System

Abstract

A system is provided.SOLUTION: A system comprising: means for a mobile medical examination unit to patrol a specific area and provide a medical examination; means for a user to make an appointment for the mobile medical examination unit via an online platform; means for a virtual medical examination unit to remotely provide a medical examination to the user; means for collecting and analyzing information on a health condition through interaction with an avatar; and means for notifying the user of an analysis result via the online platform.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, people are reluctant to go to hospitals or clinics, making it difficult to undergo health checkups. Furthermore, it is difficult to fit regular health checkups into busy schedules, which can delay early detection of illness. Furthermore, there is a need for people to undergo health checkups in a relaxed environment without feeling any psychological burden. There is a need for an efficient and comprehensive system to solve these problems and improve access to health checkups. [Means for solving the problem]

[0005] The present invention provides a system that solves the above-mentioned problems by combining a mobile health checkup unit and a virtual health checkup unit. Specifically, the mobile health checkup unit travels to a specific area to provide health checkups, and users can make reservations for the mobile health checkup unit via an online platform. The virtual health checkup unit also provides remote health checkups to users, collecting and analyzing information about their health status through dialogue with an avatar. The analysis results are notified to the user via the online platform, and a referral to a specialist is also made if necessary. The generated avatar can interact with the user and ask initial questions about their health status, providing a relaxed diagnostic environment. This improves the accessibility of diagnosis and promotes early detection and appropriate medical treatment.

[0006] A "mobile health examination unit" is a medical examination facility that uses a mobile means such as a car or truck to travel around a specific area and provide on-site health examinations.

[0007] An "online platform" is a website or application that users can access via the Internet, and is a system for booking health checkups and viewing results.

[0008] "Virtual Health Examination Unit" refers to a system and its components that provides health examinations remotely via the Internet.

[0009] An "avatar" is a computer-generated or animated character used to interact with a user, asking and answering questions using a generative AI model.

[0010] A "generative AI model" is an artificial intelligence algorithm that collects and analyzes information about a user's health status through dialogue with the user, and generates appropriate questions and answers.

[0011] "Analysis results" refers to the results of data analysis performed by the generative AI model based on the collected user health information.

[0012] "Referral to a specialist" is the process of referring a user to a doctor who provides specialized medical services when necessary, based on the user's health information and analysis results. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

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

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

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

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0028] 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.

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

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. This system provides an environment where users can easily undergo health checkups without having to go to a hospital or clinic.

[0035] System configuration

[0036] The system includes the following major components:

[0037] 1. Mobile Health Checkup Unit

[0038] 2. Online Platforms

[0039] 3. Virtual Health Check Unit

[0040] 4. Avatar

[0041] 5. Generative AI Models

[0042] Program processing

[0043] 1. Mobile Health Checkup Unit

[0044] server:

[0045] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[0046] The booking system will be published on an online platform, allowing users to book health checkups.

[0047] User:

[0048] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[0049] Terminal (system in mobile health examination unit):

[0050] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[0051] The test results are entered into the terminal and sent to the server as digital data.

[0052] 2. Virtual Health Check Unit

[0053] server:

[0054] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[0055] User:

[0056] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[0057] Device (user's PC or smartphone):

[0058] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[0059] Avatar:

[0060] Use generative AI models to ask users the right questions and collect answers, engage users in relaxed conversations, and collect reliable data.

[0061] server:

[0062] The collected data is analyzed and the results of the health check are communicated to the user via an online platform, with a referral to a specialist provided if necessary.

[0063] Specific examples

[0064] 1. Examples of mobile health checkups

[0065] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[0066] 2. Use cases for virtual health checkups

[0067] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the information obtained, and sends it to the server. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[0068] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[0069] The processing flow will be explained below.

[0070] Mobile health examination unit processing steps

[0071] Step 1:

[0072] The server identifies areas with high demand based on past health checkup data for each region.

[0073] Step 2:

[0074] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[0075] Step 3:

[0076] The server displays the configured route on an online platform for residents to make reservations.

[0077] Step 4:

[0078] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[0079] Step 5:

[0080] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[0081] Step 6:

[0082] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[0083] Step 7:

[0084] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[0085] Step 8:

[0086] The terminal (a system within the mobile health examination unit) checks the reservation list.

[0087] Step 9:

[0088] The profile guides the user through the health checkup and performs the health checkup (e.g., measuring vital signs and blood tests).

[0089] Step 10:

[0090] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[0091] Step 11:

[0092] The server analyzes the collected health check results and generates a result report.

[0093] Step 12:

[0094] The server links the results report to the user's account and sends a result notification email.

[0095] Step 13:

[0096] The user logs in to the online platform and views the medical examination result report.

[0097] Virtual Health Check Unit Processing Steps

[0098] Step 1:

[0099] The server provides a virtual health checkup reservation system on an online platform.

[0100] Step 2:

[0101] The server displays the available dates and times for users to make reservations and updates the available slots.

[0102] Step 3:

[0103] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[0104] Step 4:

[0105] The user selects the desired date and time and makes a reservation.

[0106] Step 5:

[0107] The user enters the required information and completes the reservation.

[0108] Step 6:

[0109] The server saves the reservation information in a database and sends a confirmation email to the user.

[0110] Step 7:

[0111] The user logs into the online platform at the time of the reservation.

[0112] Step 8:

[0113] The device (user's PC or smartphone) starts the virtual health check session.

[0114] Step 9:

[0115] The avatar uses a generative AI model to ask the user appropriate questions.

[0116] Step 10:

[0117] The user interacts with the avatar to answer initial questions about their health.

[0118] Step 11:

[0119] The server analyzes the response data to the initial questions in real time.

[0120] Step 12:

[0121] The server generates additional detailed questions as needed.

[0122] Step 13:

[0123] The server analyzes the collected information, compiles the results and links them to the user's account.

[0124] Step 14:

[0125] The server notifies the user of the health check result report through the online platform.

[0126] Step 15:

[0127] The user views the medical examination result report.

[0128] Step 16:

[0129] The server will provide referrals to specialists as needed.

[0130] These steps ensure that the entire system operates smoothly, providing an environment in which users can easily undergo health checkups.

[0131] Example 1

[0132] 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."

[0133] Conventional health checkup systems require users to physically visit a medical facility, which can be a burden, especially for elderly people and those without cars. Furthermore, users living in remote areas have limited opportunities for health checkups, making early detection of illness difficult. Furthermore, there was a lack of efficient and accurate methods for collecting and analyzing initial questions and health checkup results and linking them to appropriate medical treatment.

[0134] 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.

[0135] In this invention, the server includes: means for analyzing regional health checkup needs and setting a route for the mobile health checkup unit; means for users to make reservations for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to check the reservation list, guide users in order to receive the health checkup, and conduct the health checkup; means for transmitting test results to the server as digital data; means for the virtual health checkup unit to remotely provide health checkups to users; means for an avatar to ask appropriate questions of the user using a generative AI model and collect and analyze information on the user's health status; means for notifying the user of the analysis results via the online platform; and means for, if necessary, referring the user to a specialist based on the health checkup results. This allows users to easily receive health checkups at home or in their neighborhood, improving accessibility to diagnosis and enabling early detection of diseases and appropriate medical treatment.

[0136] "Analyzing health checkup needs by region" means conducting statistical analysis of the health status and demand for health checkups of residents in a specific region based on past data, demographics, etc.

[0137] "Setting a patrol route" means planning the optimal route for the health examination unit to efficiently patrol a specific area.

[0138] An "online platform" is a general term for a system that users can access via the Internet and use various services such as making reservations, checking diagnostic results, and interacting with others.

[0139] A "mobile medical examination unit" is a device or vehicle equipped with the facilities to travel to various locations using the vehicle or device and provide medical examinations.

[0140] "Reservation List" means a list for recording and managing reservations made by a User through the Online Platform.

[0141] The "Virtual Health Check Unit" is a system that provides a mechanism for conducting health checkups remotely via the Internet.

[0142] A "generative AI model" is a program that uses artificial intelligence technology to interact with users and incorporates algorithms for asking questions and conducting analysis.

[0143] An "avatar" is a virtual entity that interacts with users and collects information about their health status using a generative AI model in a virtual health checkup unit.

[0144] "Digital data" refers to data used to store, analyze, and transmit health examination results in electronic form.

[0145] "Analysis results" are the results of statistical analysis or algorithmic analysis based on collected health status data.

[0146] "Referral" refers to transferring a user to an appropriate medical professional when necessary based on collected and analyzed medical examination data.

[0147] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. The purpose of this system is to provide an environment in which users can conveniently receive health checkups without having to go to a hospital or clinic. The following describes how this system is implemented.

[0148] Hardware and Software

[0149] The system includes several hardware and software components. The major hardware components include:

[0150] Mobile health checkup unit: A vehicle such as a bus or van that has been modified to accommodate medical equipment such as blood pressure monitors, thermometers, and blood testing machines.

[0151] Server: Located on a cloud platform (e.g., Amazon Web Services (AWS), Microsoft Azure) to store and process data.

[0152] User terminal: A device such as a PC or smartphone.

[0153] The main software components include:

[0154] Online platform: A web application that provides the reservation system, user interface, and results display functions. It uses React and Angular for the front end and Node.js and Django for the back end.

[0155] Generative AI model: An algorithm for conducting user interactions and collecting health-related information. Created using a machine learning framework (e.g., TensorFlow, PyTorch).

[0156] Data analysis tools: Statistical analysis software (e.g., R, Python) to analyze the collected data.

[0157] Example of a user scenario

[0158] 1. Example of use of the mobile health checkup unit

[0159] User A checks the date and time that the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation.

[0160] The mobile health checkup unit arrives at the park at the scheduled time and Mr. A undergoes a health checkup. When measuring his blood pressure, the device records the data and immediately sends it to the server. The results can then be viewed on an online platform.

[0161] 2. Use cases for virtual health checkups

[0162] User B books a virtual health checkup on an online platform.

[0163] At the scheduled time, the person logs in from their home PC and checks their health condition through dialogue with an avatar. The generative AI model asks, "How are you feeling lately?" and Person B responds. The server analyzes this data and uploads the diagnosis results to an online platform. Person B can check the results themselves later. If necessary, they will also be referred to a specialist.

[0164] Prompt Sentence Examples

[0165] "Where can I conveniently get a health checkup near me?" (related to mobile health checkup units)

[0166] "I would like to take a health check online. What is the process?" (related to the Virtual Health Check Unit)

[0167] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[0168] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0169] Step 1: Analyze your health checkup needs

[0170] server:

[0171] Input: Past health checkup data and demographic data by region

[0172] How it works: The server uses statistical analysis software (e.g., R, Python) to analyze the health checkup needs of each region. Specifically, it calculates the incidence rates of hypertension and diabetes in specific regions and determines which regions to prioritize for dispatching mobile health checkup units.

[0173] Output: List of priority areas for routing

[0174] Step 2: Setting up a tour route

[0175] server:

[0176] Input: Priority Region List

[0177] Operation: The server calculates the optimal tour route using a routing algorithm (e.g., Dijkstra's Algorithm). The calculation takes into account distance, time, and efficiency. The route information is generated as tour route information.

[0178] Output: Tour route information

[0179] Step 3: Publish your booking system

[0180] server:

[0181] Input: Tour route information

[0182] Operation: The server publishes a reservation system for mobile health checkup units on an online platform. The user interface is implemented using a web front-end (e.g., React, Angular), and the system back-end is implemented using Node.js and Django.

[0183] Output: A booking page accessible to the user

[0184] Step 4: Accept the reservation

[0185] User:

[0186] Input: Booking page of online platform

[0187] How it works: A user visits the online platform, selects the desired date, time, and location, and enters the necessary personal information, such as name, address, and contact details. Once the reservation is complete, a confirmation email is sent to the user.

[0188] Output: Reservation information, confirmation email

[0189] Step 5: Operating a mobile health screening unit

[0190] Terminal (system in mobile health examination unit):

[0191] Input: Tour route information, reservation list

[0192] Operation: The device follows the set route to the destination, locates using a GPS system (e.g., Google Maps API), reads the appointment list and guides users through the health checkup in order, and collects vital signs and test results from each user.

[0193] Output: Collected health data

[0194] Step 6: Send your test results

[0195] Terminal (system in mobile health examination unit):

[0196] Input: Collected health data

[0197] How it works: The terminal inputs the test results as digital data, encrypts them using the HTTPS protocol, and sends them to the server.

[0198] Output: Health data stored on the server

[0199] Step 7: Offer a virtual health check

[0200] server:

[0201] Input: User reservation information

[0202] Operation: The server provides a virtual health checkup on an online platform. It generates and transmits access information so that users can log in at the scheduled time.

[0203] Output: Virtual health check access information

[0204] Step 8: Start the Virtual Health Check

[0205] User:

[0206] Input: Virtual health check access information

[0207] How it works: Users log in to the online platform at a designated time and begin a virtual health screening session. They answer initial questions about their health status through an avatar that uses a generative AI model.

[0208] Output: Information about the user's health status

[0209] Step 9: Gathering health information

[0210] Avatar (generative AI model):

[0211] Input: User's answer

[0212] How it works: Using a generative AI model, the avatar asks appropriate questions to gather information about the user's health, such as "How are you feeling these days?", and stores the information gathered in a database.

[0213] Output: Collected health status data

[0214] Step 10: Data analysis and notification

[0215] server:

[0216] Input: Collected health status data

[0217] How it works: The server analyzes the collected data using machine learning algorithms (e.g., SVM, Random Forest). Based on the analysis results, it generates a health check result and notifies the user through an online platform. If necessary, it will refer the user to a specialist.

[0218] Output: Health checkup results, referral information to specialists

[0219] In this way, the system allows users to easily undergo a health check through a series of steps, improving the accuracy and efficiency of the diagnosis.

[0220] (Application example 1)

[0221] 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."

[0222] Conventional health checkup systems require users to physically visit a hospital or clinic, and for occupations requiring regular health management as employees, time and geographical constraints make it difficult to streamline health management. In particular, for occupations that require frequent travel, such as food delivery, regular health monitoring is often not adequately carried out. This has led to a decline in the utilization rate of health checkups and an increase in employee health risks.

[0223] 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.

[0224] In this invention, the server includes a means for providing real-time health checkup results and notifications to companies that aim to manage the health of their employees, a means for a mobile health checkup unit to travel to specific areas to provide health checkups, and a means for using a generative AI model to provide supplementary information on analysis results and referrals to specialists. This enables even employees who move around a lot to receive regular health checkups, improving the efficiency of health management.

[0225] A "mobile health check unit" is a mobile diagnostic device that travels around the area to provide health checkups to users.

[0226] "Online Platform" means a web-based system that allows Users to access and use the Services.

[0227] "Reservation method" refers to a system that allows users to make reservations for health checkups through an online platform.

[0228] The "Virtual Health Check Unit" is a digital diagnostic system that provides remote health checkups to users.

[0229] An "avatar" is a virtual character that interacts with users online and collects information about their health status.

[0230] A "generative AI model" is a model generated using an artificial intelligence algorithm to analyze health checkup results and provide supplementary information.

[0231] "Analysis means" refers to the process of analyzing collected health information and generating results.

[0232] "Means of providing in real time" refers to a method for providing health examination results and notifications to users immediately.

[0233] "Means for referring to specialists" refers to a system for referring users to specialists as needed based on the results of their health checkups.

[0234] "User" means a person who receives the services of the health examination system.

[0235] "Employee health management" refers to activities undertaken by companies to manage the health status of their employees and provide appropriate care.

[0236] This invention is a system for streamlining employee health management, particularly for occupations that require frequent travel. The system includes a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, and a generative AI model.

[0237] System configuration

[0238] 1. Mobile Health Checkup Unit

[0239] server

[0240] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[0241] The booking system will be made available on an online platform, allowing users to book health checkups.

[0242] User

[0243] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[0244] Terminal (system inside the mobile health checkup unit)

[0245] They will follow a set route to arrive at the designated area, check the reservation list, guide users in order to undergo health checkups, and perform health checkups such as measuring vital signs and blood tests.

[0246] The test results are entered into the terminal and sent to the server as digital data.

[0247] 2. Virtual Health Check Unit

[0248] server

[0249] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for their appointments.

[0250] User

[0251] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[0252] Device (user's PC or smartphone)

[0253] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an on-screen avatar to answer initial questions about their health.

[0254] Avatar

[0255] Uses generative AI models to ask users the right questions and collect answers, leading to a more relaxed dialogue and collecting reliable data.

[0256] server

[0257] The collected data will be analyzed and the results of the health check will be communicated to users via an online platform, with referrals to specialists provided if necessary.

[0258] Hardware and software used

[0259] Hardware: Smartphones, servers, PCs

[0260] Software: Flask (Python web framework), MySQL (database), TensorFlow (generative AI model)

[0261] Data processing and calculation

[0262] server

[0263] Health data collected from users is stored in a database, including vital signs, blood test results, and conversation data.

[0264] Using a generative AI model, the collected data is analyzed in real time to assess the user's health status, and the results are communicated to experts who can provide appropriate advice or refer the user to a specialist if necessary.

[0265] Specific examples

[0266] 1. Health checkup appointment

[0267] Employees log in to the online platform and make a reservation by specifying the desired date, time, and location on the mobile health examination unit's reservation page.

[0268] 2. Virtual Health Checkup

[0269] Employees book a virtual consultation on their smartphone, and the generative AI model asks questions at the specified date and time.

[0270] Example prompts for generative AI models

[0271] "Please answer the following questions regarding your health: Have you been feeling unwell recently?

[0272] "What is the level of stress you experience on a daily basis?"

[0273] "Tell me about your diet and exercise habits."

[0274] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0275] Step 1:

[0276] The server analyzes the health checkup needs of each region and sets the route for the mobile health checkup unit. It uses historical data and demographic data as input, which it retrieves from a database. It uses a data analysis algorithm to calculate the optimal route and outputs the results as the route setting information.

[0277] Step 2:

[0278] The user logs in to the online platform and opens the reservation page for the mobile health examination unit. The user selects the desired date, time, and location, and enters the required personal information. The entered information is sent to the server and saved in the database as reservation information.

[0279] Step 3:

[0280] The server generates a schedule for the mobile health checkup unit based on the set route and reservation information from the user. It uses the travel route setting information and reservation information as input, creates a visit schedule list for each unit based on these, and outputs it as schedule information.

[0281] Step 4:

[0282] The terminal (a system within the mobile health checkup unit) arrives at the designated area and checks the reservation list. It uses the schedule information and reservation list data sent from the server as input. Based on this, the terminal guides users in order of their health checkup, measures their vital signs, and performs blood tests. The health checkup data is acquired and temporarily stored within the terminal.

[0283] Step 5:

[0284] The terminal sends the acquired health checkup data to the server. The measured health checkup data is used as input, converted into digital data, and uploaded to the server. The server receives this data and stores it in a database.

[0285] Step 6:

[0286] Users log in to the online platform and open the virtual health checkup reservation page. They select the desired date and time and enter the necessary information to complete the reservation. The entered reservation information is sent to the server and saved in the database.

[0287] Step 7:

[0288] The user re-logins into the online platform at the scheduled time and starts the virtual health check session. They interact with an avatar displayed on the screen and answer initial questions about their health status. The user's response data is collected as input and sent to the server.

[0289] Step 8:

[0290] The avatar analyzes the user's responses using a generative AI model. Using the collected data as input, it performs a health assessment through the analytical model. The analysis results are sent to a server and stored in a database.

[0291] Step 9:

[0292] The server generates health checkup results based on the analysis results and notifies the user via the online platform, including referral information to a specialist if necessary. It uses the analysis result data as input and generates a notification message that is output to the user.

[0293] Step 10:

[0294] If a user wishes to consult with a specialist, they can use the online platform to make an appointment with the specialist. The health checkup results and specialist referral information are used as input, and appointment information is generated based on this and sent to the server. The server then stores the appointment information in a database and notifies the specialist.

[0295] The above are the specific processing steps of the system program for carrying out the invention.

[0296] 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.

[0297] This invention relates to a system that combines a mobile health checkup unit with a virtual health checkup unit and is equipped with an emotion engine. This system provides an environment where users can easily undergo health checkups, and furthermore, recognizes the user's emotional state to improve diagnostic accuracy and user experience.

