system

Abstract

We provide the system. [Solution] A means of acquiring biological information using a measuring device, A means for acquiring an image of the affected area using an image acquisition device, An analysis method using artificial intelligence that connects to a storage device in the cloud, analyzes acquired information, and diagnoses health status, A means for generating prescription information based on diagnostic results, A method for searching for nearby medical facilities and making reservations using location information, A means of processing payment for medical consultations and providing added value, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, many people recognize that it is important to receive regular medical examinations and diagnoses to maintain health. However, there are problems that it takes effort and time to visit a medical institution. Furthermore, it is not easy to quickly respond to sudden poor health or injuries, find an appropriate medical institution, and make a reservation. Also, the procedure for settling medical expenses is troublesome for users. There is a demand for providing a mechanism that solves these problems and enables users to receive medical services quickly and effectively while staying at home.

Means for Solving the Problems

[0005] This invention includes means for acquiring biometric information (e.g., blood pressure, heart rate, body temperature) using a smartphone or portable measuring device, and means for acquiring images of the affected area using an image acquisition device. This data is transmitted to the cloud, and an analysis means using artificial intelligence diagnoses the user's health condition. It also includes means for generating prescription information based on the diagnosis results, searching for nearby medical facilities based on the user's location information, and making reservations. Furthermore, it has a function to provide added value along with payment of consultation fees, and enables automatic settlement of medical expenses by using insurance information. In this way, users can receive appropriate medical services quickly from the comfort of their homes.

[0006] A "measuring device" is a device used to acquire biological information, and includes devices such as blood pressure monitors, heart rate monitors, and thermometers.

[0007] An "image acquisition device" is a device used to capture images of affected areas or other parts of the human body and save them as digital data.

[0008] "Cloud storage" refers to a storage system on a remote server that allows data to be stored and shared via the internet.

[0009] "Analysis methods using artificial intelligence" refer to methods that utilize machine learning and data analysis technologies to analyze acquired data and output diagnostic results.

[0010] "Prescription information" refers to information that includes specific instructions regarding medications and treatments, generated based on a diagnosis.

[0011] "Location information" refers to geographical data that indicates the user's current location, and is obtained using technologies such as GPS.

[0012] "Medical facilities" is a general term for facilities that provide medical services, such as hospitals, clinics, and pharmacies.

[0013] "Means of making reservations" refers to the function that, through the system, arranges appointments for medical consultations or meetings at designated medical facilities on behalf of the user.

[0014] "Payment of consultation fees" refers to the process of completing the payment procedure for medical services received by the user.

[0015] "Added value" refers to ancillary services such as points or digital currencies that are offered as incentives to users.

[0016] "Insurance information" refers to data related to health insurance held by the user, and is used for settling and paying medical expenses.

[0017] "Automated medical expense settlement" is a system that uses pre-registered insurance information to electronically calculate the cost of medical services and automate the payment process. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8]It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] This invention is a system that uses a smartphone to diagnose a user's health condition and provide medical services. This system uses the user's smartphone, which they use daily, to measure biometric information and take images of affected areas. Specifically, the user launches an application and acquires biometric information such as blood pressure, heart rate, and body temperature using a dedicated measuring device. Furthermore, if there is an injury or skin abnormality, images of that area are also taken. This allows the user to collect necessary health data from the comfort of their home.

[0040] The device sends the collected data to a server in the cloud, which uses artificial intelligence to analyze the received data. In this analysis process, the AI ​​identifies data patterns and diagnoses potential health problems. Based on the diagnosis, it also generates prescription information, including suggestions for necessary medications and treatments. This prescription information is immediately sent to the user's device.

[0041] Furthermore, the server utilizes the user's location information to search for nearby medical facilities and schedule appointments. Users can review their diagnosis and suggested medical facilities from their homes and complete the appointment process using the system. The system also uses health insurance information to automatically process payment for consultations. During this process, users are rewarded with points or digital currency as a way to encourage usage.

[0042] For example, if a user experiences cold symptoms, the app measures their body temperature and heart rate and sends this data to a server. The server processes the data and notifies the user of the possibility of a cold and information about over-the-counter medications available at nearby pharmacies. Furthermore, it simultaneously makes a hospital appointment and, if necessary, secures a time slot for a consultation.

[0043] In this way, the present invention provides a system that enables users to easily and quickly manage their health status and receive appropriate medical services at home.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user launches the application on their smartphone. The application displays a screen prompting the user to prepare for biometric data measurement.

[0047] Step 2:

[0048] Using the device, the user obtains blood pressure, heart rate, and body temperature using a dedicated measuring device. The app also instructs the user to take images of the affected area with the camera.

[0049] Step 3:

[0050] The device transmits the measured biometric information and captured image data to a server in the cloud via encrypted communication.

[0051] Step 4:

[0052] The server passes the received data to an AI module for analysis. The AI ​​analyzes the biometric data, detects abnormal values, and diagnoses the user's health status.

[0053] Step 5:

[0054] Based on the diagnostic results, the server generates prescription information, including details about necessary medications and treatments. This information is then returned to the user's terminal.

[0055] Step 6:

[0056] The server retrieves the user's current location and searches a database for nearby medical facilities. It then selects the most suitable medical facility and accesses the reservation system.

[0057] Step 7:

[0058] The server generates reservation information and notifies the user of the result of making an appointment at the nearest medical facility. Reservation details are sent to the user's device.

[0059] Step 8:

[0060] The terminal provides users with an interface that centrally displays diagnostic results, prescription information, and appointment information, and sends notifications prompting them to take necessary actions.

[0061] Step 9:

[0062] When a user receives medical treatment and pays the consultation fee, they enter payment information through a terminal. The server then automatically processes the medical expense settlement using the insurance information.

[0063] Step 10:

[0064] After payment is completed, the server will award the user additional points or digital currency to encourage continued use. This information will be notified to the user's device.

[0065] (Example 1)

[0066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0067] Modern healthcare management requires individuals to monitor their health status on a daily basis and access medical services quickly and appropriately. However, traditional methods involve cumbersome processes such as obtaining individual biometric information, making appointments with medical institutions, and settling medical fees, making it difficult to provide consistent services. There is a need to solve these problems and provide a system that allows users to more easily manage their health and access medical care from home or other convenient locations.

[0068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0069] In this invention, the server includes means for analyzing biometric data acquired using a generative AI model to determine the user's health status, means for generating prescription instructions based on the determination results, and means for searching for nearby medical institutions and making reservations using the user's location data. This enables users to efficiently acquire biometric data from the comfort of their homes, receive appropriate diagnoses and make reservations at medical institutions, and improves the convenience of medical services.

[0070] A "measuring device" is a device used to acquire biological data, and is a device that has the function of measuring the user's blood pressure, heart rate, body temperature, etc.

[0071] An "image acquisition device" is a device used to acquire images of specific parts of a user's body, and typically has the function of taking high-resolution images using a camera.

[0072] "Cloud storage" refers to data storage accessible via the internet, and is a device used to securely store and manage acquired biometric and image data.

[0073] A "generative AI model" is a machine learning model based on a large amount of historical data, and is a program that analyzes a user's health status and performs pattern recognition.

[0074] "Analysis means" refers to the functions of a system that analyzes acquired data and performs a series of processes to determine a person's health status.

[0075] A "means for generating prescription instructions" refers to a function that suggests appropriate medications and treatments to the user based on the assessment of their health condition.

[0076] "Location data" refers to information indicating a user's geographical location, and is digital information obtained through GPS or other location measurement technologies.

[0077] The "means of searching for medical facilities and making reservations" refers to a function that uses the user's location data to search for nearby medical facilities and automatically completes the necessary reservation procedures.

[0078] "Medical expense settlement" refers to the process of calculating and settling the charges for medical services based on the user's insurance information, etc.

[0079] "Digital currency" refers to a form of currency that can be traded electronically, including points and credits offered as incentives to users.

[0080] This invention is a system that enables users to monitor their health status on a daily basis and receive appropriate medical services. This system efficiently manages the user's health by combining a measuring device, an image acquisition device, a generative AI model, and a cloud-based storage device.

[0081] First, the user launches a healthcare application using a smart device and acquires biometric data such as blood pressure, heart rate, and body temperature using a measuring device. They also take images of the affected area or other areas of concern using an image acquisition device. This smart device is equipped with Bluetooth and Wi-Fi connectivity, allowing for easy data synchronization with the measuring device.

[0082] The acquired biometric and image data is sent from the device to a cloud-based storage device. The server then uses a generated AI model to analyze the data. This AI model is machine-trained based on a large amount of historical data and determines the health status through pattern recognition. Based on the AI ​​model's analysis results, the server identifies specific health risks and generates necessary prescriptions.

[0083] The server then uses the user's location data to search for the nearest suitable medical facility. It has the ability to check facility availability in real time and make the user's desired reservation. This reservation information is immediately sent to the user's smart device.

[0084] Furthermore, the system includes a medical expense settlement function, automatically processing payments based on the insurance data registered by the user. After settlement, digital currency or points are awarded to the user as an incentive.

[0085] As a concrete example, when a user experiences the initial symptoms of a cold, they launch the app, measure their body temperature and heart rate, and send this data to the cloud. The server diagnoses the possibility of a cold and provides the user with recommendations for over-the-counter medications, along with the option to book an appointment at a nearby clinic. In this way, users can quickly manage their health from home and access medical services as needed.

[0086] Examples of prompt messages include, "Your body temperature is elevated; please provide a detailed diagnosis," and "You have a skin abnormality; please send an image for evaluation."

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] The user launches a healthcare application on their smart device. Through the application's interface, they input instructions to send to the measuring device for measuring blood pressure, heart rate, and body temperature. The measuring device acquires this biometric data and transmits it to the device. The user's specific actions involve attaching the device to their fingertip or arm and waiting for the measurement results to be displayed.

[0090] Step 2:

[0091] The terminal encrypts the acquired biometric data and sends it to a server in the cloud along with images of the affected area taken using an image acquisition device. The input for this step is biometric data and image data, and these are sent to the server as output. Specifically, the terminal transmits and receives data between the device and the measuring device via Bluetooth or Wi-Fi.

[0092] Step 3:

[0093] The server uses a cloud-based AI model to analyze the received data. In this analysis process, the server supplies biometric and image data as input to the AI ​​model and generates health status diagnostic results as output. Specifically, the AI ​​model uses pattern recognition technology to detect anomalies and assess health risks.

[0094] Step 4:

[0095] The server generates necessary prescription instructions based on the diagnostic results and sends them to the user's terminal. The input for this step is the AI-generated diagnostic results, and the output is prescription information in a user-friendly format. Specifically, the server analyzes the diagnostic results and selects the most suitable medications and treatment options.

[0096] Step 5:

[0097] The server uses the user's location data to obtain current location information as input. It then searches for nearby medical facilities, checks appointment availability, and then makes a reservation, sending the information to the user's device. As output, the user receives a reservation completion message. The server accesses a database of medical facilities and performs reservation operations in real time.

[0098] Step 6:

[0099] The server uses the user's insurance data and treatment details as input to process the settlement of medical expenses. The output is a confirmation of settlement and the awarding of digital currency or points to the user's account. Specifically, the server executes the settlement process through the payment gateway and awards incentives to the user.

[0100] (Application Example 1)

[0101] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0102] Modern healthcare systems require visits to medical facilities and involve cumbersome payment processes, creating a need for automated and easily accessible health checkups and consultations. Furthermore, there is a lack of mechanisms for electronically settling payments after receiving medical services and providing appropriate incentives to users. Therefore, the challenge lies in improving user convenience while promoting the use of healthcare services.

[0103] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0104] In this invention, the server includes means for acquiring biological information using a measuring device, means for acquiring images of a target area using an image acquisition device, processing means using artificial intelligence connected to a storage device on the cloud to analyze the acquired information and diagnose the condition, means for generating initial treatment information based on the diagnosis results, means for searching for nearby facilities using location information and performing procedures, means for performing electronic payments and providing additional functions, and means for providing rewards for using the service. As a result, users can quickly and easily understand their health status and receive necessary medical services even at home. Furthermore, the electronic settlement of medical expenses reduces hassle, and usage can be promoted through points and rewards.

[0105] A "measuring device" is a device used to acquire biological information and has the function of accurately measuring various indicator data.

[0106] An "image acquisition device" is a device used to capture images of a target area, and its purpose is to record visual information as digital data.

[0107] "Cloud storage" refers to online storage that allows data to be stored and accessed via a network, and is a system that enables data organization and storage.

[0108] "Artificial intelligence" is a technology that uses computer programs to mimic human intellectual activity, and is particularly used in data analysis and diagnostic processes.

[0109] "Initial treatment information" refers to information about treatments and therapies suggested based on the results and condition of a health checkup, and is intended to provide users with prompt action plans.

[0110] "Location information" refers to data that indicates the geographical location of a user or device, and is used for searching for nearby facilities and providing directions.

[0111] "Electronic payment" refers to the process of conducting monetary transactions through online systems, and is a technology that completes payments without using banknotes or coins.

[0112] "Additional features" refer to extra functions or services provided in addition to the basic functions, and are elements that enhance the user experience.

[0113] A "reward" is an incentive given for a specific action or use of a service, and it has value in increasing the user's motivation.

[0114] The system that implements this application example operates using the following main components:

[0115] First, the user uses their smartphone to acquire biometric information from a Bluetooth-enabled measuring device. This process uses appropriate sensor devices to accurately collect indicator data such as blood pressure and body temperature. Then, the smartphone's camera function is used to acquire images of the affected area. The acquired data is sent from the smartphone to a server in the cloud.

[0116] The server receives the acquired biometric and image data and stores it in cloud-based storage. Then, it analyzes the data using a generative AI model, and artificial intelligence automatically diagnoses the user's health condition. Based on the diagnosis, the server sends initial treatment information back to the user's device. Here, the AI ​​analyzes past data patterns to suggest the most suitable treatment or procedure for the user.

