOL) of the elderly.

[0578] The following describes the processing flow.

[0579] Step 1:

[0580] Users input information about their health, lifestyle, and emotions into their device. They record daily changes in their mood and emotions through a simple questionnaire.

[0581] Step 2:

[0582] The device sends the user's input information to the server. The transmitted data includes health information and emotional state.

[0583] Step 3:

[0584] The server analyzes the user information it receives and generates individual health profiles. It uses a generative AI model and an emotion engine to comprehensively evaluate health and emotional states.

[0585] Step 4:

[0586] The server utilizes an emotion engine to analyze the user's emotional state. Specifically, it captures changes in emotions and evaluates how they affect the user's health profile.

[0587] Step 5:

[0588] The server generates optimal health advice for the user based on the emotion analysis results. For example, if stress levels are high, it will recommend activities that are effective for relaxation.

[0589] Step 6:

[0590] The device receives health advice from the server and notifies the user. This advice is customized to take into account the user's emotional state.

[0591] Step 7:

[0592] The user incorporates the provided health advice into their daily life and records their activity levels again on the device. The device continuously transmits this activity data to the server.

[0593] Step 8:

[0594] The server continuously monitors the user's emotional state and activity data, and if an abnormal pattern is detected, it sends a confirmation message to the terminal.

[0595] Step 9:

[0596] The server takes into account the user's emotions and health status to suggest appropriate community activities and events. The terminal displays this information to the user and encourages participation.

[0597] Step 10:

[0598] Users participate in recommended community events and interact with other attendees. The server then re-evaluates the emotional changes resulting from these events and incorporates them into future advice.

[0599] (Example 2)

[0600] 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."

[0601] Maintaining and improving the health of users, including the elderly, requires personalized health guidance and flexible responses to changes in their emotional state. However, current health management systems are generally templated and lack sufficient personalization to address the emotions and social needs of individual users. To solve this problem, a system is needed that can analyze the user's condition in real time and provide appropriate health guidance and suggestions for social activities based on that analysis.

[0602] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0603] In this invention, the server includes means for receiving user information and generating individual health plans, means for analyzing emotional information and adjusting health guidance, and means for suggesting social activities with other users and notifying the user of the suggested activities. This makes it possible to provide users with personalized and situation-appropriate health guidance and opportunities for social interaction.

[0604] "User information" refers to basic personal data provided by system users, as well as information regarding their health status, lifestyle, emotional state, etc.

[0605] A "health plan" is a specific plan or goal set based on a user's individual health data, with the aim of maintaining or improving their health.

[0606] "Health guidance" refers to advice and recommended actions provided based on the user's health status and emotional analysis results.

[0607] "Emotional information" refers to data about emotions that is entered by the user or collected by the system, and it represents the user's emotional state.

[0608] "Social activities" refer to community events and gatherings that users participate in through interaction with other users.

[0609] "Feedback" refers to the opinions and evaluations that users provide regarding the guidance and suggestions offered by the system, and these are used to improve future guidance.

[0610] This invention is a system that analyzes a user's health status and emotional information to provide personalized health guidance and suggestions for social activities. This system consists of three main elements: a server, a terminal, and a user.

[0611] The server generates individualized health plans based on information received from users. This plan utilizes diverse data, including the user's basic information, lifestyle, and health status. Emotional information is analyzed using a generative AI model to adjust health guidance according to the user's emotional state. This analysis utilizes natural language processing software and a cloud-based AI platform.

[0612] The terminal serves to notify the user of health guidance and suggestions for social activities transmitted from the server. The terminal provides a visual interface using hardware such as a smartphone, tablet, or personal computer. This allows the user to receive guidance tailored to their daily health status and emotional changes.

[0613] Users input their health status and emotional information through their device and view the resulting health guidance. The system collects user feedback and uses it to improve the quality of future guidance. For example, if a user inputs "I've been feeling stressed lately," the system can suggest relaxation plans and opportunities for social interaction to reduce stress.

[0614] An example of a prompt might be, "We would like to offer health guidance and interaction suggestions based on emotion analysis for elderly individuals." Based on this prompt, the generating AI model provides the user with the most suitable health management and interaction methods.

[0615] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0616] Step 1:

[0617] The user uses a device to input data about their health status, lifestyle, and emotional state. This data is used as basic information to create the user's health plan. The entered information is sent from the device to the server to prepare for the next processing step.

[0618] Step 2:

[0619] The server analyzes the received user information and generates an individualized health plan. In this process, the server uses a generation AI model to analyze the user's health data and identify the health plan best suited to the user's needs. Specifically, it sets health goals considering past health history and current condition, and incorporates these into the plan. The output is a customized health plan for each user.

