System

Abstract

A system is provided.SOLUTION: A system comprising: means for allowing a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating optimal health management advice for the user based on an analysis result; means for allowing the user and a doctor to communicate with each other in real time through a video call; and means for centrally managing and storing information recorded during the video call.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, health management based on individual genetic information is becoming increasingly important. However, it is not easy for users to obtain specific health advice based on their genetic information, and problems include a lack of communication with doctors and a lack of centralized information management. This makes it difficult for users to create and implement appropriate and continuous health management plans. [Means for solving the problem]

[0005] The present invention provides a system for health management based on individual genetic information. Specifically, the system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing this information, a means for generating personalized health management advice for the user based on the analysis results, a means for real-time communication between the user and a doctor via video call, and a means for centrally managing and storing information recorded during the video call. This system facilitates communication between the user and a doctor, provides specific, personalized health management advice, and supports continuous health management.

[0006] "User" refers to an individual who uses the service and is the entity that provides genetic information and health information.

[0007] "Basic information" refers to personal information such as the user's name, age, gender, and email address.

[0008] "Genetic Information" refers to the user's genetic data provided by affiliated genetic testing institutions.

[0009] "Lifestyle information" is data related to the user's daily life, and includes information on diet, exercise habits, sleep, and the like.

[0010] "Storage" refers to the retention in a database of information provided by the user and data recorded during a video call.

[0011] "Analysis" refers to the use of a generative AI model based on stored basic information, genetic information, and lifestyle information to identify health risks and areas for improvement.

[0012] "Generative AI model" refers to an algorithm that uses artificial intelligence to provide health advice based on a user's individual information.

[0013] "Health management advice" refers to specific suggestions for improvement, such as diet and exercise, provided based on the user's genetic information and lifestyle.

[0014] "Video call" refers to a means of audio and video communication that allows users and doctors to communicate face-to-face in real time.

[0015] "Physician" refers to a medical professional qualified to provide professional health advice to users.

[0016] "Real-time" refers to the instantaneous exchange of information, without delay.

[0017] "Centralized management" refers to the efficient management of multiple pieces of information by integrating them into a central database.

[0018] "Recording" refers to saving information such as notes and new questions as data during a video call.

[0019] "Health Management Plan" means a set of policies and / or action plans designed to improve and maintain a User's health.

[0020] "Reservation" refers to the act of a user specifying and reserving a date and time for video consulting in advance. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0026] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0027] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] The present invention is a system that provides personalized, optimal health management advice based on genetic and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a doctor via video call, and a means for centrally managing and storing information.

[0043] A natural language description of the program's operation

[0044] The processing of the present system proceeds as follows.

[0045] User registration and provision of genetic information

[0046] 1. User:

[0047] Users register with the system through an app or website and enter basic information, including their name, age, gender, and email address.

[0048] Users obtain genetic information using a test kit from a partner genetic testing institution and upload the results to a server.

[0049] 2. Server:

[0050] The server receives the basic information entered by the user and the genetic information provided, and stores it in a database.

[0051] Video consultation booking and call management

[0052] 3. User:

[0053] Users can book a video consultation through the app or website, select the desired date and time, and confirm the appointment.

[0054] 4. Server:

[0055] The server receives the reservation information sent by the user and stores it in a database. When the reservation time arrives, it notifies both the doctor and the user.

[0056] Providing real-time advice

[0057] 5. Terminal (user / doctor terminal):

[0058] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[0059] 6. Server:

[0060] Using a generative AI model, the system generates personalized health management advice based on the user's genetic, basic, and lifestyle data, which is then provided to a doctor in real time via video call.

[0061] 7. Terminal (Doctor's terminal):

[0062] The doctor will communicate the advice provided by the server to the user and propose an appropriate health management plan, including recommendations for improving diet and exercise.

[0063] Centralized management and recording of information

[0064] 8. Terminal (user / doctor terminal):

[0065] During the video call, the doctor and user take notes and record information such as questions from the user and lifestyle changes, which are then entered into the device.

[0066] 9. Server:

[0067] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database, ensuring that the user's next consultation and health management plan reflects the most up-to-date information.

[0068] Specific examples

[0069] Tanaka's case

[0070] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and then obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the results to the server.

[0071] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[0072] Based on the advice received from the server, the doctor made specific health management suggestions to Mr. Tanaka. Any new questions or notes that arose during the call were also recorded and saved on the server.

[0073] In this way, Mr. Tanaka will be able to receive optimal, individualized health management advice based on his genetic information, and it is expected that his next consultation will also proceed smoothly.

[0074] The method of providing optimal individual health management advice realized by this system is an effective means of promoting improvement in the user's health.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[0078] Step 2:

[0079] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[0080] Step 3:

[0081] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[0082] Step 4:

[0083] The server receives the uploaded genetic information and stores it in a database.

[0084] Step 5:

[0085] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[0086] Step 6:

[0087] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[0088] Step 7:

[0089] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[0090] Step 8:

[0091] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[0092] Step 9:

[0093] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[0094] Step 10:

[0095] The doctor's terminal displays advice from the server, and the doctor uses this information to provide appropriate advice to the user and propose a health management plan.

[0096] Step 11:

[0097] During the video call, the user and doctor take notes and record the user's questions and lifestyle changes on the device.

[0098] Step 12:

[0099] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[0100] Step 13:

[0101] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[0102] Example 1

[0103] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0104] In modern society, people's lifestyles are becoming more diverse, creating a demand for customized health management advice tailored to each individual's health condition. However, existing health management systems can only provide general advice, making it difficult to provide individually tailored advice based on genetic and lifestyle information. Furthermore, when users and medical professionals make video calls for health management, there is an insufficient mechanism for centrally managing that information and effectively utilizing it for the next consultation.

[0105] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0106] In this invention, the server includes means for using a generative AI model to generate real-time advice based on user data, means for inputting prompt text into the generative AI model to generate personalized advice, and means for reminding the user of the appointment time through a notification function. This makes it possible to provide personalized, optimal health management advice in real time based on the user's genetic information and lifestyle information, and further makes it possible to effectively use this information for the next consultation.

[0107] "User" refers to an individual who uses this system and who inputs information or receives services through an application or website.

[0108] "Basic information" refers to personal information entered by the user, such as name, age, gender, and email address.

[0109] "Genetic information" refers to data obtained through a user's genetic testing, and includes information about specific health risks and physical constitutions.

[0110] "Lifestyle information" refers to data related to a user's diet, exercise, sleep, stress, etc.

[0111] "Storage" refers to the act of recording and retaining data on a server or database.

[0112] "Analysis" refers to the process of performing calculations and evaluations based on collected data to derive useful information and results.

[0113] "Individually optimal health management advice" refers to instructions and suggestions regarding optimized health management based on the user's individual genetic information and lifestyle information.

[0114] "Video calling" refers to a technology that allows users and medical professionals to communicate in real time via video and audio over the Internet.

[0115] "Medical professionals" refer to people with specialized knowledge and qualifications, such as doctors, nutritionists, and trainers, who are responsible for providing health management advice to users.

[0116] "Centralized management" refers to the unification of different types of information, organizing and storing them, and managing them efficiently.

[0117] A "generative AI model" refers to an artificial intelligence program that generates results using specific algorithms based on input data.

[0118] A "prompt" refers to a command or question that is input into a generative AI model, and serves as a trigger for the model to generate the necessary data.

[0119] "Notification" refers to the system's ability to notify users and medical professionals of important events and actions.

[0120] "Reservation System" means an online system that allows a User to select and confirm a date and time for a video call.

[0121] "Notes" refer to vague information, questions, comments, etc. recorded by users or medical professionals during video calls.

[0122] This invention is a system that provides personalized, optimal health management advice based on genetic information and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a medical professional via video call, and a means for centrally managing and storing information.

[0123] User registration and provision of genetic information

[0124] To start using the system, users must first open a dedicated application or website on their smartphone or personal computer (PC) and register. Users must enter basic information such as their name, age, gender, and email address.

[0125] Next, the user purchases a test kit from an affiliated genetic testing institution, collects a genetic sample according to the instructions, and sends it to the testing institution. When the test results are provided a few days later, the user uploads them to a dedicated application or their personal page on the website. At this time, the server receives the basic information and genetic information provided by the user and encrypts and stores it in a relational database such as MySQL or MongoDB or a NoSQL database. The encryption is performed using technologies such as AES (Advanced Encryption Standard).

[0126] Video consultation booking and call management

[0127] The user selects a date and time for a video consultation using a dedicated application or a website reservation system, and makes a reservation. The server receives this reservation information and records it in a database. When the reservation time approaches, the server sends reminder emails to both the user and the medical professional. This email is sent using an SMTP server.

[0128] Providing real-time advice

[0129] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, which is conducted using WebRTC (Web Real-Time Communication) technology.

[0130] During this time, the server launches the generative AI model and performs analysis based on the genetic information, basic information, and lifestyle habit data provided by the user. The server inputs a prompt into the generative AI model to generate personalized, optimal advice. For example, the following prompts are used:

[0131] "I'm a 37-year-old woman named Tanaka. I'm concerned about health risks based on my genetic information, and I'd like advice on improving my diet and recommending exercise. Please generate personalized, optimal health management advice based on my genetic information, basic information, and lifestyle data."

[0132] The generated advice is sent in real time to the terminal of a medical professional, who can then use the advice to propose an appropriate health management plan to the user.

[0133] Centralized management and recording of information

[0134] During the video call, the medical professional and the user can input any new questions, lifestyle changes, or other important notes into the device. This information is then recorded in a database managed by the server. This information can be used to provide more detailed health management advice during the next consultation.

[0135] As described above, this system enables optimal health management for each individual user, provides highly accurate real-time advice, and enables effective use of information in the next consultation.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] Step 1:

[0138] User Registration

[0139] 1. Users

[0140] Users can register by opening a dedicated application or website on their smartphone or PC, and entering basic information such as name, age, gender, and email address.

[0141] Input: Name, age, gender, email address

[0142] Output: User profile stored in registration database

[0143] 2. Server

[0144] We receive basic information submitted by users and store it in a database for future reference and analysis.

[0145] Input: Basic information

[0146] Output: Saved user profile

[0147] Step 2:

[0148] Genetic information provision

[0149] 1. Users

[0150] Users purchase a test kit from a partner genetic testing institution, collect a genetic sample according to the instructions, and send it to the testing institution. Test results are provided a few days later.

[0151] Input: Gene sample

[0152] Output: Genetic test result data

[0153] 2. Users

[0154] The provided genetic information is uploaded to a dedicated application or personal page on the website.

[0155] Input: Genetic test result data

[0156] Output: Uploaded genetic information

[0157] 3. Server

[0158] The system receives genetic information provided by users, encrypts it, and stores it in a database using technologies such as AES (Advanced Encryption Standard).

[0159] Input: Uploaded genetic information

[0160] Output: Encrypted and stored genetic information

[0161] Step 3:

[0162] Book a video consultation

[0163] 1. Users

[0164] Use the dedicated application or website reservation system to select the date and time of the video consultation and make a reservation. Reservation information is displayed in a calendar format, and you can select the desired date and time.

[0165] Input: Reservation date and time, user ID

[0166] Output: Reservation confirmation information

[0167] 2. Server

[0168] Reservation information sent by the user is received and recorded in the database. The reservation information includes the reservation date and time, user ID, and medical professional ID.

[0169] Input: Reservation information

[0170] Output: Saved reservation information

[0171] Step 4:

[0172] Video Consultation Notification

[0173] 1. Server

[0174] When the appointment time approaches, the server sends reminder emails to both the user and the medical professional. The server uses an SMTP server to send the reminder emails.

[0175] Input: Appointment information (date and time, user ID, medical professional ID)

[0176] Output: Reminder email

[0177] Step 5:

[0178] Starting a video call

[0179] 1. Terminals (user and medical professional terminals)

[0180] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, using WebRTC (Web Real-Time Communication) technology.

[0181] Input: Appointment information, User ID, Medical Professional ID

[0182] Output: Start a video call

[0183] Step 6:

[0184] Providing real-time advice

[0185] 1. Server

[0186] The generative AI model is activated to generate personalized health management advice based on the user's genetic information, basic information, and lifestyle data. The user enters a prompt and provides the generated advice to a medical professional during a video call.

[0187] Input: Genetic information, basic information, lifestyle data, prompt text

[0188] Output: Personalized and optimal health management advice

[0189] 2. Terminal (medical professional's terminal)

[0190] The medical professional reviews the advice provided by the server and proposes a specific health management plan to the user, such as "improving your diet" or "recommending exercise."

[0191] Input: Generated advice

[0192] Output: Health care plan provided

[0193] Step 7:

[0194] Centralized management and recording of information

[0195] 1. Terminals (user and medical professional terminals)

[0196] Enter new questions, lifestyle changes, and notes during the video call.

[0197] Input: Questions, lifestyle changes, notes

[0198] Output: Recorded information

[0199] 2. Server

[0200] All information entered during the video call is received and stored in a centralized database, which can then be used for the next consultation.

[0201] Input: Recorded information

[0202] Output: Centralized information saved

[0203] (Application example 1)

[0204] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0205] In modern society, interest in personal health management is growing, but providing personalized, optimal health management advice based on genetic and lifestyle information is difficult, and means for communicating with experts in real time are limited. Furthermore, there is a need to maintain consistency in in-store consultations and provide continuous, effective health management. The present invention aims to solve these problems and provide users with consistent, personalized, optimal health management advice.

[0206] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0207] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user to communicate with a medical professional in real time via video call; means for providing the advice generated in real time during the video call to the medical professional; means for recording the health management advice received by the user at the physical store and using the recording for the next consultation; means for centrally managing and storing information; and means for continuously providing individually optimized health management advice to the user using the generative AI model. This makes it possible to continuously provide individually optimized health management advice to the user while maintaining consistency even during health management consultations at the physical store.

[0208] "User" refers to an individual who uses the system.

[0209] "Brick and mortar" refers to a business or organization that provides services at a physical location.

[0210] "Basic information" refers to personal information such as the user's name, age, and gender.

[0211] "Genetic Information" refers to data about a user's DNA.

[0212] "Lifestyle information" refers to information about the habits and preferences of a user in their daily life.

[0213] "Server" refers to a networked computer system for storing data and performing analytical tasks.

[0214] "Analysis" refers to the process of analyzing collected data and generating meaningful information.

[0215] "Health Management Advice" means specific instructions or suggestions for maintaining or improving a User's health.

[0216] "Video calling" refers to a real-time communication method for exchanging audio and video over the Internet.

[0217] "Healthcare professional" refers to a physician or other medical professional.

[0218] "Recording" refers to the process of storing information and keeping it available for future reference.

[0219] "Centralized management" refers to the centralized management of multiple pieces of information in one place or system.

[0220] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate useful information or predictions from data.

[0221] The present invention can be implemented as a system that provides health management support in a physical store. This system is provided as a smartphone app, and allows users to input basic information, genetic information, and lifestyle information, and provides personalized, optimal health management advice based on that information.

[0222] System configuration

[0223] 1. How to enter user's basic information and genetic information:

[0224] Users download the smartphone app and enter their name, age, gender, lifestyle information, etc.

[0225] Genetic information is obtained through affiliated genetic testing services and uploaded to a server via the app.

[0226] 2. How we store and analyze your information:

[0227] The servers use Google Cloud or AWS, and the basic information, genetic information, and lifestyle information provided by users is stored in a database.

[0228] Data analysis platforms such as Python and R are used to analyze the collected information.

[0229] 3. Means for generating personalized health management advice:

[0230] Based on the analysis results, a generative AI model (e.g., ChatGPT, GPT-4) is used to generate personalized advice, including specific instructions on diet, exercise recommendations, health risk management, and more.

[0231] 4. Video calling methods:

[0232] Using the Zoom API and Twilio Video, users can conduct real-time video calls with medical professionals.

[0233] During the video call, the server provides real-time advice based on the analysis results to medical professionals.

[0234] 5. Real-time advice delivery methods:

[0235] During the video call, the generative AI model presents the generated advice to the medical professional, making appropriate suggestions to the user.

[0236] This advice also includes information to help users manage their ongoing health.

[0237] 6. Centralized information management:

[0238] The information and notes recorded by the user and medical professional during the video call are stored on the server and made available for the next consultation.

[0239] Specific examples

[0240] For example, consider the case of a 35-year-old female user using this system in a physical store. The user downloads the app, enters basic information, and uploads genetic test results. Next, she schedules a video consultation in the store and has a real-time video call with a medical professional at the scheduled time. Based on the personalized and optimized advice provided by the generative AI model, the medical professional will propose a specific health management plan. This information is stored on the server, enabling a smooth consultation the next time the user visits the store.

[0241] Prompt Sentence Examples

[0242] By inputting the following prompt sentences into the generative AI model, personalized health management advice will be generated:

[0243] We will provide the user's basic information and genetic information below. Based on this, we would like you to generate optimal health management advice for the user.

[0244] Basic information: Age 35, female, no exercise habits

[0245] Genetic information: High-risk items (cardiovascular disease risk, diabetes risk)

[0246] Lifestyle information: Desk work, drinks 3 times a week

[0247] Generate your health advice in the following format:

[0248] Improved diet

[0249] Exercise recommendations

[0250] Health Risk Management

[0251] In this way, personalized and optimal health management advice based on the user's genetic information and lifestyle information can be provided.

[0252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0253] Step 1:

[0254] The user downloads the application and enters basic information. The user enters their name, age, gender, and lifestyle information (e.g., drinking frequency, exercise habits, etc.) into the smartphone application. The application sends the entered information to the server and stores it in a database.

[0255] Step 2:

[0256] The user provides genetic information. The user obtains the genetic information using a test kit from a partner genetic testing institution. The genetic information is then uploaded to the server via a smartphone application. The server stores the received genetic information in a database.

[0257] Step 3:

[0258] The server analyzes the information provided by the user. Using a data analysis platform such as Python or R, the server analyzes the received basic information, genetic information, and lifestyle information. The results of the analysis are output as data on the user's health risks and optimal lifestyle habits, and are stored in a database.

[0259] Step 4:

[0260] A user books a video consultation. The user uses the application to book a date and time for a video consultation at a physical store. The selected date and time and the user's information are sent to the server, and the reservation information is saved in the database.

[0261] Step 5:

[0262] The server notifies the medical professional of the appointment information. When the appointment time approaches, the server sends a notification to the medical professional and the user via email or push notification so that they can prepare for the video call.

[0263] Step 6:

[0264] At the appointment time, a video call is initiated between the user's smartphone and the medical professional's device via the application, using the Zoom API and Twilio Video.

