system

Abstract

We provide the system. [Solution] A terminal device for collecting personal biometric data, A server means that receives collected biometric data and stores it in a storage device, A generation AI means equipped with an analysis unit that analyzes biometric data to detect anomalies and generates a notification message when an anomaly occurs, A transmission unit means that sends a notification message to the terminal and warns the user, An advice unit means that generates and transmits personalized advice regarding anomalies, Means to authorize information sharing with medical institutions A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 To solve the problem that people are hardly aware of their own physical condition changes and cannot quickly and appropriately cooperate with medical institutions even when they are aware of abnormalities. Also, it is necessary to solve the problem that it is difficult to convey accurate health information to doctors. 【Means for Solving the Problems】 【0005】 To address this challenge, the system provides a terminal for collecting personal biometric data, a server for receiving and storing the collected biometric data, a generation AI equipped with an analysis unit that detects anomalies and generates notification messages, a transmission unit that sends notifications to the terminal and warns the user, an advice unit that generates personalized advice regarding anomalies, and means for authorizing information sharing with medical institutions. This system enables users to detect changes in their daily health early, facilitates rapid collaboration with medical institutions, and allows them to receive appropriate diagnosis and treatment through the provision of accurate information. 【0006】 A "device for collecting personal biometric data" is a device that continuously records health-related data such as an individual's heart rate, steps taken, and sleep patterns, and has communication capabilities that allow it to transmit this data to other devices. 【0007】 A "server" is a system that includes a computing device for receiving collected biometric data, storing it in a memory device, and analyzing that data. 【0008】 "Generative AI" refers to an artificial intelligence system equipped with an algorithm that detects anomalies based on recorded biometric data and generates notifications regarding those anomalies. 【0009】 The "transmitter" is a component that has the function of transmitting notification messages generated by the generation AI to the terminal via communication, thereby conveying warnings to the user. 【0010】 The "Advice Unit" is a system that generates personalized health advice in response to detected abnormalities and provides users with detailed information about it. 【0011】 "Means for authorizing information sharing with medical institutions" refers to features that include procedures that allow biometric data to be securely delivered to medical institutions for medical purposes, but only if the user selects to do so. [Brief explanation of the drawing] 【0012】 [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention] 【0013】 Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings. 【0014】 First, the terms used in the following description will be explained. 【0015】 In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0016】 In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0017】 In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0018】 In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc. 【0019】 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." 【0020】 [First Embodiment] 【0021】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0022】 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. 【0023】 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). 【0024】 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. 【0025】 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. 【0026】 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. 【0027】 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. 【0028】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0029】 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. 【0030】 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. 【0031】 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. 【0032】 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". 【0033】 This invention is designed to efficiently collect and analyze personal biometric data, enabling users to understand their own health status and respond quickly when abnormalities occur. Specifically, it is a system that integrates terminals, servers, and generating AI. 【0034】 Data collection and transmission: 【0035】 The device collects daily health data from the user's smart device, including heart rate, steps taken, and sleep patterns. This data is stored on the device in real time. 【0036】 The collected data is properly formatted and securely transmitted to the server on a regular basis. 【0037】 Data storage and analysis: 【0038】 The server stores the received data in a database. The data is organized chronologically and managed on a per-user basis. 【0039】 The generating AI runs on a server and continuously analyzes stored biometric data. This AI also refers to past data to determine normal patterns and anomalies. 【0040】 Anomaly detection and notification: 【0041】 When an anomaly is detected, the server immediately generates a notification message. This message includes the type of anomaly and the risk level in a user-friendly format. 【0042】 The message is sent to the device and presented to the user as a push notification. 【0043】 Advice provided by: 【0044】 The server also generates personalized health advice based on detected anomalies, including preventative measures and lifestyle improvements. 【0045】 These pieces of advice are intended to have a concrete impact on the user's daily life and will be displayed in a list on the user's device after being sent. 【0046】 Information sharing with medical institutions: 【0047】 If necessary, users can choose to share information with medical institutions. In this case, the server organizes past data into a medical record format and sends it to the medical institution via a secure communication channel. 【0048】 As a concrete example, consider the case where an abnormal heart rate is detected. In this scenario, the server generates a message indicating the abnormality and sends a notification to the terminal stating, "Your heart rate has recently been higher than normal. Please check if you are experiencing stress and consult a medical institution if necessary." It also provides advice that includes a 5-minute breathing exercise, helping the user understand the next steps to take. In this way, the invention comprehensively supports individual health management. 【0049】 The following describes the processing flow. 【0050】 Step 1: 【0051】 The device continuously collects biometric data from smart devices. This data includes heart rate, steps taken, and sleep patterns. This data is organized within the device and stored chronologically. 【0052】 Step 2: 【0053】 At regular intervals, the terminal prepares to send the accumulated data to the server. The data is encoded in a secure format and organized into packets for communication. This packetized data is sent to the server via the internet. 【0054】 Step 3: 【0055】 The server quickly saves received data to the database. The data is categorized by user and stored chronologically along with past data. 【0056】 Step 4: 【0057】 The stored data is analyzed by a generative AI running on the server. The generative AI compares it to normal data patterns to determine if anomalies exist. It also refers to past data to detect anomaly patterns. 【0058】 Step 5: 【0059】 When the server detects an anomaly, it generates a notification message in a user-friendly format. The notification message includes the type of anomaly, the risk level, and recommended actions. 【0060】 Step 6: 【0061】 The generated notification message is sent from the server to the device. The device receives it and presents it to the user as a push notification. 【0062】 Step 7: 【0063】 Simultaneously, the server generates personalized advice. This advice includes specific countermeasures and preventative measures for anomalies. This advice is sent to the terminal and provided to the user. 【0064】 Step 8: 【0065】 If necessary, users can choose to share their past biometric data with designated healthcare institutions. The data is then processed in a secure format by the server and transmitted to the selected healthcare institution. 【0066】 (Example 1) 【0067】 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." 【0068】 In today's world, where health management is increasingly important, there is a need for systems that can efficiently collect and analyze personal biometric information and enable rapid response when abnormalities occur. Furthermore, there is a lack of methods to provide users with appropriate health advice and support collaboration with medical institutions as needed. Additionally, there is a need for technology that can handle data seamlessly while protecting user privacy. 【0069】 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. 【0070】 In this invention, the server includes a portable device means for aggregating an individual's biometric information, an information processing device means for receiving the aggregated biometric information and storing it in a storage device, and a generation algorithm means equipped with an analysis unit that analyzes the biometric information to detect abnormalities and creates a notification signal in the event of an abnormality. This enables monitoring of an individual's health status and rapid response in the event of an abnormality, thereby realizing comprehensive health management. 【0071】 "Personal biometric information" is a general term for data that indicates an individual's health status, such as heart rate, steps taken, and sleep patterns. 【0072】 A "portable device" is a device that a user can carry with them and that has the function of collecting health data. 【0073】 An "information processing device" is a device that receives collected data and stores and manages it. 【0074】 A "storage device" is a memory device that stores received data and organizes it chronologically. 【0075】 A "generative algorithm" is a computational method used to analyze collected biological information and detect anomalies. 【0076】 The "analysis unit" is the part of the system equipped with functions for analyzing data and identifying anomalies. 【0077】 A "notification signal" is a warning signal generated to inform the user of a detected anomaly. 【0078】 The "transmitter" is the part that has the function of sending the generated notification signal to the mobile device and displaying the notification to the user. 【0079】 The "Advice Department" is the part of the system that provides users with specific advice for maintaining their health based on the data it collects. 【0080】 A "medical facility" is an organization or institution where users can receive professional support regarding their health. 【0081】 This invention is a system that comprehensively supports individual health management, aggregating and analyzing individual biometric information to enable rapid response in the event of an abnormality. The system operates by integrating a portable device, an information processing device, and a generation algorithm. The following describes each component and its specific function. 【0082】 First, the terminal consists of portable devices such as smartphones and wearable devices. These devices collect data such as the user's heart rate, steps taken, and sleep patterns in real time. Specifically, heart rate sensors and accelerometers are used to acquire data. For example, if a user walks more than 10,000 steps every day, that number of steps will be recorded by the device. 【0083】 The collected data is transmitted to the server via Bluetooth or Wi-Fi. The server functions as an information processing device, storing the received data in a storage device. MySQL® or PostgreSQL are suitable database systems. The data is organized chronologically and categorized by user. 【0084】 Next, a generative AI running on the server analyzes the stored data. Here, machine learning software such as TENSORFLOW® and PyTorch is used to build a data analysis model. This generative algorithm detects data anomalies and generates notification signals. Predictive analysis based on past health data is also possible. 【0085】 When an anomaly is detected, the server automatically creates a notification message and sends it to the device. This message is presented to the user as a push notification. For example, it might say, "Your heart rate has been higher than normal recently. Please check if you are experiencing stress and seek medical attention if necessary." 【0086】 Furthermore, personalized health advice is generated by the AI ​​and displayed in a list on the user's device. This advice includes specific suggestions, such as a 5-minute breathing exercise. An example of a prompt message is: "Generate a prompt message to detect anomalies and provide advice based on the user's health data. Include the specific type of anomaly and recommended advice." 【0087】 Ultimately, users can share their data with healthcare facilities as needed. The server organizes the data into a medical record format and sends it to healthcare institutions using a secure API. This secure data sharing allows users to receive more specialized health management. 【0088】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0089】 Step 1: 【0090】 The device collects biometric information in real time from the user's smart device. Inputs include data from heart rate sensors and accelerometers. This data is output in the form of heart rate, steps taken, sleep patterns, etc. Specifically, the device periodically reads data as the user wears it and goes about their daily life. 【0091】 Step 2: 【0092】 The device transmits the collected biometric information to the server via Bluetooth or Wi-Fi. The biometric data obtained in step 1 is used as input. This data is appropriately formatted and encrypted before being sent to the server. Specifically, data packets are generated at regular intervals and transmitted using a secure protocol. 【0093】 Step 3: 【0094】 The server stores the received biometric information in a storage device. It uses the received data as input and saves it to a database in a chronologically organized format. The output of this data is a dataset categorized by user, ready for future analysis. Specifically, it adds records to the database using an "INSERT INTO" query. 【0095】 Step 4: 【0096】 The generating AI on the server performs analysis using the stored data. The input is the biometric information stored in step 3, and the output is the anomaly detection result. The generating AI compares this with past data and applies machine learning algorithms to detect anomalies in the current biometric information. Specifically, the data is fed into the AI ​​model to detect anomalies and assess risks. 【0097】 Step 5: 【0098】 If an anomaly is detected, the server generates a notification signal and sends a notification to the terminal. The anomaly detection result is used as input. The output is a warning message in a user-friendly format. Specifically, a prompt sentence is created based on the analysis results of the generation AI, and this is sent to the terminal as a push notification. 【0099】 Step 6: 【0100】 The server generates personalized advice for the user based on the anomaly and sends it to the terminal. It uses the anomaly detection results as input, and the output is specific advice and suggestions for the user. Specifically, it lists health improvement suggestions based on the type of anomaly and presents them to the user's terminal. 【0101】 Step 7: 【0102】 If necessary, users can choose to share their biometric information with healthcare facilities. The input is the user's past biometric data, and the output is a medical record formatted for healthcare facilities. Specifically, the server sends data to healthcare institutions via a secure API and shares the data based on the user's consent. 【0103】 (Application Example 1) 【0104】 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." 【0105】 In systems that support individual health management through the collection and analysis of biometric information, there is a need to efficiently detect abnormalities and provide warnings and advice in an easily understandable format for users. However, previous technologies have faced challenges such as insufficient data collection and analysis, and limitations in the detection rate of abnormalities. Furthermore, providing personalized health advice closely tied to the user's lifestyle has been difficult with conventional approaches. 【0106】 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. 【0107】 In this invention, the server includes equipment means for collecting personal biometric information, computer means for receiving the collected biometric information and storing it in a storage medium, and artificial intelligence means equipped with an analysis unit that analyzes the biometric information to detect anomalies and generates notification information in the event of an anomaly. This enables efficient anomaly detection and the provision of personalized health advice. 【0108】 A "device that collects personal biometric information" is a device that acquires health-related data from users, and uses sensors to measure data such as heart rate, steps taken, and sleep patterns. 【0109】 A "computer that receives collected biometric information and stores it in a storage medium" is an electronic device that receives biometric information transmitted from another device and stores it in digital format; it is essentially a server with a database. 【0110】 "An artificial intelligence equipped with an analysis unit that analyzes biometric information to detect anomalies and generates notification information when anomalies occur" refers to software that continuously analyzes biometric data, identifies data outside the normal range, and generates alerts. 【0111】 The "communication unit that sends notification information to devices and warns users" is a function that sends messages generated based on analysis results to devices and informs users through visual or auditory means. 【0112】 The "advice unit that generates and transmits personalized advice for abnormalities" is a system that creates and provides different health improvement measures and action suggestions for each user based on the detected abnormalities. 【0113】 "Means for allowing information sharing with medical institutions" refers to technology that enables the transmission of biometric information and analysis results to medical service providers via a reliable communication channel, if selected by the user. 【0114】 To implement this invention, multiple devices and software must work together to efficiently manage an individual's health. This system mainly consists of devices that collect biometric information in real time, a server that stores and analyzes the data, a terminal that notifies the user based on the analysis results, and artificial intelligence that generates personalized advice. 【0115】 The server receives biometric information transmitted by users and stores it in a database. This data is managed chronologically and prepared for subsequent analysis. A generative AI model runs on the server, analyzing the biometric information to detect abnormal patterns. In this process, past data is also referenced to determine anomalies with high accuracy. 【0116】 If an anomaly is detected, the server generates notification information and sends it to the device. The device immediately relays this information to the user and issues an appropriate warning. At this stage, the user can understand their health status and learn about necessary countermeasures. The server also uses AI to generate personalized health advice based on the anomaly and sends it to the device for display to the user. 