[0620] Step 3:

[0621] The server generates health guidance based on the health plan and further adjusts it to match the user's current emotional state by analyzing emotional information. The server specifically analyzes emotional data using natural language processing techniques to understand stress levels and emotional tendencies. This results in the generation and output of more effective and personalized guidance.

[0622] Step 4:

[0623] Health guidance and social activity suggestions generated from the server are sent to the device. The device displays the guidance content in an easy-to-understand format for the user and provides it in a way that allows for real-time action. Specifically, the device can notify the user of the date and time through push notifications and automatic addition to the calendar.

[0624] Step 5:

[0625] Users conduct instruction and input the results and feedback via their terminals. This feedback includes the effectiveness of the instruction and areas for improvement for future sessions. This information is then sent back to the server, contributing to the overall improvement of instruction quality within the system.

[0626] Step 6:

[0627] The server analyzes feedback data collected from users and incorporates it into future health guidance and suggestions. Using a generative AI model, feedback is analyzed to reconstruct more suitable guidance and social interaction opportunities for the user. This step allows the system to continuously improve and provide better services to users.

[0628] (Application Example 2)

[0629] 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."

[0630] To simultaneously promote health management and social interaction among the elderly, thereby reducing isolation and health anxieties associated with these changes. Furthermore, to provide a comfortable, real-time in-store experience by suggesting appropriate products and services that respond to the user's emotions.

[0631] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0632] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, and means for analyzing the user's emotions and suggesting products or services based on a specific state. This makes it possible to increase opportunities for user health promotion and social interaction, and to provide products and services that correspond to specific emotional states in real time.

[0633] "User information" refers to individual data collected by the system for each user, including information about their health status, lifestyle, and emotional state.

[0634] A "health profile" is a comprehensive collection of data about a user's health status and lifestyle, generated based on their individual information.

[0635] "Health advice" refers to specific guidance and suggestions generated based on the user's health profile to help promote and maintain their health.

[0636] "Means of forming communities" refers to a function that facilitates cooperation and interaction between users based on their interests and location.

[0637] "Methods for analyzing emotions" refer to technologies that use user emotional data to determine and analyze their emotional state.

[0638] "Means of suggesting products or services" refers to a function that presents appropriate products or services based on the results of user sentiment analysis.

[0639] "Activity monitoring systems" are systems that observe various activities performed by users and notify them of warnings if any abnormalities are detected.

[0640] This system configuration is designed to support user health promotion and social interaction. The server receives user information and generates an individual health profile. Based on the health profile, appropriate health advice is automatically generated and notified from the server to the terminal. The emotion engine analyzes the user's emotional data and determines their state in real time. Specifically, it performs emotion analysis based on data registered by the user using the terminal and makes suggestions for specific products and services.

[0641] In this system, wearable devices such as smart glasses function as terminals to monitor user activity. If an anomaly is detected, a confirmation message is immediately sent from the server to notify the user. Furthermore, users are matched with other users based on their interests and current location, forming a community.

[0642] For example, if a user visits a store and is wearing smart glasses, the glasses' cameras and sensors detect the user's emotional state and physical condition in real time, and appropriate products or events are suggested. Based on the generated emotional data, the generative AI model outputs prompt sentences related to specific emotions and provides the user with a corresponding experience.

[0643] An example of a prompt message is: "Jane's smart glasses analyzed her smile. The emotion engine determined that her emotional state was stable, and displayed information about a healthy salad sale." In this way, the system operates by integrating various functions that improve the user experience.

[0644] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0645] Step 1:

[0646] The server receives user information and generates individual health profiles. The input consists of data collected from the user regarding their health status, lifestyle, and emotional state, which is used to create the health profile. A database management system is used to integrate different data and calculate metrics related to the user's health.

[0647] Step 2:

[0648] The server generates health advice based on the health profile and sends it to the terminal. The input is health profile data; a generation AI model is used to perform trend analysis and edit appropriate health advice. As output, specific health management suggestions are generated and notified to the terminal.

[0649] Step 3:

[0650] The user inputs emotional data using a device. This input is feedback indicating the user's emotional state and is collected via sensors in smart glasses, etc. An emotional analysis algorithm analyzes this data and generates an output to determine the user's emotional state.

[0651] Step 4:

[0652] The server analyzes the user's emotional data and suggests products or services based on their specific state. The input is the analysis results from step 3, and it utilizes an AI-based inference engine to select highly relevant products or events in real time. As output, specific suggestions are generated and displayed on the terminal.

[0653] Step 5:

[0654] The device notifies the user of suggested products or services and encourages purchase or participation. Input is the suggested content received from the server, and output includes the presentation of suggestions to the user and tracking information of their response. Voice guidance and visual displays are used to guide the user's actions.