[0298] System configuration

[0299] The system includes the following major components:

[0300] 1. Mobile Health Checkup Unit

[0301] 2. Online Platforms

[0302] 3. Virtual Health Check Unit

[0303] 4. Avatar

[0304] 5. Generative AI Models

[0305] 6. Emotion Engine

[0306] Program processing

[0307] 1. Mobile Health Checkup Unit

[0308] server:

[0309] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[0310] The booking system will be published on an online platform, allowing users to book health checkups.

[0311] User:

[0312] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[0313] Terminal (system in mobile health examination unit):

[0314] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[0315] The test results are entered into the terminal and sent to the server as digital data.

[0316] 2. Virtual Health Check Unit

[0317] server:

[0318] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[0319] User:

[0320] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[0321] Device (user's PC or smartphone):

[0322] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[0323] Avatar:

[0324] It uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0325] The content of the dialogue is adjusted based on the user's emotional data to help the user relax. For example, if the user is nervous, the dialogue will be designed to relax the user.

[0326] server:

[0327] Analyze data from the emotion engine and adjust the difficulty and content of the initial questions.

[0328] The results of the health check will be communicated to users via an online platform, and if necessary, a referral to a specialist will be made.

[0329] Specific examples

[0330] 1. Example of use of the mobile health checkup unit

[0331] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[0332] 2. Example of use of the virtual health checkup unit

[0333] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the obtained information, and sends it to the server. The emotion engine analyzes B's facial expressions and tone of voice and engages in dialogue to help him relax. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[0334] In this way, this system allows users to easily undergo health checkups at home or nearby locations. By using the emotion engine, it is possible to improve the accuracy of the diagnosis while ensuring user comfort, thereby realizing accessibility of the diagnosis and improving the user experience.

[0335] The processing flow will be explained below.

[0336] Mobile health examination unit processing steps

[0337] Step 1:

[0338] The server identifies areas with high demand based on past health checkup data for each region.

[0339] Step 2:

[0340] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[0341] Step 3:

[0342] The server displays the configured route on an online platform for residents to make reservations.

[0343] Step 4:

[0344] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[0345] Step 5:

[0346] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[0347] Step 6:

[0348] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[0349] Step 7:

[0350] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[0351] Step 8:

[0352] The terminal (a system within the mobile health examination unit) checks the reservation list.

[0353] Step 9:

[0354] The terminal (a system within the mobile health checkup unit) guides users through the health checkup in order and performs the health checkup (e.g., measuring vital signs and blood tests).

[0355] Step 10:

[0356] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[0357] Step 11:

[0358] The server analyzes the collected health check results and generates a result report.

[0359] Step 12:

[0360] The server links the results report to the user's account and sends a result notification email.

[0361] Step 13:

[0362] The user logs in to the online platform and views the medical examination result report.

[0363] Virtual Health Check Unit Processing Steps

[0364] Step 1:

[0365] The server provides a virtual health checkup reservation system on an online platform.

[0366] Step 2:

[0367] The server displays the available dates and times for users to make reservations and updates the available slots.

[0368] Step 3:

[0369] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[0370] Step 4:

[0371] The user selects the desired date and time and makes a reservation.

[0372] Step 5:

[0373] The user enters the required information and completes the reservation.

[0374] Step 6:

[0375] The server saves the reservation information in a database and sends a confirmation email to the user.

[0376] Step 7:

[0377] The user logs into the online platform at the time of the reservation.

[0378] Step 8:

[0379] The device (user's PC or smartphone) starts the virtual health check session.

[0380] Step 9:

[0381] The avatar uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0382] Step 10:

[0383] The user interacts with the avatar to answer initial questions about their health.

[0384] Step 11:

[0385] The avatar adjusts the dialogue based on the user's emotional data to help the user relax. For example, if the user is nervous, the avatar will engage in dialogue to relax the user.

[0386] Step 12:

[0387] The server analyzes the response data to the initial questions in real time.

[0388] Step 13:

[0389] The server generates additional detailed questions as needed.

[0390] Step 14:

[0391] The server analyzes the collected information, compiles the results and links them to the user's account.

[0392] Step 15:

[0393] The server notifies the user of the health check result report through the online platform.

[0394] Step 16:

[0395] The user views the medical examination result report.

[0396] Step 17:

[0397] The server will provide referrals to specialists as needed.

[0398] Example 2

[0399] 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."

[0400] Conventional health checkup systems face problems such as insufficient access for users to undergo regular checkups and inaccurate diagnostic results. Furthermore, there are insufficient means to alleviate the tension and anxiety users feel during the diagnostic process. This makes it difficult to obtain accurate health checkup results and does not improve the user experience. Furthermore, it is difficult to provide diagnoses to users in remote locations.

[0401] 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.

[0402] In this invention, the server includes: means for analyzing regional health checkup needs and setting a mobile health checkup unit's route; means for a user to make a reservation for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to arrive at the designated area, conduct the health checkup, and transmit the results to the server; means for the virtual health checkup unit to provide a remote health checkup to the user; means for collecting and analyzing information about the user's health status through dialogue with an avatar; means for analyzing the user's emotional state using an emotion engine and adjusting the dialogue content based on the analysis results; means for notifying the user of the analysis results via the online platform; and means for referring the user to a doctor if necessary. This allows users to easily receive health checkups, and the emotion engine reduces tension and anxiety during the checkup process, providing accurate health checkup results and a high-quality user experience. Health checkups can also be provided to users in remote locations.

[0403] A "mobile health examination unit" is a unit equipped with vehicles and equipment for traveling to a specific area to provide health examinations.

[0404] "Medical checkup needs" refers to the demand for medical checkups in a particular area, analyzed based on demographics and past data.

[0405] A "patrol route" is a route set up for a mobile health examination unit to travel through a particular area.

[0406] "Online platform" means a website or application that users can access via the internet to book health checkups and check their results.

[0407] A "Virtual Health Check Unit" is a system for providing health checks to users remotely, accessible through an online platform.

[0408] An "avatar" is a virtual person or character that interacts with the user within the virtual health checkup unit.

[0409] An "emotion engine" is software that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0410] A "generative AI model" is a model that uses artificial intelligence technology to generate appropriate questions to engage in dialogue with users.

[0411] "Physical examination results" refers to the examination results of a medical examination that the user has undergone, and includes blood test results and vital sign measurement results.

[0412] "Referral to a doctor" refers to the procedure of referring the user to a specialist based on the results of the health check.

[0413] This invention is a system that integrates a mobile health checkup unit and a virtual health checkup unit, allowing users to easily undergo health checkups. It also aims to improve the accuracy of diagnosis and the user experience by using an emotion engine to recognize the user's emotional state in real time.

[0414] System Components

[0415] The system includes the following major components:

[0416] 1. Mobile Health Checkup Unit

[0417] 2. Online Platforms

[0418] 3. Virtual Health Check Unit

[0419] 4. Avatar

[0420] 5. Generative AI Models

[0421] 6. Emotion Engine

[0422] Mobile Health Checkup Unit

[0423] The server analyzes the health checkup needs of each area and plans the routes for the mobile health checkup units. To do this, it uses Python to extract data from a demographic database and compiles statistics such as age group, gender, and medical history to identify areas with high demand. It then uses AWS Lambda to run the routing algorithm and generate the optimal route.

[0424] The server publishes route information and the reservation system to an online platform. The reservation page is created using JavaScript and React, and the backend is built with Node.js. Users log in to the online platform, select the desired date, time, and location, and make a reservation.

[0425] The terminal (a system inside the mobile health checkup unit) arrives at the designated area according to a set route, and the system checks the reservation list and guides the user in order. Medical staff measure the user's vital signs and perform blood tests, and send the results to the server in real time.

[0426] Virtual Health Check Unit

[0427] The server implements a booking function using the Django framework to publish a virtual health checkup booking system on an online platform, providing users with selectable dates and times.

[0428] Users access the virtual health checkup reservation page, select the desired date and time, and make a reservation. At the scheduled time, they log in to the online platform from their home PC or smartphone to start the virtual health checkup session.

[0429] The avatar uses a generative AI model to ask initial questions about the user's health status. The model uses Python and natural language processing (NLP) techniques to generate appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize the user's emotional state in real time.

[0430] The server analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the obtained data, it generates the next dialogue content, providing a comfortable dialogue environment for the user.

[0431] Specific examples

[0432] For example, when using a mobile health checkup unit, User A checks the date and time that the mobile health checkup unit will arrive at a nearby park on the online platform, selects the desired date and time, and the park, and makes a reservation. The unit arrives on the reserved date and time, and User A undergoes the health checkup. Medical staff measure User A's blood pressure and heart rate and send the data to a server in real time. User A can check the diagnosis results later on the online platform.

[0433] When using the virtual health check unit, User B books a virtual health check on the online platform. User B selects the desired date and time and confirms the reservation. At the scheduled date and time, User B logs in from their home PC and begins a conversation with the avatar. The avatar asks, "How are you feeling lately?" and User B responds. The emotion engine analyzes User B's facial expressions and tone of voice and engages in a conversation designed to relax them. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[0434] Example prompts for generative AI models

[0435] "Use a virtual health check unit to generate initial questions to check the user's health. Take into account the user's emotional state and adjust the dialogue as needed."

[0436] In this way, the system allows users to easily undergo health checkups at home or nearby locations, and by using an emotion engine, improves the accuracy of the diagnosis while ensuring user comfort.

[0437] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0438] Step 1:

[0439] Server: Analyzes regional health checkup needs. Extracts data from a demographic database and uses Python to compile statistics such as age group, gender, and medical history to identify areas with high demand.

[0440] Input: Demographic data (age range, gender, medical history, etc.)

[0441] Output: List of areas with high demand for health checkups

[0442] What it does: The server accesses a demographic database to gather the necessary data, then analyzes the data using Python data analysis libraries (e.g., Pandas, NumPy) to identify areas with high demand.

[0443] Step 2:

[0444] Server: Plans the mobile health check unit's route based on the analysis results. AWS Lambda is used to run the route planning algorithm and generate the optimal route.

[0445] Input: List of areas with high demand for health checkups

[0446] Output: Optimal tour route

[0447] What happens: The server triggers AWS Lambda to run a pre-configured routing algorithm, which calculates the optimal route based on the list of areas and saves the results.

[0448] Step 3:

[0449] Server: Publish the reservation system on an online platform based on the set route. Create the reservation page using JavaScript and React, and build the backend using Node.js.

[0450] Input: Optimal tour route

[0451] Output: Online platform with published reservation system

[0452] What it does: The server retrieves the route information, builds the user interface using JavaScript and React, sets up a backend system using Node.js to store reservation information, and publishes it to an online platform.

[0453] Step 4:

[0454] User: Logs into the online platform, selects the desired date, time and location and makes a reservation.

[0455] Input: User login information, desired date and time, and location selection

[0456] Output: User's reservation information is saved in the database

[0457] Specific operation: A user logs in to the online platform, selects the desired date, time and location on the interface, enters the required information in the reservation form and submits it. The submitted reservation information is then stored in a database by the server.

[0458] Step 5:

[0459] Terminal (system inside the mobile health checkup unit): Arrives at the designated area according to the set route and checks the appointment list. Medical staff guides the user, measures vital signs and performs blood tests, and enters the results into the terminal.

[0460] Input: Reservation list, health check results

[0461] Output: The entered health check results are sent to the server.

[0462] Specific operation: The terminal inside the mobile unit checks the reservation list and guides each user in order. Medical staff take the user's vital signs and perform blood tests, and enter the results into the terminal. The entered data is sent to the server in real time.

[0463] Step 6:

[0464] Server: Provides a virtual health checkup booking system on an online platform. Implements the booking function using the Django framework and provides users with selectable dates and times.

[0465] Input: Virtual health check appointment information

[0466] Output: Online platform with published reservation system

[0467] What it does: The server implements the reservation function using the Django framework, provides date and time information that users can select, and publishes the reservation system on an online platform.

[0468] Step 7:

[0469] User: Visits the virtual health checkup booking page, selects the desired date and time, and makes a booking.

[0470] Input: User login information, desired date and time

[0471] Output: User's reservation information is saved in the database

[0472] Specific operation: A user logs in to the online platform, enters the desired date and time, and confirms the reservation. The entered reservation information is sent to the server and recorded in the database.

[0473] Step 8:

[0474] User: Logs into the online platform at the scheduled time and date to begin the virtual health assessment session.

[0475] Input: User login information, reservation information

[0476] Output: An interactive session with the avatar is started.

[0477] Specific operation: The user logs in at the scheduled date and time and starts the virtual health check session. Once the session starts, the user conducts the health check through interaction with the avatar.

[0478] Step 9:

[0479] Avatar: Uses generative AI models to ask the user appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0480] Input: Generative AI model, emotion engine

[0481] Output: User health information, sentiment analysis data

[0482] How it works: The avatar uses generative AI models to generate appropriate questions, and the emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize their emotional state in real time.

[0483] Step 10:

[0484] Server: Analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the information obtained, the next dialogue content is generated.

[0485] Input: Sentiment analysis data, user responses

[0486] Output: Tailored questions and dialogue

[0487] How it works: The server analyzes the data sent from the emotion engine, adjusts the difficulty and content of the initial questions, and then uses NLP models to generate the next questions and dialogue.

[0488] Step 11:

[0489] Server: Analyzes the results of the virtual health check and notifies the user via the online platform, and if necessary, provides a referral to a specialist.

[0490] Input: Virtual health check results

[0491] Output: Notification of results, referral to specialist

[0492] What it does: The server analyzes the health check results and displays them on the user's personal dashboard. If necessary, it also arranges for the user to be referred to a specialist.

[0493] (Application example 2)

[0494] 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."

[0495] There is a need to improve the efficiency and accuracy of health checkups and mental healthcare for factory workers. Conventional health checkup systems have difficulty analyzing not only the physical health status of employees but also their emotional state and providing follow-up as needed. In addition, automation of emotion analysis and data management is insufficient, making it difficult to improve the quality and efficiency of healthcare.

[0496] 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.

[0497] In this invention, the server includes a means including a factory patrol healthcare robot that performs health checks and analyzes the emotional state of employees working in a factory environment, a means for performing emotion analysis using a generative AI model and storing the results in a database, and a means for collecting and analyzing information about the health state through dialogue with an avatar. This makes it possible to analyze not only the physical health state of employees but also their emotional state in real time and provide appropriate follow-ups automatically.

[0498] A "mobile health checkup unit" is a device that travels around a specific area and provides health checkups to users.

[0499] "User" means an individual who books a medical examination or takes a virtual medical examination via the online platform.

[0500] "Online platform" refers to the online system that users use to make appointments with health examination units and check examination results.

[0501] A "virtual health examination unit" is a virtual diagnostic device for providing a remote health examination to a user.

[0502] An "avatar" is a virtual character that interacts with users on an online platform and collects information about their health status.

[0503] A "generative AI model" is an artificial intelligence algorithm used to interact with users and conduct sentiment analysis.

[0504] An "emotion engine" is software that recognizes and analyzes a user's emotional state in real time.

[0505] "Factory environment" refers to the entire working environment in which members working within a factory are active.

[0506] The "factory patrol healthcare robot" is a robot that patrols the factory, conducting health checks and analyzing emotional states.

[0507] A "health checkup" is a series of tests and evaluations to assess a user's health status.

[0508] "Emotional state" refers to the user's mental and psychological state, as analyzed by the emotion engine.

[0509] A "database" is a digital information storage system for storing the results of health checks and emotion analysis.

[0510] The system for implementing this invention consists of a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, a generative AI model, a supply device, and an emotion engine. In a factory environment, it also includes a roving healthcare robot. The specific configuration and operation method of the system are described below.

[0511] System configuration

[0512] Mobile health check unit: A device that travels around a specific area and provides health checks to users.

[0513] Online platform: An internet system where users can book health checkups and check results.

[0514] Virtual Health Check Unit: A virtual diagnostic device that provides remote health checks to users.

[0515] Avatar: A virtual character that interacts with the user and collects information about their health.

[0516] Generative AI model: An artificial intelligence algorithm that interacts with users and analyzes their emotions.

[0517] Emotion Engine: Software that recognizes and analyzes the user's emotional state in real time.

[0518] Factory-specific healthcare robot: A robot that patrols the factory, conducting health checks and analyzing emotional states.

[0519] How the program works

[0520] 1. Mobile Health Checkup Unit

[0521] Server: Analyzes health checkup needs based on historical data and demographics, and sets up round routes. Publishes the reservation system on an online platform, allowing users to select their preferred date, time, and location.

[0522] User: Logs in to the online platform and makes an appointment for a health check. The mobile health check unit will provide the health check at the designated date, time and location.

[0523] Terminal: Collects health checkup results and sends them to the server as digital data.

[0524] 2. Virtual Health Check Unit

[0525] Server: Accepts reservations for virtual health checkups through an online platform.

[0526] User: Logs in to the online platform at the scheduled time and undergoes a health check. Through dialogue with an avatar, the user answers initial questions about their health condition.

[0527] Avatar: Uses a generative AI model to ask appropriate questions, and an emotion engine to analyze the user's facial expressions and tone of voice, providing a relaxing dialogue. The analysis results are sent to a server.

[0528] 3. Factory Patrol Healthcare Robot

[0529] Server: Manages data for analyzing the health and emotional state of members working in the factory environment.

[0530] Factory-specific healthcare robot: This robot patrols the factory, conducting health checks and emotional analysis of employees. It sends the results to a server and provides follow-up as needed.

[0531] Emotion engine: Provides the results of health checkups and emotion analysis as relaxing dialogues and health advice.

[0532] Specific examples

[0533] 1. Example of use of the mobile health checkup unit

[0534] Users make a reservation through the online platform, and a mobile health screening unit arrives at the designated park to conduct the health screening. The results can be viewed later on the online platform.

[0535] 2. Example of use of the virtual health checkup unit

[0536] Users log in to the virtual health checkup from their home PC and interact with an avatar to check their health status. A generative AI model asks initial health-related questions, and an emotion engine analyzes the user's emotional state and provides relaxing dialogue.

[0537] 3. Example of use of a patrol healthcare robot in a factory

[0538] The robot patrols the factory, checking the health of employees and analyzing their stress levels using an emotion engine. The generative AI model automatically suggests appropriate follow-up measures. If an employee shows high levels of stress, it offers a dialogue to promote relaxation and health advice.

[0539] Prompt Sentence Examples

[0540] "Staff member A may be experiencing high stress due to a recent project. Please suggest some conversations to help him relax."

[0541] "Staff member B's vital signs are outside of normal range. Please suggest additional medical examinations and provide any necessary follow-up."

[0542] The above system configuration and operation method make it possible to carry out the invention.

[0543] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0544] Step 1:

[0545] The server analyzes past data and demographic data to predict health checkup needs. Using past health checkup data and demographic data as input, the server uses an analytical algorithm to determine the health checkup demand in each region and set up a tour route. The output is the set tour route.

[0546] Step 2:

[0547] A user logs in to the online platform and makes an appointment for a health checkup. The user provides the platform with their login information, desired date, time, and location as input, and submits an appointment request. The user is provided with an appointment confirmation as output.

[0548] Step 3:

[0549] The mobile health checkup unit's terminal moves to the designated area according to the set route and checks the reservation list. Using the route information and reservation list sent from the server as input, the unit carries out the health checkup corresponding to each reservation. The health checkup results are recorded on the terminal as output.

[0550] Step 4:

[0551] The terminal sends the results of the health checkup to the server. The health checkup results recorded on the terminal as input are formatted in a database format and sent to the server. The health checkup data stored on the server is obtained as output.

[0552] Step 5:

[0553] The server provides a virtual health checkup reservation system on an online platform. It receives the user's reservation information and desired date and time as input, manages the virtual health checkup schedule, and provides the user's reservation confirmation information as output.

[0554] Step 6:

[0555] Users log in to the online platform at the scheduled time and date to undergo a virtual health check. They provide their login and reservation information to the platform as input to begin the diagnostic process. The output is an interactive screen with an avatar that is displayed in real time.

[0556] Step 7:

[0557] The avatar uses a generative AI model to ask questions about the user's health status and analyzes their responses. It uses the user's response data and the emotion engine's analysis results as inputs to provide appropriate feedback. The output is the user's response data and the corresponding emotion analysis results.

[0558] Step 8:

[0559] The server notifies the user of the health checkup results and emotion analysis results through the online platform. The server uses the analyzed health checkup data and emotion data as input to generate an appropriate notification message. The notification message is then displayed on the user's platform screen as output.

[0560] Step 9:

[0561] The in-factory patrol healthcare robot patrols the factory, conducting health checks and emotional analysis of employees. It uses the employees' health and emotional data collected on-site as input and analyzes it in real time. The analysis results are sent to the robot terminal and server as output.