[0265] Step 7:

[0266] Real-time advice generation: The server uses a generative AI model (e.g., ChatGPT, GPT-4) to generate real-time health management advice, which is then provided to the medical professional's device during the video call.

[0267] Step 8:

[0268] Medical experts provide advice to users. During the video call, the medical experts propose specific health management plans to users based on advice provided by the server, including recommendations for improving diet and exercise.

[0269] Step 9:

[0270] Centralized information management and recording: During the video call, users and medical professionals record any notes, new questions, or lifestyle changes they make, and send them to the server via the application. The server stores this information in a database and makes it available for the next consultation.

[0271] At each step, data processing or calculation is performed based on specific input data, and the results are used as the output that forms the basis for the next processing step.

[0272] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0273] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and combines it with an emotion engine that recognizes the user's emotions. This system includes a means for the user to input or provide basic information and genetic information, a means for storing and analyzing this information, a means for generating personalized, optimal health management advice for the user based on the analysis results, a means for the user to communicate with a doctor in real time via video call, a means for centrally managing and storing information recorded during the video call, and an emotion engine that recognizes the user's emotions.

[0274] A natural language description of the program's operation

[0275] The processing of the present system proceeds as follows.

[0276] User registration and provision of genetic information

[0277] 1. User:

[0278] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[0279] 2. Server:

[0280] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[0281] 3. User:

[0282] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[0283] 4. Server:

[0284] The server receives the uploaded genetic information and stores it in a database.

[0285] Video consultation booking and call management

[0286] 5. User:

[0287] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[0288] 6. Server:

[0289] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[0290] Providing real-time advice

[0291] 7. Terminal (user / doctor terminal):

[0292] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[0293] 8. Server:

[0294] Using a generative AI model, the system collects genetic, basic, and lifestyle data provided by the user, analyzes it, and generates personalized health management advice that is provided to a doctor via video call in real time.

[0295] Use of emotion engine

[0296] 9. Terminal (user / doctor terminal):

[0297] During a video call, the emotion engine analyzes emotional information from the user's facial expressions, tone of voice, and choice of words.

[0298] 10. Server:

[0299] The system receives the emotional information generated by the emotion engine and adjusts the content and tone of the health management advice provided based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on relaxation methods and stress management.

[0300] Centralized management and recording of information

[0301] 11. Terminal (user / doctor terminal):

[0302] During the video call, the doctor and user take notes and record any questions or lifestyle changes the user may have.

[0303] 12. Server:

[0304] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database. This information can be reused during the next consultation, ensuring that the health management plan is always based on the most up-to-date information.

[0305] Specific examples

[0306] Tanaka's case

[0307] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the information to the server.

[0308] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[0309] At the same time, during the video call, the emotion engine analyzed Tanaka's facial expressions and tone of voice to detect changes in what she was saying and her emotions. The server also analyzed this emotional information and detected that she was feeling stressed, so it added specific advice on how to relax and manage stress.

[0310] Based on the advice, the doctor proposed a specific health management plan for Mr. Tanaka, and also recorded any new questions or notes that arose during the call. All of this information was saved on a server and used during the next consultation.

[0311] With this system, Tanaka will not only receive personalized health management advice based on her genetic information, but will also receive detailed support tailored to her emotional state, which is expected to improve both her physical and mental health.

[0312] The processing flow will be explained below.

[0313] Step 1:

[0314] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[0315] Step 2:

[0316] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[0317] Step 3:

[0318] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[0319] Step 4:

[0320] The server receives the uploaded genetic information and stores it in a database.

[0321] Step 5:

[0322] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[0323] Step 6:

[0324] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[0325] Step 7:

[0326] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[0327] Step 8:

[0328] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[0329] Step 9:

[0330] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[0331] Step 10:

[0332] The advice from the server is displayed on the terminal (doctor's terminal), and the doctor provides appropriate advice to the user based on it and proposes a health management plan.

[0333] Step 11:

[0334] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and selected words to generate emotional information.

[0335] Step 12:

[0336] The server receives the emotion information generated by the emotion engine and uses it to adjust the content and tone of the health care advice provided, for example, emphasizing relaxation and stress management advice if the user is feeling stressed.

[0337] Step 13:

[0338] At the terminals (user and doctor terminals), the user and doctor take notes and record questions from the user and lifestyle changes.

[0339] Step 14:

[0340] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[0341] Step 15:

[0342] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[0343] Example 2

[0344] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0345] In recent years, interest in health management has grown, and providing personalized, optimal health advice is becoming increasingly important. However, there is a lack of means to provide appropriate, real-time, personalized health management advice based on genetic and lifestyle information to users who need it. Furthermore, there are no systems that provide detailed advice that takes users' emotions into consideration. This leads to a lack of centralized management of information, making it difficult to provide effective health management advice tailored to the user's actual lifestyle.

[0346] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0347] In this invention, the server includes means for a user to input or provide basic information and genetic information, means for storing and analyzing the provided genetic information, basic information, and lifestyle information, and means for generating personalized health management advice for the user based on the analysis results. This allows personalized health management advice to be provided in real time based on the user's specific genetic information and lifestyle information, and further takes into account the user's emotions, enabling more effective and centralized health management.

[0348] "User basic information" refers to information that identifies an individual user, such as the user's name, age, gender, email address, and password.

[0349] "Genetic information" refers to data regarding a user's DNA sequence and the genetic characteristics based thereon.

[0350] "Lifestyle information" refers to information about the user's daily life, including eating habits, exercise habits, sleep patterns, alcohol and tobacco use, and the like.

[0351] "Means for storing and analyzing" refers to a set of hardware and software for storing genetic information, basic information, and lifestyle information provided by users in a database and performing analysis based on that data.

[0352] "Means for generating individually optimized health management advice" refers to means that have the function of using a generative AI model to generate health management suggestions and advice appropriate for the user based on stored user information.

[0353] "Video calling tool" means software and hardware that allows users to communicate with medical professionals in real time over the Internet.

[0354] "Centralized management and storage means" means a means for aggregating, managing and storing all user information, including information recorded during video calls, in a central database.

[0355] An "emotion engine" is software that analyzes a user's facial expressions, tone of voice, and word choice to generate emotional information.

[0356] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and by combining it with an emotion engine that analyzes the user's emotions, it provides detailed support. The following describes in detail the modes for implementing this system.

[0357] Registration of basic user information and genetic information

[0358] Users access the service through an application or website, open a new registration screen, and enter basic information such as name, age, gender, email address, and password. This information is sent to the server and securely stored in a database. The user obtains genetic information using a test kit from a partner genetic testing institution and uploads it to the server. The uploaded genetic information is received by the server and securely stored in a database.

[0359] Video consultation booking and real-time calls

[0360] The user books a video consultation through the application or website. The reservation information is sent to the server and stored in a database. When the appointment time approaches, a reminder notification is sent to the medical professional and the user. At the scheduled time, a video call is automatically started, allowing the user and medical professional to communicate in real time.

[0361] Providing personalized and optimal health management advice

[0362] The server uses a generative AI model to collect and analyze the genetic information, basic information, and lifestyle information provided by the user. Based on the results of this analysis, it generates personalized, optimal health management advice. The generated advice is provided in real time to a medical professional on a video call, who can provide specific advice to the user. For example, the following prompt could be used: "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Also, please add advice for when the user is feeling stressed."

[0363] Emotion analysis using an emotion engine

[0364] During a video call, the emotion engine analyzes the user's facial expressions, voice tone, and word choice in real time. Emotional information is generated and sent to the server, which then uses this information to adjust the content and tone of the health care advice. For example, if the user is feeling stressed, the engine can emphasize relaxation and stress management advice.

[0365] Centralized management and recording of information

[0366] During the video call, the medical professional and user can use the notes feature to record any questions or new lifestyle changes. This information is sent to the server and securely stored in a database. The saved information is easily accessible during the next consultation and used to provide an updated health management plan.

[0367] As a concrete example, User A (a 37-year-old woman) uses this system because she is interested in health risks based on her genetic information. She downloads the app, registers, obtains genetic information using a partner genetic testing kit, and uploads that information to the server. She then schedules a video consultation and discusses with a medical professional in real time. The server generates optimal health management advice based on User A's information, and the emotion engine analyzes her emotions to provide tailored support.

[0368] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0369] Step 1: User Registration

[0370] The user accesses an application or website, enters basic information such as name, age, gender, email address, and password on the new registration screen, and clicks the "Register" button. The input data is sent to the server as basic information data.

[0371] The server receives the submitted basic information and stores it in a database. It sends the user a confirmation email to confirm registration. The email contains an authentication link, and the user activates the account by clicking the link. The input is basic information, and the output is saving it in a database and sending a confirmation email.

[0372] Step 2: Provide genetic information

[0373] Users receive a test kit from a partner genetic testing institution, follow the instructions to take a genetic sample, and then send the test kit to the testing institution, where their genetic information is then uploaded to a server via the app or website.

[0374] The server receives the uploaded genetic information and stores it in a secure database. The input is the genetic information, and the output is storing it in the database and notifying the user.

[0375] Step 3: Book a video consultation

[0376] The user logs in to the application or website, opens the video consultation reservation screen, selects the desired date and time, and clicks the "Book" button. The reservation information is sent to the server as reservation data.

[0377] The server receives the submitted appointment information and stores it in a database. When the appointment time approaches, it sends reminder notifications to medical professionals and users. The input is the appointment information, and the output is storing it in the database and sending notifications.

[0378] Step 4: Start a video call

[0379] When the appointment time arrives, a video call will automatically start between the user and the medical professional, allowing them to communicate in real time.

[0380] The terminal establishes a video call session and sends the information to the server. The input is reservation information, and the output is the start of the video call session.

[0381] Step 5: Data collection and analysis

[0382] The server uses a generative AI model to collect genetic, basic, and lifestyle information provided by the user, and the collected data is processed as analytical data.

[0383] The generative AI model analyzes the collected data and generates personalized, optimal health management advice. In this process, a prompt is used to generate appropriate advice. For example, the prompt might read, "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Please also add advice for when the user is feeling stressed." The input is the collected basic information, genetic information, and lifestyle information, and the output is advice as a result of the analysis.

[0384] Step 6: Emotion analysis using the emotion engine

[0385] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and word choice in real time, and the analyzed emotion information is sent to the server.

[0386] The server receives the emotional information and adjusts the content and tone of the health care advice based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on stress management and relaxation methods. The input is emotional data, and the output is the adjusted advice.

[0387] Step 7: Centralize and record information

[0388] During the video call, the medical professional and the user use the notes feature to record questions and lifestyle changes, which are then sent to the server.

[0389] The server receives the transmitted information and stores it centrally in a database. The stored information is reused at the next consultation and used to provide an updated health management plan. The input is recorded information during the call, and the output is stored in the database.

[0390] These processing steps enable users to receive personalized and optimal health management advice based on genetic and lifestyle information, and also to receive detailed support that also addresses their emotional state.

[0391] (Application example 2)

[0392] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0393] Modern health management requires personalized, optimized advice based on a user's genetic and lifestyle information. However, existing systems have been unable to provide personalized advice in real time or adjust the content and tone of the advice based on the user's emotional state. Furthermore, there has been no means of providing personalized health-related advertisements, making it difficult to effectively deliver health information tailored to the user. The present invention aims to solve these problems and provide a system that provides personalized health management advice and health-related advertisements based on a user's genetic and lifestyle information.

[0394] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0395] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user and a doctor to communicate in real time via video call; means for centrally managing and storing information recorded during the video call; means for generating and displaying health-related advertisements optimized for the user based on the analyzed user's health information; and means for analyzing emotions from the user's facial expressions and tone of voice during the video call using an emotion engine and adjusting the timing and content of advertisement display based on the analysis results, thereby enabling the provision of individually optimized health management advice and health-related advertisements based on the user's genetic information and lifestyle information.

[0396] "Means for users to input or provide their basic and genetic information" refers to the interface through which users provide their basic and genetic information to the system, which may include web forms or dedicated applications.

[0397] "Means for storing and analyzing provided genetic information, basic information, and lifestyle information" refers to software and hardware configurations for storing the genetic information, basic information, and lifestyle information provided by the user in a database and analyzing that information.

[0398] The "means for generating individually optimal health management advice for a user based on the analysis results" refers to an algorithm and program for generating health management advice customized for each user based on the stored information.

[0399] "Means for real-time communication between users and doctors via video calls" refers to a system that allows users to communicate with medical professionals in real time using video calling functionality. This includes video calling applications and communication networks.

[0400] "A means for centrally managing and storing information recorded during video calls" refers to a system for storing information such as notes, questions, and comments exchanged during video calls in a database and managing them centrally.

[0401] "Means for generating and displaying health-related advertisements optimized for a user based on the analyzed health information of the user" refers to a system for generating health-related advertisements individually optimized for a user based on the analysis results and displaying them on the user's device.

[0402] "Means of using an emotion engine to analyze emotions from a user's facial expression and tone of voice during a video call, and adjusting the timing and content of advertisement display based on the analysis results" is a technology that analyzes a user's facial expression and tone of voice during a video call, and dynamically adjusts the timing and content of advertisement display according to their emotional state.

[0403] This invention provides a system that provides personalized and optimal health management advice based on a user's genetic information and lifestyle information, and further analyzes the user's emotional state to tailor health-related advertisements. Specific embodiments for implementing this system are described below.

[0404] System Overview

[0405] The present invention is composed of a series of hardware and software including a user terminal, a server, and an emotion engine. The system has the following main functions:

[0406] 1. User registration and provision of genetic information

[0407] Users access a dedicated application or website and enter or upload basic information (such as name, age, gender, and email address) and genetic information. The genetic information is obtained from affiliated genetic testing institutions.

[0408] 2. Information storage and analysis

[0409] The server stores and analyzes basic information, genetic information, and lifestyle information provided by users, using a generative AI model.

[0410] 3. Generating personalized health management advice

[0411] Based on the analysis results, the server generates personalized health care advice for the user, which is provided to a medical professional during the video call.

[0412] 4. Real-time communication via video calls

[0413] Users and medical professionals communicate in real time using the video call feature, and information recorded during the video call is stored centrally and can be used for future consultations.

[0414] 5. Generating and displaying health-related advertisements

[0415] Based on the analysis results, the server generates optimal health-related advertisements for the user and displays them on the user's device. The advertisement content is individually optimized based on the user's health condition and lifestyle.

[0416] 6. Use of Emotion Engines

[0417] During a video call, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information. The server then adjusts the timing and content of advertisements based on this emotional information.

[0418] Hardware and software used

[0419] User devices: smartphones, tablets, computers

[0420] Server: Cloud or Dedicated Server

[0421] Generative AI models: Deep learning frameworks such as TensorFlow and Keras

[0422] Emotion engine: OpenCV, TensorFlow

[0423] Specific examples

[0424] For example, let's say a male user in his 30s uses the system. This user downloads the smartphone app and enters basic information (name, age, gender). Using a kit from a partner genetic testing institution, genetic information is obtained and uploaded to the database.

[0425] Users can schedule a video call through the app, and when the time comes, they will speak with a medical professional in real time. The server analyzes the user's genetic information, basic information, and lifestyle data, and based on the results, provides the medical professional with personalized health management advice. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the timing and content of advertisements based on their emotional information.

[0426] An example prompt might look like this:

[0427] "Male in his 30s, active, and eats a balanced diet. Low genetic risk, but currently experiencing stress. Create an ad for a health supplement with a relaxing effect."

[0428] In this way, the present invention provides individualized and optimal health management advice and health-related advertisements based on the user's genetic information and lifestyle information, and is expected to help the user maintain and improve their health.

[0429] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0430] Step 1:

[0431] The user inputs or provides basic information and genetic information.

[0432] Input: Name, age, gender, email address, and genetic information entered by users through smartphone apps or websites.

[0433] Processing: The user terminal sends the entered information to the server.

[0434] Output: User's basic information and genetic information stored on the server.

[0435] Step 2:

[0436] The server stores and analyzes the provided genetic information, basic information, and lifestyle information.

[0437] Input: Basic, genetic, and lifestyle information submitted by the user.

[0438] Processing: The information is stored in a database and analyzed using generative AI models, using deep learning frameworks such as TensorFlow and Keras.

[0439] Output: Health risk data and appropriate health advice indicators generated as a result of the analysis.

[0440] Step 3:

[0441] The server generates optimal individual health management advice for the user based on the analysis results.

[0442] Input: Analysis results from a generative AI model.

[0443] Processing: Based on the analysis results, the system creates personalized health management advice, such as automatically generating dietary suggestions and exercise advice.

[0444] Output: Personalized optimal health care advice provided to the user.

[0445] Step 4:

[0446] Users and medical professionals communicate in real time via video calls.

[0447] Input: Video call appointment information and generated health care advice.

[0448] Processing: When the video call starts, the server provides the generated advice to the medical professional's device and starts the video call. During the video call, questions from the user and comments from the doctor are recorded.

[0449] Output: Feedback and further advice from a medical professional via video call.

[0450] Step 5:

[0451] The server centrally manages and stores information recorded during video calls.

[0452] Input: Notes, questions, and lifestyle changes recorded by the doctor and user during the video call.

[0453] Processing: This information is stored in a database and managed so that it can be used for the next consultation.

[0454] Output: Recording information during the video call stored in a database.

[0455] Step 6:

[0456] The server generates and displays health-related advertisements optimized for the user based on the analyzed health information of the user.

[0457] Input: Analysis results and health management advice from the generative AI model.

[0458] Processing: Based on the user's health status and lifestyle, personalized health-related advertisements are generated and displayed on the user's device.

[0459] Output: Health-related advertisements displayed on the user's device.

[0460] Step 7:

[0461] Using an emotion engine, the system analyzes the user's emotions from their facial expressions and tone of voice during a video call, and adjusts the timing and content of advertisements based on the analysis results.

[0462] Input: Your facial expressions and tone of voice during a video call.

[0463] Processing: Sentiment analysis is performed using OpenCV and TensorFlow to identify the user's emotional state, and ad timing and content are adjusted in real time based on this.

[0464] Output: Adjusted ad content and timing.

[0465] The above is a specific program processing flow based on the processing steps of the present invention.

[0466] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0467] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0468] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0469] [Second embodiment]

[0470] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0471] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0472] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0473] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0474] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0475] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0476] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0477] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0478] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0479] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0480] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0481] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0482] The present invention is a system that provides personalized, optimal health management advice based on genetic and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a doctor via video call, and a means for centrally managing and storing information.