[0655] Step 6:

[0656] Users decide to participate in or purchase products or services they are interested in. In this step, user feedback is recorded as new input for re-analysis in the next step. The user's selected actions are collected in a database, contributing to improving the accuracy of future recommendations.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] [Fourth Embodiment]

[0661] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0662] 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.

[0663] 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).

[0664] 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.

[0665] 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.

[0666] 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).

[0667] 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.

[0668] 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.

[0669] 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.

[0670] 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.

[0671] 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.

[0672] 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.

[0673] 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".

[0674] This invention describes an embodiment of a system aimed at promoting health and community building for the elderly. This system collects and analyzes user health data, provides personalized health advice, and fosters social connections. The system's program and processing overview are described below.

[0675] System Configuration

[0676] 1. Server Role

[0677] The server generates individual health profiles based on information provided by users and creates health advice based on these profiles. Furthermore, it matches users with other users based on their interests and activity levels, forming communities. It also uses data analyzed by a generative AI model to provide guides on preventive medicine and information on online medical consultations.

[0678] 2. The role of the terminal

[0679] The device displays health advice and community participation information sent from the server to the user. Through the device, users can update their health status and activity logs at any time and receive wellness messages.

[0680] 3. User Interaction

[0681] Users first install the app on their device and register their personal information, health status, and lifestyle habits. This allows them to receive health advice and exercise programs generated by the system, enabling them to manage their daily health accordingly. Furthermore, users can participate in community activities presented through matching, fostering interaction with other participants.

[0682] Specific example

[0683] Case 1: User B (68 years old, female) wants to improve her chronic lack of exercise:

[0684] Based on the information registered by user B, the server creates a program that combines light aerobic exercise and strength training. The terminal displays information about walking events that encourage participation, and users are naturally integrated into the community simply by registering.

[0685] Case 2: User C (72 years old, male) wants to learn about preventive medicine using online medical consultations:

[0686] The server uses AI generation to provide online medical information tailored to user C. Users can also select a service from the list of medical institutions displayed on their terminal and make a reservation directly.

[0687] In this way, the system addresses individual health needs, helps promote the health and maintain social relationships of the elderly, and contributes to the creation of new consumer activities.

[0688] The following describes the processing flow.

[0689] Step 1:

[0690] The user enters personal information into the application using their device. This includes age, gender, health status, exercise habits, and dietary preferences. The device then sends this information to the server.

[0691] Step 2:

[0692] The server receives information sent by the user and creates an individual health profile. This profile serves as the basis for analyzing the user's health status according to their characteristics.

[0693] Step 3:

[0694] The server uses an AI model to generate health advice based on the user's health profile. This advice includes recommended exercise plans and dietary suggestions.

[0695] Step 4:

[0696] The server generates health advice and sends it to the device. The device receives it and displays the advice to the user.

[0697] Step 5:

[0698] The user checks the display on the device and incorporates the recommended health plan into their daily life. The device periodically records the user's activity and sends feedback to the server.

[0699] Step 6:

[0700] The server matches users with other users based on their interests, location, and activity time. This ensures that users with common interests are connected.

[0701] Step 7:

[0702] The server sends the matching results to the device, and the device notifies the user of community events and group information that they can participate in.

[0703] Step 8:

[0704] Users participate in community activities and interact with other users. The server monitors these activities and periodically collects activity data.

[0705] Step 9:

[0706] If an abnormal activity pattern is detected, the server sends a confirmation message to the terminal, prompting the user to follow up.

[0707] Step 10:

[0708] The server collaborates with third-party companies to analyze collected data and provide health-related services. The terminal displays service information from partner companies to the user, encouraging their use.

[0709] (Example 1)

[0710] 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".

[0711] In systems aimed at promoting health and community building for the elderly, there is a lack of technological means to analyze individual health conditions in real time, provide appropriate health advice, and facilitate social interaction. In particular, there is a need for immediate feedback tailored to the user's health status and efficient provision of information on preventive medicine.

[0712] 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.

[0713] In this invention, the server includes means for generating a health profile based on individual health information received from a user, means for creating health advice using a generated AI model based on the health profile, and means for receiving feedback from the user and continuously updating the health profile. This enables the provision of individual health advice to the user and immediate reflection of the user's health status through continuous feedback.

[0714] "Health information" refers to data related to the user's physical condition, lifestyle, and past medical records.

[0715] A "health profile" refers to a dataset generated from health information collected from users to evaluate their individual health status.

[0716] A "generative AI model" refers to an algorithm that uses artificial intelligence technology to perform data analysis and prediction, and is used to create health advice.

[0717] "Health advice" refers to specific guidance aimed at maintaining or improving health, created based on the user's health profile.

[0718] "Communication equipment" refers to devices used to send and receive information via the internet or other digital means.

[0719] "Matching" refers to pairing users with other users based on their interests and activity times, taking into account mutual compatibility.