【0117】 For example, consider a scenario where a user's heart rate suddenly increases while they are indoors. The server detects this anomaly and sends a notification to the user's device such as, "Your heart rate is higher than normal. Take a short break and try deep breathing." It also provides further advice, such as, "To reduce stress, try a 3-minute deep breathing exercise," to help the user respond quickly. 【0118】 An example of a prompt message is: "Analyze the user's heart rate data, generate a warning if it exceeds the normal range, and suggest appropriate mitigation measures." In this way, the system comprehensively supports users' health management through real-time monitoring of health data, rapid anomaly detection, and personalized assistance. 【0119】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0120】 Step 1: 【0121】 The device collects biometric information from the user, such as heart rate, steps taken, and sleep patterns. It processes the data acquired using sensors in real time and stores it in a buffer. The input is biometric information, and the output is formatted data. For security reasons, the data is encrypted within the device. 【0122】 Step 2: 【0123】 The device transmits collected biometric information to the server. The data is transmitted using a secure communication protocol. The input is encrypted biometric information, and the output is a notification that the data transfer to the server is complete. Communication is performed periodically to ensure real-time performance. 【0124】 Step 3: 【0125】 The server stores the received biometric information in a database. The data is organized chronologically and managed on a per-user basis. The input is the received biometric information, and the output is the organized information in the database. The stored data serves as foundational information for subsequent analysis. 【0126】 Step 4: 【0127】 The AI ​​within the server analyzes biometric information to check for abnormalities. It also references past data to determine if an anomaly is detected. The input is organized biometric information, and the output is the anomaly detection result. This process utilizes a pattern recognition algorithm, enabling highly accurate anomaly detection. 【0128】 Step 5: 【0129】 The server generates notification information and sends it to the terminal when an anomaly is detected. The generating AI automatically determines the details of the anomaly and its risk level, and formats the information. The input is the anomaly detection result, and the output is the notification information to be displayed on the terminal. 【0130】 Step 6: 【0131】 The device displays received notification information to the user. It issues alerts via screen and audio to prompt the user to take prompt action. The input is notification information sent from the server, and the output is a warning message to the user. The notification is converted into a user-friendly format. 【0132】 Step 7: 【0133】 The server generates personalized advice based on the anomaly and sends it to the terminal. The generating AI constructs customized advice for each user based on the prompt text. The input is the anomaly detection result and past response history, and the output is a specific action suggestion. 【0134】 Step 8: 【0135】 The terminal displays the received advice to the user. The display follows a notification message, and visual and auditory volume adjustments are also considered. The input is advice information sent from the server, and the output is specific action suggestions for the user. 【0136】 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. 【0137】 This invention is a system that collects and analyzes individual biometric data to comprehensively manage a user's health and emotions, enabling rapid response in the event of an abnormality. In particular, by incorporating an emotion engine, it recognizes the user's emotional state and considers emotions when providing health advice, thereby achieving more effective health management. 【0138】 Data collection and transmission: 【0139】 The device continuously acquires biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. Furthermore, the device monitors the user's usage patterns and input data, collecting elements to infer their emotional state. This data is compiled over a certain period and transmitted to a server. 【0140】 Data storage and analysis: 【0141】 The server stores the received biometric data in a database and organizes it according to the user's profile. The emotion engine uses this data to estimate the user's emotions and feeds the analysis results back to the generating AI. 【0142】 Anomaly detection and notification: 【0143】 The server's AI analyzes biometric data, and if an anomaly is detected, it generates a notification message that also takes into account the user's emotional state. This message includes language that responds to the user's emotions, presenting the anomaly and recommended actions in a more user-friendly way. 【0144】 Advice provided by: 【0145】 The server generates personalized advice, incorporating emotion recognition from the emotion engine to create more personalized suggestions. This advice is sent to the device, allowing the user to receive lifestyle improvement suggestions optimized for them. 【0146】 Emotional feedback and medical information sharing: 【0147】 Users can monitor their own emotional state based on the emotional feedback provided. Furthermore, if abnormalities or persistent emotional changes persist, they can choose to share their past biometric data with a healthcare provider. The server provides this information to the healthcare provider in a secure and appropriate format. 【0148】 As a concrete example, consider a case where a user's heart rate becomes abnormally high due to stress. In this case, the emotion engine estimates that the user may be experiencing stress, and the server sends a notification stating, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend trying to take deep breaths or taking a short break." By implementing this invention, users can receive comprehensive management that takes into account not only their physical health but also their emotional well-being. 【0149】 The following describes the processing flow. 【0150】 Step 1: 【0151】 The device continuously collects biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. It also collects information such as the user's input actions and device usage patterns, which are used as data for inferring emotions. 【0152】 Step 2: 【0153】 The collected biometric data and usage pattern data are compiled at predetermined time intervals and transmitted securely to the server. The transmission is performed using an encrypted protocol to prevent data leakage. 【0154】 Step 3: 【0155】 The server stores the received data in a database. The data is categorized by user, and the history is managed in chronological order. The server then uses an emotion engine to perform analysis to infer the user's emotional state. 【0156】 Step 4: 【0157】 The generating AI operates on a server, analyzing the received biometric data and comparing it to normal health conditions to determine if there are any abnormalities. It also acquires additional information, such as the emotional state estimated by the emotion engine. 【0158】 Step 5: 【0159】 If an anomaly is detected, the server considers the nature of the anomaly and the user's emotional state to generate a message. Because it includes emotionally appropriate language, the notification is easy for the user to understand and is delivered in a sensitive manner. 【0160】 Step 6: 【0161】 The generated notification message is sent from the server to the device, which then presents it to the user as a push notification. The user immediately receives information about the anomaly and recommended actions through the device. 【0162】 Step 7: 【0163】 The server generates personalized advice optimized for the user based on the results of the generative AI and emotion engine. This advice includes suggestions that can be directly applied to the user's daily life. 【0164】 Step 8: 【0165】 If necessary, users can choose to share information with healthcare institutions. The server will follow the user's instructions and prepare to provide past biometric data and emotional information to healthcare institutions in a secure format. 【0166】 Step 9: 【0167】 Finally, the device provides the user with feedback regarding the emotional state estimated by the emotion engine. This feedback allows the user to understand their own emotions and adjust their behavior as needed. 【0168】 (Example 2) 【0169】 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". 【0170】 In modern society, there is a need for comprehensive management of individual health conditions, particularly for rapid anomaly detection and response that takes emotional states into consideration. However, existing systems struggle to effectively combine and analyze biometric data and emotional states, resulting in insufficient personalized responses. Furthermore, while seamless information sharing with medical institutions is required, data security and user privacy remain challenges. 【0171】 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. 【0172】 In this invention, the server includes a device means for collecting and periodically transmitting an individual's biometric data in batches; an information processing device means for receiving the collected biometric data and securely storing it in a database; and a generative AI means for estimating emotions using natural language processing when analyzing the biometric data, and generating anomaly detection and notification messages. This enables comprehensive analysis combining an individual's biometric data and emotional state, as well as rapid anomaly detection, and ensures secure data sharing with medical institutions. 【0173】 A "device that collects and periodically transmits personal biometric data" refers to a combination of hardware and software that acquires personal health data through smart devices and other means, and securely transmits it via a communication network at regular intervals. 【0174】 An "information processing device that receives collected biometric data and securely stores it in a database" is a server system that receives biometric data transmitted from a terminal, organizes this data appropriately, and stores it securely. 【0175】 "Generative AI that uses natural language processing to estimate emotions when analyzing biometric data and generates anomaly detection and notification messages" refers to an artificial intelligence system that analyzes an individual's biometric data while simultaneously evaluating their emotional state using natural language processing technology, and generates notifications based on that information if an anomaly is detected. 【0176】 A "communication device that sends notification messages and issues warnings using expressions based on the user's emotional state" is a device that sends messages generated in a way that takes the user's emotional state into consideration to a terminal, providing attention and warnings. 【0177】 A "personalized health improvement suggestion generator that sends personalized health advice to user terminals" is a system that creates customized health advice based on each user's health condition and emotions, and sends it to the user's terminal. 【0178】 "Means of allowing information sharing with medical institutions and providing information securely" refers to processes and technologies that enable users to share their selected biometric data and analysis results with medical institutions, while ensuring data security and user privacy. 【0179】 To implement this invention, a system is needed that collects and analyzes individual biometric data and provides advice tailored to specific situations. Specific embodiments are described below. 【0180】 First, the terminal uses devices such as smartwatches and smartphones to acquire biometric data such as the user's heart rate, steps taken, and sleep patterns. These devices have communication capabilities that collect information via Bluetooth or Wi-Fi and periodically send the data to a server. 【0181】 The server is a device for securely storing received biometric data in a database. At this stage, the data is organized according to the individual's profile and managed using a database system such as MySQL or MongoDB. 【0182】 A server equipped with a generative AI model infers the user's emotional state based on accumulated biometric data and usage patterns and text data obtained from the terminal. Pandas and NumPy in Python are used for data analysis, and libraries such as NLTK and spaCy are utilized for natural language processing. If an anomaly is detected in the user through this emotion analysis, the generative AI creates an emotionally sensitive notification message based on the prompt text. 【0183】 For example, if the generating AI detects that the user's heart rate is higher than normal and that they are under stress, it will generate a prompt such as, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend you try taking some deep breaths or take a short break." 【0184】 Based on this information notified to their device, users can take specific actions to improve their health. Furthermore, users can share past data with medical institutions as needed, and the server securely supports this process. 【0185】 This system enables comprehensive health management that takes emotions into consideration, promoting appropriate responses that take both the user's health and emotions into account. 【0186】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0187】 Step 1: 【0188】 The device collects the user's biometric data using a smart device (e.g., a smartwatch). The input here is data related to the user's daily activities and physical condition. Specifically, heart rate, steps taken, and sleep patterns are collected in real time. The data is temporarily stored on the device via Bluetooth or Wi-Fi connection, and the collected data is later sent to a server. 【0189】 Step 2: 【0190】 The device transmits the collected biometric data to the server at predetermined intervals. The input is the biometric data stored on the device, and the output is the secure transmission of this data. The data is encrypted and transmitted via a protocol (e.g., HTTPS), thus maintaining security. 【0191】 Step 3: 【0192】 The server receives the transmitted biometric data and stores it in a database. The input is the data sent from the terminal, and the output is the data stored in the database. The information is organized using database systems such as MySQL or MongoDB and stored for each user profile. 【0193】 Step 4: 【0194】 The AI ​​model on the server analyzes emotional states using biometric data stored in a database. The input is the stored biometric data, and the output is an estimated result of the emotional state. Here, a natural language processing library (e.g., spaCy) is used to estimate emotions, and this information is further analyzed. Python is used, with NumPy and Pandas also being utilized. 【0195】 Step 5: 【0196】 The server detects anomalies based on estimated emotional states and biometric data, and generates a notification message. The input is anomaly and emotional information obtained from the analysis results, and the output is a notification message including a generated prompt. The generating AI creates a friendly message based on the prompt, tailored to the user's emotions. 【0197】 Step 6: 【0198】 The device receives notification messages sent from the server and displays them to the user. The input is the notification message from the server, and the output is the warning displayed on the user's device screen. The device uses this to inform the user of changes in their health status or any important notices. 【0199】 Step 7: 【0200】 Users review notifications and advice displayed on their devices and, if necessary, choose to improve their lifestyle or provide information to healthcare providers. Input is notifications from the device, while output is changes in the user's behavior and data sharing with healthcare providers. Based on the information provided, users can manage their own health. 【0201】 (Application Example 2) 【0202】 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". 【0203】 In an aging society, there is a need to comprehensively manage the health and emotional state of those receiving care and to respond quickly and appropriately in the event of an emergency. However, the current system focuses solely on health management, and the provision of information that takes emotional states into consideration is insufficient. As a result, the stress and anxiety of those receiving care are not properly addressed, and a challenge arises in providing adequate care. 【0204】 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. 【0205】 In this invention, the server includes equipment means for collecting personal biometric information, processing means for receiving the collected biometric information and storing it in an information recording device, and generation AI means equipped with an analysis device that analyzes the biometric information to detect abnormalities and generates a notification message that takes into account the emotional state in the event of an abnormality. This makes it possible to simultaneously manage the health and emotional state of the person being cared for and to quickly provide emotionally sensitive notifications in the event of an abnormality. 【0206】 A "device that collects personal biometric information" is a device that automatically acquires data about a user's physical condition, continuously collecting information such as heart rate, steps taken, and sleep patterns. 【0207】 A "processing device for storing information in an information recording device" is a device that has the function of receiving collected biological information and saving it to an information recording device. 【0208】 An "analytical device that analyzes biological information to detect abnormalities" is a device that analyzes collected biological information and detects data that deviates from the normal range as an abnormality. 【0209】 An "analysis device that generates notification messages considering emotional state" is a device that, when an anomaly is detected, takes into account the user's emotional state and creates a notification message using the most appropriate expression. 【0210】 "Generative AI" is an artificial intelligence technology used to automatically analyze and make decisions based on biometric information, and to generate appropriate advice and notifications. 【0211】 A "system that considers the health status of the person receiving care and notifies third parties as needed" is a system that analyzes collected biometric information and automatically notifies third parties such as nurses and family members of the situation when necessary. 【0212】 This invention is a system for comprehensively monitoring the health and emotions of a person receiving care. This system utilizes "devices that collect personal biometric information," such as smartwatches and smartphones. These devices continuously acquire biometric information such as heart rate, steps taken, and sleep patterns. A server receives this data and operates as a "processing device that stores the data in an information recording device." 【0213】 The server incorporates a "generative AI" that analyzes biometric information. Specifically, it uses Python to analyze data and executes the analysis on AWS®. The analysis device has the function of "analyzing biometric information and detecting anomalies," detecting anomalies when the data deviates from the normal range. It also has the function of "generating notification messages considering emotional states," and performs emotion analysis using Google Cloud's Natural Language API. 