[0483] A natural language description of the program's operation

[0484] The processing of the present system proceeds as follows.

[0485] User registration and provision of genetic information

[0486] 1. User:

[0487] Users register with the system through an app or website and enter basic information, including their name, age, gender, and email address.

[0488] Users obtain genetic information using a test kit from a partner genetic testing institution and upload the results to a server.

[0489] 2. Server:

[0490] The server receives the basic information entered by the user and the genetic information provided, and stores it in a database.

[0491] Video consultation booking and call management

[0492] 3. User:

[0493] Users can book a video consultation through the app or website, select the desired date and time, and confirm the appointment.

[0494] 4. Server:

[0495] The server receives the reservation information sent by the user and stores it in a database. When the reservation time arrives, it notifies both the doctor and the user.

[0496] Providing real-time advice

[0497] 5. Terminal (user / doctor terminal):

[0498] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[0499] 6. Server:

[0500] Using a generative AI model, the system generates personalized health management advice based on the user's genetic, basic, and lifestyle data, which is then provided to a doctor in real time via video call.

[0501] 7. Terminal (Doctor's terminal):

[0502] The doctor will communicate the advice provided by the server to the user and propose an appropriate health management plan, including recommendations for improving diet and exercise.

[0503] Centralized management and recording of information

[0504] 8. Terminal (user / doctor terminal):

[0505] During the video call, the doctor and user take notes and record information such as questions from the user and lifestyle changes, which are then entered into the device.

[0506] 9. Server:

[0507] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database, ensuring that the user's next consultation and health management plan reflects the most up-to-date information.

[0508] Specific examples

[0509] Tanaka's case

[0510] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and then obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the results to the server.

[0511] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[0512] Based on the advice received from the server, the doctor made specific health management suggestions to Mr. Tanaka. Any new questions or notes that arose during the call were also recorded and saved on the server.

[0513] In this way, Mr. Tanaka will be able to receive optimal, individualized health management advice based on his genetic information, and it is expected that his next consultation will also proceed smoothly.

[0514] The method of providing optimal individual health management advice realized by this system is an effective means of promoting improvement in the user's health.

[0515] The processing flow will be explained below.

[0516] Step 1:

[0517] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[0518] Step 2:

[0519] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[0520] Step 3:

[0521] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[0522] Step 4:

[0523] The server receives the uploaded genetic information and stores it in a database.

[0524] Step 5:

[0525] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[0526] Step 6:

[0527] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[0528] Step 7:

[0529] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[0530] Step 8:

[0531] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[0532] Step 9:

[0533] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[0534] Step 10:

[0535] The doctor's terminal displays advice from the server, and the doctor uses this information to provide appropriate advice to the user and propose a health management plan.

[0536] Step 11:

[0537] During the video call, the user and doctor take notes and record the user's questions and lifestyle changes on the device.

[0538] Step 12:

[0539] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[0540] Step 13:

[0541] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[0542] Example 1

[0543] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0544] In modern society, people's lifestyles are becoming more diverse, creating a demand for customized health management advice tailored to each individual's health condition. However, existing health management systems can only provide general advice, making it difficult to provide individually tailored advice based on genetic and lifestyle information. Furthermore, when users and medical professionals make video calls for health management, there is an insufficient mechanism for centrally managing that information and effectively utilizing it for the next consultation.

[0545] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0546] In this invention, the server includes means for using a generative AI model to generate real-time advice based on user data, means for inputting prompt text into the generative AI model to generate personalized advice, and means for reminding the user of the appointment time through a notification function. This makes it possible to provide personalized, optimal health management advice in real time based on the user's genetic information and lifestyle information, and further makes it possible to effectively use this information for the next consultation.

[0547] "User" refers to an individual who uses this system and who inputs information or receives services through an application or website.

[0548] "Basic information" refers to personal information entered by the user, such as name, age, gender, and email address.

[0549] "Genetic information" refers to data obtained through a user's genetic testing, and includes information about specific health risks and physical constitutions.

[0550] "Lifestyle information" refers to data related to a user's diet, exercise, sleep, stress, etc.

[0551] "Storage" refers to the act of recording and retaining data on a server or database.

[0552] "Analysis" refers to the process of performing calculations and evaluations based on collected data to derive useful information and results.

[0553] "Individually optimal health management advice" refers to instructions and suggestions regarding optimized health management based on the user's individual genetic information and lifestyle information.

[0554] "Video calling" refers to a technology that allows users and medical professionals to communicate in real time via video and audio over the Internet.

[0555] "Medical professionals" refer to people with specialized knowledge and qualifications, such as doctors, nutritionists, and trainers, who are responsible for providing health management advice to users.

[0556] "Centralized management" refers to the unification of different types of information, organizing and storing them, and managing them efficiently.

[0557] A "generative AI model" refers to an artificial intelligence program that generates results using specific algorithms based on input data.

[0558] A "prompt" refers to a command or question that is input into a generative AI model, and serves as a trigger for the model to generate the necessary data.

[0559] "Notification" refers to the system's ability to notify users and medical professionals of important events and actions.

[0560] "Reservation System" means an online system that allows a User to select and confirm a date and time for a video call.

[0561] "Notes" refer to vague information, questions, comments, etc. recorded by users or medical professionals during video calls.

[0562] This invention is a system that provides personalized, optimal health management advice based on genetic information and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a medical professional via video call, and a means for centrally managing and storing information.

[0563] User registration and provision of genetic information

[0564] To start using the system, users must first open a dedicated application or website on their smartphone or personal computer (PC) and register. Users must enter basic information such as their name, age, gender, and email address.

[0565] Next, the user purchases a test kit from an affiliated genetic testing institution, collects a genetic sample according to the instructions, and sends it to the testing institution. When the test results are provided a few days later, the user uploads them to a dedicated application or their personal page on the website. At this time, the server receives the basic information and genetic information provided by the user and encrypts and stores it in a relational database such as MySQL or MongoDB or a NoSQL database. The encryption is performed using technologies such as AES (Advanced Encryption Standard).

[0566] Video consultation booking and call management

[0567] The user selects a date and time for a video consultation using a dedicated application or a website reservation system, and makes a reservation. The server receives this reservation information and records it in a database. When the reservation time approaches, the server sends reminder emails to both the user and the medical professional. This email is sent using an SMTP server.

[0568] Providing real-time advice

[0569] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, which is conducted using WebRTC (Web Real-Time Communication) technology.

[0570] During this time, the server launches the generative AI model and performs analysis based on the genetic information, basic information, and lifestyle habit data provided by the user. The server inputs a prompt into the generative AI model to generate personalized, optimal advice. For example, the following prompts are used:

[0571] "I'm a 37-year-old woman named Tanaka. I'm concerned about health risks based on my genetic information, and I'd like advice on improving my diet and recommending exercise. Please generate personalized, optimal health management advice based on my genetic information, basic information, and lifestyle data."

[0572] The generated advice is sent in real time to the terminal of a medical professional, who can then use the advice to propose an appropriate health management plan to the user.

[0573] Centralized management and recording of information

[0574] During the video call, the medical professional and the user can input any new questions, lifestyle changes, or other important notes into the device. This information is then recorded in a database managed by the server. This information can be used to provide more detailed health management advice during the next consultation.

[0575] As described above, this system enables optimal health management for each individual user, provides highly accurate real-time advice, and enables effective use of information in the next consultation.

[0576] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0577] Step 1:

[0578] User Registration

[0579] 1. Users

[0580] Users can register by opening a dedicated application or website on their smartphone or PC, and entering basic information such as name, age, gender, and email address.

[0581] Input: Name, age, gender, email address

[0582] Output: User profile stored in registration database

[0583] 2. Server

[0584] We receive basic information submitted by users and store it in a database for future reference and analysis.

[0585] Input: Basic information

[0586] Output: Saved user profile

[0587] Step 2:

[0588] Genetic information provision

[0589] 1. Users

[0590] Users purchase a test kit from a partner genetic testing institution, collect a genetic sample according to the instructions, and send it to the testing institution. Test results are provided a few days later.

[0591] Input: Gene sample

[0592] Output: Genetic test result data

[0593] 2. Users

[0594] The provided genetic information is uploaded to a dedicated application or personal page on the website.

[0595] Input: Genetic test result data

[0596] Output: Uploaded genetic information

[0597] 3. Server

[0598] The system receives genetic information provided by users, encrypts it, and stores it in a database using technologies such as AES (Advanced Encryption Standard).

[0599] Input: Uploaded genetic information

[0600] Output: Encrypted and stored genetic information

[0601] Step 3:

[0602] Book a video consultation

[0603] 1. Users

[0604] Use the dedicated application or website reservation system to select the date and time of the video consultation and make a reservation. Reservation information is displayed in a calendar format, and you can select the desired date and time.

[0605] Input: Reservation date and time, user ID

[0606] Output: Reservation confirmation information

[0607] 2. Server

[0608] Reservation information sent by the user is received and recorded in the database. The reservation information includes the reservation date and time, user ID, and medical professional ID.

[0609] Input: Reservation information

[0610] Output: Saved reservation information

[0611] Step 4:

[0612] Video Consultation Notification

[0613] 1. Server

[0614] When the appointment time approaches, the server sends reminder emails to both the user and the medical professional. The server uses an SMTP server to send the reminder emails.

[0615] Input: Appointment information (date and time, user ID, medical professional ID)

[0616] Output: Reminder email

[0617] Step 5:

[0618] Starting a video call

[0619] 1. Terminals (user and medical professional terminals)

[0620] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, using WebRTC (Web Real-Time Communication) technology.

[0621] Input: Appointment information, User ID, Medical Professional ID

[0622] Output: Start a video call

[0623] Step 6:

[0624] Providing real-time advice

[0625] 1. Server

[0626] The generative AI model is activated to generate personalized health management advice based on the user's genetic information, basic information, and lifestyle data. The user enters a prompt and provides the generated advice to a medical professional during a video call.

[0627] Input: Genetic information, basic information, lifestyle data, prompt text

[0628] Output: Personalized and optimal health management advice

[0629] 2. Terminal (medical professional's terminal)

[0630] The medical professional reviews the advice provided by the server and proposes a specific health management plan to the user, such as "improving your diet" or "recommending exercise."

[0631] Input: Generated advice

[0632] Output: Health care plan provided

[0633] Step 7:

[0634] Centralized management and recording of information

[0635] 1. Terminals (user and medical professional terminals)

[0636] Enter new questions, lifestyle changes, and notes during the video call.

[0637] Input: Questions, lifestyle changes, notes

[0638] Output: Recorded information

[0639] 2. Server

[0640] All information entered during the video call is received and stored in a centralized database, which can then be used for the next consultation.

[0641] Input: Recorded information

[0642] Output: Centralized information saved

[0643] (Application example 1)

[0644] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0645] In modern society, interest in personal health management is growing, but providing personalized, optimal health management advice based on genetic and lifestyle information is difficult, and means for communicating with experts in real time are limited. Furthermore, there is a need to maintain consistency in in-store consultations and provide continuous, effective health management. The present invention aims to solve these problems and provide users with consistent, personalized, optimal health management advice.

[0646] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0647] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user to communicate with a medical professional in real time via video call; means for providing the advice generated in real time during the video call to the medical professional; means for recording the health management advice received by the user at the physical store and using the recording for the next consultation; means for centrally managing and storing information; and means for continuously providing individually optimized health management advice to the user using the generative AI model. This makes it possible to continuously provide individually optimized health management advice to the user while maintaining consistency even during health management consultations at the physical store.

[0648] "User" refers to an individual who uses the system.

[0649] "Brick and mortar" refers to a business or organization that provides services at a physical location.

[0650] "Basic information" refers to personal information such as the user's name, age, and gender.

[0651] "Genetic Information" refers to data about a user's DNA.

[0652] "Lifestyle information" refers to information about the habits and preferences of a user in their daily life.

[0653] "Server" refers to a networked computer system for storing data and performing analytical tasks.

[0654] "Analysis" refers to the process of analyzing collected data and generating meaningful information.

[0655] "Health Management Advice" means specific instructions or suggestions for maintaining or improving a User's health.

[0656] "Video calling" refers to a real-time communication method for exchanging audio and video over the Internet.

[0657] "Healthcare professional" refers to a physician or other medical professional.

[0658] "Recording" refers to the process of storing information and keeping it available for future reference.

[0659] "Centralized management" refers to the centralized management of multiple pieces of information in one place or system.

[0660] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate useful information or predictions from data.

[0661] The present invention can be implemented as a system that provides health management support in a physical store. This system is provided as a smartphone app, and allows users to input basic information, genetic information, and lifestyle information, and provides personalized, optimal health management advice based on that information.

[0662] System configuration

[0663] 1. How to enter user's basic information and genetic information:

[0664] Users download the smartphone app and enter their name, age, gender, lifestyle information, etc.

[0665] Genetic information is obtained through affiliated genetic testing services and uploaded to a server via the app.

[0666] 2. How we store and analyze your information:

[0667] The servers use Google Cloud or AWS, and the basic information, genetic information, and lifestyle information provided by users is stored in a database.

[0668] Data analysis platforms such as Python and R are used to analyze the collected information.

[0669] 3. Means for generating personalized health management advice:

[0670] Based on the analysis results, a generative AI model (e.g., ChatGPT, GPT-4) is used to generate personalized advice, including specific instructions on diet, exercise recommendations, health risk management, and more.

[0671] 4. Video calling methods:

[0672] Using the Zoom API and Twilio Video, users can conduct real-time video calls with medical professionals.

[0673] During the video call, the server provides real-time advice based on the analysis results to medical professionals.

[0674] 5. Real-time advice delivery methods:

[0675] During the video call, the generative AI model presents the generated advice to the medical professional, making appropriate suggestions to the user.

[0676] This advice also includes information to help users manage their ongoing health.

[0677] 6. Centralized information management:

[0678] The information and notes recorded by the user and medical professional during the video call are stored on the server and made available for the next consultation.

[0679] Specific examples

[0680] For example, consider the case of a 35-year-old female user using this system in a physical store. The user downloads the app, enters basic information, and uploads genetic test results. Next, she schedules a video consultation in the store and has a real-time video call with a medical professional at the scheduled time. Based on the personalized and optimized advice provided by the generative AI model, the medical professional will propose a specific health management plan. This information is stored on the server, enabling a smooth consultation the next time the user visits the store.

[0681] Prompt Sentence Examples

[0682] By inputting the following prompt sentences into the generative AI model, personalized health management advice will be generated:

[0683] We will provide the user's basic information and genetic information below. Based on this, we would like you to generate optimal health management advice for the user.

[0684] Basic information: Age 35, female, no exercise habits

[0685] Genetic information: High-risk items (cardiovascular disease risk, diabetes risk)

[0686] Lifestyle information: Desk work, drinks 3 times a week

[0687] Generate your health advice in the following format:

[0688] Improved diet

[0689] Exercise recommendations

[0690] Health Risk Management

[0691] In this way, personalized and optimal health management advice based on the user's genetic information and lifestyle information can be provided.

[0692] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0693] Step 1:

[0694] The user downloads the application and enters basic information. The user enters their name, age, gender, and lifestyle information (e.g., drinking frequency, exercise habits, etc.) into the smartphone application. The application sends the entered information to the server and stores it in a database.

[0695] Step 2:

[0696] The user provides genetic information. The user obtains the genetic information using a test kit from a partner genetic testing institution. The genetic information is then uploaded to the server via a smartphone application. The server stores the received genetic information in a database.

[0697] Step 3:

[0698] The server analyzes the information provided by the user. Using a data analysis platform such as Python or R, the server analyzes the received basic information, genetic information, and lifestyle information. The results of the analysis are output as data on the user's health risks and optimal lifestyle habits, and are stored in a database.

[0699] Step 4:

[0700] A user books a video consultation. The user uses the application to book a date and time for a video consultation at a physical store. The selected date and time and the user's information are sent to the server, and the reservation information is saved in the database.

[0701] Step 5:

[0702] The server notifies the medical professional of the appointment information. When the appointment time approaches, the server sends a notification to the medical professional and the user via email or push notification so that they can prepare for the video call.

[0703] Step 6:

[0704] At the appointment time, a video call is initiated between the user's smartphone and the medical professional's device via the application, using the Zoom API and Twilio Video.

[0705] Step 7:

[0706] Real-time advice generation: The server uses a generative AI model (e.g., ChatGPT, GPT-4) to generate real-time health management advice, which is then provided to the medical professional's device during the video call.

[0707] Step 8:

[0708] Medical experts provide advice to users. During the video call, the medical experts propose specific health management plans to users based on advice provided by the server, including recommendations for improving diet and exercise.

[0709] Step 9:

[0710] Centralized information management and recording: During the video call, users and medical professionals record any notes, new questions, or lifestyle changes they make, and send them to the server via the application. The server stores this information in a database and makes it available for the next consultation.

[0711] At each step, data processing or calculation is performed based on specific input data, and the results are used as the output that forms the basis for the next processing step.

[0712] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0713] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and combines it with an emotion engine that recognizes the user's emotions. This system includes a means for the user to input or provide basic information and genetic information, a means for storing and analyzing this information, a means for generating personalized, optimal health management advice for the user based on the analysis results, a means for the user to communicate with a doctor in real time via video call, a means for centrally managing and storing information recorded during the video call, and an emotion engine that recognizes the user's emotions.

[0714] A natural language description of the program's operation

[0715] The processing of the present system proceeds as follows.

[0716] User registration and provision of genetic information

[0717] 1. User:

[0718] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the register button.

[0719] 2. Server:

[0720] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[0721] 3. User:

[0722] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[0723] 4. Server:

[0724] The server receives the uploaded genetic information and stores it in a database.

[0725] Video consultation booking and call management

[0726] 5. User:

[0727] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[0728] 6. Server:

[0729] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[0730] Providing real-time advice

[0731] 7. Terminal (user / doctor terminal):

[0732] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[0733] 8. Server:

[0734] Using a generative AI model, the system collects genetic, basic, and lifestyle data provided by the user, analyzes it, and generates personalized health management advice that is provided to a doctor via video call in real time.

[0735] Use of emotion engine

[0736] 9. Terminal (user / doctor terminal):

[0737] During a video call, the emotion engine analyzes emotional information from the user's facial expressions, tone of voice, and choice of words.

[0738] 10. Server:

[0739] The system receives the emotional information generated by the emotion engine and adjusts the content and tone of the health management advice provided based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on relaxation methods and stress management.

[0740] Centralized management and recording of information

[0741] 11. Terminal (user / doctor terminal):

[0742] During the video call, the doctor and user take notes and record any questions or lifestyle changes the user may have.