[0720] A "community" refers to a group of users who share common interests or activities and interact with each other and exchange information.

[0721] "Activity history" refers to past data records related to exercise and health management activities performed by the user.

[0722] "Abnormal" refers to a condition that deviates from normal health activities and may pose a risk to the user.

[0723] The "preventive field" refers to the medical field that aims to prevent the onset of disease through activities and information provision.

[0724] This system is designed for the elderly and aims to promote health and community building. It collects and analyzes users' health information and provides personalized health advice based on that information. It also has functions to support the building of social networks.

[0725] The server receives health information transmitted by the user through their device. This information includes physical condition, lifestyle, and medical history. Based on this, the server generates a health profile using a generative AI model. The generative AI model is an algorithm with data analysis and predictive capabilities that creates specific health advice tailored to the user's condition. This advice is provided, for example, as an exercise plan or dietary guidance.

[0726] The server also matches users with other users based on their interests and activity times, promoting community participation. Within this community, users can share health-related knowledge and engage in collaborative activities, strengthening their social connections.

[0727] The device displays information sent from the server to the user. Health advice and community event information are displayed on the device, and the user can check this at any time. Based on the advice, the user practices daily health management and sends feedback to the server via the device. Based on this feedback, the server updates the health profile and provides further advice.

[0728] For example, if a user wants to improve chronic lack of exercise, the generative AI model will create a mild aerobic exercise plan tailored to the user. For instance, by entering a prompt such as, "A 68-year-old woman is seeking health advice. Please generate a program to address mild lack of exercise," the server will suggest a suitable plan. Similarly, if the user is interested in preventive medicine, they can use a prompt such as, "A 72-year-old man is seeking online medical information regarding preventive medicine. Please provide a list of the best medical institutions," and the system will provide relevant information.

[0729] With the system configuration described above, users can receive information and support tailored to their individual health needs, thereby promoting the health and maintaining social relationships of the elderly.

[0730] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0731] Step 1:

[0732] The user installs and launches a dedicated application on their device. Next, the user enters personal information, health status, and lifestyle data. This data includes the user's age, gender, weight, medical history, and daily exercise habits. The device packages this information and sends it to the server.

[0733] Step 2:

[0734] The server receives health information from the terminal and stores it within the system. A generative AI model is used to analyze this data and generate a health profile for each user. Data processing includes algorithmic analysis based on the input volume. Specifically, health indicators are calculated and areas for improvement are identified. The output is a profile that quantifies the user's health status.

[0735] Step 3:

[0736] The server uses a generative AI model to create optimal health advice based on the generated health profile. The model generates advice based on prompts such as, "Suggest the best exercise program for the user." This process considers the user's past data and current health information. The output is specific health advice provided to the user.

[0737] Step 4:

[0738] The server sends health advice to the user's device. The device receives this information and displays it in a format that the user can review. The device's role is to attract the user's attention when health advice is notified, using methods such as audio or pop-up notifications. The advice is displayed to the user in text or visual format.

[0739] Step 5:

[0740] Users review health advice provided via their device and manage their health accordingly. This includes implementing suggested exercise programs and reviewing their eating habits. Users can input their results as feedback on the device. This feedback is sent to the server and used to update their health profile in the future.

[0741] Step 6:

[0742] The server receives feedback from the user and uses a generative AI model to re-adjust the health profile. This process involves analysis based on new data, updating the profile. As a result, more refined health advice is generated and provided to the user. This allows the system to continuously and dynamically support individual health management.

[0743] (Application Example 1)

[0744] 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".

[0745] There is a need to effectively manage the health status of the elderly, provide appropriate advice based on health information, and offer means to promote social connections through emergency safety checks and community building. Furthermore, the challenge is to realize a safe and secure living environment through a system that combines these functions.

[0746] 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.

[0747] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, means for monitoring user activity and sending confirmation messages if abnormalities are detected, means for generating safety confirmation information in emergencies and notifying designated contacts, and means for providing advice using an AI model generated based on the user's health data. This enables real-time management of the user's health status and the provision of services tailored to individual needs.

[0748] "User information" refers to basic personal data about the user, such as their health status, hobbies, and preferences.

[0749] A "health profile" is a dataset that represents an individual's health status and characteristics, generated based on collected user information.

[0750] "Health advice" refers to guidelines and recommended actions for maintaining or improving health, provided based on the user's health profile.

[0751] "Activity" refers to all forms of exercise, behavior, and activity that users engage in in their daily lives.

[0752] A "confirmation message" is a means of communication sent to a user for notification or confirmation, and is particularly used in the event of an abnormal situation.

[0753] A "generative AI model" is an artificial intelligence technology used to analyze a user's health data and provide personalized advice and suggestions.

[0754] A "community" is a place or group of people that connects users with common interests or concerns, fostering social interaction.