[0562] Step 10:

[0563] The emotion engine analyzes the acquired emotion data and evaluates the mental health state of the member. Data acquired from the emotion sensor is input to the emotion engine, and mental health is evaluated using an analysis algorithm. The evaluation result is obtained as output.

[0564] Step 11:

[0565] The server proposes necessary follow-up measures based on the evaluation results. Using the emotion engine's evaluation results and health checkup data as input, it generates an appropriate follow-up plan using a generative AI model. The follow-up plan is then notified to the user as output.

[0566] In this way, the entire system operates in cooperation, enabling efficient health checkups and mental health care for users.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] [Second embodiment]

[0571] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0572] 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.

[0573] 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).

[0574] 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.

[0575] 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.

[0576] 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).

[0577] 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.

[0578] 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.

[0579] 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.

[0580] 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.

[0581] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0582] 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."

[0583] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. This system provides an environment where users can easily undergo health checkups without having to go to a hospital or clinic.

[0584] System configuration

[0585] The system includes the following major components:

[0586] 1. Mobile Health Checkup Unit

[0587] 2. Online Platforms

[0588] 3. Virtual Health Check Unit

[0589] 4. Avatar

[0590] 5. Generative AI Models

[0591] Program processing

[0592] 1. Mobile Health Checkup Unit

[0593] server:

[0594] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[0595] The booking system will be published on an online platform, allowing users to book health checkups.

[0596] User:

[0597] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[0598] Terminal (system in mobile health examination unit):

[0599] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[0600] The test results are entered into the terminal and sent to the server as digital data.

[0601] 2. Virtual Health Check Unit

[0602] server:

[0603] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[0604] User:

[0605] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[0606] Device (user's PC or smartphone):

[0607] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[0608] Avatar:

[0609] Use generative AI models to ask users the right questions and collect answers, engage users in relaxed conversations, and collect reliable data.

[0610] server:

[0611] The collected data is analyzed and the results of the health check are communicated to the user via an online platform, with a referral to a specialist provided if necessary.

[0612] Specific examples

[0613] 1. Examples of mobile health checkups

[0614] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[0615] 2. Use cases for virtual health checkups

[0616] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the information obtained, and sends it to the server. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[0617] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[0618] The processing flow will be explained below.

[0619] Mobile health examination unit processing steps

[0620] Step 1:

[0621] The server identifies areas with high demand based on past health checkup data for each region.

[0622] Step 2:

[0623] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[0624] Step 3:

[0625] The server displays the configured route on an online platform for residents to make reservations.

[0626] Step 4:

[0627] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[0628] Step 5:

[0629] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[0630] Step 6:

[0631] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[0632] Step 7:

[0633] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[0634] Step 8:

[0635] The terminal (a system within the mobile health examination unit) checks the reservation list.

[0636] Step 9:

[0637] The profile guides the user through the health checkup and performs the health checkup (e.g., measuring vital signs and blood tests).

[0638] Step 10:

[0639] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[0640] Step 11:

[0641] The server analyzes the collected health check results and generates a result report.

[0642] Step 12:

[0643] The server links the results report to the user's account and sends a result notification email.

[0644] Step 13:

[0645] The user logs in to the online platform and views the medical examination result report.

[0646] Virtual Health Check Unit Processing Steps

[0647] Step 1:

[0648] The server provides a virtual health checkup reservation system on an online platform.

[0649] Step 2:

[0650] The server displays the available dates and times for users to make reservations and updates the available slots.

[0651] Step 3:

[0652] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[0653] Step 4:

[0654] The user selects the desired date and time and makes a reservation.

[0655] Step 5:

[0656] The user enters the required information and completes the reservation.

[0657] Step 6:

[0658] The server saves the reservation information in a database and sends a confirmation email to the user.

[0659] Step 7:

[0660] The user logs into the online platform at the time of the reservation.

[0661] Step 8:

[0662] The device (user's PC or smartphone) starts the virtual health check session.

[0663] Step 9:

[0664] The avatar uses a generative AI model to ask the user appropriate questions.

[0665] Step 10:

[0666] The user interacts with the avatar to answer initial questions about their health.

[0667] Step 11:

[0668] The server analyzes the response data to the initial questions in real time.

[0669] Step 12:

[0670] The server generates additional detailed questions as needed.

[0671] Step 13:

[0672] The server analyzes the collected information, compiles the results and links them to the user's account.

[0673] Step 14:

[0674] The server notifies the user of the health check result report through the online platform.

[0675] Step 15:

[0676] The user views the medical examination result report.

[0677] Step 16:

[0678] The server will provide referrals to specialists as needed.

[0679] These steps ensure that the entire system operates smoothly, providing an environment in which users can easily undergo health checkups.

[0680] Example 1

[0681] 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."

[0682] Conventional health checkup systems require users to physically visit a medical facility, which can be a burden, especially for elderly people and those without cars. Furthermore, users living in remote areas have limited opportunities for health checkups, making early detection of illness difficult. Furthermore, there was a lack of efficient and accurate methods for collecting and analyzing initial questions and health checkup results and linking them to appropriate medical treatment.

[0683] 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.

[0684] In this invention, the server includes: means for analyzing regional health checkup needs and setting a route for the mobile health checkup unit; means for users to make reservations for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to check the reservation list, guide users in order to receive the health checkup, and conduct the health checkup; means for transmitting test results to the server as digital data; means for the virtual health checkup unit to remotely provide health checkups to users; means for an avatar to ask appropriate questions of the user using a generative AI model and collect and analyze information on the user's health status; means for notifying the user of the analysis results via the online platform; and means for, if necessary, referring the user to a specialist based on the health checkup results. This allows users to easily receive health checkups at home or in their neighborhood, improving accessibility to diagnosis and enabling early detection of diseases and appropriate medical treatment.

[0685] "Analyzing health checkup needs by region" means conducting statistical analysis of the health status and demand for health checkups of residents in a specific region based on past data, demographics, etc.

[0686] "Setting a patrol route" means planning the optimal route for the health examination unit to efficiently patrol a specific area.

[0687] An "online platform" is a general term for a system that users can access via the Internet and use various services such as making reservations, checking diagnostic results, and interacting with others.

[0688] A "mobile medical examination unit" is a device or vehicle equipped with the facilities to travel to various locations using the vehicle or device and provide medical examinations.

[0689] "Reservation List" means a list for recording and managing reservations made by a User through the Online Platform.

[0690] The "Virtual Health Check Unit" is a system that provides a mechanism for conducting health checkups remotely via the Internet.

[0691] A "generative AI model" is a program that uses artificial intelligence technology to interact with users and incorporates algorithms for asking questions and conducting analysis.

[0692] An "avatar" is a virtual entity that interacts with users and collects information about their health status using a generative AI model in a virtual health checkup unit.

[0693] "Digital data" refers to data used to store, analyze, and transmit health examination results in electronic form.

[0694] "Analysis results" are the results of statistical analysis or algorithmic analysis based on collected health status data.

[0695] "Referral" refers to transferring a user to an appropriate medical professional when necessary based on collected and analyzed medical examination data.

[0696] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. The purpose of this system is to provide an environment in which users can conveniently receive health checkups without having to go to a hospital or clinic. The following describes how this system is implemented.

[0697] Hardware and Software

[0698] The system includes several hardware and software components. The major hardware components include:

[0699] Mobile health checkup unit: A vehicle such as a bus or van that has been modified to accommodate medical equipment such as blood pressure monitors, thermometers, and blood testing machines.

[0700] Server: Located on a cloud platform (e.g., Amazon Web Services (AWS), Microsoft Azure) to store and process data.

[0701] User terminal: A device such as a PC or smartphone.

[0702] The main software components include:

[0703] Online platform: A web application that provides the reservation system, user interface, and results display functions. It uses React and Angular for the front end and Node.js and Django for the back end.

[0704] Generative AI model: An algorithm for conducting user interactions and collecting health-related information. Created using a machine learning framework (e.g., TensorFlow, PyTorch).

[0705] Data analysis tools: Statistical analysis software (e.g., R, Python) to analyze the collected data.

[0706] Example of a user scenario

[0707] 1. Example of use of the mobile health checkup unit

[0708] User A checks the date and time that the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation.

[0709] The mobile health checkup unit arrives at the park at the scheduled time and Mr. A undergoes a health checkup. When measuring his blood pressure, the device records the data and immediately sends it to the server. The results can then be viewed on an online platform.

[0710] 2. Use cases for virtual health checkups

[0711] User B books a virtual health checkup on an online platform.

[0712] At the scheduled time, the person logs in from their home PC and checks their health condition through dialogue with an avatar. The generative AI model asks, "How are you feeling lately?" and Person B responds. The server analyzes this data and uploads the diagnosis results to an online platform. Person B can check the results themselves later. If necessary, they will also be referred to a specialist.

[0713] Prompt Sentence Examples

[0714] "Where can I conveniently get a health checkup near me?" (related to mobile health checkup units)

[0715] "I would like to take a health check online. What is the process?" (related to the Virtual Health Check Unit)

[0716] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[0717] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0718] Step 1: Analyze your health checkup needs

[0719] server:

[0720] Input: Past health checkup data and demographic data by region

[0721] How it works: The server uses statistical analysis software (e.g., R, Python) to analyze the health checkup needs of each region. Specifically, it calculates the incidence rates of hypertension and diabetes in specific regions and determines which regions to prioritize for dispatching mobile health checkup units.

[0722] Output: List of priority areas for routing

[0723] Step 2: Setting up a tour route

[0724] server:

[0725] Input: Priority Region List

[0726] Operation: The server calculates the optimal tour route using a routing algorithm (e.g., Dijkstra's Algorithm). The calculation takes into account distance, time, and efficiency. The route information is generated as tour route information.

[0727] Output: Tour route information

[0728] Step 3: Publish your booking system

[0729] server:

[0730] Input: Tour route information

[0731] Operation: The server publishes a reservation system for mobile health checkup units on an online platform. The user interface is implemented using a web front-end (e.g., React, Angular), and the system back-end is implemented using Node.js and Django.

[0732] Output: A booking page accessible to the user

[0733] Step 4: Accept the reservation

[0734] User:

[0735] Input: Booking page of online platform

[0736] How it works: A user visits the online platform, selects the desired date, time, and location, and enters the necessary personal information, such as name, address, and contact details. Once the reservation is complete, a confirmation email is sent to the user.

[0737] Output: Reservation information, confirmation email

[0738] Step 5: Operating a mobile health screening unit

[0739] Terminal (system in mobile health examination unit):

[0740] Input: Tour route information, reservation list

[0741] Operation: The device follows the set route to the destination, locates using a GPS system (e.g., Google Maps API), reads the appointment list and guides users through the health checkup in order, and collects vital signs and test results from each user.

[0742] Output: Collected health data

[0743] Step 6: Send your test results

[0744] Terminal (system in mobile health examination unit):

[0745] Input: Collected health data

[0746] How it works: The terminal inputs the test results as digital data, encrypts them using the HTTPS protocol, and sends them to the server.

[0747] Output: Health data stored on the server

[0748] Step 7: Offer a virtual health check

[0749] server:

[0750] Input: User reservation information

[0751] Operation: The server provides a virtual health checkup on an online platform. It generates and transmits access information so that users can log in at the scheduled time.

[0752] Output: Virtual health check access information

[0753] Step 8: Start the Virtual Health Check

[0754] User:

[0755] Input: Virtual health check access information

[0756] How it works: Users log in to the online platform at a designated time and begin a virtual health screening session. They answer initial questions about their health status through an avatar that uses a generative AI model.

[0757] Output: Information about the user's health status

[0758] Step 9: Gathering health information

[0759] Avatar (generative AI model):

[0760] Input: User's answer

[0761] How it works: Using a generative AI model, the avatar asks appropriate questions to gather information about the user's health, such as "How are you feeling these days?", and stores the information gathered in a database.

[0762] Output: Collected health status data

[0763] Step 10: Data analysis and notification

[0764] server:

[0765] Input: Collected health status data

[0766] How it works: The server analyzes the collected data using machine learning algorithms (e.g., SVM, Random Forest). Based on the analysis results, it generates a health check result and notifies the user through an online platform. If necessary, it will refer the user to a specialist.

[0767] Output: Health checkup results, referral information to specialists

[0768] In this way, the system allows users to easily undergo a health check through a series of steps, improving the accuracy and efficiency of the diagnosis.

[0769] (Application example 1)

[0770] 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."

[0771] Conventional health checkup systems require users to physically visit a hospital or clinic, and for occupations requiring regular health management as employees, time and geographical constraints make it difficult to streamline health management. In particular, for occupations that require frequent travel, such as food delivery, regular health monitoring is often not adequately carried out. This has led to a decline in the utilization rate of health checkups and an increase in employee health risks.

[0772] 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.

[0773] In this invention, the server includes a means for providing real-time health checkup results and notifications to companies that aim to manage the health of their employees, a means for a mobile health checkup unit to travel to specific areas to provide health checkups, and a means for using a generative AI model to provide supplementary information on analysis results and referrals to specialists. This enables even employees who move around a lot to receive regular health checkups, improving the efficiency of health management.

[0774] A "mobile health check unit" is a mobile diagnostic device that travels around the area to provide health checkups to users.

[0775] "Online Platform" means a web-based system that allows Users to access and use the Services.

[0776] "Reservation method" refers to a system that allows users to make reservations for health checkups through an online platform.

[0777] The "Virtual Health Check Unit" is a digital diagnostic system that provides remote health checkups to users.

[0778] An "avatar" is a virtual character that interacts with users online and collects information about their health status.

[0779] A "generative AI model" is a model generated using an artificial intelligence algorithm to analyze health checkup results and provide supplementary information.

[0780] "Analysis means" refers to the process of analyzing collected health information and generating results.

[0781] "Means of providing in real time" refers to a method for providing health examination results and notifications to users immediately.

[0782] "Means for referring to specialists" refers to a system for referring users to specialists as needed based on the results of their health checkups.

[0783] "User" means a person who receives the services of the health examination system.

[0784] "Employee health management" refers to activities undertaken by companies to manage the health status of their employees and provide appropriate care.

[0785] This invention is a system for streamlining employee health management, particularly for occupations that require frequent travel. The system includes a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, and a generative AI model.

[0786] System configuration

[0787] 1. Mobile Health Checkup Unit

[0788] server

[0789] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[0790] The booking system will be made available on an online platform, allowing users to book health checkups.

[0791] User

[0792] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[0793] Terminal (system inside the mobile health checkup unit)

[0794] They will follow a set route to arrive at the designated area, check the reservation list, guide users in order to undergo health checkups, and perform health checkups such as measuring vital signs and blood tests.

[0795] The test results are entered into the terminal and sent to the server as digital data.

[0796] 2. Virtual Health Check Unit

[0797] server

[0798] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for their appointments.

[0799] User

[0800] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[0801] Device (user's PC or smartphone)

[0802] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an on-screen avatar to answer initial questions about their health.

[0803] Avatar

[0804] Uses generative AI models to ask users the right questions and collect answers, leading to a more relaxed dialogue and collecting reliable data.

[0805] server

[0806] The collected data will be analyzed and the results of the health check will be communicated to users via an online platform, with referrals to specialists provided if necessary.

[0807] Hardware and software used

[0808] Hardware: Smartphones, servers, PCs

[0809] Software: Flask (Python web framework), MySQL (database), TensorFlow (generative AI model)

[0810] Data processing and calculation

[0811] server

[0812] Health data collected from users is stored in a database, including vital signs, blood test results, and conversation data.

[0813] Using a generative AI model, the collected data is analyzed in real time to assess the user's health status, and the results are communicated to experts who can provide appropriate advice or refer the user to a specialist if necessary.

[0814] Specific examples

[0815] 1. Health checkup appointment

[0816] Employees log in to the online platform and make a reservation by specifying the desired date, time, and location on the mobile health examination unit's reservation page.

[0817] 2. Virtual Health Checkup

[0818] Employees book a virtual consultation on their smartphone, and the generative AI model asks questions at the specified date and time.

[0819] Example prompts for generative AI models

[0820] "Please answer the following questions regarding your health: Have you been feeling unwell recently?

[0821] "What is the level of stress you experience on a daily basis?"

[0822] "Tell me about your diet and exercise habits."

[0823] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0824] Step 1:

[0825] The server analyzes the health checkup needs of each region and sets the route for the mobile health checkup unit. It uses historical data and demographic data as input, which it retrieves from a database. It uses a data analysis algorithm to calculate the optimal route and outputs the results as the route setting information.

[0826] Step 2:

[0827] The user logs in to the online platform and opens the reservation page for the mobile health examination unit. The user selects the desired date, time, and location, and enters the required personal information. The entered information is sent to the server and saved in the database as reservation information.

[0828] Step 3:

[0829] The server generates a schedule for the mobile health checkup unit based on the set route and reservation information from the user. It uses the travel route setting information and reservation information as input, creates a visit schedule list for each unit based on these, and outputs it as schedule information.

[0830] Step 4:

[0831] The terminal (a system within the mobile health checkup unit) arrives at the designated area and checks the reservation list. It uses the schedule information and reservation list data sent from the server as input. Based on this, the terminal guides users in order of their health checkup, measures their vital signs, and performs blood tests. The health checkup data is acquired and temporarily stored within the terminal.

[0832] Step 5:

[0833] The terminal sends the acquired health checkup data to the server. The measured health checkup data is used as input, converted into digital data, and uploaded to the server. The server receives this data and stores it in a database.

[0834] Step 6:

[0835] Users log in to the online platform and open the virtual health checkup reservation page. They select the desired date and time and enter the necessary information to complete the reservation. The entered reservation information is sent to the server and saved in the database.

[0836] Step 7:

[0837] The user re-logins into the online platform at the scheduled time and starts the virtual health check session. They interact with an avatar displayed on the screen and answer initial questions about their health status. The user's response data is collected as input and sent to the server.

[0838] Step 8:

[0839] The avatar analyzes the user's responses using a generative AI model. Using the collected data as input, it performs a health assessment through the analytical model. The analysis results are sent to a server and stored in a database.

[0840] Step 9:

[0841] The server generates health checkup results based on the analysis results and notifies the user via the online platform, including referral information to a specialist if necessary. It uses the analysis result data as input and generates a notification message that is output to the user.

[0842] Step 10:

[0843] If a user wishes to consult with a specialist, they can use the online platform to make an appointment with the specialist. The health checkup results and specialist referral information are used as input, and appointment information is generated based on this and sent to the server. The server then stores the appointment information in a database and notifies the specialist.

[0844] The above are the specific processing steps of the system program for carrying out the invention.

[0845] 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.

[0846] This invention relates to a system that combines a mobile health checkup unit with a virtual health checkup unit and is equipped with an emotion engine. This system provides an environment where users can easily undergo health checkups, and furthermore, recognizes the user's emotional state to improve diagnostic accuracy and user experience.

[0847] System configuration

[0848] The system includes the following major components:

[0849] 1. Mobile Health Checkup Unit

[0850] 2. Online Platforms

[0851] 3. Virtual Health Check Unit

[0852] 4. Avatar

[0853] 5. Generative AI Models

[0854] 6. Emotion Engine

[0855] Program processing

[0856] 1. Mobile Health Checkup Unit

[0857] server:

[0858] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[0859] The booking system will be published on an online platform, allowing users to book health checkups.

[0860] User:

[0861] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[0862] Terminal (system in mobile health examination unit):

[0863] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[0864] The test results are entered into the terminal and sent to the server as digital data.

[0865] 2. Virtual Health Check Unit

[0866] server:

[0867] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[0868] User:

[0869] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[0870] Device (user's PC or smartphone):

[0871] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[0872] Avatar:

[0873] It uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0874] The content of the dialogue is adjusted based on the user's emotional data to help the user relax. For example, if the user is nervous, the dialogue will be designed to relax the user.

[0875] server:

[0876] Analyze data from the emotion engine and adjust the difficulty and content of the initial questions.

[0877] The results of the health check will be communicated to users via an online platform, and if necessary, a referral to a specialist will be made.

[0878] Specific examples

[0879] 1. Example of use of the mobile health checkup unit

[0880] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[0881] 2. Example of use of the virtual health checkup unit

[0882] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the obtained information, and sends it to the server. The emotion engine analyzes B's facial expressions and tone of voice and engages in dialogue to help him relax. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[0883] In this way, this system allows users to easily undergo health checkups at home or nearby locations. By using the emotion engine, it is possible to improve the accuracy of the diagnosis while ensuring user comfort, thereby realizing accessibility of the diagnosis and improving the user experience.