[0743] 12. Server:

[0744] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database. This information can be reused during the next consultation, ensuring that the health management plan is always based on the most up-to-date information.

[0745] Specific examples

[0746] Tanaka's case

[0747] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the information to the server.

[0748] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[0749] At the same time, during the video call, the emotion engine analyzed Tanaka's facial expressions and tone of voice to detect changes in what she was saying and her emotions. The server also analyzed this emotional information and detected that she was feeling stressed, so it added specific advice on how to relax and manage stress.

[0750] Based on the advice, the doctor proposed a specific health management plan for Mr. Tanaka, and also recorded any new questions or notes that arose during the call. All of this information was saved on a server and used during the next consultation.

[0751] With this system, Tanaka will not only receive personalized health management advice based on her genetic information, but will also receive detailed support tailored to her emotional state, which is expected to improve both her physical and mental health.

[0752] The processing flow will be explained below.

[0753] Step 1:

[0754] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[0755] Step 2:

[0756] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[0757] Step 3:

[0758] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[0759] Step 4:

[0760] The server receives the uploaded genetic information and stores it in a database.

[0761] Step 5:

[0762] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[0763] Step 6:

[0764] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[0765] Step 7:

[0766] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[0767] Step 8:

[0768] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[0769] Step 9:

[0770] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[0771] Step 10:

[0772] The advice from the server is displayed on the terminal (doctor's terminal), and the doctor provides appropriate advice to the user based on it and proposes a health management plan.

[0773] Step 11:

[0774] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and selected words to generate emotional information.

[0775] Step 12:

[0776] The server receives the emotion information generated by the emotion engine and uses it to adjust the content and tone of the health care advice provided, for example, emphasizing relaxation and stress management advice if the user is feeling stressed.

[0777] Step 13:

[0778] At the terminals (user and doctor terminals), the user and doctor take notes and record questions from the user and lifestyle changes.

[0779] Step 14:

[0780] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[0781] Step 15:

[0782] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[0783] Example 2

[0784] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0785] In recent years, interest in health management has grown, and providing personalized, optimal health advice is becoming increasingly important. However, there is a lack of means to provide appropriate, real-time, personalized health management advice based on genetic and lifestyle information to users who need it. Furthermore, there are no systems that provide detailed advice that takes users' emotions into consideration. This leads to a lack of centralized management of information, making it difficult to provide effective health management advice tailored to the user's actual lifestyle.

[0786] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0787] In this invention, the server includes means for a user to input or provide basic information and genetic information, means for storing and analyzing the provided genetic information, basic information, and lifestyle information, and means for generating personalized health management advice for the user based on the analysis results. This allows personalized health management advice to be provided in real time based on the user's specific genetic information and lifestyle information, and further takes into account the user's emotions, enabling more effective and centralized health management.

[0788] "User basic information" refers to information that identifies an individual user, such as the user's name, age, gender, email address, and password.

[0789] "Genetic information" refers to data regarding a user's DNA sequence and the genetic characteristics based thereon.

[0790] "Lifestyle information" refers to information about the user's daily life, including eating habits, exercise habits, sleep patterns, alcohol and tobacco use, and the like.

[0791] "Means for storing and analyzing" refers to a set of hardware and software for storing genetic information, basic information, and lifestyle information provided by users in a database and performing analysis based on that data.

[0792] "Means for generating individually optimized health management advice" refers to means that have the function of using a generative AI model to generate health management suggestions and advice appropriate for the user based on stored user information.

[0793] "Video calling tool" means software and hardware that allows users to communicate with medical professionals in real time over the Internet.

[0794] "Centralized management and storage means" means a means for aggregating, managing and storing all user information, including information recorded during video calls, in a central database.

[0795] An "emotion engine" is software that analyzes a user's facial expressions, tone of voice, and word choice to generate emotional information.

[0796] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and by combining it with an emotion engine that analyzes the user's emotions, it provides detailed support. The following describes in detail the modes for implementing this system.

[0797] Registration of basic user information and genetic information

[0798] Users access the service through an application or website, open a new registration screen, and enter basic information such as name, age, gender, email address, and password. This information is sent to the server and securely stored in a database. The user obtains genetic information using a test kit from a partner genetic testing institution and uploads it to the server. The uploaded genetic information is received by the server and securely stored in a database.

[0799] Video consultation booking and real-time calls

[0800] The user books a video consultation through the application or website. The reservation information is sent to the server and stored in a database. When the appointment time approaches, a reminder notification is sent to the medical professional and the user. At the scheduled time, a video call is automatically started, allowing the user and medical professional to communicate in real time.

[0801] Providing personalized and optimal health management advice

[0802] The server uses a generative AI model to collect and analyze the genetic information, basic information, and lifestyle information provided by the user. Based on the results of this analysis, it generates personalized, optimal health management advice. The generated advice is provided in real time to a medical professional on a video call, who can provide specific advice to the user. For example, the following prompt could be used: "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Also, please add advice for when the user is feeling stressed."

[0803] Emotion analysis using an emotion engine

[0804] During a video call, the emotion engine analyzes the user's facial expressions, voice tone, and word choice in real time. Emotional information is generated and sent to the server, which then uses this information to adjust the content and tone of the health care advice. For example, if the user is feeling stressed, the engine can emphasize relaxation and stress management advice.

[0805] Centralized management and recording of information

[0806] During the video call, the medical professional and user can use the notes feature to record any questions or new lifestyle changes. This information is sent to the server and securely stored in a database. The saved information is easily accessible during the next consultation and used to provide an updated health management plan.

[0807] As a concrete example, User A (a 37-year-old woman) uses this system because she is interested in health risks based on her genetic information. She downloads the app, registers, obtains genetic information using a partner genetic testing kit, and uploads that information to the server. She then schedules a video consultation and discusses with a medical professional in real time. The server generates optimal health management advice based on User A's information, and the emotion engine analyzes her emotions to provide tailored support.

[0808] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0809] Step 1: User Registration

[0810] The user accesses an application or website, enters basic information such as name, age, gender, email address, and password on the new registration screen, and clicks the "Register" button. The input data is sent to the server as basic information data.

[0811] The server receives the submitted basic information and stores it in a database. It sends the user a confirmation email to confirm registration. The email contains an authentication link, and the user activates the account by clicking the link. The input is basic information, and the output is saving it in a database and sending a confirmation email.

[0812] Step 2: Provide genetic information

[0813] Users receive a test kit from a partner genetic testing institution, follow the instructions to take a genetic sample, and then send the test kit to the testing institution, where their genetic information is then uploaded to a server via the app or website.

[0814] The server receives the uploaded genetic information and stores it in a secure database. The input is the genetic information, and the output is storing it in the database and notifying the user.

[0815] Step 3: Book a video consultation

[0816] The user logs in to the application or website, opens the video consultation reservation screen, selects the desired date and time, and clicks the "Book" button. The reservation information is sent to the server as reservation data.

[0817] The server receives the submitted appointment information and stores it in a database. When the appointment time approaches, it sends reminder notifications to medical professionals and users. The input is the appointment information, and the output is storing it in the database and sending notifications.

[0818] Step 4: Start a video call

[0819] When the appointment time arrives, a video call will automatically start between the user and the medical professional, allowing them to communicate in real time.

[0820] The terminal establishes a video call session and sends the information to the server. The input is reservation information, and the output is the start of the video call session.

[0821] Step 5: Data collection and analysis

[0822] The server uses a generative AI model to collect genetic, basic, and lifestyle information provided by the user, and the collected data is processed as analytical data.

[0823] The generative AI model analyzes the collected data and generates personalized, optimal health management advice. In this process, a prompt is used to generate appropriate advice. For example, the prompt might read, "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Please also add advice for when the user is feeling stressed." The input is the collected basic information, genetic information, and lifestyle information, and the output is advice as a result of the analysis.

[0824] Step 6: Emotion analysis using the emotion engine

[0825] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and word choice in real time, and the analyzed emotion information is sent to the server.

[0826] The server receives the emotional information and adjusts the content and tone of the health care advice based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on stress management and relaxation methods. The input is emotional data, and the output is the adjusted advice.

[0827] Step 7: Centralize and record information

[0828] During the video call, the medical professional and the user use the notes feature to record questions and lifestyle changes, which are then sent to the server.

[0829] The server receives the transmitted information and stores it centrally in a database. The stored information is reused at the next consultation and used to provide an updated health management plan. The input is recorded information during the call, and the output is stored in the database.

[0830] These processing steps enable users to receive personalized and optimal health management advice based on genetic and lifestyle information, and also to receive detailed support that also addresses their emotional state.

[0831] (Application example 2)

[0832] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0833] Modern health management requires personalized, optimized advice based on a user's genetic and lifestyle information. However, existing systems have been unable to provide personalized advice in real time or adjust the content and tone of the advice based on the user's emotional state. Furthermore, there has been no means of providing personalized health-related advertisements, making it difficult to effectively deliver health information tailored to the user. The present invention aims to solve these problems and provide a system that provides personalized health management advice and health-related advertisements based on a user's genetic and lifestyle information.

[0834] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0835] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user and a doctor to communicate in real time via video call; means for centrally managing and storing information recorded during the video call; means for generating and displaying health-related advertisements optimized for the user based on the analyzed user's health information; and means for analyzing emotions from the user's facial expressions and tone of voice during the video call using an emotion engine and adjusting the timing and content of advertisement display based on the analysis results, thereby enabling the provision of individually optimized health management advice and health-related advertisements based on the user's genetic information and lifestyle information.

[0836] "Means for users to input or provide their basic and genetic information" refers to the interface through which users provide their basic and genetic information to the system, which may include web forms or dedicated applications.

[0837] "Means for storing and analyzing provided genetic information, basic information, and lifestyle information" refers to software and hardware configurations for storing the genetic information, basic information, and lifestyle information provided by the user in a database and analyzing that information.

[0838] The "means for generating individually optimal health management advice for a user based on the analysis results" refers to an algorithm and program for generating health management advice customized for each user based on the stored information.

[0839] "Means for real-time communication between users and doctors via video calls" refers to a system that allows users to communicate with medical professionals in real time using video calling functionality. This includes video calling applications and communication networks.

[0840] "A means for centrally managing and storing information recorded during video calls" refers to a system for storing information such as notes, questions, and comments exchanged during video calls in a database and managing them centrally.

[0841] "Means for generating and displaying health-related advertisements optimized for a user based on the analyzed health information of the user" refers to a system for generating health-related advertisements individually optimized for a user based on the analysis results and displaying them on the user's device.

[0842] "Means of using an emotion engine to analyze emotions from a user's facial expression and tone of voice during a video call, and adjusting the timing and content of advertisement display based on the analysis results" is a technology that analyzes a user's facial expression and tone of voice during a video call, and dynamically adjusts the timing and content of advertisement display according to their emotional state.

[0843] This invention provides a system that provides personalized and optimal health management advice based on a user's genetic information and lifestyle information, and further analyzes the user's emotional state to tailor health-related advertisements. Specific embodiments for implementing this system are described below.

[0844] System Overview

[0845] The present invention is composed of a series of hardware and software including a user terminal, a server, and an emotion engine. The system has the following main functions:

[0846] 1. User registration and provision of genetic information

[0847] Users access a dedicated application or website and enter or upload basic information (such as name, age, gender, and email address) and genetic information. The genetic information is obtained from affiliated genetic testing institutions.

[0848] 2. Information storage and analysis

[0849] The server stores and analyzes basic information, genetic information, and lifestyle information provided by users, using a generative AI model.

[0850] 3. Generating personalized health management advice

[0851] Based on the analysis results, the server generates personalized health care advice for the user, which is provided to a medical professional during the video call.

[0852] 4. Real-time communication via video calls

[0853] Users and medical professionals communicate in real time using the video call feature, and information recorded during the video call is stored centrally and can be used for future consultations.

[0854] 5. Generating and displaying health-related advertisements

[0855] Based on the analysis results, the server generates optimal health-related advertisements for the user and displays them on the user's device. The advertisement content is individually optimized based on the user's health condition and lifestyle.

[0856] 6. Use of Emotion Engines

[0857] During a video call, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information. The server then adjusts the timing and content of advertisements based on this emotional information.

[0858] Hardware and software used

[0859] User devices: smartphones, tablets, computers

[0860] Server: Cloud or Dedicated Server

[0861] Generative AI models: Deep learning frameworks such as TensorFlow and Keras

[0862] Emotion engine: OpenCV, TensorFlow

[0863] Specific examples

[0864] For example, let's say a male user in his 30s uses the system. This user downloads the smartphone app and enters basic information (name, age, gender). Using a kit from a partner genetic testing institution, genetic information is obtained and uploaded to the database.

[0865] Users can schedule a video call through the app, and when the time comes, they will speak with a medical professional in real time. The server analyzes the user's genetic information, basic information, and lifestyle data, and based on the results, provides the medical professional with personalized health management advice. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the timing and content of advertisements based on their emotional information.

[0866] An example prompt might look like this:

[0867] "Male in his 30s, active, and eats a balanced diet. Low genetic risk, but currently experiencing stress. Create an ad for a health supplement with a relaxing effect."

[0868] In this way, the present invention provides individualized and optimal health management advice and health-related advertisements based on the user's genetic information and lifestyle information, and is expected to help the user maintain and improve their health.

[0869] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0870] Step 1:

[0871] The user inputs or provides basic information and genetic information.

[0872] Input: Name, age, gender, email address, and genetic information entered by users through smartphone apps or websites.

[0873] Processing: The user terminal sends the entered information to the server.

[0874] Output: User's basic information and genetic information stored on the server.

[0875] Step 2:

[0876] The server stores and analyzes the provided genetic information, basic information, and lifestyle information.

[0877] Input: Basic, genetic, and lifestyle information submitted by the user.

[0878] Processing: The information is stored in a database and analyzed using generative AI models, using deep learning frameworks such as TensorFlow and Keras.

[0879] Output: Health risk data and appropriate health advice indicators generated as a result of the analysis.

[0880] Step 3:

[0881] The server generates optimal individual health management advice for the user based on the analysis results.

[0882] Input: Analysis results from a generative AI model.

[0883] Processing: Based on the analysis results, the system creates personalized health management advice, such as automatically generating dietary suggestions and exercise advice.

[0884] Output: Personalized optimal health care advice provided to the user.

[0885] Step 4:

[0886] Users and medical professionals communicate in real time via video calls.

[0887] Input: Video call appointment information and generated health care advice.

[0888] Processing: When the video call starts, the server provides the generated advice to the medical professional's device and starts the video call. During the video call, questions from the user and comments from the doctor are recorded.

[0889] Output: Feedback and further advice from a medical professional via video call.

[0890] Step 5:

[0891] The server centrally manages and stores information recorded during video calls.

[0892] Input: Notes, questions, and lifestyle changes recorded by the doctor and user during the video call.

[0893] Processing: This information is stored in a database and managed so that it can be used for the next consultation.

[0894] Output: Recording information during the video call stored in a database.

[0895] Step 6:

[0896] The server generates and displays health-related advertisements optimized for the user based on the analyzed health information of the user.

[0897] Input: Analysis results and health management advice from the generative AI model.

[0898] Processing: Based on the user's health status and lifestyle, personalized health-related advertisements are generated and displayed on the user's device.

[0899] Output: Health-related advertisements displayed on the user's device.

[0900] Step 7:

[0901] Using an emotion engine, the system analyzes the user's emotions from their facial expressions and tone of voice during a video call, and adjusts the timing and content of advertisements based on the analysis results.

[0902] Input: Your facial expressions and tone of voice during a video call.

[0903] Processing: Sentiment analysis is performed using OpenCV and TensorFlow to identify the user's emotional state, and ad timing and content are adjusted in real time based on this.

[0904] Output: Adjusted ad content and timing.

[0905] The above is a specific program processing flow based on the processing steps of the present invention.

[0906] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0907] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0908] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0909] [Third embodiment]

[0910] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0911] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0912] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0913] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0914] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0915] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0916] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0917] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0918] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0919] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0920] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0921] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0922] The present invention is a system that provides personalized, optimal health management advice based on genetic and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a doctor via video call, and a means for centrally managing and storing information.

[0923] A natural language description of the program's operation

[0924] The processing of the present system proceeds as follows.

[0925] User registration and provision of genetic information

[0926] 1. User:

[0927] Users register with the system through an app or website and enter basic information, including their name, age, gender, and email address.

[0928] Users obtain genetic information using a test kit from a partner genetic testing institution and upload the results to a server.

[0929] 2. Server:

[0930] The server receives the basic information entered by the user and the genetic information provided, and stores it in a database.

[0931] Video consultation booking and call management

[0932] 3. User:

[0933] Users can book a video consultation through the app or website, select the desired date and time, and confirm the appointment.

[0934] 4. Server:

[0935] The server receives the reservation information sent by the user and stores it in a database. When the reservation time arrives, it notifies both the doctor and the user.

[0936] Providing real-time advice

[0937] 5. Terminal (user / doctor terminal):

[0938] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[0939] 6. Server:

[0940] Using a generative AI model, the system generates personalized health management advice based on the user's genetic, basic, and lifestyle data, which is then provided to a doctor in real time via video call.

[0941] 7. Terminal (Doctor's terminal):

[0942] The doctor will communicate the advice provided by the server to the user and propose an appropriate health management plan, including recommendations for improving diet and exercise.

[0943] Centralized management and recording of information

[0944] 8. Terminal (user / doctor terminal):

[0945] During the video call, the doctor and user take notes and record information such as questions from the user and lifestyle changes, which are then entered into the device.

[0946] 9. Server:

[0947] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database, ensuring that the user's next consultation and health management plan reflects the most up-to-date information.

[0948] Specific examples

[0949] Tanaka's case

[0950] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and then obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the results to the server.

[0951] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[0952] Based on the advice received from the server, the doctor made specific health management suggestions to Mr. Tanaka. Any new questions or notes that arose during the call were also recorded and saved on the server.

[0953] In this way, Mr. Tanaka will be able to receive optimal, individualized health management advice based on his genetic information, and it is expected that his next consultation will also proceed smoothly.

[0954] The method of providing optimal individual health management advice realized by this system is an effective means of promoting improvement in the user's health.

[0955] The processing flow will be explained below.

[0956] Step 1:

[0957] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the register button.

[0958] Step 2:

[0959] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[0960] Step 3:

[0961] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[0962] Step 4:

[0963] The server receives the uploaded genetic information and stores it in a database.