[0755] "Means for generating safety confirmation information in emergencies" refers to a mechanism that creates information for safety confirmation when the user's condition changes and promptly notifies relevant parties.

[0756] The system that realizes this application is a health promotion platform for the elderly. It consists of a server, terminals, and user interaction.

[0757] The server receives user information and uses that data to generate individual health profiles. Based on the generated health profiles, it uses an AI model to create health advice and sends it to the user's device. The server uses Python's Scikit-learn, TensorFlow, GPT-3, etc., for data analysis and AI model operation. Furthermore, it has a function to match users with other users based on their interests and location, supporting community building. If an anomaly is detected, it sends a confirmation message and takes emergency action as needed.

[0758] The device consists of smartphones and smartwatches, and displays health advice and community participation information received from the server to the user. Users can update their health status and activities via the device and manage their daily health accordingly. The device monitors the user's activities and, in emergencies, collaborates with the server to generate safety confirmation information.

[0759] Users begin by registering their personal information and lifestyle habits with the system using the app. They then receive generated health advice and can get quick support in case of abnormalities. For example, if a user's heart rate is higher than normal, the AI ​​model can immediately generate a suggestion to take deep breaths and send an alert to emergency contacts.

[0760] An example of a prompt message is: "User A's heart rate has reached 110 beats per minute, which is extremely high compared to the normal 70. Please create advice for immediate action." In this way, the platform comprehensively manages the user's health and safety, providing an environment where they can live with peace of mind.

[0761] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0762] Step 1:

[0763] Users input personal information, health status, and lifestyle habits via their device. The device then collects this information and generates data packets to send to the server. Input includes registering information using the smartphone's touchscreen. Output is the transmission of user information to the server.

[0764] Step 2:

[0765] The server generates a health profile based on the received user information. The server's data analysis module comprehensively analyzes the user's health data using statistical analysis and machine learning. Data organization and profile generation are performed using Python's Scikit-learn and Pandas libraries. The output is a personalized health profile.

[0766] Step 3:

[0767] The server utilizes the generated health profile and uses a generative AI model to create health advice tailored to the user. In this process, the profile data is used as input, and the generative AI model predicts specific health advice. The output includes a generated prompt and the specific text in which the generative AI model provides advice.

[0768] Step 4:

[0769] The server generates community matching information for users based on their location and interests, along with health advice. Input includes user interest data and geographical information, and the server runs a data matching algorithm. Output includes community invitations and event information.

[0770] Step 5:

[0771] The server generates health advice and matching information, which is then sent to the terminal. The terminal receives this information and displays a notification to the user. The input is data packets from the server, and the output is the notification displayed on the terminal screen.

[0772] Step 6:

[0773] The user follows the advice and records their daily health status on the device. This causes the device to generate update data packets to send new health data to the server. The input is the user's new health data, and the output is the update information sent to the server.

[0774] Step 7:

[0775] When the server detects an anomaly, it generates a confirmation message and sends a notification to the relevant contact. Inputs are real-time user data and warnings from the anomaly detection algorithm. Outputs are warning messages regarding the anomaly. This enables rapid safety confirmation.

[0776] 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.

[0777] This invention describes an embodiment of a health promotion and community-building system for the elderly that combines an emotional engine. This system analyzes user information, health data, and emotional data to provide users with optimal health advice while promoting participation in diverse social activities. The system's program and its processing overview are outlined below.

[0778] System Configuration

[0779] 1. Server Role

[0780] The server generates individual health profiles based on information from the user. It also analyzes the user's emotional state using an emotion engine and adjusts health advice accordingly. By combining the health profile and emotional information, the server provides users with advice and suggests appropriate ways to participate in community activities.

[0781] 2. The role of the terminal

[0782] The device displays health advice and emotionally-based plan adjustments sent from the server to the user. Through the device, users can input their daily health status and emotional changes, receiving timely advice and suggestions.

[0783] 3. User Interaction

[0784] Users register information about their health, lifestyle, and emotions using their devices. The system detects changes in the user's emotions and adjusts health advice in real time. It also facilitates effective social interaction by recommending events and community activities that match the user's emotional state.

[0785] Specific example

[0786] Case 1: When User D (70 years old, female) is experiencing emotional distress:

[0787] The server analyzes user D's emotions using an emotion engine and recommends a yoga plan that promotes relaxation. The terminal displays information about online yoga events that contribute to emotional improvement, encouraging easy participation.

[0788] Case 2: When User E (75 years old, male) is experiencing increased anxiety:

[0789] The server recommends deep breathing exercises to reduce anxiety and notifies users via their devices. Furthermore, it recommends group chat sessions that contribute to emotional stability, allowing users to receive support from other participants.