[0884] The processing flow will be explained below.

[0885] Mobile health examination unit processing steps

[0886] Step 1:

[0887] The server identifies areas with high demand based on past health checkup data for each region.

[0888] Step 2:

[0889] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[0890] Step 3:

[0891] The server displays the configured route on an online platform for residents to make reservations.

[0892] Step 4:

[0893] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[0894] Step 5:

[0895] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[0896] Step 6:

[0897] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[0898] Step 7:

[0899] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[0900] Step 8:

[0901] The terminal (a system within the mobile health examination unit) checks the reservation list.

[0902] Step 9:

[0903] The terminal (a system within the mobile health checkup unit) guides users through the health checkup in order and performs the health checkup (e.g., measuring vital signs and blood tests).

[0904] Step 10:

[0905] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[0906] Step 11:

[0907] The server analyzes the collected health check results and generates a result report.

[0908] Step 12:

[0909] The server links the results report to the user's account and sends a result notification email.

[0910] Step 13:

[0911] The user logs in to the online platform and views the medical examination result report.

[0912] Virtual Health Check Unit Processing Steps

[0913] Step 1:

[0914] The server provides a virtual health checkup reservation system on an online platform.

[0915] Step 2:

[0916] The server displays the available dates and times for users to make reservations and updates the available slots.

[0917] Step 3:

[0918] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[0919] Step 4:

[0920] The user selects the desired date and time and makes a reservation.

[0921] Step 5:

[0922] The user enters the required information and completes the reservation.

[0923] Step 6:

[0924] The server saves the reservation information in a database and sends a confirmation email to the user.

[0925] Step 7:

[0926] The user logs into the online platform at the time of the reservation.

[0927] Step 8:

[0928] The device (user's PC or smartphone) starts the virtual health check session.

[0929] Step 9:

[0930] The avatar uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0931] Step 10:

[0932] The user interacts with the avatar to answer initial questions about their health.

[0933] Step 11:

[0934] The avatar adjusts the dialogue based on the user's emotional data to help the user relax. For example, if the user is nervous, the avatar will engage in dialogue to relax the user.

[0935] Step 12:

[0936] The server analyzes the response data to the initial questions in real time.

[0937] Step 13:

[0938] The server generates additional detailed questions as needed.

[0939] Step 14:

[0940] The server analyzes the collected information, compiles the results and links them to the user's account.

[0941] Step 15:

[0942] The server notifies the user of the health check result report through the online platform.

[0943] Step 16:

[0944] The user views the medical examination result report.

[0945] Step 17:

[0946] The server will provide referrals to specialists as needed.

[0947] Example 2

[0948] 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."

[0949] Conventional health checkup systems face problems such as insufficient access for users to undergo regular checkups and inaccurate diagnostic results. Furthermore, there are insufficient means to alleviate the tension and anxiety users feel during the diagnostic process. This makes it difficult to obtain accurate health checkup results and does not improve the user experience. Furthermore, it is difficult to provide diagnoses to users in remote locations.

[0950] 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.

[0951] In this invention, the server includes: means for analyzing regional health checkup needs and setting a mobile health checkup unit's route; means for a user to make a reservation for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to arrive at the designated area, conduct the health checkup, and transmit the results to the server; means for the virtual health checkup unit to provide a remote health checkup to the user; means for collecting and analyzing information about the user's health status through dialogue with an avatar; means for analyzing the user's emotional state using an emotion engine and adjusting the dialogue content based on the analysis results; means for notifying the user of the analysis results via the online platform; and means for referring the user to a doctor if necessary. This allows users to easily receive health checkups, and the emotion engine reduces tension and anxiety during the checkup process, providing accurate health checkup results and a high-quality user experience. Health checkups can also be provided to users in remote locations.

[0952] A "mobile health examination unit" is a unit equipped with vehicles and equipment for traveling to a specific area to provide health examinations.

[0953] "Medical checkup needs" refers to the demand for medical checkups in a particular area, analyzed based on demographics and past data.

[0954] A "patrol route" is a route set up for a mobile health examination unit to travel through a particular area.

[0955] "Online platform" means a website or application that users can access via the internet to book health checkups and check their results.

[0956] A "Virtual Health Check Unit" is a system for providing health checks to users remotely, accessible through an online platform.

[0957] An "avatar" is a virtual person or character that interacts with the user within the virtual health checkup unit.

[0958] An "emotion engine" is software that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0959] A "generative AI model" is a model that uses artificial intelligence technology to generate appropriate questions to engage in dialogue with users.

[0960] "Physical examination results" refers to the examination results of a medical examination that the user has undergone, and includes blood test results and vital sign measurement results.

[0961] "Referral to a doctor" refers to the procedure of referring the user to a specialist based on the results of the health check.

[0962] This invention is a system that integrates a mobile health checkup unit and a virtual health checkup unit, allowing users to easily undergo health checkups. It also aims to improve the accuracy of diagnosis and the user experience by using an emotion engine to recognize the user's emotional state in real time.

[0963] System Components

[0964] The system includes the following major components:

[0965] 1. Mobile Health Checkup Unit

[0966] 2. Online Platforms

[0967] 3. Virtual Health Check Unit

[0968] 4. Avatar

[0969] 5. Generative AI Models

[0970] 6. Emotion Engine

[0971] Mobile Health Checkup Unit

[0972] The server analyzes the health checkup needs of each area and plans the routes for the mobile health checkup units. To do this, it uses Python to extract data from a demographic database and compiles statistics such as age group, gender, and medical history to identify areas with high demand. It then uses AWS Lambda to run the routing algorithm and generate the optimal route.

[0973] The server publishes route information and the reservation system to an online platform. The reservation page is created using JavaScript and React, and the backend is built with Node.js. Users log in to the online platform, select the desired date, time, and location, and make a reservation.

[0974] The terminal (a system inside the mobile health checkup unit) arrives at the designated area according to a set route, and the system checks the reservation list and guides the user in order. Medical staff measure the user's vital signs and perform blood tests, and send the results to the server in real time.

[0975] Virtual Health Check Unit

[0976] The server implements a booking function using the Django framework to publish a virtual health checkup booking system on an online platform, providing users with selectable dates and times.

[0977] Users access the virtual health checkup reservation page, select the desired date and time, and make a reservation. At the scheduled time, they log in to the online platform from their home PC or smartphone to start the virtual health checkup session.

[0978] The avatar uses a generative AI model to ask initial questions about the user's health status. The model uses Python and natural language processing (NLP) techniques to generate appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize the user's emotional state in real time.

[0979] The server analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the obtained data, it generates the next dialogue content, providing a comfortable dialogue environment for the user.

[0980] Specific examples

[0981] For example, when using a mobile health checkup unit, User A checks the date and time that the mobile health checkup unit will arrive at a nearby park on the online platform, selects the desired date and time, and the park, and makes a reservation. The unit arrives on the reserved date and time, and User A undergoes the health checkup. Medical staff measure User A's blood pressure and heart rate and send the data to a server in real time. User A can check the diagnosis results later on the online platform.

[0982] When using the virtual health check unit, User B books a virtual health check on the online platform. User B selects the desired date and time and confirms the reservation. At the scheduled date and time, User B logs in from their home PC and begins a conversation with the avatar. The avatar asks, "How are you feeling lately?" and User B responds. The emotion engine analyzes User B's facial expressions and tone of voice and engages in a conversation designed to relax them. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[0983] Example prompts for generative AI models

[0984] "Use a virtual health check unit to generate initial questions to check the user's health. Take into account the user's emotional state and adjust the dialogue as needed."

[0985] In this way, the system allows users to easily undergo health checkups at home or nearby locations, and by using an emotion engine, improves the accuracy of the diagnosis while ensuring user comfort.

[0986] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0987] Step 1:

[0988] Server: Analyzes regional health checkup needs. Extracts data from a demographic database and uses Python to compile statistics such as age group, gender, and medical history to identify areas with high demand.

[0989] Input: Demographic data (age range, gender, medical history, etc.)

[0990] Output: List of areas with high demand for health checkups

[0991] What it does: The server accesses a demographic database to gather the necessary data, then analyzes the data using Python data analysis libraries (e.g., Pandas, NumPy) to identify areas with high demand.

[0992] Step 2:

[0993] Server: Plans the mobile health check unit's route based on the analysis results. AWS Lambda is used to run the route planning algorithm and generate the optimal route.

[0994] Input: List of areas with high demand for health checkups

[0995] Output: Optimal tour route

[0996] What happens: The server triggers AWS Lambda to run a pre-configured routing algorithm, which calculates the optimal route based on the list of areas and saves the results.

[0997] Step 3:

[0998] Server: Publish the reservation system on an online platform based on the set route. Create the reservation page using JavaScript and React, and build the backend using Node.js.

[0999] Input: Optimal tour route

[1000] Output: Online platform with published reservation system

[1001] What it does: The server retrieves the route information, builds the user interface using JavaScript and React, sets up a backend system using Node.js to store reservation information, and publishes it to an online platform.

[1002] Step 4:

[1003] User: Logs into the online platform, selects the desired date, time and location and makes a reservation.

[1004] Input: User login information, desired date and time, and location selection

[1005] Output: User's reservation information is saved in the database

[1006] Specific operation: A user logs in to the online platform, selects the desired date, time and location on the interface, enters the required information in the reservation form and submits it. The submitted reservation information is then stored in a database by the server.

[1007] Step 5:

[1008] Terminal (system inside the mobile health checkup unit): Arrives at the designated area according to the set route and checks the appointment list. Medical staff guides the user, measures vital signs and performs blood tests, and enters the results into the terminal.

[1009] Input: Reservation list, health check results

[1010] Output: The entered health check results are sent to the server.

[1011] Specific operation: The terminal inside the mobile unit checks the reservation list and guides each user in order. Medical staff take the user's vital signs and perform blood tests, and enter the results into the terminal. The entered data is sent to the server in real time.

[1012] Step 6:

[1013] Server: Provides a virtual health checkup booking system on an online platform. Implements the booking function using the Django framework and provides users with selectable dates and times.

[1014] Input: Virtual health check appointment information

[1015] Output: Online platform with published reservation system

[1016] What it does: The server implements the reservation function using the Django framework, provides date and time information that users can select, and publishes the reservation system on an online platform.

[1017] Step 7:

[1018] User: Visits the virtual health checkup booking page, selects the desired date and time, and makes a booking.

[1019] Input: User login information, desired date and time

[1020] Output: User's reservation information is saved in the database

[1021] Specific operation: A user logs in to the online platform, enters the desired date and time, and confirms the reservation. The entered reservation information is sent to the server and recorded in the database.

[1022] Step 8:

[1023] User: Logs into the online platform at the scheduled time and date to begin the virtual health assessment session.

[1024] Input: User login information, reservation information

[1025] Output: An interactive session with the avatar is started.

[1026] Specific operation: The user logs in at the scheduled date and time and starts the virtual health check session. Once the session starts, the user conducts the health check through interaction with the avatar.

[1027] Step 9:

[1028] Avatar: Uses generative AI models to ask the user appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1029] Input: Generative AI model, emotion engine

[1030] Output: User health information, sentiment analysis data

[1031] How it works: The avatar uses generative AI models to generate appropriate questions, and the emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize their emotional state in real time.

[1032] Step 10:

[1033] Server: Analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the information obtained, the next dialogue content is generated.

[1034] Input: Sentiment analysis data, user responses

[1035] Output: Tailored questions and dialogue

[1036] How it works: The server analyzes the data sent from the emotion engine, adjusts the difficulty and content of the initial questions, and then uses NLP models to generate the next questions and dialogue.

[1037] Step 11:

[1038] Server: Analyzes the results of the virtual health check and notifies the user via the online platform, and if necessary, provides a referral to a specialist.

[1039] Input: Virtual health check results

[1040] Output: Notification of results, referral to specialist

[1041] What it does: The server analyzes the health check results and displays them on the user's personal dashboard. If necessary, it also arranges for the user to be referred to a specialist.

[1042] (Application example 2)

[1043] 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."

[1044] There is a need to improve the efficiency and accuracy of health checkups and mental healthcare for factory workers. Conventional health checkup systems have difficulty analyzing not only the physical health status of employees but also their emotional state and providing follow-up as needed. In addition, automation of emotion analysis and data management is insufficient, making it difficult to improve the quality and efficiency of healthcare.

[1045] 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.

[1046] In this invention, the server includes a means including a factory patrol healthcare robot that performs health checks and analyzes the emotional state of employees working in a factory environment, a means for performing emotion analysis using a generative AI model and storing the results in a database, and a means for collecting and analyzing information about the health state through dialogue with an avatar. This makes it possible to analyze not only the physical health state of employees but also their emotional state in real time and provide appropriate follow-ups automatically.

[1047] A "mobile health checkup unit" is a device that travels around a specific area and provides health checkups to users.

[1048] "User" means an individual who books a medical examination or takes a virtual medical examination via the online platform.

[1049] "Online platform" refers to the online system that users use to make appointments with health examination units and check examination results.

[1050] A "virtual health examination unit" is a virtual diagnostic device for providing a remote health examination to a user.

[1051] An "avatar" is a virtual character that interacts with users on an online platform and collects information about their health status.

[1052] A "generative AI model" is an artificial intelligence algorithm used to interact with users and conduct sentiment analysis.

[1053] An "emotion engine" is software that recognizes and analyzes a user's emotional state in real time.

[1054] "Factory environment" refers to the entire working environment in which members working within a factory are active.

[1055] The "factory patrol healthcare robot" is a robot that patrols the factory, conducting health checks and analyzing emotional states.

[1056] A "health checkup" is a series of tests and evaluations to assess a user's health status.

[1057] "Emotional state" refers to the user's mental and psychological state, as analyzed by the emotion engine.

[1058] A "database" is a digital information storage system for storing the results of health checks and emotion analysis.

[1059] The system for implementing this invention consists of a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, a generative AI model, a supply device, and an emotion engine. In a factory environment, it also includes a roving healthcare robot. The specific configuration and operation method of the system are described below.

[1060] System configuration

[1061] Mobile health check unit: A device that travels around a specific area and provides health checks to users.

[1062] Online platform: An internet system where users can book health checkups and check results.

[1063] Virtual Health Check Unit: A virtual diagnostic device that provides remote health checks to users.

[1064] Avatar: A virtual character that interacts with the user and collects information about their health.

[1065] Generative AI model: An artificial intelligence algorithm that interacts with users and analyzes their emotions.

[1066] Emotion Engine: Software that recognizes and analyzes the user's emotional state in real time.

[1067] Factory-specific healthcare robot: A robot that patrols the factory, conducting health checks and analyzing emotional states.

[1068] How the program works

[1069] 1. Mobile Health Checkup Unit

[1070] Server: Analyzes health checkup needs based on historical data and demographics, and sets up round routes. Publishes the reservation system on an online platform, allowing users to select their preferred date, time, and location.

[1071] User: Logs in to the online platform and makes an appointment for a health check. The mobile health check unit will provide the health check at the designated date, time and location.

[1072] Terminal: Collects health checkup results and sends them to the server as digital data.

[1073] 2. Virtual Health Check Unit

[1074] Server: Accepts reservations for virtual health checkups through an online platform.

[1075] User: Logs in to the online platform at the scheduled time and undergoes a health check. Through dialogue with an avatar, the user answers initial questions about their health condition.

[1076] Avatar: Uses a generative AI model to ask appropriate questions, and an emotion engine to analyze the user's facial expressions and tone of voice, providing a relaxing dialogue. The analysis results are sent to a server.

[1077] 3. Factory Patrol Healthcare Robot

[1078] Server: Manages data for analyzing the health and emotional state of members working in the factory environment.

[1079] Factory-specific healthcare robot: This robot patrols the factory, conducting health checks and emotional analysis of employees. It sends the results to a server and provides follow-up as needed.

[1080] Emotion engine: Provides the results of health checkups and emotion analysis as relaxing dialogues and health advice.

[1081] Specific examples

[1082] 1. Example of use of the mobile health checkup unit

[1083] Users make a reservation through the online platform, and a mobile health screening unit arrives at the designated park to conduct the health screening. The results can be viewed later on the online platform.

[1084] 2. Example of use of the virtual health checkup unit

[1085] Users log in to the virtual health checkup from their home PC and interact with an avatar to check their health status. A generative AI model asks initial health-related questions, and an emotion engine analyzes the user's emotional state and provides relaxing dialogue.

[1086] 3. Example of use of a patrol healthcare robot in a factory

[1087] The robot patrols the factory, checking the health of employees and analyzing their stress levels using an emotion engine. The generative AI model automatically suggests appropriate follow-up measures. If an employee shows high levels of stress, it offers a dialogue to promote relaxation and health advice.

[1088] Prompt Sentence Examples

[1089] "Staff member A may be experiencing high stress due to a recent project. Please suggest some conversations to help him relax."

[1090] "Staff member B's vital signs are outside of normal range. Please suggest additional medical examinations and provide any necessary follow-up."

[1091] The above system configuration and operation method make it possible to carry out the invention.

[1092] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1093] Step 1:

[1094] The server analyzes past data and demographic data to predict health checkup needs. Using past health checkup data and demographic data as input, the server uses an analytical algorithm to determine the health checkup demand in each region and set up a tour route. The output is the set tour route.

[1095] Step 2:

[1096] A user logs in to the online platform and makes an appointment for a health checkup. The user provides the platform with their login information, desired date, time, and location as input, and submits an appointment request. The user is provided with an appointment confirmation as output.

[1097] Step 3:

[1098] The mobile health checkup unit's terminal moves to the designated area according to the set route and checks the reservation list. Using the route information and reservation list sent from the server as input, the unit carries out the health checkup corresponding to each reservation. The health checkup results are recorded on the terminal as output.

[1099] Step 4:

[1100] The terminal sends the results of the health checkup to the server. The health checkup results recorded on the terminal as input are formatted in a database format and sent to the server. The health checkup data stored on the server is obtained as output.

[1101] Step 5:

[1102] The server provides a virtual health checkup reservation system on an online platform. It receives the user's reservation information and desired date and time as input, manages the virtual health checkup schedule, and provides the user's reservation confirmation information as output.

[1103] Step 6:

[1104] Users log in to the online platform at the scheduled time and date to undergo a virtual health check. They provide their login and reservation information to the platform as input to begin the diagnostic process. The output is an interactive screen with an avatar that is displayed in real time.

[1105] Step 7:

[1106] The avatar uses a generative AI model to ask questions about the user's health status and analyzes their responses. It uses the user's response data and the emotion engine's analysis results as inputs to provide appropriate feedback. The output is the user's response data and the corresponding emotion analysis results.

[1107] Step 8:

[1108] The server notifies the user of the health checkup results and emotion analysis results through the online platform. The server uses the analyzed health checkup data and emotion data as input to generate an appropriate notification message. The notification message is then displayed on the user's platform screen as output.

[1109] Step 9:

[1110] The in-factory patrol healthcare robot patrols the factory, conducting health checks and emotional analysis of employees. It uses the employees' health and emotional data collected on-site as input and analyzes it in real time. The analysis results are sent to the robot terminal and server as output.

[1111] Step 10:

[1112] The emotion engine analyzes the acquired emotion data and evaluates the mental health state of the member. Data acquired from the emotion sensor is input to the emotion engine, and mental health is evaluated using an analysis algorithm. The evaluation result is obtained as output.

[1113] Step 11:

[1114] The server proposes necessary follow-up measures based on the evaluation results. Using the emotion engine's evaluation results and health checkup data as input, it generates an appropriate follow-up plan using a generative AI model. The follow-up plan is then notified to the user as output.

[1115] In this way, the entire system operates in cooperation, enabling efficient health checkups and mental health care for users.

[1116] 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.

[1117] 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.

[1118] 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.

[1119] [Third embodiment]

[1120] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1121] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1122] 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).

[1123] 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.

[1124] 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.

[1125] 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).

[1126] 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.

[1127] 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.

[1128] 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.

[1129] 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.

[1130] 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.

[1131] 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."

[1132] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. This system provides an environment where users can easily undergo health checkups without having to go to a hospital or clinic.

[1133] System configuration

[1134] The system includes the following major components:

[1135] 1. Mobile Health Checkup Unit

[1136] 2. Online Platforms

[1137] 3. Virtual Health Check Unit

[1138] 4. Avatar

[1139] 5. Generative AI Models

[1140] Program processing

[1141] 1. Mobile Health Checkup Unit

[1142] server:

[1143] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[1144] The booking system will be published on an online platform, allowing users to book health checkups.