[0964] Step 5:

[0965] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[0966] Step 6:

[0967] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[0968] Step 7:

[0969] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[0970] Step 8:

[0971] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[0972] Step 9:

[0973] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[0974] Step 10:

[0975] The doctor's terminal displays advice from the server, and the doctor uses this information to provide appropriate advice to the user and propose a health management plan.

[0976] Step 11:

[0977] During the video call, the user and doctor take notes and record the user's questions and lifestyle changes on the device.

[0978] Step 12:

[0979] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[0980] Step 13:

[0981] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[0982] Example 1

[0983] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0984] In modern society, people's lifestyles are becoming more diverse, creating a demand for customized health management advice tailored to each individual's health condition. However, existing health management systems can only provide general advice, making it difficult to provide individually tailored advice based on genetic and lifestyle information. Furthermore, when users and medical professionals make video calls for health management, there is an insufficient mechanism for centrally managing that information and effectively utilizing it for the next consultation.

[0985] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0986] In this invention, the server includes means for using a generative AI model to generate real-time advice based on user data, means for inputting prompt text into the generative AI model to generate personalized advice, and means for reminding the user of the appointment time through a notification function. This makes it possible to provide personalized, optimal health management advice in real time based on the user's genetic information and lifestyle information, and further makes it possible to effectively use this information for the next consultation.

[0987] "User" refers to an individual who uses this system and who inputs information or receives services through an application or website.

[0988] "Basic information" refers to personal information entered by the user, such as name, age, gender, and email address.

[0989] "Genetic information" refers to data obtained through a user's genetic testing, and includes information about specific health risks and physical constitutions.

[0990] "Lifestyle information" refers to data related to a user's diet, exercise, sleep, stress, etc.

[0991] "Storage" refers to the act of recording and retaining data on a server or database.

[0992] "Analysis" refers to the process of performing calculations and evaluations based on collected data to derive useful information and results.

[0993] "Individually optimal health management advice" refers to instructions and suggestions regarding optimized health management based on the user's individual genetic information and lifestyle information.

[0994] "Video calling" refers to a technology that allows users and medical professionals to communicate in real time via video and audio over the Internet.

[0995] "Medical professionals" refer to people with specialized knowledge and qualifications, such as doctors, nutritionists, and trainers, who are responsible for providing health management advice to users.

[0996] "Centralized management" refers to the unification of different types of information, organizing and storing them, and managing them efficiently.

[0997] A "generative AI model" refers to an artificial intelligence program that generates results using specific algorithms based on input data.

[0998] A "prompt" refers to a command or question that is input into a generative AI model, and serves as a trigger for the model to generate the necessary data.

[0999] "Notification" refers to the system's ability to notify users and medical professionals of important events and actions.

[1000] "Reservation System" means an online system that allows a User to select and confirm a date and time for a video call.

[1001] "Notes" refer to vague information, questions, comments, etc. recorded by users or medical professionals during video calls.

[1002] This invention is a system that provides personalized, optimal health management advice based on genetic information and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a medical professional via video call, and a means for centrally managing and storing information.

[1003] User registration and provision of genetic information

[1004] To start using the system, users must first open a dedicated application or website on their smartphone or personal computer (PC) and register. Users must enter basic information such as their name, age, gender, and email address.

[1005] Next, the user purchases a test kit from an affiliated genetic testing institution, collects a genetic sample according to the instructions, and sends it to the testing institution. When the test results are provided a few days later, the user uploads them to a dedicated application or their personal page on the website. At this time, the server receives the basic information and genetic information provided by the user and encrypts and stores it in a relational database such as MySQL or MongoDB or a NoSQL database. The encryption is performed using technologies such as AES (Advanced Encryption Standard).

[1006] Video consultation booking and call management

[1007] The user selects a date and time for a video consultation using a dedicated application or a website reservation system, and makes a reservation. The server receives this reservation information and records it in a database. When the reservation time approaches, the server sends reminder emails to both the user and the medical professional. This email is sent using an SMTP server.

[1008] Providing real-time advice

[1009] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, which is conducted using WebRTC (Web Real-Time Communication) technology.

[1010] During this time, the server launches the generative AI model and performs analysis based on the genetic information, basic information, and lifestyle habit data provided by the user. The server inputs a prompt into the generative AI model to generate personalized, optimal advice. For example, the following prompts are used:

[1011] "I'm a 37-year-old woman named Tanaka. I'm concerned about health risks based on my genetic information, and I'd like advice on improving my diet and recommending exercise. Please generate personalized, optimal health management advice based on my genetic information, basic information, and lifestyle data."

[1012] The generated advice is sent in real time to the terminal of a medical professional, who can then use the advice to propose an appropriate health management plan to the user.

[1013] Centralized management and recording of information

[1014] During the video call, the medical professional and the user can input any new questions, lifestyle changes, or other important notes into the device. This information is then recorded in a database managed by the server. This information can be used to provide more detailed health management advice during the next consultation.

[1015] As described above, this system enables optimal health management for each individual user, provides highly accurate real-time advice, and enables effective use of information in the next consultation.

[1016] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1017] Step 1:

[1018] User Registration

[1019] 1. Users

[1020] Users can register by opening a dedicated application or website on their smartphone or PC, and entering basic information such as name, age, gender, and email address.

[1021] Input: Name, age, gender, email address

[1022] Output: User profile stored in registration database

[1023] 2. Server

[1024] We receive basic information submitted by users and store it in a database for future reference and analysis.

[1025] Input: Basic information

[1026] Output: Saved user profile

[1027] Step 2:

[1028] Genetic information provision

[1029] 1. Users

[1030] Users purchase a test kit from a partner genetic testing institution, collect a genetic sample according to the instructions, and send it to the testing institution. Test results are provided a few days later.

[1031] Input: Gene sample

[1032] Output: Genetic test result data

[1033] 2. Users

[1034] The provided genetic information is uploaded to a dedicated application or personal page on the website.

[1035] Input: Genetic test result data

[1036] Output: Uploaded genetic information

[1037] 3. Server

[1038] The system receives genetic information provided by users, encrypts it, and stores it in a database using technologies such as AES (Advanced Encryption Standard).

[1039] Input: Uploaded genetic information

[1040] Output: Encrypted and stored genetic information

[1041] Step 3:

[1042] Book a video consultation

[1043] 1. Users

[1044] Use the dedicated application or website reservation system to select the date and time of the video consultation and make a reservation. Reservation information is displayed in a calendar format, and you can select the desired date and time.

[1045] Input: Reservation date and time, user ID

[1046] Output: Reservation confirmation information

[1047] 2. Server

[1048] Reservation information sent by the user is received and recorded in the database. The reservation information includes the reservation date and time, user ID, and medical professional ID.

[1049] Input: Reservation information

[1050] Output: Saved reservation information

[1051] Step 4:

[1052] Video Consultation Notification

[1053] 1. Server

[1054] When the appointment time approaches, the server sends reminder emails to both the user and the medical professional. The server uses an SMTP server to send the reminder emails.

[1055] Input: Appointment information (date and time, user ID, medical professional ID)

[1056] Output: Reminder email

[1057] Step 5:

[1058] Starting a video call

[1059] 1. Terminals (user and medical professional terminals)

[1060] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, using WebRTC (Web Real-Time Communication) technology.

[1061] Input: Appointment information, User ID, Medical Professional ID

[1062] Output: Start a video call

[1063] Step 6:

[1064] Providing real-time advice

[1065] 1. Server

[1066] The generative AI model is activated to generate personalized health management advice based on the user's genetic information, basic information, and lifestyle data. The user enters a prompt and provides the generated advice to a medical professional during a video call.

[1067] Input: Genetic information, basic information, lifestyle data, prompt text

[1068] Output: Personalized and optimal health management advice

[1069] 2. Terminal (medical professional's terminal)

[1070] The medical professional reviews the advice provided by the server and proposes a specific health management plan to the user, such as "improving your diet" or "recommending exercise."

[1071] Input: Generated advice

[1072] Output: Health care plan provided

[1073] Step 7:

[1074] Centralized management and recording of information

[1075] 1. Terminals (user and medical professional terminals)

[1076] Enter new questions, lifestyle changes, and notes during the video call.

[1077] Input: Questions, lifestyle changes, notes

[1078] Output: Recorded information

[1079] 2. Server

[1080] All information entered during the video call is received and stored in a centralized database, which can then be used for the next consultation.

[1081] Input: Recorded information

[1082] Output: Centralized information saved

[1083] (Application example 1)

[1084] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1085] In modern society, interest in personal health management is growing, but providing personalized, optimal health management advice based on genetic and lifestyle information is difficult, and means for communicating with experts in real time are limited. Furthermore, there is a need to maintain consistency in in-store consultations and provide continuous, effective health management. The present invention aims to solve these problems and provide users with consistent, personalized, optimal health management advice.

[1086] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1087] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user to communicate with a medical professional in real time via video call; means for providing the advice generated in real time during the video call to the medical professional; means for recording the health management advice received by the user at the physical store and using the recording for the next consultation; means for centrally managing and storing information; and means for continuously providing individually optimized health management advice to the user using the generative AI model. This makes it possible to continuously provide individually optimized health management advice to the user while maintaining consistency even during health management consultations at the physical store.

[1088] "User" refers to an individual who uses the system.

[1089] "Brick and mortar" refers to a business or organization that provides services at a physical location.

[1090] "Basic information" refers to personal information such as the user's name, age, and gender.

[1091] "Genetic Information" refers to data about a user's DNA.

[1092] "Lifestyle information" refers to information about the habits and preferences of a user in their daily life.

[1093] "Server" refers to a networked computer system for storing data and performing analytical tasks.

[1094] "Analysis" refers to the process of analyzing collected data and generating meaningful information.

[1095] "Health Management Advice" means specific instructions or suggestions for maintaining or improving a User's health.

[1096] "Video calling" refers to a real-time communication method for exchanging audio and video over the Internet.

[1097] "Healthcare professional" refers to a physician or other medical professional.

[1098] "Recording" refers to the process of storing information and keeping it available for future reference.

[1099] "Centralized management" refers to the centralized management of multiple pieces of information in one place or system.

[1100] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate useful information or predictions from data.

[1101] The present invention can be implemented as a system that provides health management support in a physical store. This system is provided as a smartphone app, and allows users to input basic information, genetic information, and lifestyle information, and provides personalized, optimal health management advice based on that information.

[1102] System configuration

[1103] 1. How to enter user's basic information and genetic information:

[1104] Users download the smartphone app and enter their name, age, gender, lifestyle information, etc.

[1105] Genetic information is obtained through affiliated genetic testing services and uploaded to a server via the app.

[1106] 2. How we store and analyze your information:

[1107] The servers use Google Cloud or AWS, and the basic information, genetic information, and lifestyle information provided by users is stored in a database.

[1108] Data analysis platforms such as Python and R are used to analyze the collected information.

[1109] 3. Means for generating personalized health management advice:

[1110] Based on the analysis results, a generative AI model (e.g., ChatGPT, GPT-4) is used to generate personalized advice, including specific instructions on diet, exercise recommendations, health risk management, and more.

[1111] 4. Video calling methods:

[1112] Using the Zoom API and Twilio Video, users can conduct real-time video calls with medical professionals.

[1113] During the video call, the server provides real-time advice based on the analysis results to medical professionals.

[1114] 5. Real-time advice delivery methods:

[1115] During the video call, the generative AI model presents the generated advice to the medical professional, making appropriate suggestions to the user.

[1116] This advice also includes information to help users manage their ongoing health.

[1117] 6. Centralized information management:

[1118] The information and notes recorded by the user and medical professional during the video call are stored on the server and made available for the next consultation.

[1119] Specific examples

[1120] For example, consider the case of a 35-year-old female user using this system in a physical store. The user downloads the app, enters basic information, and uploads genetic test results. Next, she schedules a video consultation in the store and has a real-time video call with a medical professional at the scheduled time. Based on the personalized and optimized advice provided by the generative AI model, the medical professional will propose a specific health management plan. This information is stored on the server, enabling a smooth consultation the next time the user visits the store.

[1121] Prompt Sentence Examples

[1122] By inputting the following prompt sentences into the generative AI model, personalized health management advice will be generated:

[1123] We will provide the user's basic information and genetic information below. Based on this, we would like you to generate optimal health management advice for the user.

[1124] Basic information: Age 35, female, no exercise habits

[1125] Genetic information: High-risk items (cardiovascular disease risk, diabetes risk)

[1126] Lifestyle information: Desk work, drinks 3 times a week

[1127] Generate your health advice in the following format:

[1128] Improved diet

[1129] Exercise recommendations

[1130] Health Risk Management

[1131] In this way, personalized and optimal health management advice based on the user's genetic information and lifestyle information can be provided.

[1132] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1133] Step 1:

[1134] The user downloads the application and enters basic information. The user enters their name, age, gender, and lifestyle information (e.g., drinking frequency, exercise habits, etc.) into the smartphone application. The application sends the entered information to the server and stores it in a database.

[1135] Step 2:

[1136] The user provides genetic information. The user obtains the genetic information using a test kit from a partner genetic testing institution. The genetic information is then uploaded to the server via a smartphone application. The server stores the received genetic information in a database.

[1137] Step 3:

[1138] The server analyzes the information provided by the user. Using a data analysis platform such as Python or R, the server analyzes the received basic information, genetic information, and lifestyle information. The results of the analysis are output as data on the user's health risks and optimal lifestyle habits, and are stored in a database.

[1139] Step 4:

[1140] A user books a video consultation. The user uses the application to book a date and time for a video consultation at a physical store. The selected date and time and the user's information are sent to the server, and the reservation information is saved in the database.

[1141] Step 5:

[1142] The server notifies the medical professional of the appointment information. When the appointment time approaches, the server sends a notification to the medical professional and the user via email or push notification so that they can prepare for the video call.

[1143] Step 6:

[1144] At the appointment time, a video call is initiated between the user's smartphone and the medical professional's device via the application, using the Zoom API and Twilio Video.

[1145] Step 7:

[1146] Real-time advice generation: The server uses a generative AI model (e.g., ChatGPT, GPT-4) to generate real-time health management advice, which is then provided to the medical professional's device during the video call.

[1147] Step 8:

[1148] Medical experts provide advice to users. During the video call, the medical experts propose specific health management plans to users based on advice provided by the server, including recommendations for improving diet and exercise.

[1149] Step 9:

[1150] Centralized information management and recording: During the video call, users and medical professionals record any notes, new questions, or lifestyle changes they make, and send them to the server via the application. The server stores this information in a database and makes it available for the next consultation.

[1151] At each step, data processing or calculation is performed based on specific input data, and the results are used as the output that forms the basis for the next processing step.

[1152] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1153] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and combines it with an emotion engine that recognizes the user's emotions. This system includes a means for the user to input or provide basic information and genetic information, a means for storing and analyzing this information, a means for generating personalized, optimal health management advice for the user based on the analysis results, a means for the user to communicate with a doctor in real time via video call, a means for centrally managing and storing information recorded during the video call, and an emotion engine that recognizes the user's emotions.

[1154] A natural language description of the program's operation

[1155] The processing of the present system proceeds as follows.

[1156] User registration and provision of genetic information

[1157] 1. User:

[1158] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[1159] 2. Server:

[1160] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[1161] 3. User:

[1162] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[1163] 4. Server:

[1164] The server receives the uploaded genetic information and stores it in a database.

[1165] Video consultation booking and call management

[1166] 5. User:

[1167] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[1168] 6. Server:

[1169] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[1170] Providing real-time advice

[1171] 7. Terminal (user / doctor terminal):

[1172] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[1173] 8. Server:

[1174] Using a generative AI model, the system collects genetic, basic, and lifestyle data provided by the user, analyzes it, and generates personalized health management advice that is provided to a doctor in real time via video call.

[1175] Use of emotion engine

[1176] 9. Terminal (user / doctor terminal):

[1177] During a video call, the emotion engine analyzes emotional information from the user's facial expressions, tone of voice, and choice of words.

[1178] 10. Server:

[1179] The system receives the emotional information generated by the emotion engine and adjusts the content and tone of the health management advice provided based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on relaxation methods and stress management.

[1180] Centralized management and recording of information

[1181] 11. Terminal (user / doctor terminal):

[1182] During the video call, the doctor and user take notes and record any questions or lifestyle changes the user may have.

[1183] 12. Server:

[1184] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database. This information can be reused during the next consultation, ensuring that the health management plan is always based on the most up-to-date information.

[1185] Specific examples

[1186] Tanaka's case

[1187] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the information to the server.

[1188] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[1189] At the same time, during the video call, the emotion engine analyzed Tanaka's facial expressions and tone of voice to detect changes in what she was saying and her emotions. The server also analyzed this emotional information and detected that she was feeling stressed, so it added specific advice on how to relax and manage stress.

[1190] Based on the advice, the doctor proposed a specific health management plan for Mr. Tanaka, and also recorded any new questions or notes that arose during the call. All of this information was saved on a server and used during the next consultation.

[1191] With this system, Tanaka will not only receive personalized health management advice based on her genetic information, but will also receive detailed support tailored to her emotional state, which is expected to improve both her physical and mental health.

[1192] The processing flow will be explained below.

[1193] Step 1:

[1194] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[1195] Step 2:

[1196] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[1197] Step 3:

[1198] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[1199] Step 4:

[1200] The server receives the uploaded genetic information and stores it in a database.

[1201] Step 5:

[1202] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[1203] Step 6:

[1204] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[1205] Step 7:

[1206] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[1207] Step 8:

[1208] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[1209] Step 9:

[1210] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[1211] Step 10:

[1212] The advice from the server is displayed on the terminal (doctor's terminal), and the doctor provides appropriate advice to the user based on it and proposes a health management plan.

[1213] Step 11:

[1214] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and selected words to generate emotional information.

[1215] Step 12:

[1216] The server receives the emotion information generated by the emotion engine and uses it to adjust the content and tone of the health care advice provided, for example, emphasizing relaxation and stress management advice if the user is feeling stressed.

[1217] Step 13:

[1218] At the terminals (user and doctor terminals), the user and doctor take notes and record questions from the user and lifestyle changes.

[1219] Step 14:

[1220] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[1221] Step 15:

[1222] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[1223] Example 2

[1224] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1225] In recent years, interest in health management has grown, and providing personalized, optimal health advice is becoming increasingly important. However, there is a lack of means to provide appropriate, real-time, personalized health management advice based on genetic and lifestyle information to users who need it. Furthermore, there are no systems that provide detailed advice that takes users' emotions into consideration. This leads to a lack of centralized management of information, making it difficult to provide effective health management advice tailored to the user's actual lifestyle.