【0214】 When an anomaly is detected, the server uses Firebase Cloud Messaging to send a notification message to the device. This message takes into account the emotional state of the person being cared for. For example, if the heart rate is abnormally high, a message such as "Your heart rate is above normal. Try some ways to relax" will be sent. 【0215】 Furthermore, this system also functions as a system that "considers the health status of the person receiving care and notifies third parties as needed." This ensures that the situation is communicated to nurses and family members in a timely manner, enabling a swift response. When sharing information with medical institutions, it is sent in a secure data format. 【0216】 For example, if the care recipient's sleep pattern is irregular, the system will send advice such as, "Your sleep is irregular. Try to set aside some time to relax before going to bed." The following prompt statements are used as input to the generative AI model. 【0217】 Consider how to respond when the care recipient's heart rate exceeds normal. Develop advice that takes their emotional state into account. 【0218】 This invention will realize a system that supports the health management of those receiving care from an emotional perspective as well. 【0219】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0220】 Step 1: 【0221】 The device continuously acquires biometric information such as heart rate, steps, and sleep patterns via a smartwatch or smartphone. At this point, the input is biometric information collected by sensors, and the output is biometric data that is updated in real time. The device prepares to transmit this data to a server using wireless communication technology. 【0222】 Step 2: 【0223】 The server receives biometric information transmitted from the terminal and stores it in the information recording device. The input is biometric data transmitted from the terminal. As output, the server stores the received data in a database in an organized format. The information is sorted chronologically so that it can be used for later analysis. 【0224】 Step 3: 【0225】 The analysis device on the server performs a process to detect anomalies using the received biometric information. A Python script analyzes the data and compares it to past normal data. The input for this step is stored biometric data, and the output is a dataset of data identified as abnormal. Specifically, it checks for things like abnormally high heart rates and disturbances in sleep patterns. 【0226】 Step 4: 【0227】 The analysis device uses a generative AI model to infer the emotional state after detecting an anomaly and generates an appropriate notification message. Sentiment analysis is performed using Google Cloud's Natural Language API. The input is biometric data corresponding to the anomaly, and the output is a notification message combined with the emotional state. 【0228】 Step 5: 【0229】 The server sends a notification message generated using Firebase Cloud Messaging to the device. The input here is the notification message generated by the analysis device, and the output is the warning message displayed on the device. The device receives this message and provides the user with health advice, such as stress management techniques. 【0230】 Step 6: 【0231】 If necessary, the server shares anomalous data and associated emotional information with third parties. Inputs are the data detecting anomalies and their analysis results. Outputs are notifications to relevant parties or information in an appropriate data format sent to healthcare institutions. Specifically, this is used when medical professionals need to intervene. 【0232】 Step 7: 【0233】 Ultimately, users assess their emotional state based on the displayed messages and take corrective actions if necessary. The input is the notification messages displayed on the device, and the output is feedback based on the user's actions. This process enables users to better manage both their physical and emotional well-being. 【0234】 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. 【0235】 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. 【0236】 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. 【0237】 [Second Embodiment] 【0238】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0239】 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. 【0240】 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). 【0241】 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. 【0242】 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. 【0243】 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). 【0244】 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. 【0245】 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. 【0246】 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. 【0247】 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. 【0248】 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. 【0249】 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". 【0250】 This invention is designed to efficiently collect and analyze personal biometric data, enabling users to understand their own health status and respond quickly when abnormalities occur. Specifically, it is a system that integrates terminals, servers, and generating AI. 【0251】 Data collection and transmission: 【0252】 The device collects daily health data from the user's smart device, including heart rate, steps taken, and sleep patterns. This data is stored on the device in real time. 【0253】 The collected data is properly formatted and securely transmitted to the server on a regular basis. 【0254】 Data storage and analysis: 【0255】 The server stores the received data in a database. The data is organized chronologically and managed on a per-user basis. 【0256】 The generating AI runs on a server and continuously analyzes stored biometric data. This AI also refers to past data to determine normal patterns and anomalies. 【0257】 Anomaly detection and notification: 【0258】 When an anomaly is detected, the server immediately generates a notification message. This message includes the type of anomaly and the risk level in a user-friendly format. 【0259】 The message is sent to the device and presented to the user as a push notification. 【0260】 Advice provided by: 【0261】 The server also generates personalized health advice based on detected anomalies, including preventative measures and lifestyle improvements. 【0262】 These pieces of advice are intended to have a concrete impact on the user's daily life and will be displayed in a list on the user's device after being sent. 【0263】 Information sharing with medical institutions: 【0264】 If necessary, users can choose to share information with medical institutions. In this case, the server organizes past data into a medical record format and sends it to the medical institution via a secure communication channel. 【0265】 As a concrete example, consider the case where an abnormal heart rate is detected. In this scenario, the server generates a message indicating the abnormality and sends a notification to the terminal stating, "Your heart rate has recently been higher than normal. Please check if you are experiencing stress and consult a medical institution if necessary." It also provides advice that includes a 5-minute breathing exercise, helping the user understand the next steps to take. In this way, the invention comprehensively supports individual health management. 【0266】 The following describes the processing flow. 【0267】 Step 1: 【0268】 The device continuously collects biometric data from smart devices. This data includes heart rate, steps taken, and sleep patterns. This data is organized within the device and stored chronologically. 【0269】 Step 2: 【0270】 At regular intervals, the terminal prepares to send the accumulated data to the server. The data is encoded in a secure format and organized into packets for communication. This packetized data is sent to the server via the internet. 【0271】 Step 3: 【0272】 The server quickly saves received data to the database. The data is categorized by user and stored chronologically along with past data. 【0273】 Step 4: 【0274】 The stored data is analyzed by a generative AI running on the server. The generative AI compares it to normal data patterns to determine if anomalies exist. It also refers to past data to detect anomaly patterns. 【0275】 Step 5: 【0276】 When the server detects an abnormality, it creates a notification message in a format that is easy for the user to understand. The notification message includes the type of abnormality, the risk level, and recommended actions. 【0277】 Step 6: 【0278】 The created notification message is sent from the server to the terminal. The terminal receives this and presents it to the user as a push notification. 【0279】 Step 7: 【0280】 At the same time, the server generates personalized advice. The advice includes specific countermeasures and preventive measures for the abnormality. This advice is sent to the terminal and provided to the user. 【0281】 Step 8: 【0282】 If necessary, the user chooses to share past biometric data with a medical institution specified. The data is prepared in a secure format by the server and sent to the selected medical institution. 【0283】 (Example 1) 【0284】 Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0285】 In modern times, as the importance of health management increases, there is a demand for a system that can efficiently collect and analyze personal biometric information and enable prompt response when an abnormality occurs. Also, there is a lack of a method for providing appropriate health advice to users and supporting cooperation with medical institutions as needed. Furthermore, there is a need for a technology that can handle data seamlessly while protecting the privacy of users. 【0286】 The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Example 1 is realized by the following means. 【0287】 In this invention, the server includes mobile device means for aggregating personal biometric information, information processing device means for receiving the aggregated biometric information and storing it in a storage device, and generation algorithm means including an analysis unit for analyzing the biometric information to detect abnormalities and creating a notification signal when an abnormality occurs. As a result, it becomes possible to monitor an individual's health condition and respond promptly in case of an abnormality, enabling comprehensive health management. 【0288】 "Personal biometric information" is a general term for data indicating individual health conditions such as heart rate, number of steps, and sleep pattern. 【0289】 A "mobile device" is a device that can be carried by a user and has a function of collecting health data. 【0290】 An "information processing device" is a device for receiving the collected data and storing and managing it. 【0291】 A "storage device" is a storage device that accumulates the received data and arranges it in time series. 【0292】 A "generation algorithm" is a calculation method used to analyze the collected biometric information and detect abnormalities. 【0293】 An "analysis unit" is a part equipped with a function for analyzing data and discriminating abnormalities. 【0294】 A "notification signal" is a warning signal generated to notify the user of the detected abnormality. 【0295】 A "transmission unit" is a part having a function of transmitting the generated notification signal to the mobile device and displaying the notification to the user. 【0296】 The "Advice Department" is the part of the system that provides users with specific advice for maintaining their health based on the data it collects. 【0297】 A "medical facility" is an organization or institution where users can receive professional support regarding their health. 【0298】 This invention is a system that comprehensively supports individual health management, aggregating and analyzing individual biometric information to enable rapid response in the event of an abnormality. The system operates by integrating a portable device, an information processing device, and a generation algorithm. The following describes each component and its specific function. 【0299】 First, the terminal consists of portable devices such as smartphones and wearable devices. These devices collect data such as the user's heart rate, steps taken, and sleep patterns in real time. Specifically, heart rate sensors and accelerometers are used to acquire data. For example, if a user walks more than 10,000 steps every day, that number of steps will be recorded by the device. 【0300】 The collected data is transmitted to the server via Bluetooth or Wi-Fi. The server functions as an information processing device, storing the received data in a storage device. MySQL or PostgreSQL are suitable database systems. The data is organized chronologically and categorized by user. 【0301】 Next, a generative AI running on the server analyzes the stored data. Here, machine learning software such as TensorFlow and PyTorch is used to build a data analysis model. This generative algorithm detects data anomalies and generates notification signals. Predictive analysis based on past health data is also possible. 【0302】 When an abnormality is detected, the server automatically creates a notification message and sends it to the terminal. This message is presented to the user as a push notification. As an example, a message like "Your heart rate has been higher than normal recently. Please check if you are under stress and visit a medical institution if necessary." can be considered. 【0303】 Furthermore, health advice personalized by generative AI is generated and displayed in a list on the user's terminal. This advice includes specific suggestions such as a 5-minute breathing exercise. As an example of a prompt sentence, "Based on the user's health data, generate a prompt sentence for detecting abnormalities and providing advice. Include specific types of abnormalities and recommended advice." can be given. 【0304】 Finally, if necessary, the user can share their data with a medical facility. The server formats the data into a medical record and sends it to the medical institution using a secure API. This secure data sharing enables the user to receive more specialized health management. 【0305】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0306】 Step 1: 【0307】 The terminal collects biometric information from the user's smart device in real time. As inputs, there is data obtained from a heart rate sensor and an acceleration sensor. This data is output in forms such as heart rate, number of steps, and sleep pattern. As a specific operation, while the user wears the device and goes through daily life, the device periodically reads the data. 【0308】 Step 2: 【0309】 The device transmits the collected biometric information to the server via Bluetooth or Wi-Fi. The biometric data obtained in step 1 is used as input. This data is appropriately formatted and encrypted before being sent to the server. Specifically, data packets are generated at regular intervals and transmitted using a secure protocol. 【0310】 Step 3: 【0311】 The server stores the received biometric information in a storage device. It uses the received data as input and saves it to a database in a chronologically organized format. The output of this data is a dataset categorized by user, ready for future analysis. Specifically, it adds records to the database using an "INSERT INTO" query. 【0312】 Step 4: 【0313】 The generating AI on the server performs analysis using the stored data. The input is the biometric information stored in step 3, and the output is the anomaly detection result. The generating AI compares this with past data and applies machine learning algorithms to detect anomalies in the current biometric information. Specifically, the data is fed into the AI ​​model to detect anomalies and assess risks. 【0314】 Step 5: 【0315】 If an anomaly is detected, the server generates a notification signal and sends a notification to the terminal. The anomaly detection result is used as input. The output is a warning message in a user-friendly format. Specifically, a prompt sentence is created based on the analysis results of the generation AI, and this is sent to the terminal as a push notification. 【0316】 Step 6: 【0317】 The server generates personalized advice for the user based on the anomaly and sends it to the terminal. It uses the anomaly detection results as input, and the output is specific advice and suggestions for the user. Specifically, it lists health improvement suggestions based on the type of anomaly and presents them to the user's terminal. 【0318】 Step 7: 【0319】 If necessary, users can choose to share their biometric information with healthcare facilities. The input is the user's past biometric data, and the output is a medical record formatted for healthcare facilities. Specifically, the server sends data to healthcare institutions via a secure API and shares the data based on the user's consent. 【0320】 (Application Example 1) 【0321】 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." 【0322】 In systems that support individual health management through the collection and analysis of biometric information, there is a need to efficiently detect abnormalities and provide warnings and advice in an easily understandable format for users. However, previous technologies have faced challenges such as insufficient data collection and analysis, and limitations in the detection rate of abnormalities. Furthermore, providing personalized health advice closely tied to the user's lifestyle has been difficult with conventional approaches. 【0323】 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. 【0324】 In this invention, the server includes equipment means for collecting personal biometric information, computer means for receiving the collected biometric information and storing it in a storage medium, and artificial intelligence means equipped with an analysis unit that analyzes the biometric information to detect anomalies and generates notification information in the event of an anomaly. This enables efficient anomaly detection and the provision of personalized health advice. 【0325】 A "device that collects personal biometric information" is a device that acquires health-related data from users, and uses sensors to measure data such as heart rate, steps taken, and sleep patterns. 【0326】 A "computer that receives collected biometric information and stores it in a storage medium" is an electronic device that receives biometric information transmitted from another device and stores it in digital format; it is essentially a server with a database. 【0327】 "An artificial intelligence equipped with an analysis unit that analyzes biometric information to detect anomalies and generates notification information when anomalies occur" refers to software that continuously analyzes biometric data, identifies data that falls outside the normal range, and generates alerts. 【0328】 The "communication unit that sends notification information to devices and warns users" is a function that sends messages generated based on analysis results to devices and informs users through visual or auditory means. 【0329】 The "advice unit that generates and transmits personalized advice for abnormalities" is a system that creates and provides different health improvement measures and action suggestions for each user based on the detected abnormalities. 【0330】 "Means for allowing information sharing with medical institutions" refers to technology that enables the transmission of biometric information and analysis results to medical service providers via a reliable communication channel, if selected by the user. 【0331】 To implement this invention, multiple devices and software must work together to efficiently manage an individual's health. This system mainly consists of devices that collect biometric information in real time, a server that stores and analyzes the data, a terminal that notifies the user based on the analysis results, and artificial intelligence that generates personalized advice. 