[0117] Furthermore, the server has a mechanism to obtain location information from the user's device and search for nearby medical facilities. As a necessary procedure, reservations are automated, allowing users to complete facility reservations directly. The server also automatically settles medical fees through electronic payment, and as an additional feature, it awards points or rewards to users based on service usage.

[0118] As a concrete example, when a user experiences cold symptoms, they use a measuring device via the application to obtain their body temperature and heart rate. This data is immediately sent to a server, where AI diagnoses the possibility of a mild infection and provides information on nearby clinics. Simultaneously, an appointment at the clinic is made through the application, and points are added after the consultation.

[0119] An example of a prompt message would be: "Design an app that sends blood pressure and body temperature data measured by the user on their smartphone to a cloud AI, diagnoses their health condition, and settles medical expenses via electronic payment. Also, implement a points system to encourage customer use."

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The user launches a smartphone application and acquires biometric information using a Bluetooth-enabled measuring device. The input is biometric data such as blood pressure and body temperature. The device temporarily stores this data and then prepares it for transmission to a cloud server. The output is a data package sent to the cloud. The user verifies the connection between the devices and confirms that the sensors of the measuring device are functioning correctly.

[0123] Step 2:

[0124] The device uses a smartphone camera to capture images of the affected area. The input is the visual data captured through the camera. The images are processed by a dedicated algorithm, and their size and resolution are adjusted to a standard format. The output is an image file sent to a cloud server for AI analysis. Users are instructed to capture images of the exact area and from the appropriate distance.

[0125] Step 3:

[0126] The device transmits the acquired biometric and image data to a storage device in the cloud. The input is the detailed health information acquired in steps 1 and 2. The server analyzes this data using a generating AI model to diagnose the health status. The output is text data generated as the diagnosis result, which is sent to the device. The server uses this to analyze the user's health patterns and identify potential problems.

[0127] Step 4:

[0128] The server searches for nearby medical facilities based on the diagnostic results. Inputs include the user's location and diagnostic results. It uses a map database to filter facility information and determine the most suitable facility. Outputs include a list of facilities and recommended appointment times, which are sent to the terminal. The server monitors available slots in real time and displays the best option.

[0129] Step 5:

[0130] The terminal displays the diagnostic results and facility information to the user and prompts them to select an appointment. The input consists of data from steps 3 and 4. The user completes the appointment process by approving it within the application. The output is saved on the user's terminal as an appointment confirmation. The terminal streamlines this process and minimizes response time.

[0131] Step 6:

[0132] The server performs electronic payment processing after the consultation is completed. Inputs include details of the actual medical services and cost information. It integrates with the payment platform to ensure secure settlement. Outputs include a payment completion notification and corresponding point accrual information, which are sent to the user. This ensures fast and secure transactions.

[0133] Step 7:

[0134] Users check their awarded points and prepare for their next use. Input is the point balance information displayed in the application. Output is the updated user profile, which will be used as a future incentive. The terminal manages the rewards earned by the user and helps encourage usage.

[0135] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0136] This invention provides a health management system that incorporates emotion recognition capabilities to offer personalized medical services that take into account the user's mental state. In this system, the user launches an application using a smartphone and measures biometric information. Specifically, blood pressure, heart rate, and body temperature are acquired using a dedicated measuring device. Additionally, images of the affected area are taken using the smartphone's camera function as needed.

[0137] The device transmits this biometric and image data to a server in the cloud. The server analyzes the received data using an AI module to diagnose the user's health condition. Based on this diagnosis, appropriate prescription information is generated and provided to the user.

[0138] The system's key feature, the emotion engine, identifies the user's emotional state by analyzing their voice, facial expressions, and text input. This emotional information is evaluated along with health checkup results, and medical information and advice reflecting the user's emotional state are generated.

[0139] For example, the system suggests relaxation techniques to alleviate stress reported by the user, and adjusts the dosage and type of medication according to their emotional state. It also considers the impact of emotions on health and searches for and schedules appointments at the most suitable medical facilities. Furthermore, emotional information influences the payment process for consultation fees and is used to provide financial incentives to reduce the user's mental burden. This makes it easier for users to manage not only their physical health but also their mental health.

[0140] For example, if a user is experiencing cold symptoms and high stress levels, the app will provide a prescription for cold medicine along with advice on stress reduction. Furthermore, it has a feature that prioritizes booking appointments at medical institutions that offer stress management support services. In this way, the system can provide medical services optimized for each user.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The user launches the application on their smartphone. The application displays a screen prompting the user to begin collecting biometric and emotional data.

[0144] Step 2:

[0145] The user uses a dedicated measuring device to measure blood pressure, heart rate, and body temperature. They also take images of the affected area with their smartphone camera as needed.

[0146] Step 3:

[0147] The device transmits the measured biometric information and image data to a server in the cloud. At the same time, it also records emotional data using the user's voice input, text input, and facial recognition function.

[0148] Step 4:

[0149] The server uses an AI module to analyze the received biometric and image data and diagnose the user's health status. Simultaneously, an emotion engine analyzes emotional data to recognize the user's emotional state.

[0150] Step 5:

[0151] The server generates appropriate prescription information and advice based on health check results and emotion analysis results. If necessary, it also includes recommendations for treatment methods tailored to the emotional state.

[0152] Step 6:

[0153] The server uses the user's location information to search for nearby medical facilities. Considering the user's health and emotional state, it selects the most suitable medical institution and makes an appointment.

[0154] Step 7:

[0155] The device notifies the user of diagnostic results, prescription information, and medical facility appointment information. In addition, it provides emotionally-based relaxation methods and related information.

[0156] Step 8:

[0157] After receiving medical services, users pay for the consultation fee through their device. The server uses insurance information to automatically process the medical expense settlement and awards points or digital currency based on the user's emotional state.

[0158] Step 9:

[0159] The terminal notifies the user that the payment process is complete and provides information on how to use points and digital currency.

[0160] (Example 2)

[0161] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0162] In recent years, there has been a growing need for personalized medical services that comprehensively consider both biological information and emotional states in healthcare management. However, conventional systems have struggled to manage users' physical and mental health in an integrated manner. Therefore, there is a demand for systems that enable comprehensive health management, including emotional information.

[0163] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0164] In this invention, the server includes means for collecting physical data using a device for acquiring biometric information, means for using an emotion analysis engine to identify the user's emotional state, and means for generating medical information based on the diagnostic results and searching for and booking appropriate medical facilities. This makes it possible to comprehensively manage the user's physical and mental health and provide personalized medical services.

[0165] "Biometric information" refers to data that quantifies the user's physical condition, including information such as blood pressure, heart rate, and body temperature.

[0166] An "image capture device" is a device used to photograph parts of a user's body, and includes the camera function of a smartphone.

[0167] "Cloud storage" refers to data storage areas accessible via the internet, used for data analysis and storage.

[0168] "Analysis methods using artificial intelligence" refer to technologies that analyze data acquired using machine learning algorithms to evaluate and diagnose the user's health status.

[0169] "Means for generating medical information" refers to a function that creates individualized medical advice and prescription information for users based on analysis results.

[0170] An "emotion analysis engine" is a technology that analyzes voice, images, and text to identify a user's emotional state and use it for health management.

[0171] "Means of medical fee payment and value-added provision" refers to functions that facilitate payment for medical services and provide additional services such as incentives to reduce the user's mental burden.

[0172] "A means of searching for and booking the optimal medical facility" refers to a function that finds the most suitable medical institution based on the user's health condition and allows them to book an appointment for an available date and time.

[0173] Users launch a dedicated health management application using a smartphone or other device. The application utilizes measuring devices connected via Bluetooth or Wi-Fi to acquire the user's biometric information, such as blood pressure, heart rate, and body temperature. Users can also use their smartphone's camera function to take images of areas of their body they are concerned about, as needed.

[0174] The device transmits the acquired biometric and image data to a server in the cloud. During this process, the data is encrypted using the SSL / TLS protocol for secure transmission. The server analyzes the received data using an artificial intelligence module to diagnose the user's health status. Specifically, it uses machine learning algorithms to analyze the data and compare it with past data in a database to understand health trends.

[0175] Furthermore, the emotion analysis engine installed on the server analyzes the user's voice, facial expressions, and written text to identify their emotional state. This emotional information is integrated with health checkup results to generate medical information and advice that takes the user's mental state into account.

[0176] For example, if a user experiences cold symptoms and reports high stress levels, the system will provide information on cold medicine prescriptions and advice on relaxation techniques to reduce stress. It can also prioritize booking appointments at medical facilities that offer stress management support services.

[0177] This allows users to receive support in both physical and mental health. An example of input to the generating AI model is the prompt, "Suggest the most suitable medical services based on the health and emotional state reported by the user." In this way, the system enables the provision of personalized medical services.

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The user launches a health management application using their smartphone. The application acquires biometric information such as blood pressure, heart rate, and body temperature from a measuring device connected via Bluetooth or Wi-Fi. The input at this time is the biometric information collected by the measuring device, and the application outputs this data by converting it into a digital format and saving it.

[0181] Step 2:

[0182] The user uses their smartphone's camera function to take images of the desired body parts. The input is the image data captured by the camera, and the application converts this data into an appropriate format and outputs it in a state ready for transmission to the cloud.

[0183] Step 3:

[0184] The device transmits the acquired biometric and image data to a server in the cloud. The input is the biometric and image data acquired in the previous step, and the output is securely encrypted transmission data. The data is encrypted using the SSL / TLS protocol and sent to the server.

[0185] Step 4:

[0186] The server analyzes the received data using an artificial intelligence module. The input consists of biometric information and image data sent from the terminal, which the AI ​​module analyzes using a machine learning algorithm to generate output that diagnoses the user's health status.

[0187] Step 5:

[0188] The emotion analysis engine on the server analyzes the user's voice data and facial expressions. The input consists of voice and facial information provided by the user, and the emotion analysis engine uses algorithms to analyze this data and produce an output that identifies the user's emotional state.

[0189] Step 6:

[0190] The server combines health check results and emotional information based on the analysis results to generate personalized medical advice. The input is the health check results and emotional analysis results generated by the AI, and the output is advice on medical information and relaxation methods that are suitable for the user.

[0191] Step 7:

[0192] The server sends the generated medical information and advice to the user's terminal. The input is the information generated by the server, which the terminal receives and displays as output to the user. Based on this information, the user can decide on the appropriate course of action.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] Traditional health management systems have focused primarily on assessing users' physical health, neglecting emotional and mental well-being. As a result, providing optimal medical services tailored to each user has been difficult, and flexible payment processes based on mental state-based incentives have been impossible. Furthermore, there is a growing need to reflect users' emotional states in medical services to facilitate more appropriate appointment scheduling at suitable medical facilities and to adjust prescriptions to address emotional distress.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes means for acquiring biometric information using a measuring device, means for identifying the user's emotional state using an emotion recognition function and reflecting it in the health assessment, and means for generating medical recommendations tailored based on the diagnostic results and emotional information. This makes it possible to comprehensively manage the user's physical and mental health and optimize medical services and payment processes.

[0198] A "measurement device" is a device used to acquire biometric information and accurately measure the user's physical condition.

[0199] A "video recording device" is a device used to acquire images of body parts and is equipment used to record visual data.

[0200] An "information processing device" is an electronic system that analyzes acquired data and processes information, and often operates on the cloud.

[0201] "Artificial intelligence" is a technology that uses computers to imitate human intellectual behavior, and is particularly used for analyzing data.

[0202] "Emotion recognition functionality" is a technology that identifies a user's emotional state from their voice, facial expressions, and text input.

[0203] "Local information" refers to location-based information, including data related to a specific place.

[0204] An "incentive" is added value provided to encourage a particular behavior, and refers to monetary or non-monetary rewards for the user.

[0205] The system for implementing this invention allows users to comprehensively manage their health status. Users can launch an application using their smartphone and acquire biometric information using a device. This device includes a blood pressure monitor, heart rate monitor, thermometer, etc. Image data obtained by a video recording device and biometric information are transmitted from the terminal to an information processing device in the cloud.

[0206] The information processing device uses artificial intelligence to analyze the received data. This analysis is characterized by its ability to evaluate the user's emotional state using biometric information and emotion recognition functions. Based on the analysis results, optimal medical suggestions and adjustments are made and provided to the user.

[0207] Furthermore, the system can utilize local information to search for the nearest medical institution and assist users in making appointments. In addition, it enhances the user experience by providing incentives based on the user's emotional state when paying for consultations.

[0208] For example, if a user reports cold symptoms and high stress levels are detected simultaneously, the system will provide advice on stress reduction in addition to prescribing cold medicine. It can also prioritize appointments at appropriate medical facilities and offer a payment process with incentives to alleviate mental stress.

[0209] An example of an input prompt for a generative AI model would be: "Based on the user's emotional and health data, propose available medical services and corresponding payment incentives."

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The user launches a dedicated application on their smartphone and acquires biometric information using measuring devices such as blood pressure monitors and heart rate monitors. Inputs include blood pressure, heart rate, and body temperature, and this biometric information is transmitted to the smartphone in real time. Outputs are data related to the user's physical condition.

[0213] Step 2:

[0214] The user uses their smartphone's video recording function to acquire images of body parts as needed. These images are stored within the application and sent to an information processing device in the cloud. The input is the image of the target body part, and the output is the transmitted image data.

[0215] Step 3:

[0216] The server uses artificial intelligence to analyze biometric and image data received on the cloud. The input is the aforementioned biometric and image data; the AI ​​model diagnoses the user's health status and provides a health assessment. The output is the health assessment based on the diagnosis.

[0217] Step 4:

[0218] The server uses emotion recognition to analyze the user's voice and facial expression data and identify their emotional state. The input is the user's voice and facial expression data, and the output is the identified emotional state. This data is integrated into the diagnostic results.

[0219] Step 5:

[0220] The server generates optimal medical recommendations and an incentivized payment process for the user based on diagnostic results and emotional information. It generates the prompt message, "Based on the user's emotional and health data, suggest available medical services and corresponding payment incentives." Based on this prompt message, the AI ​​determines the prescription and incentives and notifies the user. The input is health assessment and emotional state, and the output is medical recommendations and payment incentives.