[1145] User:

[1146] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[1147] Terminal (system in mobile health examination unit):

[1148] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[1149] The test results are entered into the terminal and sent to the server as digital data.

[1150] 2. Virtual Health Check Unit

[1151] server:

[1152] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[1153] User:

[1154] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[1155] Device (user's PC or smartphone):

[1156] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[1157] Avatar:

[1158] Use generative AI models to ask users the right questions and collect answers, engage users in relaxed conversations, and collect reliable data.

[1159] server:

[1160] The collected data is analyzed and the results of the health check are communicated to the user via an online platform, with a referral to a specialist provided if necessary.

[1161] Specific examples

[1162] 1. Examples of mobile health checkups

[1163] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[1164] 2. Use cases for virtual health checkups

[1165] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the information obtained, and sends it to the server. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[1166] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[1167] The processing flow will be explained below.

[1168] Mobile health examination unit processing steps

[1169] Step 1:

[1170] The server identifies areas with high demand based on past health checkup data for each region.

[1171] Step 2:

[1172] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[1173] Step 3:

[1174] The server displays the configured route on an online platform for residents to make reservations.

[1175] Step 4:

[1176] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[1177] Step 5:

[1178] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[1179] Step 6:

[1180] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[1181] Step 7:

[1182] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[1183] Step 8:

[1184] The terminal (a system within the mobile health examination unit) checks the reservation list.

[1185] Step 9:

[1186] The profile guides the user through the health checkup and performs the health checkup (e.g., measuring vital signs and blood tests).

[1187] Step 10:

[1188] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[1189] Step 11:

[1190] The server analyzes the collected health check results and generates a result report.

[1191] Step 12:

[1192] The server links the results report to the user's account and sends a result notification email.

[1193] Step 13:

[1194] The user logs in to the online platform and views the medical examination result report.

[1195] Virtual Health Check Unit Processing Steps

[1196] Step 1:

[1197] The server provides a virtual health checkup reservation system on an online platform.

[1198] Step 2:

[1199] The server displays the available dates and times for users to make reservations and updates the available slots.

[1200] Step 3:

[1201] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[1202] Step 4:

[1203] The user selects the desired date and time and makes a reservation.

[1204] Step 5:

[1205] The user enters the required information and completes the reservation.

[1206] Step 6:

[1207] The server saves the reservation information in a database and sends a confirmation email to the user.

[1208] Step 7:

[1209] The user logs into the online platform at the time of the reservation.

[1210] Step 8:

[1211] The device (user's PC or smartphone) starts the virtual health check session.

[1212] Step 9:

[1213] The avatar uses a generative AI model to ask the user appropriate questions.

[1214] Step 10:

[1215] The user interacts with the avatar to answer initial questions about their health.

[1216] Step 11:

[1217] The server analyzes the response data to the initial questions in real time.

[1218] Step 12:

[1219] The server generates additional detailed questions as needed.

[1220] Step 13:

[1221] The server analyzes the collected information, compiles the results and links them to the user's account.

[1222] Step 14:

[1223] The server notifies the user of the health check result report through the online platform.

[1224] Step 15:

[1225] The user views the medical examination result report.

[1226] Step 16:

[1227] The server will provide referrals to specialists as needed.

[1228] These steps ensure that the entire system operates smoothly, providing an environment in which users can easily undergo health checkups.

[1229] Example 1

[1230] 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."

[1231] Conventional health checkup systems require users to physically visit a medical facility, which can be a burden, especially for elderly people and those without cars. Furthermore, users living in remote areas have limited opportunities for health checkups, making early detection of illness difficult. Furthermore, there was a lack of efficient and accurate methods for collecting and analyzing initial questions and health checkup results and linking them to appropriate medical treatment.

[1232] 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.

[1233] In this invention, the server includes: means for analyzing regional health checkup needs and setting a route for the mobile health checkup unit; means for users to make reservations for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to check the reservation list, guide users in order to receive the health checkup, and conduct the health checkup; means for transmitting test results to the server as digital data; means for the virtual health checkup unit to remotely provide health checkups to users; means for an avatar to ask appropriate questions of the user using a generative AI model and collect and analyze information on the user's health status; means for notifying the user of the analysis results via the online platform; and means for, if necessary, referring the user to a specialist based on the health checkup results. This allows users to easily receive health checkups at home or in their neighborhood, improving accessibility to diagnosis and enabling early detection of diseases and appropriate medical treatment.

[1234] "Analyzing health checkup needs by region" means conducting statistical analysis of the health status and demand for health checkups of residents in a specific region based on past data, demographics, etc.

[1235] "Setting a patrol route" means planning the optimal route for the health examination unit to efficiently patrol a specific area.

[1236] An "online platform" is a general term for a system that users can access via the Internet and use various services such as making reservations, checking diagnostic results, and interacting with others.

[1237] A "mobile medical examination unit" is a device or vehicle equipped with the facilities to travel to various locations using the vehicle or device and provide medical examinations.

[1238] "Reservation List" means a list for recording and managing reservations made by a User through the Online Platform.

[1239] The "Virtual Health Check Unit" is a system that provides a mechanism for conducting health checkups remotely via the Internet.

[1240] A "generative AI model" is a program that uses artificial intelligence technology to interact with users and incorporates algorithms for asking questions and conducting analysis.

[1241] An "avatar" is a virtual entity that interacts with users and collects information about their health status using a generative AI model in a virtual health checkup unit.

[1242] "Digital data" refers to data used to store, analyze, and transmit health examination results in electronic form.

[1243] "Analysis results" are the results of statistical analysis or algorithmic analysis based on collected health status data.

[1244] "Referral" refers to transferring a user to an appropriate medical professional when necessary based on collected and analyzed medical examination data.

[1245] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. The purpose of this system is to provide an environment in which users can conveniently receive health checkups without having to go to a hospital or clinic. The following describes how this system is implemented.

[1246] Hardware and Software

[1247] The system includes several hardware and software components. The major hardware components include:

[1248] Mobile health checkup unit: A vehicle such as a bus or van that has been modified to accommodate medical equipment such as blood pressure monitors, thermometers, and blood testing machines.

[1249] Server: Located on a cloud platform (e.g., Amazon Web Services (AWS), Microsoft Azure) to store and process data.

[1250] User terminal: A device such as a PC or smartphone.

[1251] The main software components include:

[1252] Online platform: A web application that provides the reservation system, user interface, and results display functions. It uses React and Angular for the front end and Node.js and Django for the back end.

[1253] Generative AI model: An algorithm for conducting user interactions and collecting health-related information. Created using a machine learning framework (e.g., TensorFlow, PyTorch).

[1254] Data analysis tools: Statistical analysis software (e.g., R, Python) to analyze the collected data.

[1255] Example of a user scenario

[1256] 1. Example of use of the mobile health checkup unit

[1257] User A checks the date and time that the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation.

[1258] The mobile health checkup unit arrives at the park at the scheduled time and Mr. A undergoes a health checkup. When measuring his blood pressure, the device records the data and immediately sends it to the server. The results can then be viewed on an online platform.

[1259] 2. Use cases for virtual health checkups

[1260] User B books a virtual health checkup on an online platform.

[1261] At the scheduled time, the person logs in from their home PC and checks their health condition through dialogue with an avatar. The generative AI model asks, "How are you feeling lately?" and Person B responds. The server analyzes this data and uploads the diagnosis results to an online platform. Person B can check the results themselves later. If necessary, they will also be referred to a specialist.

[1262] Prompt Sentence Examples

[1263] "Where can I conveniently get a health checkup near me?" (related to mobile health checkup units)

[1264] "I would like to take a health check online. What is the process?" (related to the Virtual Health Check Unit)

[1265] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[1266] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1267] Step 1: Analyze your health checkup needs

[1268] server:

[1269] Input: Past health checkup data and demographic data by region

[1270] How it works: The server uses statistical analysis software (e.g., R, Python) to analyze the health checkup needs of each region. Specifically, it calculates the incidence rates of hypertension and diabetes in specific regions and determines which regions to prioritize for dispatching mobile health checkup units.

[1271] Output: List of priority areas for routing

[1272] Step 2: Setting up a tour route

[1273] server:

[1274] Input: Priority Region List

[1275] Operation: The server calculates the optimal tour route using a routing algorithm (e.g., Dijkstra's Algorithm). The calculation takes into account distance, time, and efficiency. The route information is generated as tour route information.

[1276] Output: Tour route information

[1277] Step 3: Publish your booking system

[1278] server:

[1279] Input: Tour route information

[1280] Operation: The server publishes a reservation system for mobile health checkup units on an online platform. The user interface is implemented using a web front-end (e.g., React, Angular), and the system back-end is implemented using Node.js and Django.

[1281] Output: A booking page accessible to the user

[1282] Step 4: Accept the reservation

[1283] User:

[1284] Input: Booking page of online platform

[1285] How it works: A user visits the online platform, selects the desired date, time, and location, and enters the necessary personal information, such as name, address, and contact details. Once the reservation is complete, a confirmation email is sent to the user.

[1286] Output: Reservation information, confirmation email

[1287] Step 5: Operating a mobile health screening unit

[1288] Terminal (system in mobile health examination unit):

[1289] Input: Tour route information, reservation list

[1290] Operation: The device follows the set route to the destination, locates using a GPS system (e.g., Google Maps API), reads the appointment list and guides users through the health checkup in order, and collects vital signs and test results from each user.

[1291] Output: Collected health data

[1292] Step 6: Send your test results

[1293] Terminal (system in mobile health examination unit):

[1294] Input: Collected health data

[1295] How it works: The terminal inputs the test results as digital data, encrypts them using the HTTPS protocol, and sends them to the server.

[1296] Output: Health data stored on the server

[1297] Step 7: Offer a virtual health check

[1298] server:

[1299] Input: User reservation information

[1300] Operation: The server provides a virtual health checkup on an online platform. It generates and transmits access information so that users can log in at the scheduled time.

[1301] Output: Virtual health check access information

[1302] Step 8: Start the Virtual Health Check

[1303] User:

[1304] Input: Virtual health check access information

[1305] How it works: Users log in to the online platform at a designated time and begin a virtual health screening session. They answer initial questions about their health status through an avatar that uses a generative AI model.

[1306] Output: Information about the user's health status

[1307] Step 9: Gathering health information

[1308] Avatar (generative AI model):

[1309] Input: User's answer

[1310] How it works: Using a generative AI model, the avatar asks appropriate questions to gather information about the user's health, such as "How are you feeling these days?", and stores the information gathered in a database.

[1311] Output: Collected health status data

[1312] Step 10: Data analysis and notification

[1313] server:

[1314] Input: Collected health status data

[1315] How it works: The server analyzes the collected data using machine learning algorithms (e.g., SVM, Random Forest). Based on the analysis results, it generates a health check result and notifies the user through an online platform. If necessary, it will refer the user to a specialist.

[1316] Output: Health checkup results, referral information to specialists

[1317] In this way, the system allows users to easily undergo a health check through a series of steps, improving the accuracy and efficiency of the diagnosis.

[1318] (Application example 1)

[1319] 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."

[1320] Conventional health checkup systems require users to physically visit a hospital or clinic, and for occupations requiring regular health management as employees, time and geographical constraints make it difficult to streamline health management. In particular, for occupations that require frequent travel, such as food delivery, regular health monitoring is often not adequately carried out. This has led to a decline in the utilization rate of health checkups and an increase in employee health risks.

[1321] 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.

[1322] In this invention, the server includes a means for providing real-time health checkup results and notifications to companies that aim to manage the health of their employees, a means for a mobile health checkup unit to travel to specific areas to provide health checkups, and a means for using a generative AI model to provide supplementary information on analysis results and referrals to specialists. This enables even employees who move around a lot to receive regular health checkups, improving the efficiency of health management.

[1323] A "mobile health check unit" is a mobile diagnostic device that travels around the area to provide health checkups to users.

[1324] "Online Platform" means a web-based system that allows Users to access and use the Services.

[1325] "Reservation method" refers to a system that allows users to make reservations for health checkups through an online platform.

[1326] The "Virtual Health Check Unit" is a digital diagnostic system that provides remote health checkups to users.

[1327] An "avatar" is a virtual character that interacts with users online and collects information about their health status.

[1328] A "generative AI model" is a model generated using an artificial intelligence algorithm to analyze health checkup results and provide supplementary information.

[1329] "Analysis means" refers to the process of analyzing collected health information and generating results.

[1330] "Means of providing in real time" refers to a method for providing health examination results and notifications to users immediately.

[1331] "Means for referring to specialists" refers to a system for referring users to specialists as needed based on the results of their health checkups.

[1332] "User" means a person who receives the services of the health examination system.

[1333] "Employee health management" refers to activities undertaken by companies to manage the health status of their employees and provide appropriate care.

[1334] This invention is a system for streamlining employee health management, particularly for occupations that require frequent travel. The system includes a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, and a generative AI model.

[1335] System configuration

[1336] 1. Mobile Health Checkup Unit

[1337] server

[1338] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[1339] The booking system will be made available on an online platform, allowing users to book health checkups.

[1340] User

[1341] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[1342] Terminal (system inside the mobile health checkup unit)

[1343] They will follow a set route to arrive at the designated area, check the reservation list, guide users in order to undergo health checkups, and perform health checkups such as measuring vital signs and blood tests.

[1344] The test results are entered into the terminal and sent to the server as digital data.

[1345] 2. Virtual Health Check Unit

[1346] server

[1347] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for their appointments.

[1348] User

[1349] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[1350] Device (user's PC or smartphone)

[1351] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an on-screen avatar to answer initial questions about their health.

[1352] Avatar

[1353] Uses generative AI models to ask users the right questions and collect answers, leading to a more relaxed dialogue and collecting reliable data.

[1354] server

[1355] The collected data will be analyzed and the results of the health check will be communicated to users via an online platform, with referrals to specialists provided if necessary.

[1356] Hardware and software used

[1357] Hardware: Smartphones, servers, PCs

[1358] Software: Flask (Python web framework), MySQL (database), TensorFlow (generative AI model)

[1359] Data processing and calculation

[1360] server

[1361] Health data collected from users is stored in a database, including vital signs, blood test results, and conversation data.

[1362] Using a generative AI model, the collected data is analyzed in real time to assess the user's health status, and the results are communicated to experts who can provide appropriate advice or refer the user to a specialist if necessary.

[1363] Specific examples

[1364] 1. Health checkup appointment

[1365] Employees log in to the online platform and make a reservation by specifying the desired date, time, and location on the mobile health examination unit's reservation page.

[1366] 2. Virtual Health Checkup

[1367] Employees book a virtual consultation on their smartphone, and the generative AI model asks questions at the specified date and time.

[1368] Example prompts for generative AI models

[1369] "Please answer the following questions regarding your health: Have you been feeling unwell recently?

[1370] "What is the level of stress you experience on a daily basis?"

[1371] "Tell me about your diet and exercise habits."

[1372] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1373] Step 1:

[1374] The server analyzes the health checkup needs of each region and sets the route for the mobile health checkup unit. It uses historical data and demographic data as input, which it retrieves from a database. It uses a data analysis algorithm to calculate the optimal route and outputs the results as the route setting information.

[1375] Step 2:

[1376] The user logs in to the online platform and opens the reservation page for the mobile health examination unit. The user selects the desired date, time, and location, and enters the required personal information. The entered information is sent to the server and saved in the database as reservation information.

[1377] Step 3:

[1378] The server generates a schedule for the mobile health checkup unit based on the set route and reservation information from the user. It uses the travel route setting information and reservation information as input, creates a visit schedule list for each unit based on these, and outputs it as schedule information.

[1379] Step 4:

[1380] The terminal (a system within the mobile health checkup unit) arrives at the designated area and checks the reservation list. It uses the schedule information and reservation list data sent from the server as input. Based on this, the terminal guides users in order of their health checkup, measures their vital signs, and performs blood tests. The health checkup data is acquired and temporarily stored within the terminal.

[1381] Step 5:

[1382] The terminal sends the acquired health checkup data to the server. The measured health checkup data is used as input, converted into digital data, and uploaded to the server. The server receives this data and stores it in a database.

[1383] Step 6:

[1384] Users log in to the online platform and open the virtual health checkup reservation page. They select the desired date and time and enter the necessary information to complete the reservation. The entered reservation information is sent to the server and saved in the database.

[1385] Step 7:

[1386] The user re-logins into the online platform at the scheduled time and starts the virtual health check session. They interact with an avatar displayed on the screen and answer initial questions about their health status. The user's response data is collected as input and sent to the server.

[1387] Step 8:

[1388] The avatar analyzes the user's responses using a generative AI model. Using the collected data as input, it performs a health assessment through the analytical model. The analysis results are sent to a server and stored in a database.

[1389] Step 9:

[1390] The server generates health checkup results based on the analysis results and notifies the user via the online platform, including referral information to a specialist if necessary. It uses the analysis result data as input and generates a notification message that is output to the user.

[1391] Step 10:

[1392] If a user wishes to consult with a specialist, they can use the online platform to make an appointment with the specialist. The health checkup results and specialist referral information are used as input, and appointment information is generated based on this and sent to the server. The server then stores the appointment information in a database and notifies the specialist.

[1393] The above are the specific processing steps of the system program for carrying out the invention.

[1394] 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.

[1395] This invention relates to a system that combines a mobile health checkup unit with a virtual health checkup unit and is equipped with an emotion engine. This system provides an environment where users can easily undergo health checkups, and furthermore, recognizes the user's emotional state to improve diagnostic accuracy and user experience.

[1396] System configuration

[1397] The system includes the following major components:

[1398] 1. Mobile Health Checkup Unit

[1399] 2. Online Platforms

[1400] 3. Virtual Health Check Unit

[1401] 4. Avatar

[1402] 5. Generative AI Models

[1403] 6. Emotion Engine

[1404] Program processing

[1405] 1. Mobile Health Checkup Unit

[1406] server:

[1407] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[1408] The booking system will be published on an online platform, allowing users to book health checkups.

[1409] User:

[1410] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[1411] Terminal (system in mobile health examination unit):

[1412] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[1413] The test results are entered into the terminal and sent to the server as digital data.

[1414] 2. Virtual Health Check Unit

[1415] server:

[1416] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[1417] User:

[1418] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[1419] Device (user's PC or smartphone):

[1420] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[1421] Avatar:

[1422] It uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1423] The content of the dialogue is adjusted based on the user's emotional data to help the user relax. For example, if the user is nervous, the dialogue will be designed to relax the user.

[1424] server:

[1425] Analyze data from the emotion engine and adjust the difficulty and content of the initial questions.

[1426] The results of the health check will be communicated to users via an online platform, and if necessary, a referral to a specialist will be made.

[1427] Specific examples

[1428] 1. Example of use of the mobile health checkup unit

[1429] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[1430] 2. Example of use of the virtual health checkup unit

[1431] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the obtained information, and sends it to the server. The emotion engine analyzes B's facial expressions and tone of voice and engages in dialogue to help him relax. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[1432] In this way, this system allows users to easily undergo health checkups at home or nearby locations. By using the emotion engine, it is possible to improve the accuracy of the diagnosis while ensuring user comfort, thereby realizing accessibility of the diagnosis and improving the user experience.

[1433] The processing flow will be explained below.

[1434] Mobile health examination unit processing steps

[1435] Step 1:

[1436] The server identifies areas with high demand based on past health checkup data for each region.

[1437] Step 2:

[1438] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[1439] Step 3:

[1440] The server displays the configured route on an online platform for residents to make reservations.

[1441] Step 4:

[1442] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[1443] Step 5:

[1444] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[1445] Step 6:

[1446] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[1447] Step 7:

[1448] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[1449] Step 8:

[1450] The terminal (a system within the mobile health examination unit) checks the reservation list.

[1451] Step 9:

[1452] The terminal (a system within the mobile health checkup unit) guides users through the health checkup in order and performs the health checkup (e.g., measuring vital signs and blood tests).

[1453] Step 10:

[1454] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[1455] Step 11:

[1456] The server analyzes the collected health check results and generates a result report.

[1457] Step 12:

[1458] The server links the results report to the user's account and sends a result notification email.

[1459] Step 13:

[1460] The user logs in to the online platform and views the medical examination result report.

[1461] Virtual Health Check Unit Processing Steps

[1462] Step 1:

[1463] The server provides a virtual health checkup reservation system on an online platform.