【0332】 The server receives biometric information transmitted by users and stores it in a database. This data is managed chronologically and prepared for subsequent analysis. A generative AI model runs on the server, analyzing the biometric information to detect abnormal patterns. In this process, past data is also referenced to determine anomalies with high accuracy. 【0333】 If an anomaly is detected, the server generates notification information and sends it to the device. The device immediately relays this information to the user and issues an appropriate warning. At this stage, the user can understand their health status and learn about necessary countermeasures. The server also uses AI to generate personalized health advice based on the anomaly and sends it to the device for display to the user. 【0334】 For example, consider a scenario where a user's heart rate suddenly increases while they are indoors. The server detects this anomaly and sends a notification to the user's device such as, "Your heart rate is higher than normal. Take a short break and try deep breathing." It also provides further advice, such as, "To reduce stress, try a 3-minute deep breathing exercise," to help the user respond quickly. 【0335】 An example of a prompt message is: "Analyze the user's heart rate data, generate a warning if it exceeds the normal range, and suggest appropriate mitigation measures." In this way, the system comprehensively supports users' health management through real-time monitoring of health data, rapid anomaly detection, and personalized assistance. 【0336】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0337】 Step 1: 【0338】 The device collects biometric information from the user, such as heart rate, steps taken, and sleep patterns. It processes the data acquired using sensors in real time and stores it in a buffer. The input is biometric information, and the output is formatted data. For security reasons, the data is encrypted within the device. 【0339】 Step 2: 【0340】 The device transmits collected biometric information to the server. The data is transmitted using a secure communication protocol. The input is encrypted biometric information, and the output is a notification that the data transfer to the server is complete. Communication is performed periodically to ensure real-time performance. 【0341】 Step 3: 【0342】 The server stores the received biometric information in a database. The data is organized chronologically and managed on a per-user basis. The input is the received biometric information, and the output is the organized information in the database. The stored data serves as foundational information for subsequent analysis. 【0343】 Step 4: 【0344】 The AI ​​within the server analyzes biometric information to check for abnormalities. It also references past data to determine if an anomaly is detected. The input is organized biometric information, and the output is the anomaly detection result. This process utilizes a pattern recognition algorithm, enabling highly accurate anomaly detection. 【0345】 Step 5: 【0346】 The server generates notification information and sends it to the terminal when an anomaly is detected. The generating AI automatically determines the details of the anomaly and its risk level, and formats the information. The input is the anomaly detection result, and the output is the notification information to be displayed on the terminal. 【0347】 Step 6: 【0348】 The device displays received notification information to the user. It issues alerts via screen and audio to prompt the user for a quick response. The input is notification information sent from the server, and the output is a warning message to the user. The notification is converted into a user-friendly format. 【0349】 Step 7: 【0350】 The server generates personalized advice based on the anomaly and sends it to the terminal. The generating AI constructs customized advice for each user based on the prompt text. The input is the anomaly detection result and past response history, and the output is a specific action suggestion. 【0351】 Step 8: 【0352】 The terminal displays the received advice to the user. The display follows a notification message, and visual and auditory volume adjustments are also considered. The input is advice information sent from the server, and the output is specific action suggestions for the user. 【0353】 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. 【0354】 This invention is a system that collects and analyzes individual biometric data to comprehensively manage a user's health and emotions, enabling rapid response in the event of an abnormality. In particular, by incorporating an emotion engine, it recognizes the user's emotional state and considers emotions when providing health advice, thereby achieving more effective health management. 【0355】 Data collection and transmission: 【0356】 The device continuously acquires biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. Furthermore, the device monitors the user's usage patterns and input data, collecting elements to infer their emotional state. This data is compiled over a certain period and transmitted to a server. 【0357】 Data storage and analysis: 【0358】 The server stores the received biometric data in a database and organizes it according to the user's profile. The emotion engine uses this data to estimate the user's emotions and feeds the analysis results back to the generating AI. 【0359】 Anomaly detection and notification: 【0360】 The server's AI analyzes biometric data, and if an anomaly is detected, it generates a notification message that also takes into account the user's emotional state. This message includes language that responds to the user's emotions, presenting the anomaly and recommended actions in a more user-friendly way. 【0361】 Advice provided by: 【0362】 The server generates personalized advice, incorporating emotion recognition from the emotion engine to create more personalized suggestions. This advice is sent to the device, allowing the user to receive lifestyle improvement suggestions optimized for them. 【0363】 Emotional feedback and medical information sharing: 【0364】 Users can monitor their own emotional state based on the emotional feedback provided. Furthermore, if abnormalities or persistent emotional changes persist, they can choose to share their past biometric data with a healthcare provider. The server provides this information to the healthcare provider in a secure and appropriate format. 【0365】 As a concrete example, consider a case where a user's heart rate becomes abnormally high due to stress. In this case, the emotion engine estimates that the user may be experiencing stress, and the server sends a notification stating, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend trying to take deep breaths or taking a short break." By implementing this invention, users can receive comprehensive management that takes into account not only their physical health but also their emotional well-being. 【0366】 The following describes the processing flow. 【0367】 Step 1: 【0368】 The device continuously collects biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. It also collects information such as the user's input actions and device usage patterns, which are used as data for inferring emotions. 【0369】 Step 2: 【0370】 The collected biometric data and usage pattern data are compiled at predetermined time intervals and transmitted securely to the server. The transmission is performed using an encrypted protocol to prevent data leakage. 【0371】 Step 3: 【0372】 The server stores the received data in a database. The data is categorized by user, and the history is managed in chronological order. The server then uses an emotion engine to perform analysis to infer the user's emotional state. 【0373】 Step 4: 【0374】 The generating AI operates on a server, analyzing the received biometric data and comparing it to normal health conditions to determine if there are any abnormalities. It also acquires additional information, such as the emotional state estimated by the emotion engine. 【0375】 Step 5: 【0376】 If an anomaly is detected, the server considers the nature of the anomaly and the user's emotional state to generate a message. Because it includes emotionally appropriate language, the notification is easy for the user to understand and is delivered in a sensitive manner. 【0377】 Step 6: 【0378】 The generated notification message is sent from the server to the device, which then presents it to the user as a push notification. The user immediately receives information about the anomaly and recommended actions through the device. 【0379】 Step 7: 【0380】 The server generates personalized advice optimized for the user based on the results of the generative AI and emotion engine. This advice includes suggestions that can be directly applied to the user's daily life. 【0381】 Step 8: 【0382】 If necessary, users can choose to share information with healthcare institutions. The server will follow the user's instructions and prepare to provide past biometric data and emotional information to healthcare institutions in a secure format. 【0383】 Step 9: 【0384】 Finally, the device provides the user with feedback regarding the emotional state estimated by the emotion engine. This feedback allows the user to understand their own emotions and adjust their behavior as needed. 【0385】 (Example 2) 【0386】 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". 【0387】 In modern society, there is a need for comprehensive management of individual health conditions, particularly for rapid anomaly detection and response that takes emotional states into consideration. However, existing systems struggle to effectively combine and analyze biometric data and emotional states, resulting in insufficient personalized responses. Furthermore, while seamless information sharing with medical institutions is required, data security and user privacy remain challenges. 【0388】 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. 【0389】 In this invention, the server includes a device means for collecting and periodically transmitting an individual's biometric data in batches; an information processing device means for receiving the collected biometric data and securely storing it in a database; and a generative AI means for estimating emotions using natural language processing when analyzing the biometric data, and generating anomaly detection and notification messages. This enables comprehensive analysis combining an individual's biometric data and emotional state, as well as rapid anomaly detection, and ensures secure data sharing with medical institutions. 【0390】 A "device that collects and periodically transmits personal biometric data" refers to a combination of hardware and software that acquires personal health data through smart devices and other means, and securely transmits it via a communication network at regular intervals. 【0391】 An "information processing device that receives collected biometric data and securely stores it in a database" is a server system that receives biometric data transmitted from a terminal, organizes this data appropriately, and stores it securely. 【0392】 "Generative AI that uses natural language processing to estimate emotions when analyzing biometric data and generates anomaly detection and notification messages" refers to an artificial intelligence system that analyzes an individual's biometric data while simultaneously evaluating their emotional state using natural language processing technology, and generates notifications based on that information if an anomaly is detected. 【0393】 A "communication device that sends notification messages and issues warnings using expressions based on the user's emotional state" is a device that sends messages generated in a way that takes the user's emotional state into consideration to a terminal, providing attention and warnings. 【0394】 A "personalized health improvement suggestion generator that sends personalized health advice to user terminals" is a system that creates customized health advice based on each user's health condition and emotions, and sends it to the user's terminal. 【0395】 "Means of allowing information sharing with medical institutions and providing information securely" refers to processes and technologies that enable users to share their selected biometric data and analysis results with medical institutions, while ensuring data security and user privacy. 【0396】 To implement this invention, a system is needed that collects and analyzes individual biometric data and provides advice tailored to specific situations. Specific embodiments are described below. 【0397】 First, the terminal uses devices such as smartwatches and smartphones to acquire biometric data such as the user's heart rate, steps taken, and sleep patterns. These devices have communication capabilities that collect information via Bluetooth or Wi-Fi and periodically send the data to a server. 【0398】 The server is a device for securely storing received biometric data in a database. At this stage, the data is organized according to the individual's profile and managed using a database system such as MySQL or MongoDB. 【0399】 A server equipped with a generative AI model infers the user's emotional state based on accumulated biometric data and usage patterns and text data obtained from the terminal. Pandas and NumPy in Python are used for data analysis, and libraries such as NLTK and spaCy are utilized for natural language processing. If an anomaly is detected in the user through this emotion analysis, the generative AI creates an emotionally sensitive notification message based on the prompt text. 【0400】 For example, if the generating AI detects that the user's heart rate is higher than normal and that they are under stress, it will generate a prompt such as, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend you try taking some deep breaths or take a short break." 【0401】 Based on this information notified to their device, users can take specific actions to improve their health. Furthermore, users can share past data with medical institutions as needed, and the server securely supports this process. 【0402】 This system enables comprehensive health management that takes emotions into consideration, promoting appropriate responses that consider both the user's health and emotions. 【0403】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0404】 Step 1: 【0405】 The device collects the user's biometric data using a smart device (e.g., a smartwatch). The input here is data related to the user's daily activities and physical condition. Specifically, heart rate, steps taken, and sleep patterns are collected in real time. The data is temporarily stored on the device via Bluetooth or Wi-Fi connection, and the collected data is later sent to a server. 【0406】 Step 2: 【0407】 The device transmits the collected biometric data to the server at predetermined intervals. The input is the biometric data stored on the device, and the output is the secure transmission of this data. The data is encrypted and transmitted via a protocol (e.g., HTTPS), thus maintaining security. 【0408】 Step 3: 【0409】 The server receives the transmitted biometric data and stores it in a database. The input is the data sent from the terminal, and the output is the data stored in the database. The information is organized using database systems such as MySQL or MongoDB and stored for each user profile. 【0410】 Step 4: 【0411】 The AI ​​model on the server analyzes emotional states using biometric data stored in a database. The input is the stored biometric data, and the output is an estimated result of the emotional state. Here, a natural language processing library (e.g., spaCy) is used to estimate emotions, and this information is further analyzed. Python is used, with NumPy and Pandas also being utilized. 【0412】 Step 5: 【0413】 The server detects anomalies based on estimated emotional states and biometric data, and generates a notification message. The input is anomaly and emotional information obtained from the analysis results, and the output is a notification message including a generated prompt. The generating AI creates a friendly message based on the prompt, tailored to the user's emotions. 【0414】 Step 6: 【0415】 The device receives notification messages sent from the server and displays them to the user. The input is the notification message from the server, and the output is the warning displayed on the user's device screen. The device uses this to inform the user of changes in their health status or any important notices. 【0416】 Step 7: 【0417】 Users review notifications and advice displayed on their devices and, if necessary, choose to improve their lifestyle or provide information to healthcare providers. Input is notifications from the device, while output is changes in the user's behavior and data sharing with healthcare providers. Based on the information provided, users can manage their own health. 【0418】 (Application Example 2) 【0419】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0420】 In an aging society, there is a need to comprehensively manage the health and emotional state of those receiving care and to respond quickly and appropriately in the event of an emergency. However, the current system focuses solely on health management, and the provision of information that takes emotional states into consideration is insufficient. As a result, the stress and anxiety of those receiving care are not properly addressed, and a challenge arises in providing adequate care. 【0421】 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. 【0422】 In this invention, the server includes equipment means for collecting personal biometric information, processing means for receiving the collected biometric information and storing it in an information recording device, and generation AI means equipped with an analysis device that analyzes the biometric information to detect abnormalities and generates a notification message that takes into account the emotional state in the event of an abnormality. This makes it possible to simultaneously manage the health and emotional state of the person being cared for and to quickly provide emotionally sensitive notifications in the event of an abnormality. 【0423】 A "device that collects personal biometric information" is a device that automatically acquires data about a user's physical condition, continuously collecting information such as heart rate, steps taken, and sleep patterns. 【0424】 A "processing device for storing information in an information recording device" is a device that has the function of receiving collected biological information and saving it to an information recording device. 【0425】 An "analytical device that analyzes biological information to detect abnormalities" is a device that analyzes collected biological information and detects data that deviates from the normal range as an abnormality. 【0426】 An "analysis device that generates notification messages considering emotional state" is a device that, when an anomaly is detected, takes into account the user's emotional state and creates a notification message using the most appropriate expression. 【0427】 "Generative AI" is an artificial intelligence technology used to automatically analyze and make decisions based on biometric information, and to generate appropriate advice and notifications. 【0428】 A "system that considers the health status of the person receiving care and notifies third parties as needed" is a system that analyzes collected biometric information and automatically notifies third parties such as nurses and family members of the situation when necessary. 