[0221] Step 6:

[0222] Based on the medical suggestions provided, users book appointments at medical facilities located within the system. The input is a list of the most suitable medical facilities, and the output is a booking confirmation notice. At the time of payment, incentives are applied based on the user's emotional state.

[0223] Step 7:

[0224] After a user's consultation is complete, payment is automatically processed based on their insurance and payment information, and a completion notification is sent to the user. Inputs are insurance information and payment data, while outputs are the payment result and payment completion notification. This allows users to manage their physical and mental health in a unified manner.

[0225] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0226] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0227] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0228] [Second Embodiment]

[0229] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0230] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0231] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0232] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0233] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0234] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0235] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0236] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0237] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0238] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0239] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0240] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0241] This invention is a system that uses a smartphone to diagnose a user's health condition and provide medical services. This system uses the user's smartphone, which they use daily, to measure biometric information and take images of affected areas. Specifically, the user launches an application and acquires biometric information such as blood pressure, heart rate, and body temperature using a dedicated measuring device. Furthermore, if there is an injury or skin abnormality, images of that area are also taken. This allows the user to collect necessary health data from the comfort of their home.

[0242] The device sends the collected data to a server in the cloud, which uses artificial intelligence to analyze the received data. In this analysis process, the AI ​​identifies data patterns and diagnoses potential health problems. Based on the diagnosis, it also generates prescription information, including suggestions for necessary medications and treatments. This prescription information is immediately sent to the user's device.

[0243] Furthermore, the server utilizes the user's location information to search for nearby medical facilities and schedule appointments. Users can review their diagnosis and suggested medical facilities from their homes and complete the appointment process using the system. The system also uses health insurance information to automatically process payment for consultations. During this process, users are rewarded with points or digital currency as a way to encourage usage.

[0244] For example, if a user experiences cold symptoms, the app measures their body temperature and heart rate and sends this data to a server. The server processes the data and notifies the user of the possibility of a cold and information about over-the-counter medications available at nearby pharmacies. Furthermore, it simultaneously makes a hospital appointment and, if necessary, secures a time slot for a consultation.

[0245] In this way, the present invention provides a system that enables users to easily and quickly manage their health status and receive appropriate medical services at home.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user launches the application on their smartphone. The application displays a screen prompting the user to prepare for biometric data measurement.

[0249] Step 2:

[0250] Using the device, the user obtains blood pressure, heart rate, and body temperature using a dedicated measuring device. The app also instructs the user to take images of the affected area with the camera.

[0251] Step 3:

[0252] The device transmits the measured biometric information and captured image data to a server in the cloud via encrypted communication.

[0253] Step 4:

[0254] The server passes the received data to an AI module for analysis. The AI ​​analyzes the biometric data, detects abnormal values, and diagnoses the user's health status.

[0255] Step 5:

[0256] Based on the diagnostic results, the server generates prescription information, including details about necessary medications and treatments. This information is then returned to the user's terminal.

[0257] Step 6:

[0258] The server retrieves the user's current location and searches a database for nearby medical facilities. It then selects the most suitable medical facility and accesses the reservation system.

[0259] Step 7:

[0260] The server generates reservation information and notifies the user of the result of making an appointment at the nearest medical facility. Reservation details are sent to the user's device.

[0261] Step 8:

[0262] The terminal provides users with an interface that centrally displays diagnostic results, prescription information, and appointment information, and sends notifications prompting them to take necessary actions.

[0263] Step 9:

[0264] When a user receives medical treatment and pays the consultation fee, they enter payment information through a terminal. The server then automatically processes the medical expense settlement using the insurance information.

[0265] Step 10:

[0266] After payment is completed, the server will award the user additional points or digital currency to encourage continued use. This information will be notified to the user's device.

[0267] (Example 1)

[0268] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0269] Modern healthcare management requires individuals to monitor their health status on a daily basis and access medical services quickly and appropriately. However, traditional methods involve cumbersome processes such as obtaining individual biometric information, making appointments with medical institutions, and settling medical fees, making it difficult to provide consistent services. There is a need to solve these problems and provide a system that allows users to more easily manage their health and access medical care from home or other convenient locations.

[0270] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0271] In this invention, the server includes means for analyzing biometric data acquired using a generative AI model to determine the user's health status, means for generating prescription instructions based on the determination results, and means for searching for nearby medical institutions and making reservations using the user's location data. This enables users to efficiently acquire biometric data from the comfort of their homes, receive appropriate diagnoses and make reservations at medical institutions, and improves the convenience of medical services.

[0272] A "measuring device" is a device used to acquire biological data, and is a device that has the function of measuring the user's blood pressure, heart rate, body temperature, etc.

[0273] An "image acquisition device" is a device used to acquire images of specific parts of a user's body, and typically has the function of taking high-resolution images using a camera.

[0274] "Cloud storage" refers to data storage accessible via the internet, and is a device used to securely store and manage acquired biometric and image data.

[0275] A "generative AI model" is a machine learning model based on a large amount of historical data, and is a program that analyzes a user's health status and performs pattern recognition.

[0276] "Analysis means" refers to the functions of a system that analyzes acquired data and performs a series of processes to determine a person's health status.

[0277] A "means for generating prescription instructions" refers to a function that suggests appropriate medications and treatments to the user based on the assessment of their health condition.

[0278] "Location data" refers to information indicating a user's geographical location, and is digital information obtained through GPS or other location measurement technologies.

[0279] The "means of searching for medical facilities and making reservations" refers to a function that uses the user's location data to search for nearby medical facilities and automatically completes the necessary reservation procedures.

[0280] "Medical expense settlement" refers to the process of calculating and settling the charges for medical services based on the user's insurance information, etc.

[0281] "Digital currency" is a form of currency that can be traded electronically and includes points and credits provided as incentives to users.

[0282] This invention is a system that enables users to routinely monitor their health status and receive appropriate medical services. This system combines a measuring device, an image acquisition device, a generated AI model, and a storage device on the cloud to efficiently manage users' health.

[0283] First, the user uses a smart device to launch a healthcare application and acquires biometric data such as blood pressure, heart rate, and body temperature with a measuring device. Also, an image of the affected area or a concerning part is taken with an image acquisition device. This smart device is equipped with Bluetooth and Wi-Fi connection functions and can easily synchronize data with the measuring device.

[0284] The acquired biometric data and image data are transmitted from the terminal to a storage device on the cloud. The server analyzes the data using the generated AI model here. This AI model is machine-learned based on a large amount of past data and determines the health status through pattern recognition. Based on the analysis results of the AI model, the server points out specific health risks and generates necessary prescription instructions.

[0285] After that, the server uses the user's location data to search for the nearest appropriate medical institution. It has a function to check the availability of the facility in real time and execute the reservation desired by the user. This reservation information is immediately transmitted to the user's smart device.

[0286] Furthermore, the system has a function to settle medical expenses and automatically performs settlement processing based on the insurance data registered by the user. After settlement, digital currency or points are given to the user as an incentive.

[0287] As a concrete example, when a user experiences the initial symptoms of a cold, they launch the app, measure their body temperature and heart rate, and send this data to the cloud. The server diagnoses the possibility of a cold and provides the user with recommendations for over-the-counter medications, along with the option to book an appointment at a nearby clinic. In this way, users can quickly manage their health from home and access medical services as needed.

[0288] Examples of prompt messages include, "Your body temperature is elevated; please provide a detailed diagnosis," and "You have a skin abnormality; please send an image for evaluation."

[0289] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0290] Step 1:

[0291] The user launches a healthcare application on their smart device. Through the application's interface, they input instructions to send to the measuring device for measuring blood pressure, heart rate, and body temperature. The measuring device acquires this biometric data and transmits it to the device. The user's specific actions involve attaching the device to their fingertip or arm and waiting for the measurement results to be displayed.

[0292] Step 2:

[0293] The terminal encrypts the acquired biometric data and sends it to a server in the cloud along with images of the affected area taken using an image acquisition device. The input for this step is biometric data and image data, and these are sent to the server as output. Specifically, the terminal transmits and receives data between the device and the measuring device via Bluetooth or Wi-Fi.

[0294] Step 3:

[0295] The server uses a cloud-based AI model to analyze the received data. In this analysis process, the server supplies biometric and image data as input to the AI ​​model and generates health status diagnostic results as output. Specifically, the AI ​​model uses pattern recognition technology to detect anomalies and assess health risks.

[0296] Step 4:

[0297] The server generates necessary prescription instructions based on the diagnostic results and sends them to the user's terminal. The input for this step is the AI-generated diagnostic results, and the output is prescription information in a user-friendly format. Specifically, the server analyzes the diagnostic results and selects the most suitable medications and treatment options.

[0298] Step 5:

[0299] The server uses the user's location data to obtain current location information as input. It then searches for nearby medical facilities, checks appointment availability, and then makes a reservation, sending the information to the user's device. As output, the user receives a reservation completion message. The server accesses a database of medical facilities and performs reservation operations in real time.

[0300] Step 6:

[0301] The server uses the user's insurance data and treatment details as input to process the settlement of medical expenses. The output is a confirmation of settlement and the awarding of digital currency or points to the user's account. Specifically, the server executes the settlement process through the payment gateway and awards incentives to the user.

[0302] (Application Example 1)

[0303] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0304] Modern health management systems require easy access to health check-ups and automated medical treatments because users need to visit medical facilities and the payment of medical expenses is complicated. In addition, there is a lack of a mechanism to electronically settle the cost of medical treatment and appropriately provide incentives to users. Therefore, it is an issue to improve the convenience of users while promoting the use of medical services.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0306] In this invention, the server includes means for acquiring biological information using a measuring device, means for acquiring an image of a target site using an image acquisition device, processing means using an artificial intelligence connected to a storage device on the cloud, analyzing the acquired information, and diagnosing the state, means for generating initial treatment information based on the diagnosis result, means for searching for surrounding facilities using location information and performing procedures, means for performing electronic settlement and providing additional functions, and means for granting rewards for service use. As a result, users can quickly and easily grasp their health status even at home and receive necessary medical services. In addition, electronic settlement of medical expenses reduces the labor, and it is possible to promote use through points and rewards.

[0307] The "measuring device" is a device used to acquire biological information and has a function of accurately measuring various index data.

[0308] The "image acquisition device" is a device for taking an image of a target site and is a device aimed at recording visual information as digital data.

[0309] The "storage device on the cloud" is an online storage that can store and access data via a network and is a system that enables data organization and storage.

[0310] "Artificial intelligence" is a technology that uses computer programs to mimic human intellectual activity, and is particularly used in data analysis and diagnostic processes.

[0311] "Initial treatment information" refers to information about treatments and therapies suggested based on the results and condition of a health checkup, and is intended to provide users with prompt action plans.

[0312] "Location information" refers to data that indicates the geographical location of a user or device, and is used for searching for nearby facilities and providing directions.

[0313] "Electronic payment" refers to the process of conducting monetary transactions through online systems, and is a technology that completes payments without using banknotes or coins.

[0314] "Additional features" refer to extra functions or services provided in addition to the basic functions, and are elements that enhance the user experience.

[0315] A "reward" is an incentive given for a specific action or use of a service, and it has value in increasing the user's motivation.

[0316] The system that implements this application example operates using the following main components:

[0317] First, the user uses their smartphone to acquire biometric information from a Bluetooth-enabled measuring device. This process uses appropriate sensor devices to accurately collect indicator data such as blood pressure and body temperature. Then, the smartphone's camera function is used to acquire images of the affected area. The acquired data is sent from the smartphone to a server in the cloud.

[0318] The server receives the acquired biometric and image data and stores it in cloud-based storage. Then, it analyzes the data using a generative AI model, and artificial intelligence automatically diagnoses the user's health condition. Based on the diagnosis, the server sends initial treatment information back to the user's device. Here, the AI ​​analyzes past data patterns to suggest the most suitable treatment or procedure for the user.

[0319] Furthermore, the server has a mechanism to obtain location information from the user's device and search for nearby medical facilities. As a necessary procedure, reservations are automated, allowing users to complete facility reservations directly. The server also automatically settles medical fees through electronic payment, and as an additional feature, it awards points or rewards to users based on service usage.

[0320] As a concrete example, when a user experiences cold symptoms, they use a measuring device via the application to obtain their body temperature and heart rate. This data is immediately sent to a server, where AI diagnoses the possibility of a mild infection and provides information on nearby clinics. Simultaneously, an appointment at the clinic is made through the application, and points are added after the consultation.

[0321] An example of a prompt message would be: "Design an app that sends blood pressure and body temperature data measured by the user on their smartphone to a cloud AI, diagnoses their health condition, and settles medical expenses via electronic payment. Also, implement a points system to encourage customer use."

[0322] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0323] Step 1:

[0324] The user launches a smartphone application and acquires biometric information using a Bluetooth-enabled measuring device. The input is biometric data such as blood pressure and body temperature. The device temporarily stores this data and then prepares it for transmission to a cloud server. The output is a data package sent to the cloud. The user verifies the connection between the devices and confirms that the sensors of the measuring device are functioning correctly.

[0325] Step 2:

[0326] The device uses a smartphone camera to capture images of the affected area. The input is the visual data captured through the camera. The images are processed by a dedicated algorithm, and their size and resolution are adjusted to a standard format. The output is an image file sent to a cloud server for AI analysis. Users are instructed to capture images of the exact area and from the appropriate distance.

[0327] Step 3:

[0328] The device transmits the acquired biometric and image data to a storage device in the cloud. The input is the detailed health information acquired in steps 1 and 2. The server analyzes this data using a generating AI model to diagnose the health status. The output is text data generated as the diagnosis result, which is sent to the device. The server uses this to analyze the user's health patterns and identify potential problems.

[0329] Step 4:

[0330] The server searches for nearby medical facilities based on the diagnostic results. Inputs include the user's location and diagnostic results. It uses a map database to filter facility information and determine the most suitable facility. Outputs include a list of facilities and recommended appointment times, which are sent to the terminal. The server monitors available slots in real time and displays the best option.