[0790] In this way, this system takes into account the user's emotional state and provides more personalized health management and social interaction opportunities, thereby improving the quality of life (QOL) of the elderly.

[0791] The following describes the processing flow.

[0792] Step 1:

[0793] Users input information about their health, lifestyle, and emotions into their device. They record daily changes in their mood and emotions through a simple questionnaire.

[0794] Step 2:

[0795] The device sends the user's input information to the server. The transmitted data includes health information and emotional state.

[0796] Step 3:

[0797] The server analyzes the user information it receives and generates individual health profiles. It uses a generative AI model and an emotion engine to comprehensively evaluate health and emotional states.

[0798] Step 4:

[0799] The server utilizes an emotion engine to analyze the user's emotional state. Specifically, it captures changes in emotions and evaluates how they affect the user's health profile.

[0800] Step 5:

[0801] The server generates optimal health advice for the user based on the emotion analysis results. For example, if stress levels are high, it will recommend activities that are effective for relaxation.

[0802] Step 6:

[0803] The device receives health advice from the server and notifies the user. This advice is customized to take into account the user's emotional state.

[0804] Step 7:

[0805] The user incorporates the provided health advice into their daily life and records their activity levels again on the device. The device continuously transmits this activity data to the server.

[0806] Step 8:

[0807] The server continuously monitors the user's emotional state and activity data, and if an abnormal pattern is detected, it sends a confirmation message to the terminal.

[0808] Step 9:

[0809] The server takes into account the user's emotions and health status to suggest appropriate community activities and events. The terminal displays this information to the user and encourages participation.

[0810] Step 10:

[0811] Users participate in recommended community events and interact with other attendees. The server then re-evaluates the emotional changes resulting from these events and incorporates them into future advice.

[0812] (Example 2)

[0813] 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".

[0814] Maintaining and improving the health of users, including the elderly, requires personalized health guidance and flexible responses to changes in their emotional state. However, current health management systems are generally templated and lack sufficient personalization to address the emotions and social needs of individual users. To solve this problem, a system is needed that can analyze the user's condition in real time and provide appropriate health guidance and suggestions for social activities based on that analysis.

[0815] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0816] In this invention, the server includes means for receiving user information and generating individual health plans, means for analyzing emotional information and adjusting health guidance, and means for suggesting social activities with other users and notifying the user of the suggested activities. This makes it possible to provide users with personalized and situation-appropriate health guidance and opportunities for social interaction.

[0817] "User information" refers to basic personal data provided by system users, as well as information regarding their health status, lifestyle, emotional state, etc.

[0818] A "health plan" is a specific plan or goal set based on a user's individual health data, with the aim of maintaining or improving their health.

[0819] "Health guidance" refers to advice and recommended actions provided based on the user's health status and emotional analysis results.

[0820] "Emotional information" refers to data about emotions that is entered by the user or collected by the system, and it represents the user's emotional state.

[0821] "Social activities" refer to community events and gatherings that users participate in through interaction with other users.

[0822] "Feedback" refers to the opinions and evaluations that users provide regarding the guidance and suggestions offered by the system, and these are used to improve future guidance.

[0823] This invention is a system that analyzes a user's health status and emotional information to provide personalized health guidance and suggestions for social activities. This system consists of three main elements: a server, a terminal, and a user.

[0824] The server generates individualized health plans based on information received from users. This plan utilizes diverse data, including the user's basic information, lifestyle, and health status. Emotional information is analyzed using a generative AI model to adjust health guidance according to the user's emotional state. This analysis utilizes natural language processing software and a cloud-based AI platform.

[0825] The terminal serves to notify the user of health guidance and suggestions for social activities transmitted from the server. The terminal provides a visual interface using hardware such as a smartphone, tablet, or personal computer. This allows the user to receive guidance tailored to their daily health status and emotional changes.

[0826] Users input their health status and emotional information through their device and view the resulting health guidance. The system collects user feedback and uses it to improve the quality of future guidance. For example, if a user inputs "I've been feeling stressed lately," the system can suggest relaxation plans and opportunities for social interaction to reduce stress.

[0827] An example of a prompt might be, "We would like to offer health guidance and interaction suggestions based on emotion analysis for elderly individuals." Based on this prompt, the generating AI model provides the user with the most suitable health management and interaction methods.

[0828] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0829] Step 1:

[0830] The user uses a device to input data about their health status, lifestyle, and emotional state. This data is used as basic information to create the user's health plan. The entered information is sent from the device to the server to prepare for the next processing step.

[0831] Step 2:

[0832] The server analyzes the received user information and generates an individualized health plan. In this process, the server uses a generation AI model to analyze the user's health data and identify the health plan best suited to the user's needs. Specifically, it sets health goals considering past health history and current condition, and incorporates these into the plan. The output is a customized health plan for each user.