【0429】 This invention is a system for comprehensively monitoring the health and emotions of a person receiving care. This system utilizes "devices that collect personal biometric information," such as smartwatches and smartphones. These devices continuously acquire biometric information such as heart rate, steps taken, and sleep patterns. A server receives this data and operates as a "processing device that stores the data in an information recording device." 【0430】 The server incorporates a "generative AI" that analyzes biometric data. Specifically, it uses Python to analyze the data and executes the analysis on AWS. The analysis device has the function of "analyzing biometric data and detecting anomalies," detecting anomalies when the data deviates from the normal range. It also has the function of "generating notification messages considering emotional states," and performs emotion analysis using Google Cloud's Natural Language API. 【0431】 When an anomaly is detected, the server uses Firebase Cloud Messaging to send a notification message to the device. This message takes into account the emotional state of the person being cared for. For example, if the heart rate is abnormally high, a message such as "Your heart rate is above normal. Try some ways to relax" will be sent. 【0432】 Furthermore, this system also functions as a system that "considers the health status of the person receiving care and notifies third parties as needed." This ensures that the situation is communicated to nurses and family members in a timely manner, enabling a swift response. When sharing information with medical institutions, it is sent in a secure data format. 【0433】 For example, if the care recipient's sleep pattern is irregular, the system will send advice such as, "Your sleep is irregular. Try to set aside some time to relax before going to bed." The following prompt statements are used as input to the generative AI model. 【0434】 Consider how to respond when the care recipient's heart rate exceeds normal. Develop advice that takes their emotional state into account. 【0435】 This invention will realize a system that supports the health management of those receiving care from an emotional perspective as well. 【0436】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0437】 Step 1: 【0438】 The device continuously acquires biometric information such as heart rate, steps, and sleep patterns via a smartwatch or smartphone. At this point, the input is biometric information collected by sensors, and the output is biometric data that is updated in real time. The device prepares to transmit this data to a server using wireless communication technology. 【0439】 Step 2: 【0440】 The server receives biometric information transmitted from the terminal and stores it in the information recording device. The input is biometric data transmitted from the terminal. As output, the server stores the received data in a database in an organized format. The information is sorted chronologically so that it can be used for later analysis. 【0441】 Step 3: 【0442】 The analysis device on the server performs a process to detect anomalies using the received biometric information. A Python script analyzes the data and compares it to past normal data. The input for this step is stored biometric data, and the output is a dataset of data identified as abnormal. Specifically, it checks for things like abnormally high heart rates and disturbances in sleep patterns. 【0443】 Step 4: 【0444】 The analysis device uses a generative AI model to infer the emotional state after detecting an anomaly and generates an appropriate notification message. Sentiment analysis is performed using Google Cloud's Natural Language API. The input is biometric data corresponding to the anomaly, and the output is a notification message combined with the emotional state. 【0445】 Step 5: 【0446】 The server sends a notification message generated using Firebase Cloud Messaging to the device. The input here is the notification message generated by the analysis device, and the output is the warning message displayed on the device. The device receives this message and provides the user with health advice, such as stress management techniques. 【0447】 Step 6: 【0448】 If necessary, the server shares anomalous data and associated emotional information with third parties. Inputs are the data detecting anomalies and their analysis results. Outputs are notifications to relevant parties or information in an appropriate data format sent to healthcare institutions. Specifically, this is used when medical professionals need to intervene. 【0449】 Step 7: 【0450】 Ultimately, users assess their emotional state based on the displayed messages and take corrective actions if necessary. The input is the notification messages displayed on the device, and the output is feedback based on the user's actions. This process enables users to better manage both their physical and emotional well-being. 【0451】 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. 【0452】 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. 【0453】 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. 【0454】 [Third Embodiment] 【0455】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0456】 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. 【0457】 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). 【0458】 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. 【0459】 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. 【0460】 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). 【0461】 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. 【0462】 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. 【0463】 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. 【0464】 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. 【0465】 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. 【0466】 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". 【0467】 This invention is designed to efficiently collect and analyze personal biometric data, enabling users to understand their own health status and respond quickly when abnormalities occur. Specifically, it is a system that integrates terminals, servers, and generating AI. 【0468】 Data collection and transmission: 【0469】 The device collects daily health data from the user's smart device, including heart rate, steps taken, and sleep patterns. This data is stored on the device in real time. 【0470】 The collected data is properly formatted and securely transmitted to the server on a regular basis. 【0471】 Data storage and analysis: 【0472】 The server stores the received data in a database. The data is organized chronologically and managed on a per-user basis. 【0473】 The generating AI runs on a server and continuously analyzes stored biometric data. This AI also refers to past data to determine normal patterns and anomalies. 【0474】 Anomaly detection and notification: 【0475】 When an anomaly is detected, the server immediately generates a notification message. This message includes the type of anomaly and the risk level in a user-friendly format. 【0476】 The message is sent to the device and presented to the user as a push notification. 【0477】 Advice provided by: 【0478】 The server also generates personalized health advice based on detected anomalies, including preventative measures and lifestyle improvements. 【0479】 These pieces of advice are intended to have a concrete impact on the user's daily life and will be displayed in a list on the user's device after being sent. 【0480】 Information sharing with medical institutions: 【0481】 If necessary, users can choose to share information with medical institutions. In this case, the server organizes past data into a medical record format and sends it to the medical institution via a secure communication channel. 【0482】 As a concrete example, consider the case where an abnormal heart rate is detected. In this scenario, the server generates a message indicating the abnormality and sends a notification to the terminal stating, "Your heart rate has recently been higher than normal. Please check if you are experiencing stress and consult a medical institution if necessary." It also provides advice that includes a 5-minute breathing exercise, helping the user understand the next steps to take. In this way, the invention comprehensively supports individual health management. 【0483】 The following describes the processing flow. 【0484】 Step 1: 【0485】 The device continuously collects biometric data from smart devices. This data includes heart rate, steps taken, and sleep patterns. This data is organized within the device and stored chronologically. 【0486】 Step 2: 【0487】 At regular intervals, the terminal prepares to send the accumulated data to the server. The data is encoded in a secure format and organized into packets for communication. This packetized data is sent to the server via the internet. 【0488】 Step 3: 【0489】 The server quickly saves received data to the database. The data is categorized by user and stored chronologically along with past data. 【0490】 Step 4: 【0491】 The stored data is analyzed by a generative AI running on the server. The generative AI compares it to normal data patterns to determine if anomalies exist. It also refers to past data to detect anomaly patterns. 【0492】 Step 5: 【0493】 When the server detects an anomaly, it generates a notification message in a user-friendly format. The notification message includes the type of anomaly, the risk level, and recommended actions. 【0494】 Step 6: 【0495】 The generated notification message is sent from the server to the device. The device receives it and presents it to the user as a push notification. 【0496】 Step 7: 【0497】 Simultaneously, the server generates personalized advice. This advice includes specific countermeasures and preventative measures for anomalies. This advice is sent to the terminal and provided to the user. 【0498】 Step 8: 【0499】 If necessary, users can choose to share their past biometric data with designated healthcare institutions. The data is then processed in a secure format by the server and transmitted to the selected healthcare institution. 【0500】 (Example 1) 【0501】 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." 【0502】 In today's world, where health management is increasingly important, there is a need for systems that can efficiently collect and analyze personal biometric information and enable rapid response when abnormalities occur. Furthermore, there is a lack of methods to provide users with appropriate health advice and support collaboration with medical institutions as needed. Additionally, there is a need for technology that can handle data seamlessly while protecting user privacy. 【0503】 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. 【0504】 In this invention, the server includes a portable device means for aggregating an individual's biometric information, an information processing device means for receiving the aggregated biometric information and storing it in a storage device, and a generation algorithm means equipped with an analysis unit that analyzes the biometric information to detect abnormalities and creates a notification signal in the event of an abnormality. This enables monitoring of an individual's health status and rapid response in the event of an abnormality, thereby realizing comprehensive health management. 【0505】 "Personal biometric information" is a general term for data that indicates an individual's health status, such as heart rate, steps taken, and sleep patterns. 【0506】 A "portable device" is a device that a user can carry with them and that has the function of collecting health data. 【0507】 An "information processing device" is a device that receives collected data and stores and manages it. 【0508】 A "storage device" is a memory device that stores received data and organizes it chronologically. 【0509】 A "generative algorithm" is a computational method used to analyze collected biological information and detect anomalies. 【0510】 The "analysis unit" is the part of the system equipped with functions for analyzing data and identifying anomalies. 【0511】 A "notification signal" is a warning signal generated to inform the user of a detected anomaly. 【0512】 The "transmitter" is the part that has the function of sending the generated notification signal to the mobile device and displaying the notification to the user. 【0513】 The "Advice Department" is the part of the system that provides users with specific advice for maintaining their health based on the data it collects. 【0514】 A "medical facility" is an organization or institution where users can receive professional support regarding their health. 【0515】 This invention is a system that comprehensively supports individual health management, aggregating and analyzing individual biometric information to enable rapid response in the event of an abnormality. The system operates by integrating a portable device, an information processing device, and a generation algorithm. The following describes each component and its specific function. 【0516】 First, the terminal consists of portable devices such as smartphones and wearable devices. These devices collect data such as the user's heart rate, steps taken, and sleep patterns in real time. Specifically, heart rate sensors and accelerometers are used to acquire data. For example, if a user walks more than 10,000 steps every day, that number of steps will be recorded by the device. 【0517】 The collected data is transmitted to the server via Bluetooth or Wi-Fi. The server functions as an information processing device, storing the received data in a storage device. MySQL or PostgreSQL are suitable database systems. The data is organized chronologically and categorized by user. 【0518】 Next, a generative AI running on the server analyzes the stored data. Here, machine learning software such as TensorFlow and PyTorch is used to build a data analysis model. This generative algorithm detects data anomalies and generates notification signals. Predictive analysis based on past health data is also possible. 【0519】 When an anomaly is detected, the server automatically creates a notification message and sends it to the device. This message is presented to the user as a push notification. For example, it might say, "Your heart rate has been higher than normal recently. Please check if you are experiencing stress and seek medical attention if necessary." 【0520】 Furthermore, personalized health advice is generated by the AI ​​and displayed in a list on the user's device. This advice includes specific suggestions, such as a 5-minute breathing exercise. An example of a prompt message is: "Generate a prompt message to detect anomalies and provide advice based on the user's health data. Include the specific type of anomaly and recommended advice." 【0521】 Ultimately, users can share their data with healthcare facilities as needed. The server organizes the data into a medical record format and sends it to healthcare institutions using a secure API. This secure data sharing allows users to receive more specialized health management. 【0522】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0523】 Step 1: 【0524】 The device collects biometric information in real time from the user's smart device. Inputs include data from heart rate sensors and accelerometers. This data is output in the form of heart rate, steps taken, sleep patterns, etc. Specifically, the device periodically reads data as the user wears it and goes about their daily life. 【0525】 Step 2: 【0526】 The device transmits the collected biometric information to the server via Bluetooth or Wi-Fi. The biometric data obtained in step 1 is used as input. This data is appropriately formatted and encrypted before being sent to the server. Specifically, data packets are generated at regular intervals and transmitted using a secure protocol. 【0527】 Step 3: 【0528】 The server stores the received biometric information in a storage device. It uses the received data as input and saves it to a database in a chronologically organized format. The output of this data is a dataset categorized by user, ready for future analysis. Specifically, it adds records to the database using an "INSERT INTO" query. 【0529】 Step 4: 【0530】 The generating AI on the server performs analysis using the stored data. The input is the biometric information stored in step 3, and the output is the anomaly detection result. The generating AI compares this with past data and applies machine learning algorithms to detect anomalies in the current biometric information. Specifically, the data is fed into the AI ​​model to detect anomalies and assess risks. 【0531】 Step 5: 【0532】 If an anomaly is detected, the server generates a notification signal and sends a notification to the terminal. The anomaly detection result is used as input. The output is a warning message in a user-friendly format. Specifically, a prompt sentence is created based on the analysis results of the generation AI, and this is sent to the terminal as a push notification. 【0533】 Step 6: 【0534】 The server generates personalized advice for the user based on the anomaly and sends it to the terminal. It uses the anomaly detection results as input, and the output is specific advice and suggestions for the user. Specifically, it lists health improvement suggestions based on the type of anomaly and presents them to the user's terminal. 【0535】 Step 7: 【0536】 If necessary, users can choose to share their biometric information with healthcare facilities. The input is the user's past biometric data, and the output is a medical record formatted for healthcare facilities. Specifically, the server sends data to healthcare institutions via a secure API and shares the data based on the user's consent. 【0537】 (Application Example 1) 【0538】 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." 【0539】 In systems that support individual health management through the collection and analysis of biometric information, there is a need to efficiently detect abnormalities and provide warnings and advice in an easily understandable format for users. However, previous technologies have faced challenges such as insufficient data collection and analysis, and limitations in the detection rate of abnormalities. Furthermore, providing personalized health advice closely tied to the user's lifestyle has been difficult with conventional approaches. 【0540】 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. 【0541】 In this invention, the server includes equipment means for collecting personal biometric information, computer means for receiving the collected biometric information and storing it in a storage medium, and artificial intelligence means equipped with an analysis unit that analyzes the biometric information to detect anomalies and generates notification information in the event of an anomaly. This enables efficient anomaly detection and the provision of personalized health advice. 【0542】 A "device that collects personal biometric information" is a device that acquires health-related data from users, and uses sensors to measure data such as heart rate, steps taken, and sleep patterns. 【0543】 A "computer that receives collected biometric information and stores it in a storage medium" is an electronic device that receives biometric information transmitted from another device and stores it in digital format; it is essentially a server with a database. 【0544】 "An artificial intelligence equipped with an analysis unit that analyzes biometric information to detect anomalies and generates notification information when anomalies occur" refers to software that continuously analyzes biometric data, identifies data that falls outside the normal range, and generates alerts. 【0545】 The "communication unit that sends notification information to devices and warns users" is a function that sends messages generated based on analysis results to devices and informs users through visual or auditory means. 