[0331] Step 5:

[0332] The terminal displays the diagnostic results and facility information to the user and prompts them to select an appointment. The input consists of data from steps 3 and 4. The user completes the appointment process by approving it within the application. The output is saved on the user's terminal as an appointment confirmation. The terminal streamlines this process and minimizes response time.

[0333] Step 6:

[0334] The server performs electronic payment processing after the consultation is completed. Inputs include details of the actual medical services and cost information. It integrates with the payment platform to ensure secure settlement. Outputs include a payment completion notification and corresponding point accrual information, which are sent to the user. This ensures fast and secure transactions.

[0335] Step 7:

[0336] Users check their awarded points and prepare for their next use. Input is the point balance information displayed in the application. Output is the updated user profile, which will be used as a future incentive. The terminal manages the rewards earned by the user and helps encourage usage.

[0337] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0338] This invention provides a health management system that incorporates emotion recognition capabilities to offer personalized medical services that take into account the user's mental state. In this system, the user launches an application using a smartphone and measures biometric information. Specifically, blood pressure, heart rate, and body temperature are acquired using a dedicated measuring device. Additionally, images of the affected area are taken using the smartphone's camera function as needed.

[0339] The device transmits this biometric and image data to a server in the cloud. The server analyzes the received data using an AI module to diagnose the user's health condition. Based on this diagnosis, appropriate prescription information is generated and provided to the user.

[0340] The system's key feature, the emotion engine, identifies the user's emotional state by analyzing their voice, facial expressions, and text input. This emotional information is evaluated along with health checkup results, and medical information and advice reflecting the user's emotional state are generated.

[0341] For example, the system suggests relaxation techniques to alleviate stress reported by the user, and adjusts the dosage and type of medication according to their emotional state. It also considers the impact of emotions on health and searches for and schedules appointments at the most suitable medical facilities. Furthermore, emotional information influences the payment process for consultation fees and is used to provide financial incentives to reduce the user's mental burden. This makes it easier for users to manage not only their physical health but also their mental health.

[0342] For example, if a user is experiencing cold symptoms and high stress levels, the app will provide a prescription for cold medicine along with advice on stress reduction. Furthermore, it has a feature that prioritizes booking appointments at medical institutions that offer stress management support services. In this way, the system can provide medical services optimized for each user.

[0343] The following describes the processing flow.

[0344] Step 1:

[0345] The user launches the application on their smartphone. The application displays a screen prompting the user to begin collecting biometric and emotional data.

[0346] Step 2:

[0347] The user uses a dedicated measuring device to measure blood pressure, heart rate, and body temperature. They also take images of the affected area with their smartphone camera as needed.

[0348] Step 3:

[0349] The device transmits the measured biometric information and image data to a server in the cloud. At the same time, it also records emotional data using the user's voice input, text input, and facial recognition function.

[0350] Step 4:

[0351] The server uses an AI module to analyze the received biometric and image data and diagnose the user's health status. Simultaneously, an emotion engine analyzes emotional data to recognize the user's emotional state.

[0352] Step 5:

[0353] The server generates appropriate prescription information and advice based on health check results and emotion analysis results. If necessary, it also includes recommendations for treatment methods tailored to the emotional state.

[0354] Step 6:

[0355] The server uses the user's location information to search for nearby medical facilities. Considering the user's health and emotional state, it selects the most suitable medical institution and makes an appointment.

[0356] Step 7:

[0357] The device notifies the user of diagnostic results, prescription information, and medical facility appointment information. In addition, it provides emotionally-based relaxation methods and related information.

[0358] Step 8:

[0359] After receiving medical services, users pay for the consultation fee through their device. The server uses insurance information to automatically process the medical expense settlement and awards points or digital currency based on the user's emotional state.

[0360] Step 9:

[0361] The terminal notifies the user that the payment process is complete and provides information on how to use points and digital currency.

[0362] (Example 2)

[0363] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0364] In recent years, there has been a growing need for personalized medical services that comprehensively consider both biological information and emotional states in healthcare management. However, conventional systems have struggled to manage users' physical and mental health in an integrated manner. Therefore, there is a demand for systems that enable comprehensive health management, including emotional information.

[0365] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0366] In this invention, the server includes means for collecting physical data using a device for acquiring biometric information, means for using an emotion analysis engine to identify the user's emotional state, and means for generating medical information based on the diagnostic results and searching for and booking appropriate medical facilities. This makes it possible to comprehensively manage the user's physical and mental health and provide personalized medical services.

[0367] "Biometric information" refers to data that quantifies the user's physical condition, including information such as blood pressure, heart rate, and body temperature.

[0368] An "image capture device" is a device used to photograph parts of a user's body, and includes the camera function of a smartphone.

[0369] "Cloud storage" refers to data storage areas accessible via the internet, used for data analysis and storage.

[0370] "Analysis methods using artificial intelligence" refer to technologies that analyze data acquired using machine learning algorithms to evaluate and diagnose the user's health status.

[0371] "Means for generating medical information" refers to a function that creates individualized medical advice and prescription information for users based on analysis results.

[0372] An "emotion analysis engine" is a technology that analyzes voice, images, and text to identify a user's emotional state and use it for health management.

[0373] "Means of medical fee payment and value-added provision" refers to functions that facilitate payment for medical services and provide additional services such as incentives to reduce the user's mental burden.

[0374] "A means of searching for and booking the optimal medical facility" refers to a function that finds the most suitable medical institution based on the user's health condition and allows them to book an appointment for an available date and time.

[0375] Users launch a dedicated health management application using a smartphone or other device. The application utilizes measuring devices connected via Bluetooth or Wi-Fi to acquire the user's biometric information, such as blood pressure, heart rate, and body temperature. Users can also use their smartphone's camera function to take images of areas of their body they are concerned about, as needed.

[0376] The device transmits the acquired biometric and image data to a server in the cloud. During this process, the data is encrypted using the SSL / TLS protocol for secure transmission. The server analyzes the received data using an artificial intelligence module to diagnose the user's health status. Specifically, it uses machine learning algorithms to analyze the data and compare it with past data in a database to understand health trends.

[0377] Furthermore, the emotion analysis engine installed on the server analyzes the user's voice, facial expressions, and written text to identify their emotional state. This emotional information is integrated with health checkup results to generate medical information and advice that takes the user's mental state into account.

[0378] For example, if a user experiences cold symptoms and reports high stress levels, the system will provide information on cold medicine prescriptions and advice on relaxation techniques to reduce stress. It can also prioritize booking appointments at medical facilities that offer stress management support services.

[0379] This allows users to receive support in both physical and mental health. An example of input to the generating AI model is the prompt, "Suggest the most suitable medical services based on the health and emotional state reported by the user." In this way, the system enables the provision of personalized medical services.

[0380] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0381] Step 1:

[0382] The user launches a health management application using their smartphone. The application acquires biometric information such as blood pressure, heart rate, and body temperature from a measuring device connected via Bluetooth or Wi-Fi. The input at this time is the biometric information collected by the measuring device, and the application outputs this data by converting it into a digital format and saving it.

[0383] Step 2:

[0384] The user uses their smartphone's camera function to take images of the desired body parts. The input is the image data captured by the camera, and the application converts this data into an appropriate format and outputs it in a state ready for transmission to the cloud.

[0385] Step 3:

[0386] The device transmits the acquired biometric and image data to a server in the cloud. The input is the biometric and image data acquired in the previous step, and the output is securely encrypted transmission data. The data is encrypted using the SSL / TLS protocol and sent to the server.

[0387] Step 4:

[0388] The server analyzes the received data using an artificial intelligence module. The input consists of biometric information and image data sent from the terminal, which the AI ​​module analyzes using a machine learning algorithm to generate output that diagnoses the user's health status.

[0389] Step 5:

[0390] The emotion analysis engine on the server analyzes the user's voice data and facial expressions. The input consists of voice and facial information provided by the user, and the emotion analysis engine uses algorithms to analyze this data and produce an output that identifies the user's emotional state.

[0391] Step 6:

[0392] The server combines health check results and emotional information based on the analysis results to generate personalized medical advice. The input is the health check results and emotional analysis results generated by the AI, and the output is advice on medical information and relaxation methods that are suitable for the user.

[0393] Step 7:

[0394] The server sends the generated medical information and advice to the user's terminal. The input is the information generated by the server, which the terminal receives and displays as output to the user. Based on this information, the user can decide on the appropriate course of action.

[0395] (Application Example 2)

[0396] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0397] Traditional health management systems have focused primarily on assessing users' physical health, neglecting emotional and mental well-being. As a result, providing optimal medical services tailored to each user has been difficult, and flexible payment processes based on mental state-based incentives have been impossible. Furthermore, there is a growing need to reflect users' emotional states in medical services to facilitate more appropriate appointment scheduling at suitable medical facilities and to adjust prescriptions to address emotional distress.

[0398] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0399] In this invention, the server includes means for acquiring biometric information using a measuring device, means for identifying the user's emotional state using an emotion recognition function and reflecting it in the health assessment, and means for generating medical recommendations tailored based on the diagnostic results and emotional information. This makes it possible to comprehensively manage the user's physical and mental health and optimize medical services and payment processes.

[0400] A "measurement device" is a device used to acquire biometric information and accurately measure the user's physical condition.

[0401] A "video recording device" is a device used to acquire images of body parts and is equipment used to record visual data.

[0402] An "information processing device" is an electronic system that analyzes acquired data and processes information, and often operates on the cloud.

[0403] "Artificial intelligence" is a technology that uses computers to imitate human intellectual behavior, and is particularly used for analyzing data.

[0404] "Emotion recognition functionality" is a technology that identifies a user's emotional state from their voice, facial expressions, and text input.

[0405] "Local information" refers to location-based information, including data related to a specific place.

[0406] An "incentive" is added value provided to encourage a particular behavior, and refers to monetary or non-monetary rewards for the user.

[0407] The system for implementing this invention allows users to comprehensively manage their health status. Users can launch an application using their smartphone and acquire biometric information using a device. This device includes a blood pressure monitor, heart rate monitor, thermometer, etc. Image data obtained by a video recording device and biometric information are transmitted from the terminal to an information processing device in the cloud.

[0408] The information processing device uses artificial intelligence to analyze the received data. This analysis is characterized by its ability to evaluate the user's emotional state using biometric information and emotion recognition functions. Based on the analysis results, optimal medical suggestions and adjustments are made and provided to the user.

[0409] Furthermore, the system can utilize local information to search for the nearest medical institution and assist users in making appointments. In addition, it enhances the user experience by providing incentives based on the user's emotional state when paying for consultations.

[0410] For example, if a user reports cold symptoms and high stress levels are detected simultaneously, the system will provide advice on stress reduction in addition to prescribing cold medicine. It can also prioritize appointments at appropriate medical facilities and offer a payment process with incentives to alleviate mental stress.

[0411] An example of an input prompt for a generative AI model would be: "Based on the user's emotional and health data, propose available medical services and corresponding payment incentives."

[0412] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0413] Step 1:

[0414] The user launches a dedicated application on their smartphone and acquires biometric information using measuring devices such as blood pressure monitors and heart rate monitors. Inputs include blood pressure, heart rate, and body temperature, and this biometric information is transmitted to the smartphone in real time. Outputs are data related to the user's physical condition.

[0415] Step 2:

[0416] The user uses their smartphone's video recording function to acquire images of body parts as needed. These images are stored within the application and sent to an information processing device in the cloud. The input is the image of the target body part, and the output is the transmitted image data.

[0417] Step 3:

[0418] The server uses artificial intelligence to analyze biometric and image data received on the cloud. The input is the aforementioned biometric and image data; the AI ​​model diagnoses the user's health status and provides a health assessment. The output is the health assessment based on the diagnosis.

[0419] Step 4:

[0420] The server uses emotion recognition to analyze the user's voice and facial expression data and identify their emotional state. The input is the user's voice and facial expression data, and the output is the identified emotional state. This data is integrated into the diagnostic results.

[0421] Step 5:

[0422] The server generates optimal medical recommendations and an incentivized payment process for the user based on diagnostic results and emotional information. It generates the prompt message, "Based on the user's emotional and health data, suggest available medical services and corresponding payment incentives." Based on this prompt message, the AI ​​determines the prescription and incentives and notifies the user. The input is health assessment and emotional state, and the output is medical recommendations and payment incentives.

[0423] Step 6:

[0424] Based on the medical suggestions provided, users book appointments at medical facilities located within the system. The input is a list of the most suitable medical facilities, and the output is a booking confirmation notice. At the time of payment, incentives are applied based on the user's emotional state.

[0425] Step 7:

[0426] After a user's consultation is complete, payment is automatically processed based on their insurance and payment information, and a completion notification is sent to the user. Inputs are insurance information and payment data, while outputs are the payment result and payment completion notification. This allows users to manage their physical and mental health in a unified manner.

[0427] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0428] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0429] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0430] [Third Embodiment]

[0431] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0432] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0433] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0434] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0435] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0436] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0437] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0438] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0439] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0440] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0441] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0442] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0443] This invention is a system that uses a smartphone to diagnose a user's health condition and provide medical services. This system uses the user's smartphone, which they use daily, to measure biometric information and take images of affected areas. Specifically, the user launches an application and acquires biometric information such as blood pressure, heart rate, and body temperature using a dedicated measuring device. Furthermore, if there is an injury or skin abnormality, images of that area are also taken. This allows the user to collect necessary health data from the comfort of their home.

[0444] The device sends the collected data to a server in the cloud, which uses artificial intelligence to analyze the received data. In this analysis process, the AI ​​identifies data patterns and diagnoses potential health problems. Based on the diagnosis, it also generates prescription information, including suggestions for necessary medications and treatments. This prescription information is immediately sent to the user's device.

[0445] Furthermore, the server utilizes the user's location information to search for nearby medical facilities and schedule appointments. Users can review their diagnosis and suggested medical facilities from their homes and complete the appointment process using the system. The system also uses health insurance information to automatically process payment for consultations. During this process, users are rewarded with points or digital currency as a way to encourage usage.