[0833] Step 3:

[0834] The server generates health guidance based on the health plan and further adjusts it to match the user's current emotional state by analyzing emotional information. The server specifically analyzes emotional data using natural language processing techniques to understand stress levels and emotional tendencies. This results in the generation and output of more effective and personalized guidance.

[0835] Step 4:

[0836] Health guidance and social activity suggestions generated from the server are sent to the device. The device displays the guidance content in an easy-to-understand format for the user and provides it in a way that allows for real-time action. Specifically, the device can notify the user of the date and time through push notifications and automatic addition to the calendar.

[0837] Step 5:

[0838] Users conduct instruction and input the results and feedback via their terminals. This feedback includes the effectiveness of the instruction and areas for improvement for future sessions. This information is then sent back to the server, contributing to the overall improvement of instruction quality within the system.

[0839] Step 6:

[0840] The server analyzes feedback data collected from users and incorporates it into future health guidance and suggestions. Using a generative AI model, feedback is analyzed to reconstruct more suitable guidance and social interaction opportunities for the user. This step allows the system to continuously improve and provide better services to users.

[0841] (Application Example 2)

[0842] 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".

[0843] To simultaneously promote health management and social interaction among the elderly, thereby reducing isolation and health anxieties associated with these changes. Furthermore, to provide a comfortable, real-time in-store experience by suggesting appropriate products and services that respond to the user's emotions.

[0844] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0845] In this invention, the server includes means for receiving user information and generating an individual health profile, means for generating health advice based on the health profile, and means for analyzing the user's emotions and suggesting products or services based on a specific state. This makes it possible to increase opportunities for user health promotion and social interaction, and to provide products and services that correspond to specific emotional states in real time.

[0846] "User information" refers to individual data collected by the system for each user, including information about their health status, lifestyle, and emotional state.

[0847] A "health profile" is a comprehensive collection of data about a user's health status and lifestyle, generated based on their individual information.

[0848] "Health advice" refers to specific guidance and suggestions generated based on the user's health profile to help promote and maintain their health.

[0849] "Means of forming communities" refers to a function that facilitates cooperation and interaction between users based on their interests and location.

[0850] "Methods for analyzing emotions" refer to technologies that use user emotional data to determine and analyze their emotional state.

[0851] "Means of suggesting products or services" refers to a function that presents appropriate products or services based on the results of user sentiment analysis.

[0852] "Activity monitoring systems" are systems that observe various activities performed by users and notify them of warnings if any abnormalities are detected.

[0853] This system configuration is designed to support user health promotion and social interaction. The server receives user information and generates an individual health profile. Based on the health profile, appropriate health advice is automatically generated and notified from the server to the terminal. The emotion engine analyzes the user's emotional data and determines their state in real time. Specifically, it performs emotion analysis based on data registered by the user using the terminal and makes suggestions for specific products and services.

[0854] In this system, wearable devices such as smart glasses function as terminals to monitor user activity. If an anomaly is detected, a confirmation message is immediately sent from the server to notify the user. Furthermore, users are matched with other users based on their interests and current location, forming a community.

[0855] For example, if a user visits a store and is wearing smart glasses, the glasses' cameras and sensors detect the user's emotional state and physical condition in real time, and appropriate products or events are suggested. Based on the generated emotional data, the generative AI model outputs prompt sentences related to specific emotions and provides the user with a corresponding experience.

[0856] An example of a prompt message is: "Jane's smart glasses analyzed her smile. The emotion engine determined that her emotional state was stable, and displayed information about a healthy salad sale." In this way, the system operates by integrating various functions that improve the user experience.

[0857] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0858] Step 1:

[0859] The server receives user information and generates individual health profiles. The input consists of data collected from the user regarding their health status, lifestyle, and emotional state, which is used to create the health profile. A database management system is used to integrate different data and calculate metrics related to the user's health.

[0860] Step 2:

[0861] The server generates health advice based on the health profile and sends it to the terminal. The input is health profile data; a generation AI model is used to perform trend analysis and edit appropriate health advice. As output, specific health management suggestions are generated and notified to the terminal.

[0862] Step 3:

[0863] The user inputs emotional data using a device. This input is feedback indicating the user's emotional state and is collected via sensors in smart glasses, etc. An emotional analysis algorithm analyzes this data and generates an output to determine the user's emotional state.

[0864] Step 4:

[0865] The server analyzes the user's emotional data and suggests products or services based on their specific state. The input is the analysis results from step 3, and it utilizes an AI-based inference engine to select highly relevant products or events in real time. As output, specific suggestions are generated and displayed on the terminal.

[0866] Step 5:

[0867] The device notifies the user of suggested products or services and encourages purchase or participation. Input is the suggested content received from the server, and output includes the presentation of suggestions to the user and tracking information of their response. Voice guidance and visual displays are used to guide the user's actions.