[1464] Step 2:

[1465] The server displays the available dates and times for users to make reservations and updates the available slots.

[1466] Step 3:

[1467] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[1468] Step 4:

[1469] The user selects the desired date and time and makes a reservation.

[1470] Step 5:

[1471] The user enters the required information and completes the reservation.

[1472] Step 6:

[1473] The server saves the reservation information in a database and sends a confirmation email to the user.

[1474] Step 7:

[1475] The user logs into the online platform at the time of the reservation.

[1476] Step 8:

[1477] The device (user's PC or smartphone) starts the virtual health check session.

[1478] Step 9:

[1479] The avatar uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1480] Step 10:

[1481] The user interacts with the avatar to answer initial questions about their health.

[1482] Step 11:

[1483] The avatar adjusts the dialogue based on the user's emotional data to help the user relax. For example, if the user is nervous, the avatar will engage in dialogue to relax the user.

[1484] Step 12:

[1485] The server analyzes the response data to the initial questions in real time.

[1486] Step 13:

[1487] The server generates additional detailed questions as needed.

[1488] Step 14:

[1489] The server analyzes the collected information, compiles the results and links them to the user's account.

[1490] Step 15:

[1491] The server notifies the user of the health check result report through the online platform.

[1492] Step 16:

[1493] The user views the medical examination result report.

[1494] Step 17:

[1495] The server will provide referrals to specialists as needed.

[1496] Example 2

[1497] 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."

[1498] Conventional health checkup systems face problems such as insufficient access for users to undergo regular checkups and inaccurate diagnostic results. Furthermore, there are insufficient means to alleviate the tension and anxiety users feel during the diagnostic process. This makes it difficult to obtain accurate health checkup results and does not improve the user experience. Furthermore, it is difficult to provide diagnoses to users in remote locations.

[1499] 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.

[1500] In this invention, the server includes: means for analyzing regional health checkup needs and setting a mobile health checkup unit's route; means for a user to make a reservation for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to arrive at the designated area, conduct the health checkup, and transmit the results to the server; means for the virtual health checkup unit to provide a remote health checkup to the user; means for collecting and analyzing information about the user's health status through dialogue with an avatar; means for analyzing the user's emotional state using an emotion engine and adjusting the dialogue content based on the analysis results; means for notifying the user of the analysis results via the online platform; and means for referring the user to a doctor if necessary. This allows users to easily receive health checkups, and the emotion engine reduces tension and anxiety during the checkup process, providing accurate health checkup results and a high-quality user experience. Health checkups can also be provided to users in remote locations.

[1501] A "mobile health examination unit" is a unit equipped with vehicles and equipment for traveling to a specific area to provide health examinations.

[1502] "Medical checkup needs" refers to the demand for medical checkups in a particular area, analyzed based on demographics and past data.

[1503] A "patrol route" is a route set up for a mobile health examination unit to travel through a particular area.

[1504] "Online platform" means a website or application that users can access via the internet to book health checkups and check their results.

[1505] A "Virtual Health Check Unit" is a system for providing health checks to users remotely, accessible through an online platform.

[1506] An "avatar" is a virtual person or character that interacts with the user within the virtual health checkup unit.

[1507] An "emotion engine" is software that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1508] A "generative AI model" is a model that uses artificial intelligence technology to generate appropriate questions to engage in dialogue with users.

[1509] "Physical examination results" refers to the examination results of a medical examination that the user has undergone, and includes blood test results and vital sign measurement results.

[1510] "Referral to a doctor" refers to the procedure of referring the user to a specialist based on the results of the health check.

[1511] This invention is a system that integrates a mobile health checkup unit and a virtual health checkup unit, allowing users to easily undergo health checkups. It also aims to improve the accuracy of diagnosis and the user experience by using an emotion engine to recognize the user's emotional state in real time.

[1512] System Components

[1513] The system includes the following major components:

[1514] 1. Mobile Health Checkup Unit

[1515] 2. Online Platforms

[1516] 3. Virtual Health Check Unit

[1517] 4. Avatar

[1518] 5. Generative AI Models

[1519] 6. Emotion Engine

[1520] Mobile Health Checkup Unit

[1521] The server analyzes the health checkup needs of each area and plans the routes for the mobile health checkup units. To do this, it uses Python to extract data from a demographic database and compiles statistics such as age group, gender, and medical history to identify areas with high demand. It then uses AWS Lambda to run the routing algorithm and generate the optimal route.

[1522] The server publishes route information and the reservation system to an online platform. The reservation page is created using JavaScript and React, and the backend is built with Node.js. Users log in to the online platform, select the desired date, time, and location, and make a reservation.

[1523] The terminal (a system inside the mobile health checkup unit) arrives at the designated area according to a set route, and the system checks the reservation list and guides the user in order. Medical staff measure the user's vital signs and perform blood tests, and send the results to the server in real time.

[1524] Virtual Health Check Unit

[1525] The server implements a booking function using the Django framework to publish a virtual health checkup booking system on an online platform, providing users with selectable dates and times.

[1526] Users access the virtual health checkup reservation page, select the desired date and time, and make a reservation. At the scheduled time, they log in to the online platform from their home PC or smartphone to start the virtual health checkup session.

[1527] The avatar uses a generative AI model to ask initial questions about the user's health status. The model uses Python and natural language processing (NLP) techniques to generate appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize the user's emotional state in real time.

[1528] The server analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the obtained data, it generates the next dialogue content, providing a comfortable dialogue environment for the user.

[1529] Specific examples

[1530] For example, when using a mobile health checkup unit, User A checks the date and time that the mobile health checkup unit will arrive at a nearby park on the online platform, selects the desired date and time, and the park, and makes a reservation. The unit arrives on the reserved date and time, and User A undergoes the health checkup. Medical staff measure User A's blood pressure and heart rate and send the data to a server in real time. User A can check the diagnosis results later on the online platform.

[1531] When using the virtual health check unit, User B books a virtual health check on the online platform. User B selects the desired date and time and confirms the reservation. At the scheduled date and time, User B logs in from their home PC and begins a conversation with the avatar. The avatar asks, "How are you feeling lately?" and User B responds. The emotion engine analyzes User B's facial expressions and tone of voice and engages in a conversation designed to relax them. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[1532] Example prompts for generative AI models

[1533] "Use a virtual health check unit to generate initial questions to check the user's health. Take into account the user's emotional state and adjust the dialogue as needed."

[1534] In this way, the system allows users to easily undergo health checkups at home or nearby locations, and by using an emotion engine, improves the accuracy of the diagnosis while ensuring user comfort.

[1535] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1536] Step 1:

[1537] Server: Analyzes regional health checkup needs. Extracts data from a demographic database and uses Python to compile statistics such as age group, gender, and medical history to identify areas with high demand.

[1538] Input: Demographic data (age range, gender, medical history, etc.)

[1539] Output: List of areas with high demand for health checkups

[1540] What it does: The server accesses a demographic database to gather the necessary data, then analyzes the data using Python data analysis libraries (e.g., Pandas, NumPy) to identify areas with high demand.

[1541] Step 2:

[1542] Server: Plans the mobile health check unit's route based on the analysis results. AWS Lambda is used to run the route planning algorithm and generate the optimal route.

[1543] Input: List of areas with high demand for health checkups

[1544] Output: Optimal tour route

[1545] What happens: The server triggers AWS Lambda to run a pre-configured routing algorithm, which calculates the optimal route based on the list of areas and saves the results.

[1546] Step 3:

[1547] Server: Publish the reservation system on an online platform based on the set route. Create the reservation page using JavaScript and React, and build the backend using Node.js.

[1548] Input: Optimal tour route

[1549] Output: Online platform with published reservation system

[1550] What it does: The server retrieves the route information, builds the user interface using JavaScript and React, sets up a backend system using Node.js to store reservation information, and publishes it to an online platform.

[1551] Step 4:

[1552] User: Logs into the online platform, selects the desired date, time and location and makes a reservation.

[1553] Input: User login information, desired date and time, and location selection

[1554] Output: User's reservation information is saved in the database

[1555] Specific operation: A user logs in to the online platform, selects the desired date, time and location on the interface, enters the required information in the reservation form and submits it. The submitted reservation information is then stored in a database by the server.

[1556] Step 5:

[1557] Terminal (system inside the mobile health checkup unit): Arrives at the designated area according to the set route and checks the appointment list. Medical staff guides the user, measures vital signs and performs blood tests, and enters the results into the terminal.

[1558] Input: Reservation list, health check results

[1559] Output: The entered health check results are sent to the server.

[1560] Specific operation: The terminal inside the mobile unit checks the reservation list and guides each user in order. Medical staff take the user's vital signs and perform blood tests, and enter the results into the terminal. The entered data is sent to the server in real time.

[1561] Step 6:

[1562] Server: Provides a virtual health checkup booking system on an online platform. Implements the booking function using the Django framework and provides users with selectable dates and times.

[1563] Input: Virtual health check appointment information

[1564] Output: Online platform with published reservation system

[1565] What it does: The server implements the reservation function using the Django framework, provides date and time information that users can select, and publishes the reservation system on an online platform.

[1566] Step 7:

[1567] User: Visits the virtual health checkup booking page, selects the desired date and time, and makes a booking.

[1568] Input: User login information, desired date and time

[1569] Output: User's reservation information is saved in the database

[1570] Specific operation: A user logs in to the online platform, enters the desired date and time, and confirms the reservation. The entered reservation information is sent to the server and recorded in the database.

[1571] Step 8:

[1572] User: Logs into the online platform at the scheduled time and date to begin the virtual health assessment session.

[1573] Input: User login information, reservation information

[1574] Output: An interactive session with the avatar is started.

[1575] Specific operation: The user logs in at the scheduled date and time and starts the virtual health check session. Once the session starts, the user conducts the health check through interaction with the avatar.

[1576] Step 9:

[1577] Avatar: Uses generative AI models to ask the user appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1578] Input: Generative AI model, emotion engine

[1579] Output: User health information, sentiment analysis data

[1580] How it works: The avatar uses generative AI models to generate appropriate questions, and the emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize their emotional state in real time.

[1581] Step 10:

[1582] Server: Analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the information obtained, the next dialogue content is generated.

[1583] Input: Sentiment analysis data, user responses

[1584] Output: Tailored questions and dialogue

[1585] How it works: The server analyzes the data sent from the emotion engine, adjusts the difficulty and content of the initial questions, and then uses NLP models to generate the next questions and dialogue.

[1586] Step 11:

[1587] Server: Analyzes the results of the virtual health check and notifies the user via the online platform, and if necessary, provides a referral to a specialist.

[1588] Input: Virtual health check results

[1589] Output: Notification of results, referral to specialist

[1590] What it does: The server analyzes the health check results and displays them on the user's personal dashboard. If necessary, it also arranges for the user to be referred to a specialist.

[1591] (Application example 2)

[1592] 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."

[1593] There is a need to improve the efficiency and accuracy of health checkups and mental healthcare for factory workers. Conventional health checkup systems have difficulty analyzing not only the physical health status of employees but also their emotional state and providing follow-up as needed. In addition, automation of emotion analysis and data management is insufficient, making it difficult to improve the quality and efficiency of healthcare.

[1594] 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.

[1595] In this invention, the server includes a means including a factory patrol healthcare robot that performs health checks and analyzes the emotional state of employees working in a factory environment, a means for performing emotion analysis using a generative AI model and storing the results in a database, and a means for collecting and analyzing information about the health state through dialogue with an avatar. This makes it possible to analyze not only the physical health state of employees but also their emotional state in real time and provide appropriate follow-ups automatically.

[1596] A "mobile health checkup unit" is a device that travels around a specific area and provides health checkups to users.

[1597] "User" means an individual who books a medical examination or takes a virtual medical examination via the online platform.

[1598] "Online platform" refers to the online system that users use to make appointments with health examination units and check examination results.

[1599] A "virtual health examination unit" is a virtual diagnostic device for providing a remote health examination to a user.

[1600] An "avatar" is a virtual character that interacts with users on an online platform and collects information about their health status.

[1601] A "generative AI model" is an artificial intelligence algorithm used to interact with users and conduct sentiment analysis.

[1602] An "emotion engine" is software that recognizes and analyzes a user's emotional state in real time.

[1603] "Factory environment" refers to the entire working environment in which members working within a factory are active.

[1604] The "factory patrol healthcare robot" is a robot that patrols the factory, conducting health checks and analyzing emotional states.

[1605] A "health checkup" is a series of tests and evaluations to assess a user's health status.

[1606] "Emotional state" refers to the user's mental and psychological state, as analyzed by the emotion engine.

[1607] A "database" is a digital information storage system for storing the results of health checks and emotion analysis.

[1608] The system for implementing this invention consists of a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, a generative AI model, a supply device, and an emotion engine. In a factory environment, it also includes a roving healthcare robot. The specific configuration and operation method of the system are described below.

[1609] System configuration

[1610] Mobile health check unit: A device that travels around a specific area and provides health checks to users.

[1611] Online platform: An internet system where users can book health checkups and check results.

[1612] Virtual Health Check Unit: A virtual diagnostic device that provides remote health checks to users.

[1613] Avatar: A virtual character that interacts with the user and collects information about their health.

[1614] Generative AI model: An artificial intelligence algorithm that interacts with users and analyzes their emotions.

[1615] Emotion Engine: Software that recognizes and analyzes the user's emotional state in real time.

[1616] Factory-specific healthcare robot: A robot that patrols the factory, conducting health checks and analyzing emotional states.

[1617] How the program works

[1618] 1. Mobile Health Checkup Unit

[1619] Server: Analyzes health checkup needs based on historical data and demographics, and sets up round routes. Publishes the reservation system on an online platform, allowing users to select their preferred date, time, and location.

[1620] User: Logs in to the online platform and makes an appointment for a health check. The mobile health check unit will provide the health check at the designated date, time and location.

[1621] Terminal: Collects health checkup results and sends them to the server as digital data.

[1622] 2. Virtual Health Check Unit

[1623] Server: Accepts reservations for virtual health checkups through an online platform.

[1624] User: Logs in to the online platform at the scheduled time and undergoes a health check. Through dialogue with an avatar, the user answers initial questions about their health condition.

[1625] Avatar: Uses a generative AI model to ask appropriate questions, and an emotion engine to analyze the user's facial expressions and tone of voice, providing a relaxing dialogue. The analysis results are sent to a server.

[1626] 3. Factory Patrol Healthcare Robot

[1627] Server: Manages data for analyzing the health and emotional state of members working in the factory environment.

[1628] Factory-specific healthcare robot: This robot patrols the factory, conducting health checks and emotional analysis of employees. It sends the results to a server and provides follow-up as needed.

[1629] Emotion engine: Provides the results of health checkups and emotion analysis as relaxing dialogues and health advice.

[1630] Specific examples

[1631] 1. Example of use of the mobile health checkup unit

[1632] Users make a reservation through the online platform, and a mobile health screening unit arrives at the designated park to conduct the health screening. The results can be viewed later on the online platform.

[1633] 2. Example of use of the virtual health checkup unit

[1634] Users log in to the virtual health checkup from their home PC and interact with an avatar to check their health status. A generative AI model asks initial health-related questions, and an emotion engine analyzes the user's emotional state and provides relaxing dialogue.

[1635] 3. Example of use of a patrol healthcare robot in a factory

[1636] The robot patrols the factory, checking the health of employees and analyzing their stress levels using an emotion engine. The generative AI model automatically suggests appropriate follow-up measures. If an employee shows high levels of stress, it offers a dialogue to promote relaxation and health advice.

[1637] Prompt Sentence Examples

[1638] "Staff member A may be experiencing high stress due to a recent project. Please suggest some conversations to help him relax."

[1639] "Staff member B's vital signs are outside of normal range. Please suggest additional medical examinations and provide any necessary follow-up."

[1640] The above system configuration and operation method make it possible to carry out the invention.

[1641] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1642] Step 1:

[1643] The server analyzes past data and demographic data to predict health checkup needs. Using past health checkup data and demographic data as input, the server uses an analytical algorithm to determine the health checkup demand in each region and set up a tour route. The output is the set tour route.

[1644] Step 2:

[1645] A user logs in to the online platform and makes an appointment for a health checkup. The user provides the platform with their login information, desired date, time, and location as input, and submits an appointment request. The user is provided with an appointment confirmation as output.

[1646] Step 3:

[1647] The mobile health checkup unit's terminal moves to the designated area according to the set route and checks the reservation list. Using the route information and reservation list sent from the server as input, the unit carries out the health checkup corresponding to each reservation. The health checkup results are recorded on the terminal as output.

[1648] Step 4:

[1649] The terminal sends the results of the health checkup to the server. The health checkup results recorded on the terminal as input are formatted in a database format and sent to the server. The health checkup data stored on the server is obtained as output.

[1650] Step 5:

[1651] The server provides a virtual health checkup reservation system on an online platform. It receives the user's reservation information and desired date and time as input, manages the virtual health checkup schedule, and provides the user's reservation confirmation information as output.

[1652] Step 6:

[1653] Users log in to the online platform at the scheduled time and date to undergo a virtual health check. They provide their login and reservation information to the platform as input to begin the diagnostic process. The output is an interactive screen with an avatar that is displayed in real time.

[1654] Step 7:

[1655] The avatar uses a generative AI model to ask questions about the user's health status and analyzes their responses. It uses the user's response data and the emotion engine's analysis results as inputs to provide appropriate feedback. The output is the user's response data and the corresponding emotion analysis results.

[1656] Step 8:

[1657] The server notifies the user of the health checkup results and emotion analysis results through the online platform. The server uses the analyzed health checkup data and emotion data as input to generate an appropriate notification message. The notification message is then displayed on the user's platform screen as output.

[1658] Step 9:

[1659] The in-factory patrol healthcare robot patrols the factory, conducting health checks and emotional analysis of employees. It uses the employees' health and emotional data collected on-site as input and analyzes it in real time. The analysis results are sent to the robot terminal and server as output.

[1660] Step 10:

[1661] The emotion engine analyzes the acquired emotion data and evaluates the mental health state of the member. Data acquired from the emotion sensor is input to the emotion engine, and mental health is evaluated using an analysis algorithm. The evaluation result is obtained as output.

[1662] Step 11:

[1663] The server proposes necessary follow-up measures based on the evaluation results. Using the emotion engine's evaluation results and health checkup data as input, it generates an appropriate follow-up plan using a generative AI model. The follow-up plan is then notified to the user as output.

[1664] In this way, the entire system operates in cooperation, enabling efficient health checkups and mental health care for users.

[1665] 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.

[1666] 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.

[1667] 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.

[1668] [Fourth embodiment]

[1669] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1670] 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.

[1671] 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).

[1672] 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.

[1673] 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.

[1674] 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).

[1675] 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.

[1676] 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.

[1677] 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.

[1678] 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.

[1679] 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.

[1680] 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.

[1681] 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."

[1682] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. This system provides an environment where users can easily undergo health checkups without having to go to a hospital or clinic.

[1683] System configuration

[1684] The system includes the following major components:

[1685] 1. Mobile Health Checkup Unit

[1686] 2. Online Platforms

[1687] 3. Virtual Health Check Unit

[1688] 4. Avatar

[1689] 5. Generative AI Models

[1690] Program processing

[1691] 1. Mobile Health Checkup Unit

[1692] server:

[1693] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[1694] The booking system will be published on an online platform, allowing users to book health checkups.

[1695] User:

[1696] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[1697] Terminal (system in mobile health examination unit):

[1698] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[1699] The test results are entered into the terminal and sent to the server as digital data.

[1700] 2. Virtual Health Check Unit

[1701] server:

[1702] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[1703] User:

[1704] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[1705] Device (user's PC or smartphone):

[1706] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[1707] Avatar:

[1708] Use generative AI models to ask users the right questions and collect answers, engage users in relaxed conversations, and collect reliable data.

[1709] server:

[1710] The collected data is analyzed and the results of the health check are communicated to the user via an online platform, with a referral to a specialist provided if necessary.

[1711] Specific examples

[1712] 1. Examples of mobile health checkups

[1713] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[1714] 2. Use cases for virtual health checkups

[1715] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the information obtained, and sends it to the server. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[1716] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[1717] The processing flow will be explained below.

[1718] Mobile health examination unit processing steps

[1719] Step 1:

[1720] The server identifies areas with high demand based on past health checkup data for each region.