[0446] For example, if a user experiences cold symptoms, the app measures their body temperature and heart rate and sends this data to a server. The server processes the data and notifies the user of the possibility of a cold and information about over-the-counter medications available at nearby pharmacies. Furthermore, it simultaneously makes a hospital appointment and, if necessary, secures a time slot for a consultation.

[0447] In this way, the present invention provides a system that enables users to easily and quickly manage their health status and receive appropriate medical services at home.

[0448] The following describes the processing flow.

[0449] Step 1:

[0450] The user launches the application on their smartphone. The application displays a screen prompting the user to prepare for biometric data measurement.

[0451] Step 2:

[0452] Using the device, the user obtains blood pressure, heart rate, and body temperature using a dedicated measuring device. The app also instructs the user to take images of the affected area with the camera.

[0453] Step 3:

[0454] The device transmits the measured biometric information and captured image data to a server in the cloud via encrypted communication.

[0455] Step 4:

[0456] The server passes the received data to an AI module for analysis. The AI ​​analyzes the biometric data, detects abnormal values, and diagnoses the user's health status.

[0457] Step 5:

[0458] Based on the diagnostic results, the server generates prescription information, including details about necessary medications and treatments. This information is then returned to the user's terminal.

[0459] Step 6:

[0460] The server retrieves the user's current location and searches a database for nearby medical facilities. It then selects the most suitable medical facility and accesses the reservation system.

[0461] Step 7:

[0462] The server generates reservation information and notifies the user of the result of making an appointment at the nearest medical facility. Reservation details are sent to the user's device.

[0463] Step 8:

[0464] The terminal provides users with an interface that centrally displays diagnostic results, prescription information, and appointment information, and sends notifications prompting them to take necessary actions.

[0465] Step 9:

[0466] When a user receives medical treatment and pays the consultation fee, they enter payment information through a terminal. The server then automatically processes the medical expense settlement using the insurance information.

[0467] Step 10:

[0468] After payment is completed, the server will award the user additional points or digital currency to encourage continued use. This information will be notified to the user's device.

[0469] (Example 1)

[0470] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0471] Modern healthcare management requires individuals to monitor their health status on a daily basis and access medical services quickly and appropriately. However, traditional methods involve cumbersome processes such as obtaining individual biometric information, making appointments with medical institutions, and settling medical fees, making it difficult to provide consistent services. There is a need to solve these problems and provide a system that allows users to more easily manage their health and access medical care from home or other convenient locations.

[0472] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0473] In this invention, the server includes means for analyzing biometric data acquired using a generative AI model to determine the user's health status, means for generating prescription instructions based on the determination results, and means for searching for nearby medical institutions and making reservations using the user's location data. This enables users to efficiently acquire biometric data from the comfort of their homes, receive appropriate diagnoses and make reservations at medical institutions, and improves the convenience of medical services.

[0474] A "measuring device" is a device used to acquire biological data, and is a device that has the function of measuring the user's blood pressure, heart rate, body temperature, etc.

[0475] An "image acquisition device" is a device used to acquire images of specific parts of a user's body, and typically has the function of taking high-resolution images using a camera.

[0476] "Cloud storage" refers to data storage accessible via the internet, and is a device used to securely store and manage acquired biometric and image data.

[0477] A "generative AI model" is a machine learning model based on a large amount of historical data, and is a program that analyzes a user's health status and performs pattern recognition.

[0478] "Analysis means" refers to the functions of a system that analyzes acquired data and performs a series of processes to determine a person's health status.

[0479] A "means for generating prescription instructions" refers to a function that suggests appropriate medications and treatments to the user based on the assessment of their health condition.

[0480] "Location data" refers to information indicating a user's geographical location, and is digital information obtained through GPS or other location measurement technologies.

[0481] The "means of searching for medical facilities and making reservations" refers to a function that uses the user's location data to search for nearby medical facilities and automatically completes the necessary reservation procedures.

[0482] "Medical expense settlement" refers to the process of calculating and settling the charges for medical services based on the user's insurance information, etc.

[0483] "Digital currency" refers to a form of currency that can be traded electronically, including points and credits offered as incentives to users.

[0484] This invention is a system that enables users to monitor their health status on a daily basis and receive appropriate medical services. This system efficiently manages the user's health by combining a measuring device, an image acquisition device, a generative AI model, and a cloud-based storage device.

[0485] First, the user launches a healthcare application using a smart device and acquires biometric data such as blood pressure, heart rate, and body temperature using a measuring device. They also take images of the affected area or other areas of concern using an image acquisition device. This smart device is equipped with Bluetooth and Wi-Fi connectivity, allowing for easy data synchronization with the measuring device.

[0486] The acquired biometric and image data is sent from the device to a cloud-based storage device. The server then uses a generated AI model to analyze the data. This AI model is machine-trained based on a large amount of historical data and determines the health status through pattern recognition. Based on the AI ​​model's analysis results, the server identifies specific health risks and generates necessary prescriptions.

[0487] The server then uses the user's location data to search for the nearest suitable medical facility. It has the ability to check facility availability in real time and make the user's desired reservation. This reservation information is immediately sent to the user's smart device.

[0488] Furthermore, the system includes a medical expense settlement function, automatically processing payments based on the insurance data registered by the user. After settlement, digital currency or points are awarded to the user as an incentive.

[0489] As a concrete example, when a user experiences the initial symptoms of a cold, they launch the app, measure their body temperature and heart rate, and send this data to the cloud. The server diagnoses the possibility of a cold and provides the user with recommendations for over-the-counter medications, along with the option to book an appointment at a nearby clinic. In this way, users can quickly manage their health from home and access medical services as needed.

[0490] Examples of prompt messages include, "Your body temperature is elevated; please provide a detailed diagnosis," and "You have a skin abnormality; please send an image for evaluation."

[0491] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0492] Step 1:

[0493] The user launches a healthcare application on their smart device. Through the application's interface, they input instructions to send to the measuring device for measuring blood pressure, heart rate, and body temperature. The measuring device acquires this biometric data and transmits it to the device. The user's specific actions involve attaching the device to their fingertip or arm and waiting for the measurement results to be displayed.

[0494] Step 2:

[0495] The terminal encrypts the acquired biometric data and sends it to a server in the cloud along with images of the affected area taken using an image acquisition device. The input for this step is biometric data and image data, and these are sent to the server as output. Specifically, the terminal transmits and receives data between the device and the measuring device via Bluetooth or Wi-Fi.

[0496] Step 3:

[0497] The server uses a cloud-based AI model to analyze the received data. In this analysis process, the server supplies biometric and image data as input to the AI ​​model and generates health status diagnostic results as output. Specifically, the AI ​​model uses pattern recognition technology to detect anomalies and assess health risks.

[0498] Step 4:

[0499] The server generates necessary prescription instructions based on the diagnostic results and sends them to the user's terminal. The input for this step is the AI-generated diagnostic results, and the output is prescription information in a user-friendly format. Specifically, the server analyzes the diagnostic results and selects the most suitable medications and treatment options.

[0500] Step 5:

[0501] The server uses the user's location data to obtain current location information as input. It then searches for nearby medical facilities, checks appointment availability, and then makes a reservation, sending the information to the user's device. As output, the user receives a reservation completion message. The server accesses a database of medical facilities and performs reservation operations in real time.

[0502] Step 6:

[0503] The server uses the user's insurance data and treatment details as input to process the settlement of medical expenses. The output is a confirmation of settlement and the awarding of digital currency or points to the user's account. Specifically, the server executes the settlement process through the payment gateway and awards incentives to the user.

[0504] (Application Example 1)

[0505] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0506] Modern healthcare systems require visits to medical facilities and involve cumbersome payment processes, creating a need for automated and easily accessible health checkups and consultations. Furthermore, there is a lack of mechanisms for electronically settling payments after receiving medical services and providing appropriate incentives to users. Therefore, the challenge lies in improving user convenience while promoting the use of healthcare services.

[0507] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0508] In this invention, the server includes means for acquiring biological information using a measuring device, means for acquiring images of a target area using an image acquisition device, processing means using artificial intelligence connected to a storage device on the cloud to analyze the acquired information and diagnose the condition, means for generating initial treatment information based on the diagnosis results, means for searching for nearby facilities using location information and performing procedures, means for performing electronic payments and providing additional functions, and means for providing rewards for using the service. As a result, users can quickly and easily understand their health status and receive necessary medical services even at home. Furthermore, the electronic settlement of medical expenses reduces hassle, and usage can be promoted through points and rewards.

[0509] A "measuring device" is a device used to acquire biological information and has the function of accurately measuring various indicator data.

[0510] An "image acquisition device" is a device used to capture images of a target area, and its purpose is to record visual information as digital data.

[0511] "Cloud storage" refers to online storage that allows data to be stored and accessed via a network, and is a system that enables data organization and storage.

[0512] "Artificial intelligence" is a technology that uses computer programs to mimic human intellectual activity, and is particularly used in data analysis and diagnostic processes.

[0513] "Initial treatment information" refers to information about treatments and therapies suggested based on the results and condition of a health checkup, and is intended to provide users with prompt action plans.

[0514] "Location information" refers to data that indicates the geographical location of a user or device, and is used for searching for nearby facilities and providing directions.

[0515] "Electronic payment" refers to the process of conducting monetary transactions through online systems, and is a technology that completes payments without using banknotes or coins.

[0516] "Additional features" refer to extra functions or services provided in addition to the basic functions, and are elements that enhance the user experience.

[0517] A "reward" is an incentive given for a specific action or use of a service, and it has value in increasing the user's motivation.

[0518] The system that implements this application example operates using the following main components:

[0519] First, the user uses their smartphone to acquire biometric information from a Bluetooth-enabled measuring device. This process uses appropriate sensor devices to accurately collect indicator data such as blood pressure and body temperature. Then, the smartphone's camera function is used to acquire images of the affected area. The acquired data is transmitted from the smartphone to a server in the cloud.

[0520] The server receives the acquired biometric and image data and stores it in cloud-based storage. Then, it analyzes the data using a generative AI model, and artificial intelligence automatically diagnoses the user's health condition. Based on the diagnosis, the server sends initial treatment information back to the user's device. Here, the AI ​​analyzes past data patterns to suggest the most suitable treatment or procedure for the user.

[0521] Furthermore, the server has a mechanism to obtain location information from the user's device and search for nearby medical facilities. As a necessary procedure, reservations are automated, allowing users to complete facility reservations directly. The server also automatically settles medical fees through electronic payment, and as an additional feature, it awards points or rewards to users based on service usage.

[0522] As a concrete example, when a user experiences cold symptoms, they use a measuring device via the application to obtain their body temperature and heart rate. This data is immediately sent to a server, where AI diagnoses the possibility of a mild infection and provides information on nearby clinics. Simultaneously, an appointment at the clinic is made through the application, and points are added after the consultation.

[0523] An example of a prompt message would be: "Design an app that sends blood pressure and body temperature data measured by the user on their smartphone to a cloud AI, diagnoses their health condition, and settles medical expenses via electronic payment. Also, implement a points system to encourage customer use."

[0524] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0525] Step 1:

[0526] The user launches a smartphone application and acquires biometric information using a Bluetooth-enabled measuring device. The input is biometric data such as blood pressure and body temperature. The device temporarily stores this data and then prepares it for transmission to a cloud server. The output is a data package sent to the cloud. The user verifies the connection between the devices and confirms that the sensors of the measuring device are functioning correctly.

[0527] Step 2:

[0528] The device uses a smartphone camera to capture images of the affected area. The input is the visual data captured through the camera. The images are processed by a dedicated algorithm, and their size and resolution are adjusted to a standard format. The output is an image file sent to a cloud server for AI analysis. Users are instructed to capture images of the exact area and from the appropriate distance.

[0529] Step 3:

[0530] The device transmits the acquired biometric and image data to a storage device in the cloud. The input is the detailed health information acquired in steps 1 and 2. The server analyzes this data using a generating AI model to diagnose the health status. The output is text data generated as the diagnosis result, which is sent to the device. The server uses this to analyze the user's health patterns and identify potential problems.

[0531] Step 4:

[0532] The server searches for nearby medical facilities based on the diagnostic results. Inputs include the user's location and diagnostic results. It uses a map database to filter facility information and determine the most suitable facility. Outputs include a list of facilities and recommended appointment times, which are sent to the terminal. The server monitors available slots in real time and displays the best option.

[0533] Step 5:

[0534] The terminal displays the diagnostic results and facility information to the user and prompts them to select an appointment. The input consists of data from steps 3 and 4. The user completes the appointment process by approving it within the application. The output is saved on the user's terminal as an appointment confirmation. The terminal streamlines this process and minimizes response time.

[0535] Step 6:

[0536] The server performs electronic payment processing after the consultation is completed. Inputs include details of the actual medical services and cost information. It integrates with the payment platform to ensure secure settlement. Outputs include a payment completion notification and corresponding point accrual information, which are sent to the user. This ensures fast and secure transactions.

[0537] Step 7:

[0538] Users check their awarded points and prepare for their next use. Input is the point balance information displayed in the application. Output is the updated user profile, which will be used as a future incentive. The terminal manages the rewards earned by the user and helps encourage usage.

[0539] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0540] This invention provides a health management system that incorporates emotion recognition capabilities to offer personalized medical services that take into account the user's mental state. In this system, the user launches an application using a smartphone and measures biometric information. Specifically, blood pressure, heart rate, and body temperature are acquired using a dedicated measuring device. Additionally, images of the affected area are taken using the smartphone's camera function as needed.

[0541] The device transmits this biometric and image data to a server in the cloud. The server analyzes the received data using an AI module to diagnose the user's health condition. Based on this diagnosis, appropriate prescription information is generated and provided to the user.

[0542] The system's key feature, the emotion engine, identifies the user's emotional state by analyzing their voice, facial expressions, and text input. This emotional information is evaluated along with health checkup results, and medical information and advice reflecting the user's emotional state are generated.