[1226] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1227] In this invention, the server includes means for a user to input or provide basic information and genetic information, means for storing and analyzing the provided genetic information, basic information, and lifestyle information, and means for generating personalized health management advice for the user based on the analysis results. This allows personalized health management advice to be provided in real time based on the user's specific genetic information and lifestyle information, and further takes into account the user's emotions, enabling more effective and centralized health management.

[1228] "User basic information" refers to information that identifies an individual user, such as the user's name, age, gender, email address, and password.

[1229] "Genetic information" refers to data regarding a user's DNA sequence and the genetic characteristics based thereon.

[1230] "Lifestyle information" refers to information about the user's daily life, including eating habits, exercise habits, sleep patterns, alcohol and tobacco use, and the like.

[1231] "Means for storing and analyzing" refers to a set of hardware and software for storing genetic information, basic information, and lifestyle information provided by users in a database and performing analysis based on that data.

[1232] "Means for generating individually optimized health management advice" refers to means that have the function of using a generative AI model to generate health management suggestions and advice appropriate for the user based on stored user information.

[1233] "Video calling tool" means software and hardware that allows users to communicate with medical professionals in real time over the Internet.

[1234] "Centralized management and storage means" means a means for aggregating, managing and storing all user information, including information recorded during video calls, in a central database.

[1235] An "emotion engine" is software that analyzes a user's facial expressions, tone of voice, and word choice to generate emotional information.

[1236] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and by combining it with an emotion engine that analyzes the user's emotions, it provides detailed support. The following describes in detail the modes for implementing this system.

[1237] Registration of basic user information and genetic information

[1238] Users access the service through an application or website, open a new registration screen, and enter basic information such as name, age, gender, email address, and password. This information is sent to the server and securely stored in a database. The user obtains genetic information using a test kit from a partner genetic testing institution and uploads it to the server. The uploaded genetic information is received by the server and securely stored in a database.

[1239] Video consultation booking and real-time calls

[1240] The user books a video consultation through the application or website. The reservation information is sent to the server and stored in a database. When the appointment time approaches, a reminder notification is sent to the medical professional and the user. At the scheduled time, a video call is automatically started, allowing the user and medical professional to communicate in real time.

[1241] Providing personalized and optimal health management advice

[1242] The server uses a generative AI model to collect and analyze the genetic information, basic information, and lifestyle information provided by the user. Based on the results of this analysis, it generates personalized, optimal health management advice. The generated advice is provided in real time to a medical professional on a video call, who can provide specific advice to the user. For example, the following prompt could be used: "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Also, please add advice for when the user is feeling stressed."

[1243] Emotion analysis using an emotion engine

[1244] During a video call, the emotion engine analyzes the user's facial expressions, voice tone, and word choice in real time. Emotional information is generated and sent to the server, which then uses this information to adjust the content and tone of the health care advice. For example, if the user is feeling stressed, the engine can emphasize relaxation and stress management advice.

[1245] Centralized management and recording of information

[1246] During the video call, the medical professional and user can use the notes feature to record any questions or new lifestyle changes. This information is sent to the server and securely stored in a database. The saved information is easily accessible during the next consultation and used to provide an updated health management plan.

[1247] As a concrete example, User A (a 37-year-old woman) uses this system because she is interested in health risks based on her genetic information. She downloads the app, registers, obtains genetic information using a partner genetic testing kit, and uploads that information to the server. She then schedules a video consultation and discusses with a medical professional in real time. The server generates optimal health management advice based on User A's information, and the emotion engine analyzes her emotions to provide tailored support.

[1248] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1249] Step 1: User Registration

[1250] The user accesses an application or website, enters basic information such as name, age, gender, email address, and password on the new registration screen, and clicks the "Register" button. The input data is sent to the server as basic information data.

[1251] The server receives the submitted basic information and stores it in a database. It sends the user a confirmation email to confirm registration. The email contains an authentication link, and the user activates the account by clicking the link. The input is basic information, and the output is saving it in a database and sending a confirmation email.

[1252] Step 2: Provide genetic information

[1253] Users receive a test kit from a partner genetic testing institution, follow the instructions to take a genetic sample, and then send the test kit to the testing institution, where their genetic information is then uploaded to a server via the app or website.

[1254] The server receives the uploaded genetic information and stores it in a secure database. The input is the genetic information, and the output is storing it in the database and notifying the user.

[1255] Step 3: Book a video consultation

[1256] The user logs in to the application or website, opens the video consultation reservation screen, selects the desired date and time, and clicks the "Book" button. The reservation information is sent to the server as reservation data.

[1257] The server receives the submitted appointment information and stores it in a database. When the appointment time approaches, it sends reminder notifications to medical professionals and users. The input is the appointment information, and the output is storing it in the database and sending notifications.

[1258] Step 4: Start a video call

[1259] When the appointment time arrives, a video call will automatically start between the user and the medical professional, allowing them to communicate in real time.

[1260] The terminal establishes a video call session and sends the information to the server. The input is reservation information, and the output is the start of the video call session.

[1261] Step 5: Data collection and analysis

[1262] The server uses a generative AI model to collect genetic, basic, and lifestyle information provided by the user, and the collected data is processed as analytical data.

[1263] The generative AI model analyzes the collected data and generates personalized, optimal health management advice. In this process, a prompt is used to generate appropriate advice. For example, the prompt might read, "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Please also add advice for when the user is feeling stressed." The input is the collected basic information, genetic information, and lifestyle information, and the output is advice as a result of the analysis.

[1264] Step 6: Emotion analysis using the emotion engine

[1265] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and word choice in real time, and the analyzed emotion information is sent to the server.

[1266] The server receives the emotional information and adjusts the content and tone of the health care advice based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on stress management and relaxation methods. The input is emotional data, and the output is the adjusted advice.

[1267] Step 7: Centralize and record information

[1268] During the video call, the medical professional and the user use the notes feature to record questions and lifestyle changes, which are then sent to the server.

[1269] The server receives the transmitted information and stores it centrally in a database. The stored information is reused at the next consultation and used to provide an updated health management plan. The input is recorded information during the call, and the output is stored in the database.

[1270] These processing steps enable users to receive personalized and optimal health management advice based on genetic and lifestyle information, and also to receive detailed support that also addresses their emotional state.

[1271] (Application example 2)

[1272] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1273] Modern health management requires personalized, optimized advice based on a user's genetic and lifestyle information. However, existing systems have been unable to provide personalized advice in real time or adjust the content and tone of the advice based on the user's emotional state. Furthermore, there has been no means of providing personalized health-related advertisements, making it difficult to effectively deliver health information tailored to the user. The present invention aims to solve these problems and provide a system that provides personalized health management advice and health-related advertisements based on a user's genetic and lifestyle information.

[1274] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1275] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user and a doctor to communicate in real time via video call; means for centrally managing and storing information recorded during the video call; means for generating and displaying health-related advertisements optimized for the user based on the analyzed user's health information; and means for analyzing emotions from the user's facial expressions and tone of voice during the video call using an emotion engine and adjusting the timing and content of advertisement display based on the analysis results, thereby enabling the provision of individually optimized health management advice and health-related advertisements based on the user's genetic information and lifestyle information.

[1276] "Means for users to input or provide their basic and genetic information" refers to the interface through which users provide their basic and genetic information to the system, which may include web forms or dedicated applications.

[1277] "Means for storing and analyzing provided genetic information, basic information, and lifestyle information" refers to software and hardware configurations for storing the genetic information, basic information, and lifestyle information provided by the user in a database and analyzing that information.

[1278] The "means for generating individually optimal health management advice for a user based on the analysis results" refers to an algorithm and program for generating health management advice customized for each user based on the stored information.

[1279] "Means for real-time communication between users and doctors via video calls" refers to a system that allows users to communicate with medical professionals in real time using video calling functionality. This includes video calling applications and communication networks.

[1280] "A means for centrally managing and storing information recorded during video calls" refers to a system for storing information such as notes, questions, and comments exchanged during video calls in a database and managing them centrally.

[1281] "Means for generating and displaying health-related advertisements optimized for a user based on the analyzed health information of the user" refers to a system for generating health-related advertisements individually optimized for a user based on the analysis results and displaying them on the user's device.

[1282] "Means of using an emotion engine to analyze emotions from a user's facial expression and tone of voice during a video call, and adjusting the timing and content of advertisement display based on the analysis results" is a technology that analyzes a user's facial expression and tone of voice during a video call, and dynamically adjusts the timing and content of advertisement display according to their emotional state.

[1283] This invention provides a system that provides personalized and optimal health management advice based on a user's genetic information and lifestyle information, and further analyzes the user's emotional state to tailor health-related advertisements. Specific embodiments for implementing this system are described below.

[1284] System Overview

[1285] The present invention is composed of a series of hardware and software including a user terminal, a server, and an emotion engine. The system has the following main functions:

[1286] 1. User registration and provision of genetic information

[1287] Users access a dedicated application or website and enter or upload basic information (such as name, age, gender, and email address) and genetic information. The genetic information is obtained from affiliated genetic testing institutions.

[1288] 2. Information storage and analysis

[1289] The server stores and analyzes basic information, genetic information, and lifestyle information provided by users, using a generative AI model.

[1290] 3. Generating personalized health management advice

[1291] Based on the analysis results, the server generates personalized health care advice for the user, which is provided to a medical professional during the video call.

[1292] 4. Real-time communication via video calls

[1293] Users and medical professionals communicate in real time using the video call feature, and information recorded during the video call is stored centrally and can be used for future consultations.

[1294] 5. Generating and displaying health-related advertisements

[1295] Based on the analysis results, the server generates optimal health-related advertisements for the user and displays them on the user's device. The advertisement content is individually optimized based on the user's health condition and lifestyle.

[1296] 6. Use of Emotion Engines

[1297] During a video call, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information. The server then adjusts the timing and content of advertisements based on this emotional information.

[1298] Hardware and software used

[1299] User devices: smartphones, tablets, computers

[1300] Server: Cloud or Dedicated Server

[1301] Generative AI models: Deep learning frameworks such as TensorFlow and Keras

[1302] Emotion engine: OpenCV, TensorFlow

[1303] Specific examples

[1304] For example, let's say a male user in his 30s uses the system. This user downloads the smartphone app and enters basic information (name, age, gender). Using a kit from a partner genetic testing institution, genetic information is obtained and uploaded to the database.

[1305] Users can schedule a video call through the app, and when the time comes, they will speak with a medical professional in real time. The server analyzes the user's genetic information, basic information, and lifestyle data, and based on the results, provides the medical professional with personalized health management advice. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the timing and content of advertisements based on their emotional information.

[1306] An example prompt might look like this:

[1307] "Male in his 30s, active, and eats a balanced diet. Low genetic risk, but currently experiencing stress. Create an ad for a health supplement with a relaxing effect."

[1308] In this way, the present invention provides individualized and optimal health management advice and health-related advertisements based on the user's genetic information and lifestyle information, and is expected to help the user maintain and improve their health.

[1309] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1310] Step 1:

[1311] The user inputs or provides basic information and genetic information.

[1312] Input: Name, age, gender, email address, and genetic information entered by users through smartphone apps or websites.

[1313] Processing: The user terminal sends the entered information to the server.

[1314] Output: User's basic information and genetic information stored on the server.

[1315] Step 2:

[1316] The server stores and analyzes the provided genetic information, basic information, and lifestyle information.

[1317] Input: Basic, genetic, and lifestyle information submitted by the user.

[1318] Processing: The information is stored in a database and analyzed using generative AI models, using deep learning frameworks such as TensorFlow and Keras.

[1319] Output: Health risk data and appropriate health advice indicators generated as a result of the analysis.

[1320] Step 3:

[1321] The server generates optimal individual health management advice for the user based on the analysis results.

[1322] Input: Analysis results from a generative AI model.

[1323] Processing: Based on the analysis results, the system creates personalized health management advice, such as automatically generating dietary suggestions and exercise advice.

[1324] Output: Personalized optimal health care advice provided to the user.

[1325] Step 4:

[1326] Users and medical professionals communicate in real time via video calls.

[1327] Input: Video call appointment information and generated health care advice.

[1328] Processing: When the video call starts, the server provides the generated advice to the medical professional's device and starts the video call. During the video call, questions from the user and comments from the doctor are recorded.

[1329] Output: Feedback and further advice from a medical professional via video call.

[1330] Step 5:

[1331] The server centrally manages and stores information recorded during video calls.

[1332] Input: Notes, questions, and lifestyle changes recorded by the doctor and user during the video call.

[1333] Processing: This information is stored in a database and managed so that it can be used for the next consultation.

[1334] Output: Recording information during the video call stored in a database.

[1335] Step 6:

[1336] The server generates and displays health-related advertisements optimized for the user based on the analyzed health information of the user.

[1337] Input: Analysis results and health management advice from the generative AI model.

[1338] Processing: Based on the user's health status and lifestyle, personalized health-related advertisements are generated and displayed on the user's device.

[1339] Output: Health-related advertisements displayed on the user's device.

[1340] Step 7:

[1341] Using an emotion engine, the system analyzes the user's emotions from their facial expressions and tone of voice during a video call, and adjusts the timing and content of advertisements based on the analysis results.

[1342] Input: Your facial expressions and tone of voice during a video call.

[1343] Processing: Sentiment analysis is performed using OpenCV and TensorFlow to identify the user's emotional state, and ad timing and content are adjusted in real time based on this.

[1344] Output: Adjusted ad content and timing.

[1345] The above is a specific program processing flow based on the processing steps of the present invention.

[1346] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1347] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1348] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1349] [Fourth embodiment]

[1350] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1351] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1352] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1353] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1354] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1355] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1356] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1357] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1358] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1359] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1360] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1361] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1362] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1363] The present invention is a system that provides personalized, optimal health management advice based on genetic and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a doctor via video call, and a means for centrally managing and storing information.

[1364] A natural language description of the program's operation

[1365] The processing of the present system proceeds as follows.

[1366] User registration and provision of genetic information

[1367] 1. User:

[1368] Users register with the system through an app or website and enter basic information, including their name, age, gender, and email address.

[1369] Users obtain genetic information using a test kit from a partner genetic testing institution and upload the results to a server.

[1370] 2. Server:

[1371] The server receives the basic information entered by the user and the genetic information provided, and stores it in a database.

[1372] Video consultation booking and call management

[1373] 3. User:

[1374] Users can book a video consultation through the app or website, select the desired date and time, and confirm the appointment.

[1375] 4. Server:

[1376] The server receives the reservation information sent by the user and stores it in a database. When the reservation time arrives, it notifies both the doctor and the user.

[1377] Providing real-time advice

[1378] 5. Terminal (user / doctor terminal):

[1379] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[1380] 6. Server:

[1381] Using a generative AI model, the system generates personalized health management advice based on the user's genetic, basic, and lifestyle data, which is then provided to a doctor in real time via video call.

[1382] 7. Terminal (Doctor's terminal):

[1383] The doctor will communicate the advice provided by the server to the user and propose an appropriate health management plan, including recommendations for improving diet and exercise.

[1384] Centralized management and recording of information

[1385] 8. Terminal (user / doctor terminal):

[1386] During the video call, the doctor and user take notes and record information such as questions from the user and lifestyle changes, which are then entered into the device.

[1387] 9. Server:

[1388] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database, ensuring that the user's next consultation and health management plan reflects the most up-to-date information.

[1389] Specific examples

[1390] Tanaka's case

[1391] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and then obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the results to the server.

[1392] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[1393] Based on the advice received from the server, the doctor made specific health management suggestions to Mr. Tanaka. Any new questions or notes that arose during the call were also recorded and saved on the server.

[1394] In this way, Mr. Tanaka will be able to receive optimal, individualized health management advice based on his genetic information, and it is expected that his next consultation will also proceed smoothly.

[1395] The method of providing optimal individual health management advice realized by this system is an effective means of promoting improvement in the user's health.

[1396] The processing flow will be explained below.

[1397] Step 1:

[1398] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[1399] Step 2:

[1400] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[1401] Step 3:

[1402] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[1403] Step 4:

[1404] The server receives the uploaded genetic information and stores it in a database.

[1405] Step 5:

[1406] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[1407] Step 6:

[1408] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[1409] Step 7:

[1410] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[1411] Step 8:

[1412] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[1413] Step 9:

[1414] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[1415] Step 10:

[1416] The doctor's terminal displays advice from the server, and the doctor uses this information to provide appropriate advice to the user and propose a health management plan.

[1417] Step 11:

[1418] During the video call, the user and doctor take notes and record the user's questions and lifestyle changes on the device.

[1419] Step 12:

[1420] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[1421] Step 13:

[1422] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[1423] Example 1

[1424] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1425] In modern society, people's lifestyles are becoming more diverse, creating a demand for customized health management advice tailored to each individual's health condition. However, existing health management systems can only provide general advice, making it difficult to provide individually tailored advice based on genetic and lifestyle information. Furthermore, when users and medical professionals make video calls for health management, there is an insufficient mechanism for centrally managing that information and effectively utilizing it for the next consultation.

[1426] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1427] In this invention, the server includes means for using a generative AI model to generate real-time advice based on user data, means for inputting prompt text into the generative AI model to generate personalized advice, and means for reminding the user of the appointment time through a notification function. This makes it possible to provide personalized, optimal health management advice in real time based on the user's genetic information and lifestyle information, and further makes it possible to effectively use this information for the next consultation.

[1428] "User" refers to an individual who uses this system and who inputs information or receives services through an application or website.

[1429] "Basic information" refers to personal information entered by the user, such as name, age, gender, and email address.

[1430] "Genetic information" refers to data obtained through a user's genetic testing, and includes information about specific health risks and physical constitutions.

[1431] "Lifestyle information" refers to data related to a user's diet, exercise, sleep, stress, etc.

[1432] "Storage" refers to the act of recording and retaining data on a server or database.

[1433] "Analysis" refers to the process of performing calculations and evaluations based on collected data to derive useful information and results.

[1434] "Individually optimal health management advice" refers to instructions and suggestions regarding optimized health management based on the user's individual genetic information and lifestyle information.

[1435] "Video calling" refers to a technology that allows users and medical professionals to communicate in real time via video and audio over the Internet.

[1436] "Medical professionals" refer to people with specialized knowledge and qualifications, such as doctors, nutritionists, and trainers, who are responsible for providing health management advice to users.

[1437] "Centralized management" refers to the unification of different types of information, organizing and storing them, and managing them efficiently.

[1438] A "generative AI model" refers to an artificial intelligence program that generates results using specific algorithms based on input data.

[1439] A "prompt" refers to a command or question that is input into a generative AI model, and serves as a trigger for the model to generate the necessary data.