【0546】 The "advice unit that generates and transmits personalized advice for abnormalities" is a system that creates and provides different health improvement measures and action suggestions for each user based on the detected abnormalities. 【0547】 "Means for allowing information sharing with medical institutions" refers to technology that enables the transmission of biometric information and analysis results to medical service providers via a reliable communication channel, if selected by the user. 【0548】 To implement this invention, multiple devices and software must work together to efficiently manage an individual's health. This system mainly consists of devices that collect biometric information in real time, a server that stores and analyzes the data, a terminal that notifies the user based on the analysis results, and artificial intelligence that generates personalized advice. 【0549】 The server receives biometric information transmitted by users and stores it in a database. This data is managed chronologically and prepared for subsequent analysis. A generative AI model runs on the server, analyzing the biometric information to detect abnormal patterns. In this process, past data is also referenced to determine anomalies with high accuracy. 【0550】 If an anomaly is detected, the server generates notification information and sends it to the device. The device immediately relays this information to the user and issues an appropriate warning. At this stage, the user can understand their health status and learn about necessary countermeasures. The server also uses AI to generate personalized health advice based on the anomaly and sends it to the device for display to the user. 【0551】 For example, consider a scenario where a user's heart rate suddenly increases while they are indoors. The server detects this anomaly and sends a notification to the user's device such as, "Your heart rate is higher than normal. Take a short break and try deep breathing." It also provides further advice, such as, "To reduce stress, try a 3-minute deep breathing exercise," to help the user respond quickly. 【0552】 An example of a prompt message is: "Analyze the user's heart rate data, generate a warning if it exceeds the normal range, and suggest appropriate mitigation measures." In this way, the system comprehensively supports users' health management through real-time monitoring of health data, rapid anomaly detection, and personalized assistance. 【0553】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0554】 Step 1: 【0555】 The device collects biometric information from the user, such as heart rate, steps taken, and sleep patterns. It processes the data acquired using sensors in real time and stores it in a buffer. The input is biometric information, and the output is formatted data. For security reasons, the data is encrypted within the device. 【0556】 Step 2: 【0557】 The device transmits collected biometric information to the server. The data is transmitted using a secure communication protocol. The input is encrypted biometric information, and the output is a notification that the data transfer to the server is complete. Communication is performed periodically to ensure real-time performance. 【0558】 Step 3: 【0559】 The server stores the received biometric information in a database. The data is organized chronologically and managed on a per-user basis. The input is the received biometric information, and the output is the organized information in the database. The stored data serves as foundational information for subsequent analysis. 【0560】 Step 4: 【0561】 The AI ​​within the server analyzes biometric information to check for abnormalities. It also references past data to determine if an anomaly is detected. The input is organized biometric information, and the output is the anomaly detection result. This process utilizes a pattern recognition algorithm, enabling highly accurate anomaly detection. 【0562】 Step 5: 【0563】 The server generates notification information and sends it to the terminal when an anomaly is detected. The generating AI automatically determines the details of the anomaly and its risk level, and formats the information. The input is the anomaly detection result, and the output is the notification information to be displayed on the terminal. 【0564】 Step 6: 【0565】 The device displays received notification information to the user. It issues alerts via screen and audio to prompt the user for a quick response. The input is notification information sent from the server, and the output is a warning message to the user. The notification is converted into a user-friendly format. 【0566】 Step 7: 【0567】 The server generates personalized advice based on the anomaly and sends it to the terminal. The generating AI constructs customized advice for each user based on the prompt text. The input is the anomaly detection result and past response history, and the output is a specific action suggestion. 【0568】 Step 8: 【0569】 The terminal displays the received advice to the user. The display follows a notification message, and visual and auditory volume adjustments are also considered. The input is advice information sent from the server, and the output is specific action suggestions for the user. 【0570】 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. 【0571】 This invention is a system that collects and analyzes individual biometric data to comprehensively manage a user's health and emotions, enabling rapid response in the event of an abnormality. In particular, by incorporating an emotion engine, it recognizes the user's emotional state and considers emotions when providing health advice, thereby achieving more effective health management. 【0572】 Data collection and transmission: 【0573】 The device continuously acquires biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. Furthermore, the device monitors the user's usage patterns and input data, collecting elements to infer their emotional state. This data is compiled over a certain period and transmitted to a server. 【0574】 Data storage and analysis: 【0575】 The server stores the received biometric data in a database and organizes it according to the user's profile. The emotion engine uses this data to estimate the user's emotions and feeds the analysis results back to the generating AI. 【0576】 Anomaly detection and notification: 【0577】 The server's AI analyzes biometric data, and if an anomaly is detected, it generates a notification message that also takes into account the user's emotional state. This message includes language that responds to the user's emotions, presenting the anomaly and recommended actions in a more user-friendly way. 【0578】 Advice provided by: 【0579】 The server generates personalized advice, incorporating emotion recognition from the emotion engine to create more personalized suggestions. This advice is sent to the device, allowing the user to receive lifestyle improvement suggestions optimized for them. 【0580】 Emotional feedback and medical information sharing: 【0581】 Users can monitor their own emotional state based on the emotional feedback provided. Furthermore, if abnormalities or persistent emotional changes persist, they can choose to share their past biometric data with a healthcare provider. The server provides this information to the healthcare provider in a secure and appropriate format. 【0582】 As a concrete example, consider a case where a user's heart rate becomes abnormally high due to stress. In this case, the emotion engine estimates that the user may be experiencing stress, and the server sends a notification stating, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend trying to take deep breaths or taking a short break." By implementing this invention, users can receive comprehensive management that takes into account not only their physical health but also their emotional well-being. 【0583】 The following describes the processing flow. 【0584】 Step 1: 【0585】 The device continuously collects biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. It also collects information such as the user's input actions and device usage patterns, which are used as data for inferring emotions. 【0586】 Step 2: 【0587】 The collected biometric data and usage pattern data are compiled at predetermined time intervals and transmitted securely to the server. The transmission is performed using an encrypted protocol to prevent data leakage. 【0588】 Step 3: 【0589】 The server stores the received data in a database. The data is categorized by user, and the history is managed in chronological order. The server then uses an emotion engine to perform analysis to infer the user's emotional state. 【0590】 Step 4: 【0591】 The generating AI operates on a server, analyzing the received biometric data and comparing it to normal health conditions to determine if there are any abnormalities. It also acquires additional information, such as the emotional state estimated by the emotion engine. 【0592】 Step 5: 【0593】 If an anomaly is detected, the server considers the nature of the anomaly and the user's emotional state to generate a message. Because it includes emotionally appropriate language, the notification is easy for the user to understand and is delivered in a sensitive manner. 【0594】 Step 6: 【0595】 The generated notification message is sent from the server to the device, which then presents it to the user as a push notification. The user immediately receives information about the anomaly and recommended actions through the device. 【0596】 Step 7: 【0597】 The server generates personalized advice optimized for the user based on the results of the generative AI and emotion engine. This advice includes suggestions that can be directly applied to the user's daily life. 【0598】 Step 8: 【0599】 If necessary, users can choose to share information with healthcare institutions. The server will follow the user's instructions and prepare to provide past biometric data and emotional information to healthcare institutions in a secure format. 【0600】 Step 9: 【0601】 Finally, the device provides the user with feedback regarding the emotional state estimated by the emotion engine. This feedback allows the user to understand their own emotions and adjust their behavior as needed. 【0602】 (Example 2) 【0603】 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." 【0604】 In modern society, there is a need for comprehensive management of individual health conditions, particularly for rapid anomaly detection and response that takes emotional states into consideration. However, existing systems struggle to effectively combine and analyze biometric data and emotional states, resulting in insufficient personalized responses. Furthermore, while seamless information sharing with medical institutions is required, data security and user privacy remain challenges. 【0605】 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. 【0606】 In this invention, the server includes a device means for collecting and periodically transmitting an individual's biometric data in batches; an information processing device means for receiving the collected biometric data and securely storing it in a database; and a generative AI means for estimating emotions using natural language processing when analyzing the biometric data, and generating anomaly detection and notification messages. This enables comprehensive analysis combining an individual's biometric data and emotional state, as well as rapid anomaly detection, and ensures secure data sharing with medical institutions. 【0607】 A "device that collects and periodically transmits personal biometric data" refers to a combination of hardware and software that acquires personal health data through smart devices and other means, and securely transmits it via a communication network at regular intervals. 【0608】 An "information processing device that receives collected biometric data and securely stores it in a database" is a server system that receives biometric data transmitted from a terminal, organizes this data appropriately, and stores it securely. 【0609】 "Generative AI that uses natural language processing to estimate emotions when analyzing biometric data and generates anomaly detection and notification messages" refers to an artificial intelligence system that analyzes an individual's biometric data while simultaneously evaluating their emotional state using natural language processing technology, and generates notifications based on that information if an anomaly is detected. 【0610】 A "communication device that sends notification messages and issues warnings using expressions based on the user's emotional state" is a device that sends messages generated in a way that takes the user's emotional state into consideration to a terminal, providing attention and warnings. 【0611】 A "personalized health improvement suggestion generator that sends personalized health advice to user terminals" is a system that creates customized health advice based on each user's health condition and emotions, and sends it to the user's terminal. 【0612】 "Means of allowing information sharing with medical institutions and providing information securely" refers to processes and technologies that enable users to share their selected biometric data and analysis results with medical institutions, while ensuring data security and user privacy. 【0613】 To implement this invention, a system is needed that collects and analyzes individual biometric data and provides advice tailored to specific situations. Specific embodiments are described below. 【0614】 First, the terminal uses devices such as smartwatches and smartphones to acquire biometric data such as the user's heart rate, steps taken, and sleep patterns. These devices have communication capabilities that collect information via Bluetooth or Wi-Fi and periodically send the data to a server. 【0615】 The server is a device for securely storing received biometric data in a database. At this stage, the data is organized according to the individual's profile and managed using a database system such as MySQL or MongoDB. 【0616】 A server equipped with a generative AI model infers the user's emotional state based on accumulated biometric data and usage patterns and text data obtained from the terminal. Pandas and NumPy in Python are used for data analysis, and libraries such as NLTK and spaCy are utilized for natural language processing. If an anomaly is detected in the user through this emotion analysis, the generative AI creates an emotionally sensitive notification message based on the prompt text. 【0617】 For example, if the generating AI detects that the user's heart rate is higher than normal and that they are under stress, it will generate a prompt such as, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend you try taking some deep breaths or take a short break." 【0618】 Based on this information notified to their device, users can take specific actions to improve their health. Furthermore, users can share past data with medical institutions as needed, and the server securely supports this process. 【0619】 This system enables comprehensive health management that takes emotions into consideration, promoting appropriate responses that consider both the user's health and emotions. 【0620】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0621】 Step 1: 【0622】 The device collects the user's biometric data using a smart device (e.g., a smartwatch). The input here is data related to the user's daily activities and physical condition. Specifically, heart rate, steps taken, and sleep patterns are collected in real time. The data is temporarily stored on the device via Bluetooth or Wi-Fi connection, and the collected data is later sent to a server. 【0623】 Step 2: 【0624】 The device transmits the collected biometric data to the server at predetermined intervals. The input is the biometric data stored on the device, and the output is the secure transmission of this data. The data is encrypted and transmitted via a protocol (e.g., HTTPS), thus maintaining security. 【0625】 Step 3: 【0626】 The server receives the transmitted biometric data and stores it in a database. The input is the data sent from the terminal, and the output is the data stored in the database. The information is organized using database systems such as MySQL or MongoDB and stored for each user profile. 【0627】 Step 4: 【0628】 The AI ​​model on the server analyzes emotional states using biometric data stored in a database. The input is the stored biometric data, and the output is an estimated result of the emotional state. Here, a natural language processing library (e.g., spaCy) is used to estimate emotions, and this information is further analyzed. Python is used, with NumPy and Pandas also being utilized. 【0629】 Step 5: 【0630】 The server detects anomalies based on estimated emotional states and biometric data, and generates a notification message. The input is anomaly and emotional information obtained from the analysis results, and the output is a notification message including a generated prompt. The generating AI creates a friendly message based on the prompt, tailored to the user's emotions. 【0631】 Step 6: 【0632】 The device receives notification messages sent from the server and displays them to the user. The input is the notification message from the server, and the output is the warning displayed on the user's device screen. The device uses this to inform the user of changes in their health status or any important notices. 【0633】 Step 7: 【0634】 Users review notifications and advice displayed on their devices and, if necessary, choose to improve their lifestyle or provide information to healthcare providers. Input is notifications from the device, while output is changes in the user's behavior and data sharing with healthcare providers. Based on the information provided, users can manage their own health. 【0635】 (Application Example 2) 【0636】 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." 【0637】 In an aging society, there is a need to comprehensively manage the health and emotional state of those receiving care and to respond quickly and appropriately in the event of an emergency. However, the current system focuses solely on health management, and the provision of information that takes emotional states into consideration is insufficient. As a result, the stress and anxiety of those receiving care are not properly addressed, and a challenge arises in providing adequate care. 【0638】 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. 【0639】 In this invention, the server includes equipment means for collecting personal biometric information, processing means for receiving the collected biometric information and storing it in an information recording device, and generation AI means equipped with an analysis device that analyzes the biometric information to detect abnormalities and generates a notification message that takes into account the emotional state in the event of an abnormality. This makes it possible to simultaneously manage the health and emotional state of the person being cared for and to quickly provide emotionally sensitive notifications in the event of an abnormality. 【0640】 A "device that collects personal biometric information" is a device that automatically acquires data about a user's physical condition, continuously collecting information such as heart rate, steps taken, and sleep patterns. 【0641】 A "processing device for storing information in an information recording device" is a device that has the function of receiving collected biological information and saving it to an information recording device. 【0642】 An "analytical device that analyzes biological information to detect abnormalities" is a device that analyzes collected biological information and detects data that deviates from the normal range as an abnormality. 【0643】 An "analysis device that generates notification messages considering emotional state" is a device that, when an anomaly is detected, takes into account the user's emotional state and creates a notification message using the most appropriate expression. 