[0543] For example, the system suggests relaxation techniques to alleviate stress reported by the user, and adjusts the dosage and type of medication according to their emotional state. It also considers the impact of emotions on health and searches for and schedules appointments at the most suitable medical facilities. Furthermore, emotional information influences the payment process for consultation fees and is used to provide financial incentives to reduce the user's mental burden. This makes it easier for users to manage not only their physical health but also their mental health.

[0544] For example, if a user is experiencing cold symptoms and high stress levels, the app will provide a prescription for cold medicine along with advice on stress reduction. Furthermore, it has a feature that prioritizes booking appointments at medical institutions that offer stress management support services. In this way, the system can provide medical services optimized for each individual user.

[0545] The following describes the processing flow.

[0546] Step 1:

[0547] The user launches the application on their smartphone. The application displays a screen prompting the user to begin collecting biometric and emotional data.

[0548] Step 2:

[0549] The user uses a dedicated measuring device to measure blood pressure, heart rate, and body temperature. They also take images of the affected area with their smartphone camera as needed.

[0550] Step 3:

[0551] The device transmits the measured biometric information and image data to a server in the cloud. At the same time, it also records emotional data using the user's voice input, text input, and facial recognition function.

[0552] Step 4:

[0553] The server uses an AI module to analyze the received biometric and image data and diagnose the user's health status. Simultaneously, an emotion engine analyzes emotional data to recognize the user's emotional state.

[0554] Step 5:

[0555] The server generates appropriate prescription information and advice based on health check results and emotion analysis results. If necessary, it also includes recommendations for treatment methods tailored to the emotional state.

[0556] Step 6:

[0557] The server uses the user's location information to search for nearby medical facilities. Considering the user's health and emotional state, it selects the most suitable medical institution and makes an appointment.

[0558] Step 7:

[0559] The device notifies the user of diagnostic results, prescription information, and medical facility appointment information. In addition, it provides emotionally-based relaxation methods and related information.

[0560] Step 8:

[0561] After receiving medical services, users pay for the consultation fee through their device. The server uses insurance information to automatically process the medical expense settlement and awards points or digital currency based on the user's emotional state.

[0562] Step 9:

[0563] The terminal notifies the user that the payment process is complete and provides information on how to use points and digital currency.

[0564] (Example 2)

[0565] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0566] In recent years, there has been a growing need for personalized medical services that comprehensively consider both biological information and emotional states in healthcare management. However, conventional systems have struggled to manage users' physical and mental health in an integrated manner. Therefore, there is a demand for systems that enable comprehensive health management, including emotional information.

[0567] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0568] In this invention, the server includes means for collecting physical data using a device for acquiring biometric information, means for using an emotion analysis engine to identify the user's emotional state, and means for generating medical information based on the diagnostic results and searching for and booking appropriate medical facilities. This makes it possible to comprehensively manage the user's physical and mental health and provide personalized medical services.

[0569] "Biometric information" refers to data that quantifies the user's physical condition, including information such as blood pressure, heart rate, and body temperature.

[0570] An "image capture device" is a device used to photograph parts of a user's body, and includes the camera function of a smartphone.

[0571] "Cloud storage" refers to data storage areas accessible via the internet, used for data analysis and storage.

[0572] "Analysis methods using artificial intelligence" refer to technologies that analyze data acquired using machine learning algorithms to evaluate and diagnose the user's health status.

[0573] "Means for generating medical information" refers to a function that creates individualized medical advice and prescription information for users based on analysis results.

[0574] An "emotion analysis engine" is a technology that analyzes voice, images, and text to identify a user's emotional state and use it for health management.

[0575] "Means of medical fee payment and value-added provision" refers to functions that facilitate payment for medical services and provide additional services such as incentives to reduce the user's mental burden.

[0576] "A means of searching for and booking the optimal medical facility" refers to a function that finds the most suitable medical institution based on the user's health condition and allows them to book an appointment for an available date and time.

[0577] Users launch a dedicated health management application using a smartphone or other device. The application utilizes measuring devices connected via Bluetooth or Wi-Fi to acquire the user's biometric information, such as blood pressure, heart rate, and body temperature. Users can also use their smartphone's camera function to take images of areas of their body they are concerned about, as needed.

[0578] The device transmits the acquired biometric and image data to a server in the cloud. During this process, the data is encrypted using the SSL / TLS protocol for secure transmission. The server analyzes the received data using an artificial intelligence module to diagnose the user's health status. Specifically, it uses machine learning algorithms to analyze the data and compare it with past data in a database to understand health trends.

[0579] Furthermore, the emotion analysis engine installed on the server analyzes the user's voice, facial expressions, and written text to identify their emotional state. This emotional information is integrated with health checkup results to generate medical information and advice that takes the user's mental state into account.

[0580] For example, if a user experiences cold symptoms and reports high stress levels, the system will provide information on cold medicine prescriptions and advice on relaxation techniques to reduce stress. It can also prioritize booking appointments at medical facilities that offer stress management support services.

[0581] This allows users to receive support in both physical and mental health. An example of input to the generating AI model is the prompt, "Suggest the most suitable medical services based on the health and emotional state reported by the user." In this way, the system enables the provision of personalized medical services.

[0582] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0583] Step 1:

[0584] The user launches a health management application using their smartphone. The application acquires biometric information such as blood pressure, heart rate, and body temperature from a measuring device connected via Bluetooth or Wi-Fi. The input at this time is the biometric information collected by the measuring device, and the application outputs this data by converting it into a digital format and saving it.

[0585] Step 2:

[0586] The user uses their smartphone's camera function to take images of the desired body parts. The input is the image data captured by the camera, and the application converts this data into an appropriate format and outputs it in a state ready for transmission to the cloud.

[0587] Step 3:

[0588] The device transmits the acquired biometric and image data to a server in the cloud. The input is the biometric and image data acquired in the previous step, and the output is securely encrypted transmission data. The data is encrypted using the SSL / TLS protocol and sent to the server.

[0589] Step 4:

[0590] The server analyzes the received data using an artificial intelligence module. The input consists of biometric information and image data sent from the terminal, which the AI ​​module analyzes using a machine learning algorithm to generate output that diagnoses the user's health status.

[0591] Step 5:

[0592] The emotion analysis engine on the server analyzes the user's voice data and facial expressions. The input consists of voice and facial information provided by the user, and the emotion analysis engine uses algorithms to analyze this data and produce an output that identifies the user's emotional state.

[0593] Step 6:

[0594] The server combines health check results and emotional information based on the analysis results to generate personalized medical advice. The input is the health check results and emotional analysis results generated by the AI, and the output is advice on medical information and relaxation methods that are suitable for the user.

[0595] Step 7:

[0596] The server sends the generated medical information and advice to the user's terminal. The input is the information generated by the server, which the terminal receives and displays as output to the user. Based on this information, the user can decide on the appropriate course of action.

[0597] (Application Example 2)

[0598] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0599] Traditional health management systems have focused primarily on assessing users' physical health, neglecting emotional and mental well-being. As a result, providing optimal medical services tailored to each user has been difficult, and flexible payment processes based on mental state-based incentives have been impossible. Furthermore, there is a growing need to reflect users' emotional states in medical services to facilitate more appropriate appointment scheduling at suitable medical facilities and to adjust prescriptions to address emotional distress.

[0600] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0601] In this invention, the server includes means for acquiring biometric information using a measuring device, means for identifying the user's emotional state using an emotion recognition function and reflecting it in the health assessment, and means for generating medical recommendations tailored based on the diagnostic results and emotional information. This makes it possible to comprehensively manage the user's physical and mental health and optimize medical services and payment processes.

[0602] A "measurement device" is a device used to acquire biometric information and accurately measure the user's physical condition.

[0603] A "video recording device" is a device used to acquire images of body parts and is equipment used to record visual data.

[0604] An "information processing device" is an electronic system that analyzes acquired data and processes information, and often operates on the cloud.

[0605] "Artificial intelligence" is a technology that uses computers to imitate human intellectual behavior, and is particularly used for analyzing data.

[0606] "Emotion recognition functionality" is a technology that identifies a user's emotional state from their voice, facial expressions, and text input.

[0607] "Local information" refers to location-based information, including data related to a specific place.

[0608] An "incentive" is added value provided to encourage a particular behavior, and refers to monetary or non-monetary rewards for the user.

[0609] The system for implementing this invention allows users to comprehensively manage their health status. Users can launch an application using their smartphone and acquire biometric information using a device. This device includes a blood pressure monitor, heart rate monitor, thermometer, etc. Image data obtained by a video recording device and biometric information are transmitted from the terminal to an information processing device in the cloud.

[0610] The information processing device uses artificial intelligence to analyze the received data. This analysis is characterized by its ability to evaluate the user's emotional state using biometric information and emotion recognition functions. Based on the analysis results, optimal medical suggestions and adjustments are made and provided to the user.

[0611] Furthermore, the system can utilize local information to search for the nearest medical institution and assist users in making appointments. In addition, it enhances the user experience by providing incentives based on the user's emotional state when paying for consultations.

[0612] For example, if a user reports cold symptoms and high stress levels are detected simultaneously, the system will provide advice on stress reduction in addition to prescribing cold medicine. It can also prioritize appointments at appropriate medical facilities and offer a payment process with incentives to alleviate mental stress.

[0613] An example of an input prompt for a generative AI model would be: "Based on the user's emotional and health data, propose available medical services and corresponding payment incentives."

[0614] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0615] Step 1:

[0616] The user launches a dedicated application on their smartphone and acquires biometric information using measuring devices such as blood pressure monitors and heart rate monitors. Inputs include blood pressure, heart rate, and body temperature, and this biometric information is transmitted to the smartphone in real time. Outputs are data related to the user's physical condition.

[0617] Step 2:

[0618] The user uses their smartphone's video recording function to acquire images of body parts as needed. These images are stored within the application and sent to an information processing device in the cloud. The input is the image of the target body part, and the output is the transmitted image data.

[0619] Step 3:

[0620] The server uses artificial intelligence to analyze biometric and image data received on the cloud. The input is the aforementioned biometric and image data; the AI ​​model diagnoses the user's health status and provides a health assessment. The output is the health assessment based on the diagnosis.

[0621] Step 4:

[0622] The server uses emotion recognition to analyze the user's voice and facial expression data and identify their emotional state. The input is the user's voice and facial expression data, and the output is the identified emotional state. This data is integrated into the diagnostic results.

[0623] Step 5:

[0624] The server generates optimal medical recommendations and an incentivized payment process for the user based on diagnostic results and emotional information. It generates the prompt message, "Based on the user's emotional and health data, suggest available medical services and corresponding payment incentives." Based on this prompt message, the AI ​​determines the prescription and incentives and notifies the user. The input is health assessment and emotional state, and the output is medical recommendations and payment incentives.

[0625] Step 6:

[0626] Based on the medical suggestions provided, users book appointments at medical facilities located within the system. The input is a list of the most suitable medical facilities, and the output is a booking confirmation notice. At the time of payment, incentives are applied based on the user's emotional state.

[0627] Step 7:

[0628] After a user's consultation is complete, payment is automatically processed based on their insurance and payment information, and a completion notification is sent to the user. Inputs are insurance information and payment data, while outputs are the payment result and a payment completion notification. This allows users to manage their physical and mental health in a unified manner.

[0629] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0630] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0631] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0632] [Fourth Embodiment]

[0633] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0634] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0635] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0636] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0637] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0638] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0639] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0640] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0641] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0642] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0643] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0644] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0645] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0646] This invention is a system that uses a smartphone to diagnose a user's health condition and provide medical services. This system uses the user's smartphone, which they use daily, to measure biometric information and take images of affected areas. Specifically, the user launches an application and acquires biometric information such as blood pressure, heart rate, and body temperature using a dedicated measuring device. Furthermore, if there is an injury or skin abnormality, images of that area are also taken. This allows the user to collect necessary health data from the comfort of their home.

[0647] The device sends the collected data to a server in the cloud, which uses artificial intelligence to analyze the received data. In this analysis process, the AI ​​identifies data patterns and diagnoses potential health problems. Based on the diagnosis, it also generates prescription information, including suggestions for necessary medications and treatments. This prescription information is immediately sent to the user's device.

[0648] Furthermore, the server utilizes the user's location information to search for nearby medical facilities and schedule appointments. Users can review their diagnosis and suggested medical facilities from their homes and complete the appointment process using the system. The system also uses health insurance information to automatically process payment for consultations. During this process, users are rewarded with points or digital currency as a way to encourage usage.

[0649] For example, if a user experiences cold symptoms, the app measures their body temperature and heart rate and sends this data to a server. The server processes the data and notifies the user of the possibility of a cold and information about over-the-counter medications available at nearby pharmacies. Furthermore, it simultaneously makes a hospital appointment and, if necessary, secures a time slot for a consultation.

[0650] In this way, the present invention provides a system that enables users to easily and quickly manage their health status and receive appropriate medical services at home.

[0651] The following describes the processing flow.

[0652] Step 1:

[0653] The user launches the application on their smartphone. The application displays a screen prompting the user to prepare for biometric data measurement.

[0654] Step 2:

[0655] Using the device, the user obtains blood pressure, heart rate, and body temperature using a dedicated measuring device. The app also instructs the user to take images of the affected area with the camera.

[0656] Step 3:

[0657] The device transmits the measured biometric information and captured image data to a server in the cloud via encrypted communication.

[0658] Step 4:

[0659] The server passes the received data to an AI module for analysis. The AI ​​analyzes the biometric data, detects abnormal values, and diagnoses the user's health status.

[0660] Step 5:

[0661] Based on the diagnostic results, the server generates prescription information, including details about necessary medications and treatments. This information is then returned to the user's terminal.

[0662] Step 6:

[0663] The server retrieves the user's current location and searches a database for nearby medical facilities. It then selects the most suitable medical facility and accesses the reservation system.

[0664] Step 7:

[0665] The server generates reservation information and notifies the user of the result of making an appointment at the nearest medical facility. Reservation details are sent to the user's device.

[0666] Step 8:

[0667] The terminal provides users with an interface that centrally displays diagnostic results, prescription information, and appointment information, and sends notifications prompting them to take necessary actions.