[1440] "Notification" refers to the system's ability to notify users and medical professionals of important events and actions.

[1441] "Reservation System" means an online system that allows a User to select and confirm a date and time for a video call.

[1442] "Notes" refer to vague information, questions, comments, etc. recorded by users or medical professionals during video calls.

[1443] This invention is a system that provides personalized, optimal health management advice based on genetic information and lifestyle information provided by a user. This system includes a means for a user to input or provide basic information and genetic information, a means for storing and analyzing the provided information, a means for generating health management advice based on the analysis results, a means for real-time communication between the user and a medical professional via video call, and a means for centrally managing and storing information.

[1444] User registration and provision of genetic information

[1445] To start using the system, users must first open a dedicated application or website on their smartphone or personal computer (PC) and register. Users must enter basic information such as their name, age, gender, and email address.

[1446] Next, the user purchases a test kit from an affiliated genetic testing institution, collects a genetic sample according to the instructions, and sends it to the testing institution. When the test results are provided a few days later, the user uploads them to a dedicated application or their personal page on the website. At this time, the server receives the basic information and genetic information provided by the user and encrypts and stores it in a relational database such as MySQL or MongoDB or a NoSQL database. The encryption is performed using technologies such as AES (Advanced Encryption Standard).

[1447] Video consultation booking and call management

[1448] The user selects a date and time for a video consultation using a dedicated application or a website reservation system, and makes a reservation. The server receives this reservation information and records it in a database. When the reservation time approaches, the server sends reminder emails to both the user and the medical professional. This email is sent using an SMTP server.

[1449] Providing real-time advice

[1450] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, which is conducted using WebRTC (Web Real-Time Communication) technology.

[1451] During this time, the server launches the generative AI model and performs analysis based on the genetic information, basic information, and lifestyle habit data provided by the user. The server inputs a prompt into the generative AI model to generate personalized, optimal advice. For example, the following prompts are used:

[1452] "I'm a 37-year-old woman named Tanaka. I'm concerned about health risks based on my genetic information, and I'd like advice on improving my diet and recommending exercise. Please generate personalized, optimal health management advice based on my genetic information, basic information, and lifestyle data."

[1453] The generated advice is sent in real time to the terminal of a medical professional, who can then use the advice to propose an appropriate health management plan to the user.

[1454] Centralized management and recording of information

[1455] During the video call, the medical professional and the user can input any new questions, lifestyle changes, or other important notes into the device. This information is then recorded in a database managed by the server. This information can be used to provide more detailed health management advice during the next consultation.

[1456] As described above, this system enables optimal health management for each individual user, provides highly accurate real-time advice, and enables effective use of information in the next consultation.

[1457] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1458] Step 1:

[1459] User Registration

[1460] 1. Users

[1461] Users can register by opening a dedicated application or website on their smartphone or PC, and entering basic information such as name, age, gender, and email address.

[1462] Input: Name, age, gender, email address

[1463] Output: User profile stored in registration database

[1464] 2. Server

[1465] We receive basic information submitted by users and store it in a database for future reference and analysis.

[1466] Input: Basic information

[1467] Output: Saved user profile

[1468] Step 2:

[1469] Genetic information provision

[1470] 1. Users

[1471] Users purchase a test kit from a partner genetic testing institution, collect a genetic sample according to the instructions, and send it to the testing institution. Test results are provided a few days later.

[1472] Input: Gene sample

[1473] Output: Genetic test result data

[1474] 2. Users

[1475] The provided genetic information is uploaded to a dedicated application or personal page on the website.

[1476] Input: Genetic test result data

[1477] Output: Uploaded genetic information

[1478] 3. Server

[1479] The system receives genetic information provided by users, encrypts it, and stores it in a database using technologies such as AES (Advanced Encryption Standard).

[1480] Input: Uploaded genetic information

[1481] Output: Encrypted and stored genetic information

[1482] Step 3:

[1483] Book a video consultation

[1484] 1. Users

[1485] Use the dedicated application or website reservation system to select the date and time of the video consultation and make a reservation. Reservation information is displayed in a calendar format, and you can select the desired date and time.

[1486] Input: Reservation date and time, user ID

[1487] Output: Reservation confirmation information

[1488] 2. Server

[1489] Reservation information sent by the user is received and recorded in the database. The reservation information includes the reservation date and time, user ID, and medical professional ID.

[1490] Input: Reservation information

[1491] Output: Saved reservation information

[1492] Step 4:

[1493] Video Consultation Notification

[1494] 1. Server

[1495] When the appointment time approaches, the server sends reminder emails to both the user and the medical professional. The server uses an SMTP server to send the reminder emails.

[1496] Input: Appointment information (date and time, user ID, medical professional ID)

[1497] Output: Reminder email

[1498] Step 5:

[1499] Starting a video call

[1500] 1. Terminals (user and medical professional terminals)

[1501] When the appointment time arrives, the user and medical professional connect using the video call function of the dedicated application or website, using WebRTC (Web Real-Time Communication) technology.

[1502] Input: Appointment information, User ID, Medical Professional ID

[1503] Output: Start a video call

[1504] Step 6:

[1505] Providing real-time advice

[1506] 1. Server

[1507] The generative AI model is activated to generate personalized health management advice based on the user's genetic information, basic information, and lifestyle data. The user enters a prompt and provides the generated advice to a medical professional during a video call.

[1508] Input: Genetic information, basic information, lifestyle data, prompt text

[1509] Output: Personalized and optimal health management advice

[1510] 2. Terminal (medical professional's terminal)

[1511] The medical professional reviews the advice provided by the server and proposes a specific health management plan to the user, such as "improving your diet" or "recommending exercise."

[1512] Input: Generated advice

[1513] Output: Health care plan provided

[1514] Step 7:

[1515] Centralized management and recording of information

[1516] 1. Terminals (user and medical professional terminals)

[1517] Enter new questions, lifestyle changes, and notes during the video call.

[1518] Input: Questions, lifestyle changes, notes

[1519] Output: Recorded information

[1520] 2. Server

[1521] All information entered during the video call is received and stored in a centralized database, which can then be used for the next consultation.

[1522] Input: Recorded information

[1523] Output: Centralized information saved

[1524] (Application example 1)

[1525] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1526] In modern society, interest in personal health management is growing, but providing personalized, optimal health management advice based on genetic and lifestyle information is difficult, and means for communicating with experts in real time are limited. Furthermore, there is a need to maintain consistency in in-store consultations and provide continuous, effective health management. The present invention aims to solve these problems and provide users with consistent, personalized, optimal health management advice.

[1527] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1528] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user to communicate with a medical professional in real time via video call; means for providing the advice generated in real time during the video call to the medical professional; means for recording the health management advice received by the user at the physical store and using the recording for the next consultation; means for centrally managing and storing information; and means for continuously providing individually optimized health management advice to the user using the generative AI model. This makes it possible to continuously provide individually optimized health management advice to the user while maintaining consistency even during health management consultations at the physical store.

[1529] "User" refers to an individual who uses the system.

[1530] "Brick and mortar" refers to a business or organization that provides services at a physical location.

[1531] "Basic information" refers to personal information such as the user's name, age, and gender.

[1532] "Genetic Information" refers to data about a user's DNA.

[1533] "Lifestyle information" refers to information about the habits and preferences of a user in their daily life.

[1534] "Server" refers to a networked computer system for storing data and performing analytical tasks.

[1535] "Analysis" refers to the process of analyzing collected data and generating meaningful information.

[1536] "Health Management Advice" means specific instructions or suggestions for maintaining or improving a User's health.

[1537] "Video calling" refers to a real-time communication method for exchanging audio and video over the Internet.

[1538] "Healthcare professional" refers to a physician or other medical professional.

[1539] "Recording" refers to the process of storing information and keeping it available for future reference.

[1540] "Centralized management" refers to the centralized management of multiple pieces of information in one place or system.

[1541] A "generative AI model" refers to an algorithm that uses artificial intelligence to generate useful information or predictions from data.

[1542] The present invention can be implemented as a system that provides health management support in a physical store. This system is provided as a smartphone app, and allows users to input basic information, genetic information, and lifestyle information, and provides personalized, optimal health management advice based on that information.

[1543] System configuration

[1544] 1. How to enter user's basic information and genetic information:

[1545] Users download the smartphone app and enter their name, age, gender, lifestyle information, etc.

[1546] Genetic information is obtained through affiliated genetic testing services and uploaded to a server via the app.

[1547] 2. How we store and analyze your information:

[1548] The servers use Google Cloud or AWS, and the basic information, genetic information, and lifestyle information provided by users is stored in a database.

[1549] Data analysis platforms such as Python and R are used to analyze the collected information.

[1550] 3. Means for generating personalized health management advice:

[1551] Based on the analysis results, a generative AI model (e.g., ChatGPT, GPT-4) is used to generate personalized advice, including specific instructions on diet, exercise recommendations, health risk management, and more.

[1552] 4. Video calling methods:

[1553] Using the Zoom API and Twilio Video, users can conduct real-time video calls with medical professionals.

[1554] During the video call, the server provides real-time advice based on the analysis results to medical professionals.

[1555] 5. Real-time advice delivery methods:

[1556] During the video call, the generative AI model presents the generated advice to the medical professional, making appropriate suggestions to the user.

[1557] This advice also includes information to help users manage their ongoing health.

[1558] 6. Centralized information management:

[1559] The information and notes recorded by the user and medical professional during the video call are stored on the server and made available for the next consultation.

[1560] Specific examples

[1561] For example, consider the case of a 35-year-old female user using this system in a physical store. The user downloads the app, enters basic information, and uploads genetic test results. Next, she schedules a video consultation in the store and has a real-time video call with a medical professional at the scheduled time. Based on the personalized and optimized advice provided by the generative AI model, the medical professional will propose a specific health management plan. This information is stored on the server, enabling a smooth consultation the next time the user visits the store.

[1562] Prompt Sentence Examples

[1563] By inputting the following prompt sentences into the generative AI model, personalized health management advice will be generated:

[1564] We will provide the user's basic information and genetic information below. Based on this, we would like you to generate optimal health management advice for the user.

[1565] Basic information: Age 35, female, no exercise habits

[1566] Genetic information: High-risk items (cardiovascular disease risk, diabetes risk)

[1567] Lifestyle information: Desk work, drinks 3 times a week

[1568] Generate your health advice in the following format:

[1569] Improved diet

[1570] Exercise recommendations

[1571] Health Risk Management

[1572] In this way, personalized and optimal health management advice based on the user's genetic information and lifestyle information can be provided.

[1573] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1574] Step 1:

[1575] The user downloads the application and enters basic information. The user enters their name, age, gender, and lifestyle information (e.g., drinking frequency, exercise habits, etc.) into the smartphone application. The application sends the entered information to the server and stores it in a database.

[1576] Step 2:

[1577] The user provides genetic information. The user obtains the genetic information using a test kit from a partner genetic testing institution. The genetic information is then uploaded to the server via a smartphone application. The server stores the received genetic information in a database.

[1578] Step 3:

[1579] The server analyzes the information provided by the user. Using a data analysis platform such as Python or R, the server analyzes the received basic information, genetic information, and lifestyle information. The results of the analysis are output as data on the user's health risks and optimal lifestyle habits, and are stored in a database.

[1580] Step 4:

[1581] A user books a video consultation. The user uses the application to book a date and time for a video consultation at a physical store. The selected date and time and the user's information are sent to the server, and the reservation information is saved in the database.

[1582] Step 5:

[1583] The server notifies the medical professional of the appointment information. When the appointment time approaches, the server sends a notification to the medical professional and the user via email or push notification so that they can prepare for the video call.

[1584] Step 6:

[1585] At the appointment time, a video call is initiated between the user's smartphone and the medical professional's device via the application, using the Zoom API and Twilio Video.

[1586] Step 7:

[1587] Real-time advice generation: The server uses a generative AI model (e.g., ChatGPT, GPT-4) to generate real-time health management advice, which is then provided to the medical professional's device during the video call.

[1588] Step 8:

[1589] Medical experts provide advice to users. During the video call, the medical experts propose specific health management plans to users based on advice provided by the server, including recommendations for improving diet and exercise.

[1590] Step 9:

[1591] Centralized information management and recording: During the video call, users and medical professionals record any notes, new questions, or lifestyle changes they make, and send them to the server via the application. The server stores this information in a database and makes it available for the next consultation.

[1592] At each step, data processing or calculation is performed based on specific input data, and the results are used as the output that forms the basis for the next processing step.

[1593] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1594] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and combines it with an emotion engine that recognizes the user's emotions. This system includes a means for the user to input or provide basic information and genetic information, a means for storing and analyzing this information, a means for generating personalized, optimal health management advice for the user based on the analysis results, a means for the user to communicate with a doctor in real time via video call, a means for centrally managing and storing information recorded during the video call, and an emotion engine that recognizes the user's emotions.

[1595] A natural language description of the program's operation

[1596] The processing of the present system proceeds as follows.

[1597] User registration and provision of genetic information

[1598] 1. User:

[1599] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[1600] 2. Server:

[1601] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[1602] 3. User:

[1603] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[1604] 4. Server:

[1605] The server receives the uploaded genetic information and stores it in a database.

[1606] Video consultation booking and call management

[1607] 5. User:

[1608] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[1609] 6. Server:

[1610] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[1611] Providing real-time advice

[1612] 7. Terminal (user / doctor terminal):

[1613] At the scheduled time, the video call begins, and the user and doctor communicate in real time.

[1614] 8. Server:

[1615] Using a generative AI model, the system collects genetic, basic, and lifestyle data provided by the user, analyzes it, and generates personalized health management advice that is provided to a doctor via video call in real time.

[1616] Use of emotion engine

[1617] 9. Terminal (user / doctor terminal):

[1618] During a video call, the emotion engine analyzes emotional information from the user's facial expressions, tone of voice, and choice of words.

[1619] 10. Server:

[1620] The system receives the emotional information generated by the emotion engine and adjusts the content and tone of the health management advice provided based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on relaxation methods and stress management.

[1621] Centralized management and recording of information

[1622] 11. Terminal (user / doctor terminal):

[1623] During the video call, the doctor and user take notes and record any questions or lifestyle changes the user may have.

[1624] 12. Server:

[1625] The server receives notes, questions, and lifestyle changes recorded during the video call and stores them in a centralized database. This information can be reused during the next consultation, ensuring that the health management plan is always based on the most up-to-date information.

[1626] Specific examples

[1627] Tanaka's case

[1628] Ms. Tanaka, a 37-year-old woman, decided to use this system because she was concerned about health risks based on her genetic information. First, she downloaded the app and registered. She entered her name, age, gender, and email address, and obtained her genetic information using a test kit from an affiliated genetic testing institution. She then uploaded the information to the server.

[1629] Mr. Tanaka then booked a date and time for a video consultation through the website. At the scheduled time, the video call began, allowing him to discuss with the doctor in real time. The server performed an analysis based on Mr. Tanaka's genetic information, basic information, and lifestyle data, and provided the results to the doctor in real time.

[1630] At the same time, during the video call, the emotion engine analyzed Tanaka's facial expressions and tone of voice to detect changes in what she was saying and her emotions. The server also analyzed this emotional information and detected that she was feeling stressed, so it added specific advice on how to relax and manage stress.

[1631] Based on the advice, the doctor proposed a specific health management plan for Mr. Tanaka, and also recorded any new questions or notes that arose during the call. All of this information was saved on a server and used during the next consultation.

[1632] With this system, Tanaka will not only receive personalized health management advice based on her genetic information, but will also receive detailed support tailored to her emotional state, which is expected to improve both her physical and mental health.

[1633] The processing flow will be explained below.

[1634] Step 1:

[1635] A user accesses an app or website, opens the new registration screen, enters basic information such as name, age, gender, email address, and password, and clicks the registration button.

[1636] Step 2:

[1637] The server receives the registration information sent by the user, stores it in a database, and sends the user a confirmation email to confirm the completion of registration.

[1638] Step 3:

[1639] Users obtain genetic information using a test kit from a partner genetic testing institution, and then upload the obtained genetic information to a server.

[1640] Step 4:

[1641] The server receives the uploaded genetic information and stores it in a database.

[1642] Step 5:

[1643] Users log in to the app or website, open the video consultation booking page, select the desired date and time, and confirm the appointment.

[1644] Step 6:

[1645] The server receives the reservation information sent by the user, stores it in a database, and sends notifications to the doctor and the user when the reservation time approaches.

[1646] Step 7:

[1647] When the appointment time arrives, a video call will automatically start between the user and the doctor's devices.

[1648] Step 8:

[1649] The server collects the user's genetic information, basic information, and lifestyle data and analyzes it using a generative AI model.

[1650] Step 9:

[1651] The server generates individually optimized health management advice based on the analysis results and provides this advice to doctors in real time.

[1652] Step 10:

[1653] The advice from the server is displayed on the terminal (doctor's terminal), and the doctor provides appropriate advice to the user based on it and proposes a health management plan.

[1654] Step 11:

[1655] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and selected words to generate emotional information.

[1656] Step 12:

[1657] The server receives the emotion information generated by the emotion engine and uses it to adjust the content and tone of the health care advice provided, for example, emphasizing relaxation and stress management advice if the user is feeling stressed.

[1658] Step 13:

[1659] At the terminals (user and doctor terminals), the user and doctor take notes and record questions from the user and lifestyle changes.

[1660] Step 14:

[1661] The server centrally manages and stores notes, questions, and lifestyle changes recorded during video calls in a database.

[1662] Step 15:

[1663] The server uses the stored information to prepare for the user's next consultation, ensuring that the user always receives an up-to-date and consistent health management plan.

[1664] Example 2

[1665] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1666] In recent years, interest in health management has grown, and providing personalized, optimal health advice is becoming increasingly important. However, there is a lack of means to provide appropriate, real-time, personalized health management advice based on genetic and lifestyle information to users who need it. Furthermore, there are no systems that provide detailed advice that takes users' emotions into consideration. This leads to a lack of centralized management of information, making it difficult to provide effective health management advice tailored to the user's actual lifestyle.

[1667] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1668] In this invention, the server includes means for a user to input or provide basic information and genetic information, means for storing and analyzing the provided genetic information, basic information, and lifestyle information, and means for generating personalized health management advice for the user based on the analysis results. This allows personalized health management advice to be provided in real time based on the user's specific genetic information and lifestyle information, and further takes into account the user's emotions, enabling more effective and centralized health management.

[1669] "User basic information" refers to information that identifies an individual user, such as the user's name, age, gender, email address, and password.