【0644】 "Generative AI" is an artificial intelligence technology used to automatically analyze and make decisions based on biometric information, and to generate appropriate advice and notifications. 【0645】 A "system that considers the health status of the person receiving care and notifies third parties as needed" is a system that analyzes collected biometric information and automatically notifies third parties such as nurses and family members of the situation when necessary. 【0646】 This invention is a system for comprehensively monitoring the health and emotions of a person receiving care. This system utilizes "devices that collect personal biometric information," such as smartwatches and smartphones. These devices continuously acquire biometric information such as heart rate, steps taken, and sleep patterns. A server receives this data and operates as a "processing device that stores the data in an information recording device." 【0647】 The server incorporates a "generative AI" that analyzes biometric data. Specifically, it uses Python to analyze the data and executes the analysis on AWS. The analysis device has the function of "analyzing biometric data and detecting anomalies," detecting anomalies when the data deviates from the normal range. It also has the function of "generating notification messages considering emotional states," and performs emotion analysis using Google Cloud's Natural Language API. 【0648】 When an anomaly is detected, the server uses Firebase Cloud Messaging to send a notification message to the device. This message takes into account the emotional state of the person being cared for. For example, if the heart rate is abnormally high, a message such as "Your heart rate is above normal. Try some ways to relax" will be sent. 【0649】 Furthermore, this system also functions as a system that "considers the health status of the person receiving care and notifies third parties as needed." This ensures that the situation is communicated to nurses and family members in a timely manner, enabling a swift response. When sharing information with medical institutions, it is sent in a secure data format. 【0650】 For example, if the care recipient's sleep pattern is irregular, the system will send advice such as, "Your sleep is irregular. Try to set aside some time to relax before going to bed." The following prompt statements are used as input to the generative AI model. 【0651】 Consider how to respond when the care recipient's heart rate exceeds normal. Develop advice that takes their emotional state into account. 【0652】 This invention will realize a system that supports the health management of those receiving care from an emotional perspective as well. 【0653】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0654】 Step 1: 【0655】 The device continuously acquires biometric information such as heart rate, steps, and sleep patterns via a smartwatch or smartphone. At this point, the input is biometric information collected by sensors, and the output is biometric data that is updated in real time. The device prepares to transmit this data to a server using wireless communication technology. 【0656】 Step 2: 【0657】 The server receives biometric information transmitted from the terminal and stores it in the information recording device. The input is biometric data transmitted from the terminal. As output, the server stores the received data in a database in an organized format. The information is sorted chronologically so that it can be used for later analysis. 【0658】 Step 3: 【0659】 The analysis device on the server performs a process to detect anomalies using the received biometric information. A Python script analyzes the data and compares it to past normal data. The input for this step is stored biometric data, and the output is a dataset of data identified as abnormal. Specifically, it checks for things like abnormally high heart rates and disturbances in sleep patterns. 【0660】 Step 4: 【0661】 The analysis device uses a generative AI model to infer the emotional state after detecting an anomaly and generates an appropriate notification message. Sentiment analysis is performed using Google Cloud's Natural Language API. The input is biometric data corresponding to the anomaly, and the output is a notification message combined with the emotional state. 【0662】 Step 5: 【0663】 The server sends a notification message generated using Firebase Cloud Messaging to the device. The input here is the notification message generated by the analysis device, and the output is the warning message displayed on the device. The device receives this message and provides the user with health advice, such as stress management techniques. 【0664】 Step 6: 【0665】 If necessary, the server shares anomalous data and associated emotional information with third parties. Inputs are the data detecting anomalies and their analysis results. Outputs are notifications to relevant parties or information in an appropriate data format sent to healthcare institutions. Specifically, this is used when medical professionals need to intervene. 【0666】 Step 7: 【0667】 Ultimately, users assess their emotional state based on the displayed messages and take corrective actions if necessary. The input is the notification messages displayed on the device, and the output is feedback based on the user's actions. This process enables users to better manage both their physical and emotional well-being. 【0668】 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. 【0669】 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. 【0670】 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. 【0671】 [Fourth Embodiment] 【0672】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0673】 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. 【0674】 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). 【0675】 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. 【0676】 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. 【0677】 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). 【0678】 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. 【0679】 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. 【0680】 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. 【0681】 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. 【0682】 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. 【0683】 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. 【0684】 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". 【0685】 This invention is designed to efficiently collect and analyze personal biometric data, enabling users to understand their own health status and respond quickly when abnormalities occur. Specifically, it is a system that integrates terminals, servers, and generating AI. 【0686】 Data collection and transmission: 【0687】 The device collects daily health data from the user's smart device, including heart rate, steps taken, and sleep patterns. This data is stored on the device in real time. 【0688】 The collected data is properly formatted and securely transmitted to the server on a regular basis. 【0689】 Data storage and analysis: 【0690】 The server stores the received data in a database. The data is organized chronologically and managed on a per-user basis. 【0691】 The generating AI runs on a server and continuously analyzes stored biometric data. This AI also refers to past data to determine normal patterns and anomalies. 【0692】 Anomaly detection and notification: 【0693】 When an anomaly is detected, the server immediately generates a notification message. This message includes the type of anomaly and the risk level in a user-friendly format. 【0694】 The message is sent to the device and presented to the user as a push notification. 【0695】 Advice provided by: 【0696】 The server also generates personalized health advice based on detected anomalies, including preventative measures and lifestyle improvements. 【0697】 These pieces of advice are intended to have a concrete impact on the user's daily life and will be displayed in a list on the user's device after being sent. 【0698】 Information sharing with medical institutions: 【0699】 If necessary, users can choose to share information with medical institutions. In this case, the server organizes past data into a medical record format and sends it to the medical institution via a secure communication channel. 【0700】 As a concrete example, consider the case where an abnormal heart rate is detected. In this scenario, the server generates a message indicating the abnormality and sends a notification to the terminal stating, "Your heart rate has recently been higher than normal. Please check if you are experiencing stress and consult a medical institution if necessary." It also provides advice that includes a 5-minute breathing exercise, helping the user understand the next steps to take. In this way, the invention comprehensively supports individual health management. 【0701】 The following describes the processing flow. 【0702】 Step 1: 【0703】 The device continuously collects biometric data from smart devices. This data includes heart rate, steps taken, and sleep patterns. This data is organized within the device and stored chronologically. 【0704】 Step 2: 【0705】 At regular intervals, the terminal prepares to send the accumulated data to the server. The data is encoded in a secure format and organized into packets for communication. This packetized data is sent to the server via the internet. 【0706】 Step 3: 【0707】 The server quickly saves received data to the database. The data is categorized by user and stored chronologically along with past data. 【0708】 Step 4: 【0709】 The stored data is analyzed by a generative AI running on the server. The generative AI compares it to normal data patterns to determine if anomalies exist. It also refers to past data to detect anomaly patterns. 【0710】 Step 5: 【0711】 When the server detects an anomaly, it generates a notification message in a user-friendly format. The notification message includes the type of anomaly, the risk level, and recommended actions. 【0712】 Step 6: 【0713】 The generated notification message is sent from the server to the device. The device receives it and presents it to the user as a push notification. 【0714】 Step 7: 【0715】 Simultaneously, the server generates personalized advice. This advice includes specific countermeasures and preventative measures for anomalies. This advice is sent to the terminal and provided to the user. 【0716】 Step 8: 【0717】 If necessary, users can choose to share their past biometric data with designated healthcare institutions. The data is then processed in a secure format by the server and transmitted to the selected healthcare institution. 【0718】 (Example 1) 【0719】 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". 【0720】 In today's world, where health management is increasingly important, there is a need for systems that can efficiently collect and analyze personal biometric information and enable rapid response when abnormalities occur. Furthermore, there is a lack of methods to provide users with appropriate health advice and support collaboration with medical institutions as needed. Additionally, there is a need for technology that can handle data seamlessly while protecting user privacy. 【0721】 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. 【0722】 In this invention, the server includes a portable device means for aggregating an individual's biometric information, an information processing device means for receiving the aggregated biometric information and storing it in a storage device, and a generation algorithm means equipped with an analysis unit that analyzes the biometric information to detect abnormalities and creates a notification signal in the event of an abnormality. This enables monitoring of an individual's health status and rapid response in the event of an abnormality, thereby realizing comprehensive health management. 【0723】 "Personal biometric information" is a general term for data that indicates an individual's health status, such as heart rate, steps taken, and sleep patterns. 【0724】 A "portable device" is a device that a user can carry with them and that has the function of collecting health data. 【0725】 An "information processing device" is a device that receives collected data and stores and manages it. 【0726】 A "storage device" is a memory device that stores received data and organizes it chronologically. 【0727】 A "generative algorithm" is a computational method used to analyze collected biological information and detect anomalies. 【0728】 The "analysis unit" is the part of the system equipped with functions for analyzing data and identifying anomalies. 【0729】 A "notification signal" is a warning signal generated to inform the user of a detected anomaly. 【0730】 The "transmitter" is the part that has the function of sending the generated notification signal to the mobile device and displaying the notification to the user. 【0731】 The "Advice Department" is the part of the system that provides users with specific advice for maintaining their health based on the data it collects. 【0732】 A "medical facility" is an organization or institution where users can receive professional support regarding their health. 【0733】 This invention is a system that comprehensively supports individual health management, aggregating and analyzing individual biometric information to enable rapid response in the event of an abnormality. The system operates by integrating a portable device, an information processing device, and a generation algorithm. The following describes each component and its specific function. 【0734】 First, the terminal consists of portable devices such as smartphones and wearable devices. These devices collect data such as the user's heart rate, steps taken, and sleep patterns in real time. Specifically, heart rate sensors and accelerometers are used to acquire data. For example, if a user walks more than 10,000 steps every day, that number of steps will be recorded by the device. 【0735】 The collected data is transmitted to the server via Bluetooth or Wi-Fi. The server functions as an information processing device, storing the received data in a storage device. MySQL or PostgreSQL are suitable database systems. The data is organized chronologically and categorized by user. 【0736】 Next, a generative AI running on the server analyzes the stored data. Here, machine learning software such as TensorFlow and PyTorch is used to build a data analysis model. This generative algorithm detects data anomalies and generates notification signals. Predictive analysis based on past health data is also possible. 【0737】 When an anomaly is detected, the server automatically creates a notification message and sends it to the device. This message is presented to the user as a push notification. For example, it might say, "Your heart rate has been higher than normal recently. Please check if you are experiencing stress and seek medical attention if necessary." 【0738】 Furthermore, personalized health advice is generated by the AI ​​and displayed in a list on the user's device. This advice includes specific suggestions, such as a 5-minute breathing exercise. An example of a prompt message is: "Generate a prompt message to detect anomalies and provide advice based on the user's health data. Include the specific type of anomaly and recommended advice." 【0739】 Ultimately, users can share their data with healthcare facilities as needed. The server organizes the data into a medical record format and sends it to healthcare institutions using a secure API. This secure data sharing allows users to receive more specialized health management. 【0740】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0741】 Step 1: 【0742】 The device collects biometric information in real time from the user's smart device. Inputs include data from heart rate sensors and accelerometers. This data is output in the form of heart rate, steps taken, sleep patterns, etc. Specifically, the device periodically reads data as the user wears it and goes about their daily life. 【0743】 Step 2: 【0744】 The device transmits the collected biometric information to the server via Bluetooth or Wi-Fi. The biometric data obtained in step 1 is used as input. This data is appropriately formatted and encrypted before being sent to the server. Specifically, data packets are generated at regular intervals and transmitted using a secure protocol. 【0745】 Step 3: 【0746】 The server stores the received biometric information in a storage device. It uses the received data as input and saves it to a database in a chronologically organized format. The output of this data is a dataset categorized by user, ready for future analysis. Specifically, it adds records to the database using an "INSERT INTO" query. 【0747】 Step 4: 【0748】 The generating AI on the server performs analysis using the stored data. The input is the biometric information stored in step 3, and the output is the anomaly detection result. The generating AI compares this with past data and applies machine learning algorithms to detect anomalies in the current biometric information. Specifically, the data is fed into the AI ​​model to detect anomalies and assess risks. 【0749】 Step 5: 【0750】 If an anomaly is detected, the server generates a notification signal and sends a notification to the terminal. The anomaly detection result is used as input. The output is a warning message in a user-friendly format. Specifically, a prompt sentence is created based on the analysis results of the generation AI, and this is sent to the terminal as a push notification. 【0751】 Step 6: 【0752】 The server generates personalized advice for the user based on the anomaly and sends it to the terminal. It uses the anomaly detection results as input, and the output is specific advice and suggestions for the user. Specifically, it lists health improvement suggestions based on the type of anomaly and presents them to the user's terminal. 【0753】 Step 7: 【0754】 If necessary, users can choose to share their biometric information with healthcare facilities. The input is the user's past biometric data, and the output is a medical record formatted for healthcare facilities. Specifically, the server sends data to healthcare institutions via a secure API and shares the data based on the user's consent. 【0755】 (Application Example 1) 【0756】 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". 【0757】 In systems that support individual health management through the collection and analysis of biometric information, there is a need to efficiently detect abnormalities and provide warnings and advice in an easily understandable format for users. However, previous technologies have faced challenges such as insufficient data collection and analysis, and limitations in the detection rate of abnormalities. Furthermore, providing personalized health advice closely tied to the user's lifestyle has been difficult with conventional approaches. 【0758】 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. 【0759】 In this invention, the server includes equipment means for collecting personal biometric information, computer means for receiving the collected biometric information and storing it in a storage medium, and artificial intelligence means equipped with an analysis unit that analyzes the biometric information to detect anomalies and generates notification information in the event of an anomaly. This enables efficient anomaly detection and the provision of personalized health advice. 【0760】 A "device that collects personal biometric information" is a device that acquires health-related data from users, and uses sensors to measure data such as heart rate, steps taken, and sleep patterns. 【0761】 A "computer that receives collected biometric information and stores it in a storage medium" is an electronic device that receives biometric information transmitted from another device and stores it in digital format; it is essentially a server with a database. 