[0668] Step 9:

[0669] When a user receives medical treatment and pays the consultation fee, they enter payment information through a terminal. The server then automatically processes the medical expense settlement using the insurance information.

[0670] Step 10:

[0671] After payment is completed, the server will award the user additional points or digital currency to encourage continued use. This information will be notified to the user's device.

[0672] (Example 1)

[0673] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0674] Modern healthcare management requires individuals to monitor their health status on a daily basis and access medical services quickly and appropriately. However, traditional methods involve cumbersome processes such as obtaining individual biometric information, making appointments with medical institutions, and settling medical fees, making it difficult to provide consistent services. There is a need to solve these problems and provide a system that allows users to more easily manage their health and access medical care from home or other convenient locations.

[0675] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0676] In this invention, the server includes means for analyzing biometric data acquired using a generative AI model to determine the user's health status, means for generating prescription instructions based on the determination results, and means for searching for nearby medical institutions and making reservations using the user's location data. This enables users to efficiently acquire biometric data from the comfort of their homes, receive appropriate diagnoses and make reservations at medical institutions, and improves the convenience of medical services.

[0677] A "measuring device" is a device used to acquire biological data, and is a device that has the function of measuring the user's blood pressure, heart rate, body temperature, etc.

[0678] An "image acquisition device" is a device used to acquire images of specific parts of a user's body, and typically has the function of taking high-resolution images using a camera.

[0679] "Cloud storage" refers to data storage accessible via the internet, and is a device used to securely store and manage acquired biometric and image data.

[0680] A "generative AI model" is a machine learning model based on a large amount of historical data, and is a program that analyzes a user's health status and performs pattern recognition.

[0681] "Analysis means" refers to the functions of a system that analyzes acquired data and performs a series of processes to determine a person's health status.

[0682] A "means for generating prescription instructions" refers to a function that suggests appropriate medications and treatments to the user based on the assessment of their health condition.

[0683] "Location data" refers to information indicating a user's geographical location, and is digital information obtained through GPS or other location measurement technologies.

[0684] The "means of searching for medical facilities and making reservations" refers to a function that uses the user's location data to search for nearby medical facilities and automatically completes the necessary reservation procedures.

[0685] "Medical expense settlement" refers to the process of calculating and settling the charges for medical services based on the user's insurance information, etc.

[0686] "Digital currency" refers to a form of currency that can be traded electronically, including points and credits offered as incentives to users.

[0687] This invention is a system that enables users to monitor their health status on a daily basis and receive appropriate medical services. This system efficiently manages the user's health by combining a measuring device, an image acquisition device, a generative AI model, and a cloud-based storage device.

[0688] First, the user launches a healthcare application using a smart device and acquires biometric data such as blood pressure, heart rate, and body temperature using a measuring device. They also take images of the affected area or other areas of concern using an image acquisition device. This smart device is equipped with Bluetooth and Wi-Fi connectivity, allowing for easy data synchronization with the measuring device.

[0689] The acquired biometric and image data is sent from the device to a cloud-based storage device. The server then uses a generated AI model to analyze the data. This AI model is machine-trained based on a large amount of historical data and determines the health status through pattern recognition. Based on the AI ​​model's analysis results, the server identifies specific health risks and generates necessary prescriptions.

[0690] The server then uses the user's location data to search for the nearest suitable medical facility. It has the ability to check facility availability in real time and make the user's desired reservation. This reservation information is immediately sent to the user's smart device.

[0691] Furthermore, the system includes a medical expense settlement function, automatically processing payments based on the insurance data registered by the user. After settlement, digital currency or points are awarded to the user as an incentive.

[0692] As a concrete example, when a user experiences the initial symptoms of a cold, they launch the app, measure their body temperature and heart rate, and send this data to the cloud. The server diagnoses the possibility of a cold and provides the user with recommendations for over-the-counter medications, along with the option to book an appointment at a nearby clinic. In this way, users can quickly manage their health from home and access medical services as needed.

[0693] Examples of prompt messages include, "Your body temperature is elevated; please provide a detailed diagnosis," and "You have a skin abnormality; please send an image for evaluation."

[0694] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0695] Step 1:

[0696] The user launches a healthcare application on their smart device. Through the application's interface, they input instructions to send to the measuring device for measuring blood pressure, heart rate, and body temperature. The measuring device acquires this biometric data and transmits it to the device. The user's specific actions involve attaching the device to their fingertip or arm and waiting for the measurement results to be displayed.

[0697] Step 2:

[0698] The terminal encrypts the acquired biometric data and sends it to a server in the cloud along with images of the affected area taken using an image acquisition device. The input for this step is biometric data and image data, and these are sent to the server as output. Specifically, the terminal transmits and receives data between the device and the measuring device via Bluetooth or Wi-Fi.

[0699] Step 3:

[0700] The server uses a cloud-based AI model to analyze the received data. In this analysis process, the server supplies biometric and image data as input to the AI ​​model and generates health status diagnostic results as output. Specifically, the AI ​​model uses pattern recognition technology to detect anomalies and assess health risks.

[0701] Step 4:

[0702] The server generates necessary prescription instructions based on the diagnostic results and sends them to the user's terminal. The input for this step is the AI-generated diagnostic results, and the output is prescription information in a user-friendly format. Specifically, the server analyzes the diagnostic results and selects the most suitable medications and treatment options.

[0703] Step 5:

[0704] The server uses the user's location data to obtain current location information as input. It then searches for nearby medical facilities, checks appointment availability, and then makes a reservation, sending the information to the user's device. As output, the user receives a reservation completion message. The server accesses a database of medical facilities and performs reservation operations in real time.

[0705] Step 6:

[0706] The server uses the user's insurance data and treatment details as input to process the settlement of medical expenses. The output is a confirmation of settlement and the awarding of digital currency or points to the user's account. Specifically, the server executes the settlement process through the payment gateway and awards incentives to the user.

[0707] (Application Example 1)

[0708] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0709] Modern healthcare systems require visits to medical facilities and involve cumbersome payment processes, creating a need for automated and easily accessible health checkups and consultations. Furthermore, there is a lack of mechanisms for electronically settling payments after receiving medical services and providing appropriate incentives to users. Therefore, the challenge lies in improving user convenience while promoting the use of healthcare services.

[0710] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0711] In this invention, the server includes means for acquiring biological information using a measuring device, means for acquiring images of a target area using an image acquisition device, processing means using artificial intelligence connected to a storage device on the cloud to analyze the acquired information and diagnose the condition, means for generating initial treatment information based on the diagnosis results, means for searching for nearby facilities using location information and performing procedures, means for performing electronic payments and providing additional functions, and means for providing rewards for using the service. As a result, users can quickly and easily understand their health status and receive necessary medical services even at home. Furthermore, the electronic settlement of medical expenses reduces hassle, and usage can be promoted through points and rewards.

[0712] A "measuring device" is a device used to acquire biological information and has the function of accurately measuring various indicator data.

[0713] An "image acquisition device" is a device used to capture images of a target area, and its purpose is to record visual information as digital data.

[0714] "Cloud storage" refers to online storage that allows data to be stored and accessed via a network, and is a system that enables data organization and storage.

[0715] "Artificial intelligence" is a technology that uses computer programs to mimic human intellectual activity, and is particularly used in data analysis and diagnostic processes.

[0716] "Initial treatment information" refers to information about treatments and therapies suggested based on the results and condition of a health checkup, and is intended to provide users with prompt action plans.

[0717] "Location information" refers to data that indicates the geographical location of a user or device, and is used for searching for nearby facilities and providing directions.

[0718] "Electronic payment" refers to the process of conducting monetary transactions through online systems, and is a technology that completes payments without using banknotes or coins.

[0719] "Additional features" refer to extra functions or services provided in addition to the basic functions, and are elements that enhance the user experience.

[0720] A "reward" is an incentive given for a specific action or use of a service, and it has value in increasing the user's motivation.

[0721] The system that implements this application example operates using the following main components:

[0722] First, the user uses their smartphone to acquire biometric information from a Bluetooth-enabled measuring device. This process uses appropriate sensor devices to accurately collect indicator data such as blood pressure and body temperature. Then, the smartphone's camera function is used to acquire images of the affected area. The acquired data is transmitted from the smartphone to a server in the cloud.

[0723] The server receives the acquired biometric and image data and stores it in cloud-based storage. Then, it analyzes the data using a generative AI model, and artificial intelligence automatically diagnoses the user's health condition. Based on the diagnosis, the server sends initial treatment information back to the user's device. Here, the AI ​​analyzes past data patterns to suggest the most suitable treatment or procedure for the user.

[0724] Furthermore, the server has a mechanism to obtain location information from the user's device and search for nearby medical facilities. As a necessary procedure, reservations are automated, allowing users to complete facility reservations directly. The server also automatically settles medical fees through electronic payment, and as an additional feature, it awards points or rewards to users based on service usage.

[0725] As a concrete example, when a user experiences cold symptoms, they use a measuring device via the application to obtain their body temperature and heart rate. This data is immediately sent to a server, where AI diagnoses the possibility of a mild infection and provides information on nearby clinics. Simultaneously, an appointment at the clinic is made through the application, and points are added after the consultation.

[0726] An example of a prompt message would be: "Design an app that sends blood pressure and body temperature data measured by the user on their smartphone to a cloud AI, diagnoses their health condition, and settles medical expenses via electronic payment. Also, implement a points system to encourage customer use."

[0727] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0728] Step 1:

[0729] The user launches a smartphone application and acquires biometric information using a Bluetooth-enabled measuring device. The input is biometric data such as blood pressure and body temperature. The device temporarily stores this data and then prepares it for transmission to a cloud server. The output is a data package sent to the cloud. The user verifies the connection between the devices and confirms that the sensors of the measuring device are functioning correctly.

[0730] Step 2:

[0731] The device uses a smartphone camera to capture images of the affected area. The input is the visual data captured through the camera. The images are processed by a dedicated algorithm, and their size and resolution are adjusted to a standard format. The output is an image file sent to a cloud server for AI analysis. Users are instructed to capture images of the exact area and from the appropriate distance.

[0732] Step 3:

[0733] The device transmits the acquired biometric and image data to a storage device in the cloud. The input is the detailed health information acquired in steps 1 and 2. The server analyzes this data using a generating AI model to diagnose the health status. The output is text data generated as the diagnosis result, which is sent to the device. The server uses this to analyze the user's health patterns and identify potential problems.

[0734] Step 4:

[0735] The server searches for nearby medical facilities based on the diagnostic results. Inputs include the user's location and diagnostic results. It uses a map database to filter facility information and determine the most suitable facility. Outputs include a list of facilities and recommended appointment times, which are sent to the terminal. The server monitors available slots in real time and displays the best option.

[0736] Step 5:

[0737] The terminal displays the diagnostic results and facility information to the user and prompts them to select an appointment. The input consists of data from steps 3 and 4. The user completes the appointment process by approving it within the application. The output is saved on the user's terminal as an appointment confirmation. The terminal streamlines this process and minimizes response time.

[0738] Step 6:

[0739] The server performs electronic payment processing after the consultation is completed. Inputs include details of the actual medical services and cost information. It integrates with the payment platform to ensure secure settlement. Outputs include a payment completion notification and corresponding point accrual information, which are sent to the user. This ensures fast and secure transactions.

[0740] Step 7:

[0741] Users check their awarded points and prepare for their next use. Input is the point balance information displayed in the application. Output is the updated user profile, which will be used as a future incentive. The terminal manages the rewards earned by the user and helps encourage usage.

[0742] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0743] This invention provides a health management system that incorporates emotion recognition capabilities to offer personalized medical services that take into account the user's mental state. In this system, the user launches an application using a smartphone and measures biometric information. Specifically, blood pressure, heart rate, and body temperature are acquired using a dedicated measuring device. Additionally, images of the affected area are taken using the smartphone's camera function as needed.

[0744] The device transmits this biometric and image data to a server in the cloud. The server analyzes the received data using an AI module to diagnose the user's health condition. Based on this diagnosis, appropriate prescription information is generated and provided to the user.

[0745] The system's key feature, the emotion engine, identifies the user's emotional state by analyzing their voice, facial expressions, and text input. This emotional information is evaluated along with health checkup results, and medical information and advice reflecting the user's emotional state are generated.

[0746] For example, the system suggests relaxation techniques to alleviate stress reported by the user, and adjusts the dosage and type of medication according to their emotional state. It also considers the impact of emotions on health and searches for and schedules appointments at the most suitable medical facilities. Furthermore, emotional information influences the payment process for consultation fees and is used to provide financial incentives to reduce the user's mental burden. This makes it easier for users to manage not only their physical health but also their mental health.

[0747] For example, if a user is experiencing cold symptoms and high stress levels, the app will provide a prescription for cold medicine along with advice on stress reduction. Furthermore, it has a feature that prioritizes booking appointments at medical institutions that offer stress management support services. In this way, the system can provide medical services optimized for each user.

[0748] The following describes the processing flow.

[0749] Step 1:

[0750] The user launches the application on their smartphone. The application displays a screen prompting the user to begin collecting biometric and emotional data.

[0751] Step 2:

[0752] The user uses a dedicated measuring device to measure blood pressure, heart rate, and body temperature. They also take images of the affected area with their smartphone camera as needed.

[0753] Step 3:

[0754] The device transmits the measured biometric information and image data to a server in the cloud. At the same time, it also records emotional data using the user's voice input, text input, and facial recognition function.

[0755] Step 4:

[0756] The server uses an AI module to analyze the received biometric and image data and diagnose the user's health status. Simultaneously, an emotion engine analyzes emotional data to recognize the user's emotional state.

[0757] Step 5:

[0758] The server generates appropriate prescription information and advice based on health check results and emotion analysis results. If necessary, it also includes recommendations for treatment methods tailored to the emotional state.

[0759] Step 6:

[0760] The server uses the user's location information to search for nearby medical facilities. Considering the user's health and emotional state, it selects the most suitable medical institution and makes an appointment.

[0761] Step 7:

[0762] The device notifies the user of diagnostic results, prescription information, and medical facility appointment information. In addition, it provides emotionally-based relaxation methods and related information.