[1670] "Genetic information" refers to data regarding a user's DNA sequence and the genetic characteristics based thereon.

[1671] "Lifestyle information" refers to information about the user's daily life, including eating habits, exercise habits, sleep patterns, alcohol and tobacco use, and the like.

[1672] "Means for storing and analyzing" refers to a set of hardware and software for storing genetic information, basic information, and lifestyle information provided by users in a database and performing analysis based on that data.

[1673] "Means for generating individually optimized health management advice" refers to means that have the function of using a generative AI model to generate health management suggestions and advice appropriate for the user based on stored user information.

[1674] "Video calling tool" means software and hardware that allows users to communicate with medical professionals in real time over the Internet.

[1675] "Centralized management and storage means" means a means for aggregating, managing and storing all user information, including information recorded during video calls, in a central database.

[1676] An "emotion engine" is software that analyzes a user's facial expressions, tone of voice, and word choice to generate emotional information.

[1677] The present invention is a system that provides personalized, optimal health management advice based on a user's genetic information and lifestyle information, and by combining it with an emotion engine that analyzes the user's emotions, it provides detailed support. The following describes in detail the modes for implementing this system.

[1678] Registration of basic user information and genetic information

[1679] Users access the service through an application or website, open a new registration screen, and enter basic information such as name, age, gender, email address, and password. This information is sent to the server and securely stored in a database. The user obtains genetic information using a test kit from a partner genetic testing institution and uploads it to the server. The uploaded genetic information is received by the server and securely stored in a database.

[1680] Video consultation booking and real-time calls

[1681] The user books a video consultation through the application or website. The reservation information is sent to the server and stored in a database. When the appointment time approaches, a reminder notification is sent to the medical professional and the user. At the scheduled time, a video call is automatically started, allowing the user and medical professional to communicate in real time.

[1682] Providing personalized and optimal health management advice

[1683] The server uses a generative AI model to collect and analyze the genetic information, basic information, and lifestyle information provided by the user. Based on the results of this analysis, it generates personalized, optimal health management advice. The generated advice is provided in real time to a medical professional on a video call, who can provide specific advice to the user. For example, the following prompt could be used: "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Also, please add advice for when the user is feeling stressed."

[1684] Emotion analysis using an emotion engine

[1685] During a video call, the emotion engine analyzes the user's facial expressions, voice tone, and word choice in real time. Emotional information is generated and sent to the server, which then uses this information to adjust the content and tone of the health care advice. For example, if the user is feeling stressed, the engine can emphasize relaxation and stress management advice.

[1686] Centralized management and recording of information

[1687] During the video call, the medical professional and user can use the notes feature to record any questions or new lifestyle changes. This information is sent to the server and securely stored in a database. The saved information is easily accessible during the next consultation and used to provide an updated health management plan.

[1688] As a concrete example, User A (a 37-year-old woman) uses this system because she is interested in health risks based on her genetic information. She downloads the app, registers, obtains genetic information using a partner genetic testing kit, and uploads that information to the server. She then schedules a video consultation and discusses with a medical professional in real time. The server generates optimal health management advice based on User A's information, and the emotion engine analyzes her emotions to provide tailored support.

[1689] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1690] Step 1: User Registration

[1691] The user accesses an application or website, enters basic information such as name, age, gender, email address, and password on the new registration screen, and clicks the "Register" button. The input data is sent to the server as basic information data.

[1692] The server receives the submitted basic information and stores it in a database. It sends the user a confirmation email to confirm registration. The email contains an authentication link, and the user activates the account by clicking the link. The input is basic information, and the output is saving it in a database and sending a confirmation email.

[1693] Step 2: Provide genetic information

[1694] Users receive a test kit from a partner genetic testing institution, follow the instructions to take a genetic sample, and then send the test kit to the testing institution, where their genetic information is then uploaded to a server via the app or website.

[1695] The server receives the uploaded genetic information and stores it in a secure database. The input is the genetic information, and the output is storing it in the database and notifying the user.

[1696] Step 3: Book a video consultation

[1697] The user logs in to the application or website, opens the video consultation reservation screen, selects the desired date and time, and clicks the "Book" button. The reservation information is sent to the server as reservation data.

[1698] The server receives the submitted appointment information and stores it in a database. When the appointment time approaches, it sends reminder notifications to medical professionals and users. The input is the appointment information, and the output is storing it in the database and sending notifications.

[1699] Step 4: Start a video call

[1700] When the appointment time arrives, a video call will automatically start between the user and the medical professional, allowing them to communicate in real time.

[1701] The terminal establishes a video call session and sends the information to the server. The input is reservation information, and the output is the start of the video call session.

[1702] Step 5: Data collection and analysis

[1703] The server uses a generative AI model to collect genetic, basic, and lifestyle information provided by the user, and the collected data is processed as analytical data.

[1704] The generative AI model analyzes the collected data and generates personalized, optimal health management advice. In this process, a prompt is used to generate appropriate advice. For example, the prompt might read, "Generate personalized, optimal health management advice based on user X's genetic and lifestyle information. The user's genetic information is xx, lifestyle information is xx, and basic information is yy. Please also add advice for when the user is feeling stressed." The input is the collected basic information, genetic information, and lifestyle information, and the output is advice as a result of the analysis.

[1705] Step 6: Emotion analysis using the emotion engine

[1706] During a video call, the emotion engine analyzes the user's facial expressions, tone of voice, and word choice in real time, and the analyzed emotion information is sent to the server.

[1707] The server receives the emotional information and adjusts the content and tone of the health care advice based on the analysis results. For example, if the user is feeling stressed, it will emphasize advice on stress management and relaxation methods. The input is emotional data, and the output is the adjusted advice.

[1708] Step 7: Centralize and record information

[1709] During the video call, the medical professional and the user use the notes feature to record questions and lifestyle changes, which are then sent to the server.

[1710] The server receives the transmitted information and stores it centrally in a database. The stored information is reused at the next consultation and used to provide an updated health management plan. The input is recorded information during the call, and the output is stored in the database.

[1711] These processing steps enable users to receive personalized and optimal health management advice based on genetic and lifestyle information, and also to receive detailed support that also addresses their emotional state.

[1712] (Application example 2)

[1713] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1714] Modern health management requires personalized, optimized advice based on a user's genetic and lifestyle information. However, existing systems have been unable to provide personalized advice in real time or adjust the content and tone of the advice based on the user's emotional state. Furthermore, there has been no means of providing personalized health-related advertisements, making it difficult to effectively deliver health information tailored to the user. The present invention aims to solve these problems and provide a system that provides personalized health management advice and health-related advertisements based on a user's genetic and lifestyle information.

[1715] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1716] In this invention, the server includes: means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; means for generating individually optimized health management advice for the user based on the analysis results; means for the user and a doctor to communicate in real time via video call; means for centrally managing and storing information recorded during the video call; means for generating and displaying health-related advertisements optimized for the user based on the analyzed user's health information; and means for analyzing emotions from the user's facial expressions and tone of voice during the video call using an emotion engine and adjusting the timing and content of advertisement display based on the analysis results, thereby enabling the provision of individually optimized health management advice and health-related advertisements based on the user's genetic information and lifestyle information.

[1717] "Means for users to input or provide their basic and genetic information" refers to the interface through which users provide their basic and genetic information to the system, which may include web forms or dedicated applications.

[1718] "Means for storing and analyzing provided genetic information, basic information, and lifestyle information" refers to software and hardware configurations for storing the genetic information, basic information, and lifestyle information provided by the user in a database and analyzing that information.

[1719] The "means for generating individually optimal health management advice for a user based on the analysis results" refers to an algorithm and program for generating health management advice customized for each user based on the stored information.

[1720] "Means for real-time communication between users and doctors via video calls" refers to a system that allows users to communicate with medical professionals in real time using video calling functionality. This includes video calling applications and communication networks.

[1721] "A means for centrally managing and storing information recorded during video calls" refers to a system for storing information such as notes, questions, and comments exchanged during video calls in a database and managing them centrally.

[1722] "Means for generating and displaying health-related advertisements optimized for a user based on the analyzed health information of the user" refers to a system for generating health-related advertisements individually optimized for a user based on the analysis results and displaying them on the user's device.

[1723] "Means of using an emotion engine to analyze emotions from a user's facial expression and tone of voice during a video call, and adjusting the timing and content of advertisement display based on the analysis results" is a technology that analyzes a user's facial expression and tone of voice during a video call, and dynamically adjusts the timing and content of advertisement display according to their emotional state.

[1724] This invention provides a system that provides personalized and optimal health management advice based on a user's genetic information and lifestyle information, and further analyzes the user's emotional state to tailor health-related advertisements. Specific embodiments for implementing this system are described below.

[1725] System Overview

[1726] The present invention is composed of a series of hardware and software including a user terminal, a server, and an emotion engine. The system has the following main functions:

[1727] 1. User registration and provision of genetic information

[1728] Users access a dedicated application or website and enter or upload basic information (such as name, age, gender, and email address) and genetic information. The genetic information is obtained from affiliated genetic testing institutions.

[1729] 2. Information storage and analysis

[1730] The server stores and analyzes basic information, genetic information, and lifestyle information provided by users, using a generative AI model.

[1731] 3. Generating personalized health management advice

[1732] Based on the analysis results, the server generates personalized health care advice for the user, which is provided to a medical professional during the video call.

[1733] 4. Real-time communication via video calls

[1734] Users and medical professionals communicate in real time using the video call feature, and information recorded during the video call is stored centrally and can be used for future consultations.

[1735] 5. Generating and displaying health-related advertisements

[1736] Based on the analysis results, the server generates optimal health-related advertisements for the user and displays them on the user's device. The advertisement content is individually optimized based on the user's health condition and lifestyle.

[1737] 6. Use of Emotion Engines

[1738] During a video call, the emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional information. The server then adjusts the timing and content of advertisements based on this emotional information.

[1739] Hardware and software used

[1740] User devices: smartphones, tablets, computers

[1741] Server: Cloud or Dedicated Server

[1742] Generative AI models: Deep learning frameworks such as TensorFlow and Keras

[1743] Emotion engine: OpenCV, TensorFlow

[1744] Specific examples

[1745] For example, let's say a male user in his 30s uses the system. This user downloads the smartphone app and enters basic information (name, age, gender). Using a kit from a partner genetic testing institution, genetic information is obtained and uploaded to the database.

[1746] Users can schedule a video call through the app, and when the time comes, they will speak with a medical professional in real time. The server analyzes the user's genetic information, basic information, and lifestyle data, and based on the results, provides the medical professional with personalized health management advice. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice, and adjusts the timing and content of advertisements based on their emotional information.

[1747] An example prompt might look like this:

[1748] "Male in his 30s, active, and eats a balanced diet. Low genetic risk, but currently experiencing stress. Create an ad for a health supplement with a relaxing effect."

[1749] In this way, the present invention provides individualized and optimal health management advice and health-related advertisements based on the user's genetic information and lifestyle information, and is expected to help the user maintain and improve their health.

[1750] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1751] Step 1:

[1752] The user inputs or provides basic information and genetic information.

[1753] Input: Name, age, gender, email address, and genetic information entered by users through smartphone apps or websites.

[1754] Processing: The user terminal sends the entered information to the server.

[1755] Output: User's basic information and genetic information stored on the server.

[1756] Step 2:

[1757] The server stores and analyzes the provided genetic information, basic information, and lifestyle information.

[1758] Input: Basic, genetic, and lifestyle information submitted by the user.

[1759] Processing: The information is stored in a database and analyzed using generative AI models, using deep learning frameworks such as TensorFlow and Keras.

[1760] Output: Health risk data and appropriate health advice indicators generated as a result of the analysis.

[1761] Step 3:

[1762] The server generates optimal individual health management advice for the user based on the analysis results.

[1763] Input: Analysis results from a generative AI model.

[1764] Processing: Based on the analysis results, the system creates personalized health management advice, such as automatically generating dietary suggestions and exercise advice.

[1765] Output: Personalized optimal health care advice provided to the user.

[1766] Step 4:

[1767] Users and medical professionals communicate in real time via video calls.

[1768] Input: Video call appointment information and generated health care advice.

[1769] Processing: When the video call starts, the server provides the generated advice to the medical professional's device and starts the video call. During the video call, questions from the user and comments from the doctor are recorded.

[1770] Output: Feedback and further advice from a medical professional via video call.

[1771] Step 5:

[1772] The server centrally manages and stores information recorded during video calls.

[1773] Input: Notes, questions, and lifestyle changes recorded by the doctor and user during the video call.

[1774] Processing: This information is stored in a database and managed so that it can be used for the next consultation.

[1775] Output: Recording information during the video call stored in a database.

[1776] Step 6:

[1777] The server generates and displays health-related advertisements optimized for the user based on the analyzed health information of the user.

[1778] Input: Analysis results and health management advice from the generative AI model.

[1779] Processing: Based on the user's health status and lifestyle, personalized health-related advertisements are generated and displayed on the user's device.

[1780] Output: Health-related advertisements displayed on the user's device.

[1781] Step 7:

[1782] Using an emotion engine, the system analyzes the user's emotions from their facial expressions and tone of voice during a video call, and adjusts the timing and content of advertisements based on the analysis results.

[1783] Input: Your facial expressions and tone of voice during a video call.

[1784] Processing: Sentiment analysis is performed using OpenCV and TensorFlow to identify the user's emotional state, and ad timing and content are adjusted in real time based on this.

[1785] Output: Adjusted ad content and timing.

[1786] The above is a specific program processing flow based on the processing steps of the present invention.

[1787] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1788] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1789] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1790] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1791] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1792] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1793] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1794] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1795] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1796] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1797] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1798] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1799] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1800] 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.

[1801] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1802] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1803] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1804] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1805] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1806] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1807] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1808] The following is further disclosed regarding the above embodiment.

[1809] (Claim 1)

[1810] a means for a user to input or provide basic information and genetic information;

[1811] means for storing and analyzing the provided genetic information, basic information, and lifestyle information;

[1812] A means for generating optimal individual health management advice for a user based on the analysis results;

[1813] A means for users and doctors to communicate in real time via video calls;

[1814] A means for centrally managing and storing information recorded during video calls;

[1815] A system including:

[1816] (Claim 2)

[1817] 10. The system of claim 1, wherein real-time generated advice is provided to a physician during a video call.

[1818] (Claim 3)

[1819] 2. The system according to claim 1, wherein the stored information is analyzed and used at the next consultation.

[1820] "Example 1"

[1821] (Claim 1)

[1822] a means for a user to input or provide basic information and genetic information;

[1823] A means for storing and analyzing the provided genetic information, basic information, and lifestyle information;

[1824] A means for generating optimal individual health management advice for a user based on the analysis results;

[1825] A means for users to communicate with medical professionals in real time via video calls;

[1826] A means for centrally managing and storing information recorded during video calls;

[1827] A means for generating real-time advice based on user data using a generative AI model; and

[1828] A means for inputting the prompt sentence into a generative AI model to generate personalized advice;

[1829] A means to book a video consultation through our booking system;

[1830] A means to remind you of your appointment time through notifications,

[1831] A way to save notes and questions and use them for your next consultation.

[1832] A system including:

[1833] (Claim 2)

[1834] 10. The system of claim 1, wherein the system provides real-time generated advice to a medical professional during a video call.

[1835] (Claim 3)

[1836] 2. The system according to claim 1, wherein the stored information is analyzed and used at the next consultation.

[1837] "Application Example 1"

[1838] (Claim 1)

[1839] a means for a user to input or provide basic information and genetic information;

[1840] means for storing and analyzing the provided genetic information, basic information, and lifestyle information;

[1841] A means for generating optimal individual health management advice for a user based on the analysis results;

[1842] A means for users to communicate with medical professionals in real time via video calls;

[1843] a means of providing real-time generated advice to medical professionals during video calls;

[1844] A means to record the health management advice received by the user at the physical store and use it for the next consultation;

[1845] A means of centrally managing and storing information;

[1846] a means for using the generative AI model to continually provide users with tailored health management advice; and

[1847] A system including:

[1848] (Claim 2)

[1849] 10. The system of claim 1, wherein the system provides real-time generated advice to a medical professional during a user consultation at a physical store.

[1850] (Claim 3)

[1851] The system of claim 1 analyzes the stored information and uses it the next time the customer consults at a physical store.

[1852] "Example 2: Combining Emotion Engines"

[1853] (Claim 1)

[1854] a means for a user to input or provide basic information and genetic information;

[1855] means for storing and analyzing the provided genetic information, basic information, and lifestyle information;

[1856] A means for generating optimal individual health management advice for a user based on the analysis results;

[1857] A means for users to communicate with medical professionals in real time via video calls;

[1858] A means for centrally managing and storing information recorded during video calls;

[1859] a means for recognizing a user's emotions and analyzing the emotional information to adjust the content and tone of health management advice;

[1860] …

[1861] A system including:

[1862] (Claim 2)

[1863] 10. The system of claim 1, wherein the system provides real-time generated advice to a medical professional during a video call.

[1864] (Claim 3)

[1865] 2. The system according to claim 1, wherein the stored information is analyzed and used at the next consultation.

[1866] "Application example 2 when combining emotion engines"

[1867] (Claim 1)

[1868] a means for a user to input or provide basic information and genetic information;

[1869] means for storing and analyzing the provided genetic information, basic information, and lifestyle information;

[1870] A means for generating optimal individual health management advice for a user based on the analysis results;

[1871] A means for users and doctors to communicate in real time via video calls;

[1872] A means for centrally managing and storing information recorded during video calls;

[1873] A means for generating and displaying health-related advertisements optimized for the user based on the analyzed health information of the user;

[1874] A system that uses an emotion engine to analyze emotions from a user's facial expressions and tone of voice during a video call, and includes a means for adjusting the timing and content of advertisement display based on the analysis results.

[1875] (Claim 2)

[1876] 10. The system of claim 1, wherein the system provides real-time generated advice to a medical professional during a video call.

[1877] (Claim 3)

[1878] 2. The system according to claim 1, wherein the stored information is analyzed and used at the next consultation. [Explanation of symbols]

[1879] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for a user to input or provide basic information and genetic information; means for storing and analyzing the provided genetic information, basic information, and lifestyle information; A means for generating optimal individual health management advice for a user based on the analysis results; A means for users and doctors to communicate in real time via video calls; A means for centrally managing and storing information recorded during video calls; A system including:

2. The system of claim 1 , wherein the system provides real-time generated advice to a doctor during a video call.

3. 2. The system according to claim 1, wherein the stored information is analyzed and used at the next consulting session.

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