[0868] Step 6:

[0869] Users decide to participate in or purchase products or services they are interested in. In this step, user feedback is recorded as new input for re-analysis in the next step. The user's selected actions are collected in a database, contributing to improving the accuracy of future recommendations.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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."

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] The following is further disclosed regarding the embodiments described above.

[0892] (Claim 1)

[0893] A means of receiving user information and generating individual health profiles,

[0894] A means for generating health advice based on the aforementioned health profile,

[0895] A means for notifying the user of the aforementioned health advice,

[0896] A means of matching users with other users based on their interests and location, and forming a community.

[0897] A means of monitoring user activity and sending a confirmation message if an anomaly is detected,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, further comprising means for providing guides on preventive medicine and online medical consultation information.

[0901] (Claim 3)

[0902] The system according to claim 1, further comprising means of collaborating with a third-party company to analyze collected user data and provide health-related services.

[0903] "Example 1"

[0904] (Claim 1)

[0905] A means of generating a health profile based on individual health information received from a user,

[0906] A means for creating health advice using a generated AI model based on the aforementioned health profile,

[0907] A means for notifying the user of the aforementioned health advice via a communication device,

[0908] A means of matching users with other users based on their interests and activity time to form a community,

[0909] A means of monitoring the user's activity history and sending notifications when an anomaly is detected,

[0910] A means of receiving user feedback and continuously updating health profiles,

[0911] A system that includes this.

[0912] (Claim 2)

[0913] The system according to claim 1, further comprising means for providing guidance on the field of prevention using a generative AI model and for displaying online medical information.

[0914] (Claim 3)

[0915] The system according to claim 1, further comprising means for collaborating with external organizations to analyze collected user information and provide health-related services.

[0916] "Application Example 1"

[0917] (Claim 1)

[0918] A means of receiving user information and generating individual health profiles,

[0919] A means for generating health advice based on the aforementioned health profile,

[0920] A means for notifying the user of the aforementioned health advice,

[0921] A means of matching users with other users based on their interests and location, and forming a community.

[0922] A means of monitoring user activity and sending a confirmation message if an anomaly is detected,

[0923] A means of generating safety confirmation information in an emergency and notifying designated contacts,

[0924] A means of providing advice using an AI model based on the user's health data,

[0925] A system that includes this.

[0926] (Claim 2)

[0927] The system according to claim 1, further comprising means for providing guides on preventive medicine and online medical consultation information.

[0928] (Claim 3)

[0929] The system according to claim 1, further comprising means of collaborating with a third-party company to analyze collected user data and provide health-related services.

[0930] "Example 2 of combining an emotion engine"

[0931] (Claim 1)

[0932] A means of receiving user information and generating an individual health plan,

[0933] A means for generating health guidance based on the aforementioned health plan,

[0934] A means of analyzing emotional information obtained from users and adjusting health guidance based on the analysis results,

[0935] A means for notifying the user of the aforementioned health guidance,

[0936] A means of proposing social activities with other users and notifying them of the content of those proposals,

[0937] A means of collecting user feedback and incorporating that data into future instruction,

[0938] A system that includes this.

[0939] (Claim 2)

[0940] The system according to claim 1, further comprising means for providing guidance on preventive medicine and online medical information.

[0941] (Claim 3)

[0942] The system according to claim 1, further comprising means for collaborating with external organizations to analyze collected user data and provide health-related services.

[0943] "Application example 2 when combining with an emotional engine"

[0944] (Claim 1)

[0945] A means of receiving user information and generating individual health profiles,

[0946] A means for generating health advice based on the aforementioned health profile,

[0947] A means for notifying the user of the aforementioned health advice,

[0948] A means of matching users with other users based on their interests and location, and forming a community.

[0949] A means of analyzing user emotions and suggesting products or services based on specific states,

[0950] A means of monitoring user activity and sending a confirmation message if an anomaly is detected,

[0951] A system that includes this.

[0952] (Claim 2)

[0953] The system according to claim 1, further comprising means for providing guides on preventive medicine and online medical consultation information.

[0954] (Claim 3)

[0955] The system according to claim 1, further comprising means of collaborating with a third-party company to analyze collected user data and provide health-related services. [Explanation of Symbols]

[0956] 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 means of receiving user information and generating individual health profiles, A means for generating health advice based on the aforementioned health profile, A means for notifying the user of the aforementioned health advice, A means of matching users with other users based on their interests and location, and forming a community. A means of monitoring user activity and sending a confirmation message if an anomaly is detected, A system that includes this.

2. The system according to claim 1, further comprising means for providing guides on preventive medicine and online medical consultation information.

3. The system according to claim 1, further comprising means of collaborating with a third-party company to analyze collected user data and provide health-related services.

Images