[0763] Step 8:

[0764] After receiving medical services, users pay for the consultation fee through their device. The server uses insurance information to automatically process the medical expense settlement and awards points or digital currency based on the user's emotional state.

[0765] Step 9:

[0766] The terminal notifies the user that the payment process is complete and provides information on how to use points and digital currency.

[0767] (Example 2)

[0768] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0769] In recent years, there has been a growing need for personalized medical services that comprehensively consider both biological information and emotional states in healthcare management. However, conventional systems have struggled to manage users' physical and mental health in an integrated manner. Therefore, there is a demand for systems that enable comprehensive health management, including emotional information.

[0770] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0771] In this invention, the server includes means for collecting physical data using a device for acquiring biometric information, means for using an emotion analysis engine to identify the user's emotional state, and means for generating medical information based on the diagnostic results and searching for and booking appropriate medical facilities. This makes it possible to comprehensively manage the user's physical and mental health and provide personalized medical services.

[0772] "Biometric information" refers to data that quantifies the user's physical condition, including information such as blood pressure, heart rate, and body temperature.

[0773] An "image capture device" is a device used to photograph parts of a user's body, and includes the camera function of a smartphone.

[0774] "Cloud storage" refers to data storage areas accessible via the internet, used for data analysis and storage.

[0775] "Analysis methods using artificial intelligence" refer to technologies that analyze data acquired using machine learning algorithms to evaluate and diagnose the user's health status.

[0776] "Means for generating medical information" refers to a function that creates individualized medical advice and prescription information for users based on analysis results.

[0777] An "emotion analysis engine" is a technology that analyzes voice, images, and text to identify a user's emotional state and use it for health management.

[0778] "Means of medical fee payment and value-added provision" refers to functions that facilitate payment for medical services and provide additional services such as incentives to reduce the user's mental burden.

[0779] "A means of searching for and booking the optimal medical facility" refers to a function that finds the most suitable medical institution based on the user's health condition and allows them to book an appointment for an available date and time.

[0780] Users launch a dedicated health management application using a smartphone or other device. The application utilizes measuring devices connected via Bluetooth or Wi-Fi to acquire the user's biometric information, such as blood pressure, heart rate, and body temperature. Users can also use their smartphone's camera function to take images of areas of their body they are concerned about, as needed.

[0781] The device transmits the acquired biometric and image data to a server in the cloud. During this process, the data is encrypted using the SSL / TLS protocol for secure transmission. The server analyzes the received data using an artificial intelligence module to diagnose the user's health status. Specifically, it uses machine learning algorithms to analyze the data and compare it with past data in a database to understand health trends.

[0782] Furthermore, the emotion analysis engine installed on the server analyzes the user's voice, facial expressions, and written text to identify their emotional state. This emotional information is integrated with health checkup results to generate medical information and advice that takes the user's mental state into account.

[0783] For example, if a user experiences cold symptoms and reports high stress levels, the system will provide information on cold medicine prescriptions and advice on relaxation techniques to reduce stress. It can also prioritize booking appointments at medical facilities that offer stress management support services.

[0784] This allows users to receive support in both physical and mental health. An example of input to the generating AI model is the prompt, "Suggest the most suitable medical services based on the health and emotional state reported by the user." In this way, the system enables the provision of personalized medical services.

[0785] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0786] Step 1:

[0787] The user launches a health management application using their smartphone. The application acquires biometric information such as blood pressure, heart rate, and body temperature from a measuring device connected via Bluetooth or Wi-Fi. The input at this time is the biometric information collected by the measuring device, and the application outputs this data by converting it into a digital format and saving it.

[0788] Step 2:

[0789] The user uses their smartphone's camera function to take images of the desired body parts. The input is the image data captured by the camera, and the application converts this data into an appropriate format and outputs it in a state ready for transmission to the cloud.

[0790] Step 3:

[0791] The device transmits the acquired biometric and image data to a server in the cloud. The input is the biometric and image data acquired in the previous step, and the output is securely encrypted transmission data. The data is encrypted using the SSL / TLS protocol and sent to the server.

[0792] Step 4:

[0793] The server analyzes the received data using an artificial intelligence module. The input consists of biometric information and image data sent from the terminal, which the AI ​​module analyzes using a machine learning algorithm to generate output that diagnoses the user's health status.

[0794] Step 5:

[0795] The emotion analysis engine on the server analyzes the user's voice data and facial expressions. The input consists of voice and facial information provided by the user, and the emotion analysis engine uses algorithms to analyze this data and produce an output that identifies the user's emotional state.

[0796] Step 6:

[0797] The server combines health check results and emotional information based on the analysis results to generate personalized medical advice. The input is the health check results and emotional analysis results generated by the AI, and the output is advice on medical information and relaxation methods that are suitable for the user.

[0798] Step 7:

[0799] The server sends the generated medical information and advice to the user's terminal. The input is the information generated by the server, which the terminal receives and displays as output to the user. Based on this information, the user can decide on the appropriate course of action.

[0800] (Application Example 2)

[0801] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0802] Traditional health management systems have focused primarily on assessing users' physical health, neglecting emotional and mental well-being. As a result, providing optimal medical services tailored to each user has been difficult, and flexible payment processes based on mental state-based incentives have been impossible. Furthermore, there is a growing need to reflect users' emotional states in medical services to facilitate more appropriate appointment scheduling at suitable medical facilities and to adjust prescriptions to address emotional distress.

[0803] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0804] In this invention, the server includes means for acquiring biometric information using a measuring device, means for identifying the user's emotional state using an emotion recognition function and reflecting it in the health assessment, and means for generating medical recommendations tailored based on the diagnostic results and emotional information. This makes it possible to comprehensively manage the user's physical and mental health and optimize medical services and payment processes.

[0805] A "measurement device" is a device used to acquire biometric information and accurately measure the user's physical condition.

[0806] A "video recording device" is a device used to acquire images of body parts and is equipment used to record visual data.

[0807] An "information processing device" is an electronic system that analyzes acquired data and processes information, and often operates on the cloud.

[0808] "Artificial intelligence" is a technology that uses computers to imitate human intellectual behavior, and is particularly used for analyzing data.

[0809] "Emotion recognition functionality" is a technology that identifies a user's emotional state from their voice, facial expressions, and text input.

[0810] "Local information" refers to location-based information, including data related to a specific place.

[0811] An "incentive" is added value provided to encourage a particular behavior, and refers to monetary or non-monetary rewards for the user.

[0812] The system for implementing this invention allows users to comprehensively manage their health status. Users can launch an application using their smartphone and acquire biometric information using a device. This device includes a blood pressure monitor, heart rate monitor, thermometer, etc. Image data obtained by a video recording device and biometric information are transmitted from the terminal to an information processing device in the cloud.

[0813] The information processing device uses artificial intelligence to analyze the received data. This analysis is characterized by its ability to evaluate the user's emotional state using biometric information and emotion recognition functions. Based on the analysis results, optimal medical suggestions and adjustments are made and provided to the user.

[0814] Furthermore, the system can utilize local information to search for the nearest medical institution and assist users in making appointments. In addition, it enhances the user experience by providing incentives based on the user's emotional state when paying for consultations.

[0815] For example, if a user reports cold symptoms and high stress levels are detected simultaneously, the system will provide advice on stress reduction in addition to prescribing cold medicine. It can also prioritize appointments at appropriate medical facilities and offer a payment process with incentives to alleviate mental stress.

[0816] An example of an input prompt for a generative AI model would be: "Based on the user's emotional and health data, propose available medical services and corresponding payment incentives."

[0817] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0818] Step 1:

[0819] The user launches a dedicated application on their smartphone and acquires biometric information using measuring devices such as blood pressure monitors and heart rate monitors. Inputs include blood pressure, heart rate, and body temperature, and this biometric information is transmitted to the smartphone in real time. Outputs are data related to the user's physical condition.

[0820] Step 2:

[0821] The user uses their smartphone's video recording function to acquire images of body parts as needed. These images are stored within the application and sent to an information processing device in the cloud. The input is the image of the target body part, and the output is the transmitted image data.

[0822] Step 3:

[0823] The server uses artificial intelligence to analyze biometric and image data received on the cloud. The input is the aforementioned biometric and image data; the AI ​​model diagnoses the user's health status and provides a health assessment. The output is the health assessment based on the diagnosis.

[0824] Step 4:

[0825] The server uses emotion recognition to analyze the user's voice and facial expression data and identify their emotional state. The input is the user's voice and facial expression data, and the output is the identified emotional state. This data is integrated into the diagnostic results.

[0826] Step 5:

[0827] The server generates optimal medical recommendations and an incentivized payment process for the user based on diagnostic results and emotional information. It generates the prompt message, "Based on the user's emotional and health data, suggest available medical services and corresponding payment incentives." Based on this prompt message, the AI ​​determines the prescription and incentives and notifies the user. The input is health assessment and emotional state, and the output is medical recommendations and payment incentives.

[0828] Step 6:

[0829] Based on the medical suggestions provided, users book appointments at medical facilities located within the system. The input is a list of the most suitable medical facilities, and the output is a booking confirmation notice. At the time of payment, incentives are applied based on the user's emotional state.

[0830] Step 7:

[0831] After a user's consultation is complete, payment is automatically processed based on their insurance and payment information, and a completion notification is sent to the user. Inputs are insurance information and payment data, while outputs are the payment result and a payment completion notification. This allows users to manage their physical and mental health in a unified manner.

[0832] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0833] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0834] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0835] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0836] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0837] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0838] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0839] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0840] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0841] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0842] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0843] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0844] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0845] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0846] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0847] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0848] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0849] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0850] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0851] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0852] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0853] The following is further disclosed regarding the embodiments described above.

[0854] (Claim 1)

[0855] A means of acquiring biological information using a measuring device,

[0856] A means for acquiring an image of the affected area using an image acquisition device,

[0857] An analysis method using artificial intelligence that connects to a storage device in the cloud, analyzes acquired information, and diagnoses health status,

[0858] A means for generating prescription information based on diagnostic results,

[0859] A method for searching for nearby medical facilities and making reservations using location information,

[0860] A means of processing payment for medical consultations and providing added value,

[0861] A system that includes this.

[0862] (Claim 2)

[0863] The system according to claim 1, which measures blood pressure, heart rate, and body temperature as biological information.

[0864] (Claim 3)

[0865] The system according to claim 1, which automatically settles medical expenses using insurance information.

[0866] "Example 1"

[0867] (Claim 1)

[0868] A means of acquiring biological data using a measuring device,

[0869] A means for acquiring a localized image using an image acquisition device,

[0870] An analysis method using a generative AI model that connects to a storage device in the cloud, analyzes acquired data, and determines health status,

[0871] A means for generating prescription instructions based on the judgment result,

[0872] A method for searching for nearby medical facilities using location data and making reservations,

[0873] A means of settling medical expenses and providing digital currency,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, which measures blood pressure, heart rate, and body temperature as biometric data.

[0877] (Claim 3)

[0878] The system according to claim 1, which automatically settles medical expenses using insurance data.

[0879] "Application Example 1"

[0880] (Claim 1)

[0881] A means of acquiring biological information using a measuring device,

[0882] A means for acquiring an image of the target area using an image acquisition device,

[0883] A processing means using artificial intelligence that connects to a storage device in the cloud, analyzes acquired information, and diagnoses the state,

[0884] A means for generating initial treatment information based on diagnostic results,

[0885] A means of searching for nearby facilities and carrying out procedures using location information,

[0886] A means of conducting electronic payments and providing additional functions,

[0887] A means of providing compensation for using the service,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1 for measuring indicator data as biological information.

[0891] (Claim 3)

[0892] The system according to claim 1, which automatically settles expenses using data.

[0893] "Example 2 of combining an emotion engine"

[0894] (Claim 1)

[0895] A means of collecting user physical data using a device that acquires biometric information,

[0896] A means for acquiring images of body parts using an image acquisition device,

[0897] An analysis method using artificial intelligence that connects to a storage medium in the cloud, analyzes acquired information, and diagnoses the user's health condition,

[0898] A means for generating medical information based on the analysis results,

[0899] A means of identifying a user's emotional state by analyzing voice, images, and text using an emotion analysis engine,

[0900] A means of providing medical advice that takes emotional states into consideration,

[0901] A method of searching for and booking the most suitable medical facility using location information,

[0902] A means of providing payment for medical expenses and added value to alleviate the mental burden on users,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, which measures blood pressure, heart rate, and body temperature data as biological information.

[0906] (Claim 3)

[0907] The system according to claim 1, which uses insurance data to automate the payment of medical expenses.

[0908] "Application example 2 when combining with an emotional engine"

[0909] (Claim 1)

[0910] A means of acquiring biological information using a measuring device,

[0911] A means of acquiring images of body parts using a video recording device,

[0912] An analysis means using artificial intelligence, which is connected to an information processing device, analyzes acquired information, and identifies the health status,

[0913] A means of identifying a user's emotional state using emotion recognition functionality and reflecting it in health assessment,

[0914] A means for generating medical recommendations adjusted based on diagnostic results and emotional information,

[0915] A method for searching for nearby medical facilities and making reservations using local information,

[0916] A means of settling consultation fees and providing incentives based on mental state,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, which measures blood pressure, heart rate, and body temperature as biological information and analyzes emotional information.

[0920] (Claim 3)

[0921] The system according to claim 1, which uses insurance information to automatically settle medical expenses and optimizes settlement according to health status and emotional assessment. [Explanation of Symbols]

[0922] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring biological information using a measuring device, A means for acquiring an image of the affected area using an image acquisition device, An analysis method using artificial intelligence that connects to a storage device in the cloud, analyzes acquired information, and diagnoses health status, A means for generating prescription information based on diagnostic results, A method for searching for nearby medical facilities and making reservations using location information, A means of processing payment for medical consultations and providing added value, A system that includes this.

2. The system according to claim 1, which measures blood pressure, heart rate, and body temperature as biological information.

3. The system according to claim 1, which automatically settles medical expenses using insurance information.

Images