[1721] Step 2:

[1722] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[1723] Step 3:

[1724] The server displays the configured route on an online platform for residents to make reservations.

[1725] Step 4:

[1726] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[1727] Step 5:

[1728] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[1729] Step 6:

[1730] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[1731] Step 7:

[1732] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[1733] Step 8:

[1734] The terminal (a system within the mobile health examination unit) checks the reservation list.

[1735] Step 9:

[1736] The profile guides the user through the health checkup and performs the health checkup (e.g., measuring vital signs and blood tests).

[1737] Step 10:

[1738] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[1739] Step 11:

[1740] The server analyzes the collected health check results and generates a result report.

[1741] Step 12:

[1742] The server links the results report to the user's account and sends a result notification email.

[1743] Step 13:

[1744] The user logs in to the online platform and views the medical examination result report.

[1745] Virtual Health Check Unit Processing Steps

[1746] Step 1:

[1747] The server provides a virtual health checkup reservation system on an online platform.

[1748] Step 2:

[1749] The server displays the available dates and times for users to make reservations and updates the available slots.

[1750] Step 3:

[1751] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[1752] Step 4:

[1753] The user selects the desired date and time and makes a reservation.

[1754] Step 5:

[1755] The user enters the required information and completes the reservation.

[1756] Step 6:

[1757] The server saves the reservation information in a database and sends a confirmation email to the user.

[1758] Step 7:

[1759] The user logs into the online platform at the time of the reservation.

[1760] Step 8:

[1761] The device (user's PC or smartphone) starts the virtual health check session.

[1762] Step 9:

[1763] The avatar uses a generative AI model to ask the user appropriate questions.

[1764] Step 10:

[1765] The user interacts with the avatar to answer initial questions about their health.

[1766] Step 11:

[1767] The server analyzes the response data to the initial questions in real time.

[1768] Step 12:

[1769] The server generates additional detailed questions as needed.

[1770] Step 13:

[1771] The server analyzes the collected information, compiles the results and links them to the user's account.

[1772] Step 14:

[1773] The server notifies the user of the health check result report through the online platform.

[1774] Step 15:

[1775] The user views the medical examination result report.

[1776] Step 16:

[1777] The server will provide referrals to specialists as needed.

[1778] These steps ensure that the entire system operates smoothly, providing an environment in which users can easily undergo health checkups.

[1779] Example 1

[1780] 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."

[1781] Conventional health checkup systems require users to physically visit a medical facility, which can be a burden, especially for elderly people and those without cars. Furthermore, users living in remote areas have limited opportunities for health checkups, making early detection of illness difficult. Furthermore, there was a lack of efficient and accurate methods for collecting and analyzing initial questions and health checkup results and linking them to appropriate medical treatment.

[1782] 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.

[1783] In this invention, the server includes: means for analyzing regional health checkup needs and setting a route for the mobile health checkup unit; means for users to make reservations for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to check the reservation list, guide users in order to receive the health checkup, and conduct the health checkup; means for transmitting test results to the server as digital data; means for the virtual health checkup unit to remotely provide health checkups to users; means for an avatar to ask appropriate questions of the user using a generative AI model and collect and analyze information on the user's health status; means for notifying the user of the analysis results via the online platform; and means for, if necessary, referring the user to a specialist based on the health checkup results. This allows users to easily receive health checkups at home or in their neighborhood, improving accessibility to diagnosis and enabling early detection of diseases and appropriate medical treatment.

[1784] "Analyzing health checkup needs by region" means conducting statistical analysis of the health status and demand for health checkups of residents in a specific region based on past data, demographics, etc.

[1785] "Setting a patrol route" means planning the optimal route for the health examination unit to efficiently patrol a specific area.

[1786] An "online platform" is a general term for a system that users can access via the Internet and use various services such as making reservations, checking diagnostic results, and interacting with others.

[1787] A "mobile medical examination unit" is a device or vehicle equipped with the facilities to travel to various locations using the vehicle or device and provide medical examinations.

[1788] "Reservation List" means a list for recording and managing reservations made by a User through the Online Platform.

[1789] The "Virtual Health Check Unit" is a system that provides a mechanism for conducting health checkups remotely via the Internet.

[1790] A "generative AI model" is a program that uses artificial intelligence technology to interact with users and incorporates algorithms for asking questions and conducting analysis.

[1791] An "avatar" is a virtual entity that interacts with users and collects information about their health status using a generative AI model in a virtual health checkup unit.

[1792] "Digital data" refers to data used to store, analyze, and transmit health examination results in electronic form.

[1793] "Analysis results" are the results of statistical analysis or algorithmic analysis based on collected health status data.

[1794] "Referral" refers to transferring a user to an appropriate medical professional when necessary based on collected and analyzed medical examination data.

[1795] The present invention relates to a health checkup system that combines a mobile health checkup unit and a virtual health checkup unit. The purpose of this system is to provide an environment in which users can conveniently receive health checkups without having to go to a hospital or clinic. The following describes how this system is implemented.

[1796] Hardware and Software

[1797] The system includes several hardware and software components. The major hardware components include:

[1798] Mobile health checkup unit: A vehicle such as a bus or van that has been modified to accommodate medical equipment such as blood pressure monitors, thermometers, and blood testing machines.

[1799] Server: Located on a cloud platform (e.g., Amazon Web Services (AWS), Microsoft Azure) to store and process data.

[1800] User terminal: A device such as a PC or smartphone.

[1801] The main software components include:

[1802] Online platform: A web application that provides the reservation system, user interface, and results display functions. It uses React and Angular for the front end and Node.js and Django for the back end.

[1803] Generative AI model: An algorithm for conducting user interactions and collecting health-related information. Created using a machine learning framework (e.g., TensorFlow, PyTorch).

[1804] Data analysis tools: Statistical analysis software (e.g., R, Python) to analyze the collected data.

[1805] Example of a user scenario

[1806] 1. Example of use of the mobile health checkup unit

[1807] User A checks the date and time that the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation.

[1808] The mobile health checkup unit arrives at the park at the scheduled time and Mr. A undergoes a health checkup. When measuring his blood pressure, the device records the data and immediately sends it to the server. The results can then be viewed on an online platform.

[1809] 2. Use cases for virtual health checkups

[1810] User B books a virtual health checkup on an online platform.

[1811] At the scheduled time, the person logs in from their home PC and checks their health condition through dialogue with an avatar. The generative AI model asks, "How are you feeling lately?" and Person B responds. The server analyzes this data and uploads the diagnosis results to an online platform. Person B can check the results themselves later. If necessary, they will also be referred to a specialist.

[1812] Prompt Sentence Examples

[1813] "Where can I conveniently get a health checkup near me?" (related to mobile health checkup units)

[1814] "I would like to take a health check online. What is the process?" (related to the Virtual Health Check Unit)

[1815] In this way, this system allows users to easily undergo health checkups at home or nearby locations, improving the accessibility of diagnosis and enabling early detection of illness and appropriate medical treatment.

[1816] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1817] Step 1: Analyze your health checkup needs

[1818] server:

[1819] Input: Past health checkup data and demographic data by region

[1820] How it works: The server uses statistical analysis software (e.g., R, Python) to analyze the health checkup needs of each region. Specifically, it calculates the incidence rates of hypertension and diabetes in specific regions and determines which regions to prioritize for dispatching mobile health checkup units.

[1821] Output: List of priority areas for routing

[1822] Step 2: Setting up a tour route

[1823] server:

[1824] Input: Priority Region List

[1825] Operation: The server calculates the optimal tour route using a routing algorithm (e.g., Dijkstra's Algorithm). The calculation takes into account distance, time, and efficiency. The route information is generated as tour route information.

[1826] Output: Tour route information

[1827] Step 3: Publish your booking system

[1828] server:

[1829] Input: Tour route information

[1830] Operation: The server publishes a reservation system for mobile health checkup units on an online platform. The user interface is implemented using a web front-end (e.g., React, Angular), and the system back-end is implemented using Node.js and Django.

[1831] Output: A booking page accessible to the user

[1832] Step 4: Accept the reservation

[1833] User:

[1834] Input: Booking page of online platform

[1835] How it works: A user visits the online platform, selects the desired date, time, and location, and enters the necessary personal information, such as name, address, and contact details. Once the reservation is complete, a confirmation email is sent to the user.

[1836] Output: Reservation information, confirmation email

[1837] Step 5: Operating a mobile health screening unit

[1838] Terminal (system in mobile health examination unit):

[1839] Input: Tour route information, reservation list

[1840] Operation: The device follows the set route to the destination, locates using a GPS system (e.g., Google Maps API), reads the appointment list and guides users through the health checkup in order, and collects vital signs and test results from each user.

[1841] Output: Collected health data

[1842] Step 6: Send your test results

[1843] Terminal (system in mobile health examination unit):

[1844] Input: Collected health data

[1845] How it works: The terminal inputs the test results as digital data, encrypts them using the HTTPS protocol, and sends them to the server.

[1846] Output: Health data stored on the server

[1847] Step 7: Offer a virtual health check

[1848] server:

[1849] Input: User reservation information

[1850] Operation: The server provides a virtual health checkup on an online platform. It generates and transmits access information so that users can log in at the scheduled time.

[1851] Output: Virtual health check access information

[1852] Step 8: Start the Virtual Health Check

[1853] User:

[1854] Input: Virtual health check access information

[1855] How it works: Users log in to the online platform at a designated time and begin a virtual health screening session. They answer initial questions about their health status through an avatar that uses a generative AI model.

[1856] Output: Information about the user's health status

[1857] Step 9: Gathering health information

[1858] Avatar (generative AI model):

[1859] Input: User's answer

[1860] How it works: Using a generative AI model, the avatar asks appropriate questions to gather information about the user's health, such as "How are you feeling these days?", and stores the information gathered in a database.

[1861] Output: Collected health status data

[1862] Step 10: Data analysis and notification

[1863] server:

[1864] Input: Collected health status data

[1865] How it works: The server analyzes the collected data using machine learning algorithms (e.g., SVM, Random Forest). Based on the analysis results, it generates a health check result and notifies the user through an online platform. If necessary, it will refer the user to a specialist.

[1866] Output: Health checkup results, referral information to specialists

[1867] In this way, the system allows users to easily undergo a health check through a series of steps, improving the accuracy and efficiency of the diagnosis.

[1868] (Application example 1)

[1869] 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."

[1870] Conventional health checkup systems require users to physically visit a hospital or clinic, and for occupations requiring regular health management as employees, time and geographical constraints make it difficult to streamline health management. In particular, for occupations that require frequent travel, such as food delivery, regular health monitoring is often not adequately carried out. This has led to a decline in the utilization rate of health checkups and an increase in employee health risks.

[1871] 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.

[1872] In this invention, the server includes a means for providing real-time health checkup results and notifications to companies that aim to manage the health of their employees, a means for a mobile health checkup unit to travel to specific areas to provide health checkups, and a means for using a generative AI model to provide supplementary information on analysis results and referrals to specialists. This enables even employees who move around a lot to receive regular health checkups, improving the efficiency of health management.

[1873] A "mobile health check unit" is a mobile diagnostic device that travels around the area to provide health checkups to users.

[1874] "Online Platform" means a web-based system that allows Users to access and use the Services.

[1875] "Reservation method" refers to a system that allows users to make reservations for health checkups through an online platform.

[1876] The "Virtual Health Check Unit" is a digital diagnostic system that provides remote health checkups to users.

[1877] An "avatar" is a virtual character that interacts with users online and collects information about their health status.

[1878] A "generative AI model" is a model generated using an artificial intelligence algorithm to analyze health checkup results and provide supplementary information.

[1879] "Analysis means" refers to the process of analyzing collected health information and generating results.

[1880] "Means of providing in real time" refers to a method for providing health examination results and notifications to users immediately.

[1881] "Means for referring to specialists" refers to a system for referring users to specialists as needed based on the results of their health checkups.

[1882] "User" means a person who receives the services of the health examination system.

[1883] "Employee health management" refers to activities undertaken by companies to manage the health status of their employees and provide appropriate care.

[1884] This invention is a system for streamlining employee health management, particularly for occupations that require frequent travel. The system includes a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, and a generative AI model.

[1885] System configuration

[1886] 1. Mobile Health Checkup Unit

[1887] server

[1888] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[1889] The booking system will be made available on an online platform, allowing users to book health checkups.

[1890] User

[1891] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[1892] Terminal (system inside the mobile health checkup unit)

[1893] They will follow a set route to arrive at the designated area, check the reservation list, guide users in order to undergo health checkups, and perform health checkups such as measuring vital signs and blood tests.

[1894] The test results are entered into the terminal and sent to the server as digital data.

[1895] 2. Virtual Health Check Unit

[1896] server

[1897] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for their appointments.

[1898] User

[1899] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[1900] Device (user's PC or smartphone)

[1901] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an on-screen avatar to answer initial questions about their health.

[1902] Avatar

[1903] Uses generative AI models to ask users the right questions and collect answers, leading to a more relaxed dialogue and collecting reliable data.

[1904] server

[1905] The collected data will be analyzed and the results of the health check will be communicated to users via an online platform, with referrals to specialists provided if necessary.

[1906] Hardware and software used

[1907] Hardware: Smartphones, servers, PCs

[1908] Software: Flask (Python web framework), MySQL (database), TensorFlow (generative AI model)

[1909] Data processing and calculation

[1910] server

[1911] Health data collected from users is stored in a database, including vital signs, blood test results, and conversation data.

[1912] Using a generative AI model, the collected data is analyzed in real time to assess the user's health status, and the results are communicated to experts who can provide appropriate advice or refer the user to a specialist if necessary.

[1913] Specific examples

[1914] 1. Health checkup appointment

[1915] Employees log in to the online platform and make a reservation by specifying the desired date, time, and location on the mobile health examination unit's reservation page.

[1916] 2. Virtual Health Checkup

[1917] Employees book a virtual consultation on their smartphone, and the generative AI model asks questions at the specified date and time.

[1918] Example prompts for generative AI models

[1919] "Please answer the following questions regarding your health: Have you been feeling unwell recently?

[1920] "What is the level of stress you experience on a daily basis?"

[1921] "Tell me about your diet and exercise habits."

[1922] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1923] Step 1:

[1924] The server analyzes the health checkup needs of each region and sets the route for the mobile health checkup unit. It uses historical data and demographic data as input, which it retrieves from a database. It uses a data analysis algorithm to calculate the optimal route and outputs the results as the route setting information.

[1925] Step 2:

[1926] The user logs in to the online platform and opens the reservation page for the mobile health examination unit. The user selects the desired date, time, and location, and enters the required personal information. The entered information is sent to the server and saved in the database as reservation information.

[1927] Step 3:

[1928] The server generates a schedule for the mobile health checkup unit based on the set route and reservation information from the user. It uses the travel route setting information and reservation information as input, creates a visit schedule list for each unit based on these, and outputs it as schedule information.

[1929] Step 4:

[1930] The terminal (a system within the mobile health checkup unit) arrives at the designated area and checks the reservation list. It uses the schedule information and reservation list data sent from the server as input. Based on this, the terminal guides users in order of their health checkup, measures their vital signs, and performs blood tests. The health checkup data is acquired and temporarily stored within the terminal.

[1931] Step 5:

[1932] The terminal sends the acquired health checkup data to the server. The measured health checkup data is used as input, converted into digital data, and uploaded to the server. The server receives this data and stores it in a database.

[1933] Step 6:

[1934] Users log in to the online platform and open the virtual health checkup reservation page. They select the desired date and time and enter the necessary information to complete the reservation. The entered reservation information is sent to the server and saved in the database.

[1935] Step 7:

[1936] The user re-logins into the online platform at the scheduled time and starts the virtual health check session. They interact with an avatar displayed on the screen and answer initial questions about their health status. The user's response data is collected as input and sent to the server.

[1937] Step 8:

[1938] The avatar analyzes the user's responses using a generative AI model. Using the collected data as input, it performs a health assessment through the analytical model. The analysis results are sent to a server and stored in a database.

[1939] Step 9:

[1940] The server generates health checkup results based on the analysis results and notifies the user via the online platform, including referral information to a specialist if necessary. It uses the analysis result data as input and generates a notification message that is output to the user.

[1941] Step 10:

[1942] If a user wishes to consult with a specialist, they can use the online platform to make an appointment with the specialist. The health checkup results and specialist referral information are used as input, and appointment information is generated based on this and sent to the server. The server then stores the appointment information in a database and notifies the specialist.

[1943] The above are the specific processing steps of the system program for carrying out the invention.

[1944] 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.

[1945] This invention relates to a system that combines a mobile health checkup unit with a virtual health checkup unit and is equipped with an emotion engine. This system provides an environment where users can easily undergo health checkups, and furthermore, recognizes the user's emotional state to improve diagnostic accuracy and user experience.

[1946] System configuration

[1947] The system includes the following major components:

[1948] 1. Mobile Health Checkup Unit

[1949] 2. Online Platforms

[1950] 3. Virtual Health Check Unit

[1951] 4. Avatar

[1952] 5. Generative AI Models

[1953] 6. Emotion Engine

[1954] Program processing

[1955] 1. Mobile Health Checkup Unit

[1956] server:

[1957] Analyze the health checkup needs of each region and set up routes for the mobile health checkup units, taking into account past data and demographic trends.

[1958] The booking system will be published on an online platform, allowing users to book health checkups.

[1959] User:

[1960] Log in to the online platform and open the mobile health screening unit booking page. Select the desired date, time and location, and enter the required information to complete the booking.

[1961] Terminal (system in mobile health examination unit):

[1962] The robot follows a set route to arrive at the designated area, checks the reservation list, guides users in order to undergo health checkups, and performs health checkups such as measuring vital signs and blood tests.

[1963] The test results are entered into the terminal and sent to the server as digital data.

[1964] 2. Virtual Health Check Unit

[1965] server:

[1966] It provides a virtual health checkup booking system on an online platform, allowing users to select available dates and times for booking.

[1967] User:

[1968] Log in to the online platform, select the desired date and time on the virtual health checkup reservation page, enter the required information, and complete the reservation.

[1969] Device (user's PC or smartphone):

[1970] At the scheduled time, users log in to the online platform to begin their virtual health screening session, where they interact with an avatar displayed on the screen to answer initial questions about their health.

[1971] Avatar:

[1972] It uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1973] The content of the dialogue is adjusted based on the user's emotional data to help the user relax. For example, if the user is nervous, the dialogue will be designed to relax the user.

[1974] server:

[1975] Analyze data from the emotion engine and adjust the difficulty and content of the initial questions.

[1976] The results of the health check will be communicated to users via an online platform, and if necessary, a referral to a specialist will be made.

[1977] Specific examples

[1978] 1. Example of use of the mobile health checkup unit

[1979] User A checks the date and time the mobile health check unit will arrive at a nearby park on the online platform and makes a reservation. The mobile health check unit arrives at the park on the scheduled date and time, and User A undergoes a health check. The results of the check can be viewed later on the online platform.

[1980] 2. Example of use of the virtual health checkup unit

[1981] User B books a virtual health checkup on the online platform. He logs in from his home PC at the scheduled time and confirms his health condition through dialogue with an avatar. The generative AI model asks initial health-related questions, analyzes the obtained information, and sends it to the server. The emotion engine analyzes B's facial expressions and tone of voice and engages in dialogue to help him relax. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[1982] In this way, this system allows users to easily undergo health checkups at home or nearby locations. By using the emotion engine, it is possible to improve the accuracy of the diagnosis while ensuring user comfort, thereby realizing accessibility of the diagnosis and improving the user experience.

[1983] The processing flow will be explained below.

[1984] Mobile health examination unit processing steps

[1985] Step 1:

[1986] The server identifies areas with high demand based on past health checkup data for each region.

[1987] Step 2:

[1988] The server runs an algorithm to optimize the mobile health examination unit's route and determines the weekly route.

[1989] Step 3:

[1990] The server displays the configured route on an online platform for residents to make reservations.

[1991] Step 4:

[1992] The user logs into the online platform and opens the booking page for the mobile health checkup unit.

[1993] Step 5:

[1994] The user selects the desired date, time and location, and enters the necessary information to complete the reservation.

[1995] Step 6:

[1996] The server saves the entered reservation information in a database and sends a confirmation email to the user.

[1997] Step 7:

[1998] The terminal (a system within a mobile health examination unit) arrives at a designated area according to a set route.

[1999] Step 8:

[2000] The terminal (a system within the mobile health examination unit) checks the reservation list.

[2001] Step 9:

[2002] The terminal (a system within the mobile health checkup unit) guides users through the health checkup in order and performs the health checkup (e.g., measuring vital signs and blood tests).

[2003] Step 10:

[2004] The terminal (a system within the mobile health examination unit) digitally records the test results and transmits them to a server.

[2005] Step 11:

[2006] The server analyzes the collected health check results and generates a result report.

[2007] Step 12:

[2008] The server links the results report to the user's account and sends a result notification email.

[2009] Step 13:

[2010] The user logs in to the online platform and views the medical examination result report.

[2011] Virtual Health Check Unit Processing Steps

[2012] Step 1:

[2013] The server provides a virtual health checkup reservation system on an online platform.

[2014] Step 2:

[2015] The server displays the available dates and times for users to make reservations and updates the available slots.

[2016] Step 3:

[2017] A user logs in to the online platform and accesses the virtual health checkup appointment page.

[2018] Step 4:

[2019] The user selects the desired date and time and makes a reservation.

[2020] Step 5:

[2021] The user enters the required information and completes the reservation.

[2022] Step 6:

[2023] The server saves the reservation information in a database and sends a confirmation email to the user.

[2024] Step 7:

[2025] The user logs into the online platform at the time of the reservation.

[2026] Step 8:

[2027] The device (user's PC or smartphone) starts the virtual health check session.

[2028] Step 9:

[2029] The avatar uses a generative AI model to ask the user appropriate questions, where an emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[2030] Step 10:

[2031] The user interacts with the avatar to answer initial questions about their health.

[2032] Step 11:

[2033] The avatar adjusts the dialogue based on the user's emotional data to help the user relax. For example, if the user is nervous, the avatar will engage in dialogue to relax the user.

[2034] Step 12:

[2035] The server analyzes the response data to the initial questions in real time.

[2036] Step 13:

[2037] The server generates additional detailed questions as needed.

[2038] Step 14:

[2039] The server analyzes the collected information, compiles the results and links them to the user's account.

[2040] Step 15:

[2041] The server notifies the user of the health check result report through the online platform.

[2042] Step 16:

[2043] The user views the medical examination result report.

[2044] Step 17:

[2045] The server will provide referrals to specialists as needed.

[2046] Example 2

[2047] 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."

[2048] Conventional health checkup systems face problems such as insufficient access for users to undergo regular checkups and inaccurate diagnostic results. Furthermore, there are insufficient means to alleviate the tension and anxiety users feel during the diagnostic process. This makes it difficult to obtain accurate health checkup results and does not improve the user experience. Furthermore, it is difficult to provide diagnoses to users in remote locations.

[2049] 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.

[2050] In this invention, the server includes: means for analyzing regional health checkup needs and setting a mobile health checkup unit's route; means for a user to make a reservation for the mobile health checkup unit via an online platform; means for the mobile health checkup unit to arrive at the designated area, conduct the health checkup, and transmit the results to the server; means for the virtual health checkup unit to provide a remote health checkup to the user; means for collecting and analyzing information about the user's health status through dialogue with an avatar; means for analyzing the user's emotional state using an emotion engine and adjusting the dialogue content based on the analysis results; means for notifying the user of the analysis results via the online platform; and means for referring the user to a doctor if necessary. This allows users to easily receive health checkups, and the emotion engine reduces tension and anxiety during the checkup process, providing accurate health checkup results and a high-quality user experience. Health checkups can also be provided to users in remote locations.

[2051] A "mobile health examination unit" is a unit equipped with vehicles and equipment for traveling to a specific area to provide health examinations.

[2052] "Medical checkup needs" refers to the demand for medical checkups in a particular area, analyzed based on demographics and past data.

[2053] A "patrol route" is a route set up for a mobile health examination unit to travel through a particular area.

[2054] "Online platform" means a website or application that users can access via the internet to book health checkups and check their results.

[2055] A "Virtual Health Check Unit" is a system for providing health checks to users remotely, accessible through an online platform.

[2056] An "avatar" is a virtual person or character that interacts with the user within the virtual health checkup unit.

[2057] An "emotion engine" is software that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[2058] A "generative AI model" is a model that uses artificial intelligence technology to generate appropriate questions to engage in dialogue with users.

[2059] "Physical examination results" refers to the examination results of a medical examination that the user has undergone, and includes blood test results and vital sign measurement results.

[2060] "Referral to a doctor" refers to the procedure of referring the user to a specialist based on the results of the health check.

[2061] This invention is a system that integrates a mobile health checkup unit and a virtual health checkup unit, allowing users to easily undergo health checkups. It also aims to improve the accuracy of diagnosis and the user experience by using an emotion engine to recognize the user's emotional state in real time.

[2062] System Components

[2063] The system includes the following major components:

[2064] 1. Mobile Health Checkup Unit

[2065] 2. Online Platforms

[2066] 3. Virtual Health Check Unit

[2067] 4. Avatar

[2068] 5. Generative AI Models

[2069] 6. Emotion Engine

[2070] Mobile Health Checkup Unit

[2071] The server analyzes the health checkup needs of each area and plans the routes for the mobile health checkup units. To do this, it uses Python to extract data from a demographic database and compiles statistics such as age group, gender, and medical history to identify areas with high demand. It then uses AWS Lambda to run the routing algorithm and generate the optimal route.

[2072] The server publishes route information and the reservation system to an online platform. The reservation page is created using JavaScript and React, and the backend is built with Node.js. Users log in to the online platform, select the desired date, time, and location, and make a reservation.

[2073] The terminal (a system inside the mobile health checkup unit) arrives at the designated area according to a set route, and the system checks the reservation list and guides the user in order. Medical staff measure the user's vital signs and perform blood tests, and send the results to the server in real time.

[2074] Virtual Health Check Unit

[2075] The server implements a booking function using the Django framework to publish a virtual health checkup booking system on an online platform, providing users with selectable dates and times.

[2076] Users access the virtual health checkup reservation page, select the desired date and time, and make a reservation. At the scheduled time, they log in to the online platform from their home PC or smartphone to start the virtual health checkup session.

[2077] The avatar uses a generative AI model to ask initial questions about the user's health status. The model uses Python and natural language processing (NLP) techniques to generate appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize the user's emotional state in real time.

[2078] The server analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the obtained data, it generates the next dialogue content, providing a comfortable dialogue environment for the user.

[2079] Specific examples

[2080] For example, when using a mobile health checkup unit, User A checks the date and time that the mobile health checkup unit will arrive at a nearby park on the online platform, selects the desired date and time, and the park, and makes a reservation. The unit arrives on the reserved date and time, and User A undergoes the health checkup. Medical staff measure User A's blood pressure and heart rate and send the data to a server in real time. User A can check the diagnosis results later on the online platform.

[2081] When using the virtual health check unit, User B books a virtual health check on the online platform. User B selects the desired date and time and confirms the reservation. At the scheduled date and time, User B logs in from their home PC and begins a conversation with the avatar. The avatar asks, "How are you feeling lately?" and User B responds. The emotion engine analyzes User B's facial expressions and tone of voice and engages in a conversation designed to relax them. The results can be viewed on the online platform, and if necessary, a referral to a specialist will be made.

[2082] Example prompts for generative AI models

[2083] "Use a virtual health check unit to generate initial questions to check the user's health. Take into account the user's emotional state and adjust the dialogue as needed."

[2084] In this way, the system allows users to easily undergo health checkups at home or nearby locations, and by using an emotion engine, improves the accuracy of the diagnosis while ensuring user comfort.

[2085] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2086] Step 1:

[2087] Server: Analyzes regional health checkup needs. Extracts data from a demographic database and uses Python to compile statistics such as age group, gender, and medical history to identify areas with high demand.

[2088] Input: Demographic data (age range, gender, medical history, etc.)

[2089] Output: List of areas with high demand for health checkups

[2090] What it does: The server accesses a demographic database to gather the necessary data, then analyzes the data using Python data analysis libraries (e.g., Pandas, NumPy) to identify areas with high demand.

[2091] Step 2:

[2092] Server: Plans the mobile health check unit's route based on the analysis results. AWS Lambda is used to run the route planning algorithm and generate the optimal route.

[2093] Input: List of areas with high demand for health checkups

[2094] Output: Optimal tour route

[2095] What happens: The server triggers AWS Lambda to run a pre-configured routing algorithm, which calculates the optimal route based on the list of areas and saves the results.

[2096] Step 3:

[2097] Server: Publish the reservation system on an online platform based on the set route. Create the reservation page using JavaScript and React, and build the backend using Node.js.

[2098] Input: Optimal tour route

[2099] Output: Online platform with published reservation system

[2100] What it does: The server retrieves the route information, builds the user interface using JavaScript and React, sets up a backend system using Node.js to store reservation information, and publishes it to an online platform.

[2101] Step 4:

[2102] User: Logs into the online platform, selects the desired date, time and location and makes a reservation.

[2103] Input: User login information, desired date and time, and location selection

[2104] Output: User's reservation information is saved in the database

[2105] Specific operation: A user logs in to the online platform, selects the desired date, time and location on the interface, enters the required information in the reservation form and submits it. The submitted reservation information is then stored in a database by the server.

[2106] Step 5:

[2107] Terminal (system inside the mobile health checkup unit): Arrives at the designated area according to the set route and checks the appointment list. Medical staff guides the user, measures vital signs and performs blood tests, and enters the results into the terminal.

[2108] Input: Reservation list, health check results

[2109] Output: The entered health check results are sent to the server.

[2110] Specific operation: The terminal inside the mobile unit checks the reservation list and guides each user in order. Medical staff take the user's vital signs and perform blood tests, and enter the results into the terminal. The entered data is sent to the server in real time.

[2111] Step 6:

[2112] Server: Provides a virtual health checkup booking system on an online platform. Implements the booking function using the Django framework and provides users with selectable dates and times.

[2113] Input: Virtual health check appointment information

[2114] Output: Online platform with published reservation system

[2115] What it does: The server implements the reservation function using the Django framework, provides date and time information that users can select, and publishes the reservation system on an online platform.

[2116] Step 7:

[2117] User: Visits the virtual health checkup booking page, selects the desired date and time, and makes a booking.

[2118] Input: User login information, desired date and time

[2119] Output: User's reservation information is saved in the database

[2120] Specific operation: A user logs in to the online platform, enters the desired date and time, and confirms the reservation. The entered reservation information is sent to the server and recorded in the database.

[2121] Step 8:

[2122] User: Logs into the online platform at the scheduled time and date to begin the virtual health assessment session.

[2123] Input: User login information, reservation information

[2124] Output: An interactive session with the avatar is started.

[2125] Specific operation: The user logs in at the scheduled date and time and starts the virtual health check session. Once the session starts, the user conducts the health check through interaction with the avatar.

[2126] Step 9:

[2127] Avatar: Uses generative AI models to ask the user appropriate questions. An emotion engine analyzes the user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[2128] Input: Generative AI model, emotion engine

[2129] Output: User health information, sentiment analysis data

[2130] How it works: The avatar uses generative AI models to generate appropriate questions, and the emotion engine analyzes the user's facial expressions and tone of voice via the camera and microphone to recognize their emotional state in real time.

[2131] Step 10:

[2132] Server: Analyzes the data obtained from the emotion engine and adjusts the difficulty and content of the initial questions. Based on the information obtained, the next dialogue content is generated.

[2133] Input: Sentiment analysis data, user responses

[2134] Output: Tailored questions and dialogue

[2135] How it works: The server analyzes the data sent from the emotion engine, adjusts the difficulty and content of the initial questions, and then uses NLP models to generate the next questions and dialogue.

[2136] Step 11:

[2137] Server: Analyzes the results of the virtual health check and notifies the user via the online platform, and if necessary, provides a referral to a specialist.

[2138] Input: Virtual health check results

[2139] Output: Notification of results, referral to specialist

[2140] What it does: The server analyzes the health check results and displays them on the user's personal dashboard. If necessary, it also arranges for the user to be referred to a specialist.

[2141] (Application example 2)

[2142] 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."

[2143] There is a need to improve the efficiency and accuracy of health checkups and mental healthcare for factory workers. Conventional health checkup systems have difficulty analyzing not only the physical health status of employees but also their emotional state and providing follow-up as needed. In addition, automation of emotion analysis and data management is insufficient, making it difficult to improve the quality and efficiency of healthcare.

[2144] 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.

[2145] In this invention, the server includes a means including a factory patrol healthcare robot that performs health checks and analyzes the emotional state of employees working in a factory environment, a means for performing emotion analysis using a generative AI model and storing the results in a database, and a means for collecting and analyzing information about the health state through dialogue with an avatar. This makes it possible to analyze not only the physical health state of employees but also their emotional state in real time and provide appropriate follow-ups automatically.

[2146] A "mobile health checkup unit" is a device that travels around a specific area and provides health checkups to users.

[2147] "User" means an individual who books a medical examination or takes a virtual medical examination via the online platform.

[2148] "Online platform" refers to the online system that users use to make appointments with health examination units and check examination results.

[2149] A "virtual health examination unit" is a virtual diagnostic device for providing a remote health examination to a user.

[2150] An "avatar" is a virtual character that interacts with users on an online platform and collects information about their health status.

[2151] A "generative AI model" is an artificial intelligence algorithm used to interact with users and conduct sentiment analysis.

[2152] An "emotion engine" is software that recognizes and analyzes a user's emotional state in real time.

[2153] "Factory environment" refers to the entire working environment in which members working within a factory are active.

[2154] The "factory patrol healthcare robot" is a robot that patrols the factory, conducting health checks and analyzing emotional states.

[2155] A "health checkup" is a series of tests and evaluations to assess a user's health status.

[2156] "Emotional state" refers to the user's mental and psychological state, as analyzed by the emotion engine.

[2157] A "database" is a digital information storage system for storing the results of health checks and emotion analysis.

[2158] The system for implementing this invention consists of a mobile health checkup unit, an online platform, a virtual health checkup unit, an avatar, a generative AI model, a supply device, and an emotion engine. In a factory environment, it also includes a roving healthcare robot. The specific configuration and operation method of the system are described below.

[2159] System configuration

[2160] Mobile health check unit: A device that travels around a specific area and provides health checks to users.

[2161] Online platform: An internet system where users can book health checkups and check results.

[2162] Virtual Health Check Unit: A virtual diagnostic device that provides remote health checks to users.

[2163] Avatar: A virtual character that interacts with the user and collects information about their health.

[2164] Generative AI model: An artificial intelligence algorithm that interacts with users and analyzes their emotions.

[2165] Emotion Engine: Software that recognizes and analyzes the user's emotional state in real time.

[2166] Factory-specific healthcare robot: A robot that patrols the factory, conducting health checks and analyzing emotional states.

[2167] How the program works

[2168] 1. Mobile Health Checkup Unit

[2169] Server: Analyzes health checkup needs based on historical data and demographics, and sets up round routes. Publishes the reservation system on an online platform, allowing users to select their preferred date, time, and location.

[2170] User: Logs in to the online platform and makes an appointment for a health check. The mobile health check unit will provide the health check at the designated date, time and location.

[2171] Terminal: Collects health checkup results and sends them to the server as digital data.

[2172] 2. Virtual Health Check Unit

[2173] Server: Accepts reservations for virtual health checkups through an online platform.

[2174] User: Logs in to the online platform at the scheduled time and undergoes a health check. Through dialogue with an avatar, the user answers initial questions about their health condition.

[2175] Avatar: Uses a generative AI model to ask appropriate questions, and an emotion engine to analyze the user's facial expressions and tone of voice, providing a relaxing dialogue. The analysis results are sent to a server.

[2176] 3. Factory Patrol Healthcare Robot

[2177] Server: Manages data for analyzing the health and emotional state of members working in the factory environment.

[2178] Factory-specific healthcare robot: This robot patrols the factory, conducting health checks and emotional analysis of employees. It sends the results to a server and provides follow-up as needed.

[2179] Emotion engine: Provides the results of health checkups and emotion analysis as relaxing dialogues and health advice.

[2180] Specific examples

[2181] 1. Example of use of the mobile health checkup unit

[2182] Users make a reservation through the online platform, and a mobile health screening unit arrives at the designated park to conduct the health screening. The results can be viewed later on the online platform.

[2183] 2. Example of use of the virtual health checkup unit

[2184] Users log in to the virtual health checkup from their home PC and interact with an avatar to check their health status. A generative AI model asks initial health-related questions, and an emotion engine analyzes the user's emotional state and provides relaxing dialogue.

[2185] 3. Example of use of a patrol healthcare robot in a factory

[2186] The robot patrols the factory, checking the health of employees and analyzing their stress levels using an emotion engine. The generative AI model automatically suggests appropriate follow-up measures. If an employee shows high levels of stress, it offers a dialogue to promote relaxation and health advice.

[2187] Prompt Sentence Examples

[2188] "Staff member A may be experiencing high stress due to a recent project. Please suggest some conversations to help him relax."

[2189] "Staff member B's vital signs are outside of normal range. Please suggest additional medical examinations and provide any necessary follow-up."

[2190] The above system configuration and operation method make it possible to carry out the invention.

[2191] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2192] Step 1:

[2193] The server analyzes past data and demographic data to predict health checkup needs. Using past health checkup data and demographic data as input, the server uses an analytical algorithm to determine the health checkup demand in each region and set up a tour route. The output is the set tour route.

[2194] Step 2:

[2195] A user logs in to the online platform and makes an appointment for a health checkup. The user provides the platform with their login information, desired date, time, and location as input, and submits an appointment request. The user is provided with an appointment confirmation as output.

[2196] Step 3:

[2197] The mobile health checkup unit's terminal moves to the designated area according to the set route and checks the reservation list. Using the route information and reservation list sent from the server as input, the unit carries out the health checkup corresponding to each reservation. The health checkup results are recorded on the terminal as output.

[2198] Step 4:

[2199] The terminal sends the results of the health checkup to the server. The health checkup results recorded on the terminal as input are formatted in a database format and sent to the server. The health checkup data stored on the server is obtained as output.

[2200] Step 5:

[2201] The server provides a virtual health checkup reservation system on an online platform. It receives the user's reservation information and desired date and time as input, manages the virtual health checkup schedule, and provides the user's reservation confirmation information as output.

[2202] Step 6:

[2203] Users log in to the online platform at the scheduled time and date to undergo a virtual health check. They provide their login and reservation information to the platform as input to begin the diagnostic process. The output is an interactive screen with an avatar that is displayed in real time.

[2204] Step 7:

[2205] The avatar uses a generative AI model to ask questions about the user's health status and analyzes their responses. It uses the user's response data and the emotion engine's analysis results as inputs to provide appropriate feedback. The output is the user's response data and the corresponding emotion analysis results.

[2206] Step 8:

[2207] The server notifies the user of the health checkup results and emotion analysis results through the online platform. The server uses the analyzed health checkup data and emotion data as input to generate an appropriate notification message. The notification message is then displayed on the user's platform screen as output.

[2208] Step 9:

[2209] The in-factory patrol healthcare robot patrols the factory, conducting health checks and emotional analysis of employees. It uses the employees' health and emotional data collected on-site as input and analyzes it in real time. The analysis results are sent to the robot terminal and server as output.

[2210] Step 10:

[2211] The emotion engine analyzes the acquired emotion data and evaluates the mental health state of the member. Data acquired from the emotion sensor is input to the emotion engine, and mental health is evaluated using an analysis algorithm. The evaluation result is obtained as output.

[2212] Step 11:

[2213] The server proposes necessary follow-up measures based on the evaluation results. Using the emotion engine's evaluation results and health checkup data as input, it generates an appropriate follow-up plan using a generative AI model. The follow-up plan is then notified to the user as output.

[2214] In this way, the entire system operates in cooperation, enabling efficient health checkups and mental health care for users.

[2215] 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.

[2216] 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.

[2217] 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.

[2218] 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.

[2219] 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.

[2220] 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.

[2221] 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).

[2222] 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.

[2223] 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."

[2224] 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.

[2225] 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).

[2226] 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.

[2227] 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) ...

Claims

1. A mobile health screening unit provides health screening in a specific area; a means for a user to make an appointment for the mobile health examination unit via an online platform; a means for the virtual health examination unit to remotely provide a health examination to a user; A means for collecting and analyzing information about health status through interaction with an avatar; a means for notifying the user of the analysis results via an online platform; A system including:

2. The system of claim 1 , wherein the generated avatar includes means for interacting with the user and conducting initial health questions.

3. The system of claim 1 further comprising means for analyzing the user's medical examination results and providing a referral to a doctor if necessary.

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