【0762】 "An artificial intelligence equipped with an analysis unit that analyzes biometric information to detect anomalies and generates notification information when anomalies occur" refers to software that continuously analyzes biometric data, identifies data that falls outside the normal range, and generates alerts. 【0763】 The "communication unit that sends notification information to devices and warns users" is a function that sends messages generated based on analysis results to devices and informs users through visual or auditory means. 【0764】 The "advice unit that generates and transmits personalized advice for abnormalities" is a system that creates and provides different health improvement measures and action suggestions for each user based on the detected abnormalities. 【0765】 "Means for allowing information sharing with medical institutions" refers to technology that enables the transmission of biometric information and analysis results to medical service providers via a reliable communication channel, if selected by the user. 【0766】 To implement this invention, multiple devices and software must work together to efficiently manage an individual's health. This system mainly consists of devices that collect biometric information in real time, a server that stores and analyzes the data, a terminal that notifies the user based on the analysis results, and artificial intelligence that generates personalized advice. 【0767】 The server receives biometric information transmitted by users and stores it in a database. This data is managed chronologically and prepared for subsequent analysis. A generative AI model runs on the server, analyzing the biometric information to detect abnormal patterns. In this process, past data is also referenced to determine anomalies with high accuracy. 【0768】 If an anomaly is detected, the server generates notification information and sends it to the device. The device immediately relays this information to the user and issues an appropriate warning. At this stage, the user can understand their health status and learn about necessary countermeasures. The server also uses AI to generate personalized health advice based on the anomaly and sends it to the device for display to the user. 【0769】 For example, consider a scenario where a user's heart rate suddenly increases while they are indoors. The server detects this anomaly and sends a notification to the user's device such as, "Your heart rate is higher than normal. Take a short break and try deep breathing." It also provides further advice, such as, "To reduce stress, try a 3-minute deep breathing exercise," to help the user respond quickly. 【0770】 An example of a prompt message is: "Analyze the user's heart rate data, generate a warning if it exceeds the normal range, and suggest appropriate mitigation measures." In this way, the system comprehensively supports users' health management through real-time monitoring of health data, rapid anomaly detection, and personalized assistance. 【0771】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0772】 Step 1: 【0773】 The device collects biometric information from the user, such as heart rate, steps taken, and sleep patterns. It processes the data acquired using sensors in real time and stores it in a buffer. The input is biometric information, and the output is formatted data. For security reasons, the data is encrypted within the device. 【0774】 Step 2: 【0775】 The device transmits collected biometric information to the server. The data is transmitted using a secure communication protocol. The input is encrypted biometric information, and the output is a notification that the data transfer to the server is complete. Communication is performed periodically to ensure real-time performance. 【0776】 Step 3: 【0777】 The server stores the received biometric information in a database. The data is organized chronologically and managed on a per-user basis. The input is the received biometric information, and the output is the organized information in the database. The stored data serves as foundational information for subsequent analysis. 【0778】 Step 4: 【0779】 The AI ​​within the server analyzes biometric information to check for abnormalities. It also references past data to determine if an anomaly is detected. The input is organized biometric information, and the output is the anomaly detection result. This process utilizes a pattern recognition algorithm, enabling highly accurate anomaly detection. 【0780】 Step 5: 【0781】 The server generates notification information and sends it to the terminal when an anomaly is detected. The generating AI automatically determines the details of the anomaly and its risk level, and formats the information. The input is the anomaly detection result, and the output is the notification information to be displayed on the terminal. 【0782】 Step 6: 【0783】 The device displays received notification information to the user. It issues alerts via screen and audio to prompt the user for a quick response. The input is notification information sent from the server, and the output is a warning message to the user. The notification is converted into a user-friendly format. 【0784】 Step 7: 【0785】 The server generates personalized advice based on the anomaly and sends it to the terminal. The generating AI constructs customized advice for each user based on the prompt text. The input is the anomaly detection result and past response history, and the output is a specific action suggestion. 【0786】 Step 8: 【0787】 The terminal displays the received advice to the user. The display follows a notification message, and visual and auditory volume adjustments are also considered. The input is advice information sent from the server, and the output is specific action suggestions for the user. 【0788】 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. 【0789】 This invention is a system that collects and analyzes individual biometric data to comprehensively manage a user's health and emotions, enabling rapid response in the event of an abnormality. In particular, by incorporating an emotion engine, it recognizes the user's emotional state and considers emotions when providing health advice, thereby achieving more effective health management. 【0790】 Data collection and transmission: 【0791】 The device continuously acquires biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. Furthermore, the device monitors the user's usage patterns and input data, collecting elements to infer their emotional state. This data is compiled over a certain period and transmitted to a server. 【0792】 Data storage and analysis: 【0793】 The server stores the received biometric data in a database and organizes it according to the user's profile. The emotion engine uses this data to estimate the user's emotions and feeds the analysis results back to the generating AI. 【0794】 Anomaly detection and notification: 【0795】 The server's AI analyzes biometric data, and if an anomaly is detected, it generates a notification message that also takes into account the user's emotional state. This message includes language that responds to the user's emotions, presenting the anomaly and recommended actions in a more user-friendly way. 【0796】 Advice provided by: 【0797】 The server generates personalized advice, incorporating emotion recognition from the emotion engine to create more personalized suggestions. This advice is sent to the device, allowing the user to receive lifestyle improvement suggestions optimized for them. 【0798】 Emotional feedback and medical information sharing: 【0799】 Users can monitor their own emotional state based on the emotional feedback provided. Furthermore, if abnormalities or persistent emotional changes persist, they can choose to share their past biometric data with a healthcare provider. The server provides this information to the healthcare provider in a secure and appropriate format. 【0800】 As a concrete example, consider a case where a user's heart rate becomes abnormally high due to stress. In this case, the emotion engine estimates that the user may be experiencing stress, and the server sends a notification stating, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend trying to take deep breaths or taking a short break." By implementing this invention, users can receive comprehensive management that takes into account not only their physical health but also their emotional well-being. 【0801】 The following describes the processing flow. 【0802】 Step 1: 【0803】 The device continuously collects biometric data such as heart rate, steps taken, and sleep patterns from the user's smart device. It also collects information such as the user's input actions and device usage patterns, which are used as data for inferring emotions. 【0804】 Step 2: 【0805】 The collected biometric data and usage pattern data are compiled at predetermined time intervals and transmitted securely to the server. The transmission is performed using an encrypted protocol to prevent data leakage. 【0806】 Step 3: 【0807】 The server stores the received data in a database. The data is categorized by user, and the history is managed in chronological order. The server then uses an emotion engine to perform analysis to infer the user's emotional state. 【0808】 Step 4: 【0809】 The generating AI operates on a server, analyzing the received biometric data and comparing it to normal health conditions to determine if there are any abnormalities. It also acquires additional information, such as the emotional state estimated by the emotion engine. 【0810】 Step 5: 【0811】 If an anomaly is detected, the server considers the nature of the anomaly and the user's emotional state to generate a message. Because it includes emotionally appropriate language, the notification is easy for the user to understand and is delivered in a sensitive manner. 【0812】 Step 6: 【0813】 The generated notification message is sent from the server to the device, which then presents it to the user as a push notification. The user immediately receives information about the anomaly and recommended actions through the device. 【0814】 Step 7: 【0815】 The server generates personalized advice optimized for the user based on the results of the generative AI and emotion engine. This advice includes suggestions that can be directly applied to the user's daily life. 【0816】 Step 8: 【0817】 If necessary, users can choose to share information with healthcare institutions. The server will follow the user's instructions and prepare to provide past biometric data and emotional information to healthcare institutions in a secure format. 【0818】 Step 9: 【0819】 Finally, the device provides the user with feedback regarding the emotional state estimated by the emotion engine. This feedback allows the user to understand their own emotions and adjust their behavior as needed. 【0820】 (Example 2) 【0821】 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". 【0822】 In modern society, there is a need for comprehensive management of individual health conditions, particularly for rapid anomaly detection and response that takes emotional states into consideration. However, existing systems struggle to effectively combine and analyze biometric data and emotional states, resulting in insufficient personalized responses. Furthermore, while seamless information sharing with medical institutions is required, data security and user privacy remain challenges. 【0823】 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. 【0824】 In this invention, the server includes a device means for collecting and periodically transmitting an individual's biometric data in batches; an information processing device means for receiving the collected biometric data and securely storing it in a database; and a generative AI means for estimating emotions using natural language processing when analyzing the biometric data, and generating anomaly detection and notification messages. This enables comprehensive analysis combining an individual's biometric data and emotional state, as well as rapid anomaly detection, and ensures secure data sharing with medical institutions. 【0825】 A "device that collects and periodically transmits personal biometric data" refers to a combination of hardware and software that acquires personal health data through smart devices and other means, and securely transmits it via a communication network at regular intervals. 【0826】 An "information processing device that receives collected biometric data and securely stores it in a database" is a server system that receives biometric data transmitted from a terminal, organizes this data appropriately, and stores it securely. 【0827】 "Generative AI that uses natural language processing to estimate emotions when analyzing biometric data and generates anomaly detection and notification messages" refers to an artificial intelligence system that analyzes an individual's biometric data while simultaneously evaluating their emotional state using natural language processing technology, and generates notifications based on that information if an anomaly is detected. 【0828】 A "communication device that sends notification messages and issues warnings using expressions based on the user's emotional state" is a device that sends messages generated in a way that takes the user's emotional state into consideration to a terminal, providing attention and warnings. 【0829】 A "personalized health improvement suggestion generator that sends personalized health advice to user terminals" is a system that creates customized health advice based on each user's health condition and emotions, and sends it to the user's terminal. 【0830】 "Means of allowing information sharing with medical institutions and providing information securely" refers to processes and technologies that enable users to share their selected biometric data and analysis results with medical institutions, while ensuring data security and user privacy. 【0831】 To implement this invention, a system is needed that collects and analyzes individual biometric data and provides advice tailored to specific situations. Specific embodiments are described below. 【0832】 First, the terminal uses devices such as smartwatches and smartphones to acquire biometric data such as the user's heart rate, steps taken, and sleep patterns. These devices have communication capabilities that collect information via Bluetooth or Wi-Fi and periodically send the data to a server. 【0833】 The server is a device for securely storing received biometric data in a database. At this stage, the data is organized according to the individual's profile and managed using a database system such as MySQL or MongoDB. 【0834】 A server equipped with a generative AI model infers the user's emotional state based on accumulated biometric data and usage patterns and text data obtained from the terminal. Pandas and NumPy in Python are used for data analysis, and libraries such as NLTK and spaCy are utilized for natural language processing. If an anomaly is detected in the user through this emotion analysis, the generative AI creates an emotionally sensitive notification message based on the prompt text. 【0835】 For example, if the generating AI detects that the user's heart rate is higher than normal and that they are under stress, it will generate a prompt such as, "Your heart rate is higher than normal, and you may be feeling stressed. We recommend you try taking some deep breaths or take a short break." 【0836】 Based on this information notified to their device, users can take specific actions to improve their health. Furthermore, users can share past data with medical institutions as needed, and the server securely supports this process. 【0837】 This system enables comprehensive health management that takes emotions into consideration, promoting appropriate responses that consider both the user's health and emotions. 【0838】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0839】 Step 1: 【0840】 The device collects the user's biometric data using a smart device (e.g., a smartwatch). The input here is data related to the user's daily activities and physical condition. Specifically, heart rate, steps taken, and sleep patterns are collected in real time. The data is temporarily stored on the device via Bluetooth or Wi-Fi connection, and the collected data is later sent to a server. 【0841】 Step 2: 【0842】 The device transmits the collected biometric data to the server at predetermined intervals. The input is the biometric data stored on the device, and the output is the secure transmission of this data. The data is encrypted and transmitted via a protocol (e.g., HTTPS), thus maintaining security. 【0843】 Step 3: 【0844】 The server receives the transmitted biometric data and stores it in a database. The input is the data sent from the terminal, and the output is the data stored in the database. The information is organized using database systems such as MySQL or MongoDB and stored for each user profile. 【0845】 Step 4: 【0846】 The AI ​​model on the server analyzes emotional states using biometric data stored in a database. The input is the stored biometric data, and the output is an estimated result of the emotional state. Here, a natural language processing library (e.g., spaCy) is used to estimate emotions, and this information is further analyzed. Python is used, with NumPy and Pandas also being utilized. 【0847】 Step 5: 【0848】 The server detects anomalies based on estimated emotional states and biometric data, and generates a notification message. The input is anomaly and emotional information obtained from the analysis results, and the output is a notification message including a generated prompt. The generating AI creates a friendly message based on the prompt, tailored to the user's emotions. 【0849】 Step 6: 【0850】 The device receives notification messages sent from the server and displays them to the user. The input is the notification message from the server, and the output is the warning displayed on the user's device screen. The device uses this to inform the user of changes in their health status or any important notices. 【0851】 Step 7: 【0852】 Users review notifications and advice displayed on their devices and, if necessary, choose to improve their lifestyle or provide information to healthcare providers. Input is notifications from the device, while output is changes in the user's behavior and data sharing with healthcare providers. Based on the information provided, users can manage their own health. 【0853】 (Application Example 2) 【0854】 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". 【0855】 In an aging society, there is a need to comprehensively manage the health and emotional state of those receiving care and to respond quickly and appropriately in the event of an emergency. However, the current system focuses solely on health management, and the provision of information that takes emotional states into consideration is insufficient. As a result, the stress and anxiety of those receiving care are not properly addressed, and a challenge arises in providing adequate care. 【0856】 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. 【0857】 In this invention, the server includes equipment means for collecting personal biometric information, processing means for receiving the collected biometric information and storing it in an information recording device, and generation AI means equipped with an analysis device that analyzes the biometric information to detect abnormalities and generates a notification message that takes into account the emotional state in the event of an abnormality. This makes it possible to simultaneously manage the health and emotional state of the person being cared for and to quickly provide emotionally sensitive notifications in the event of an abnormality. 【0858】 A "device that collects personal biometric information" is a device that automatically acquires data about a user's physical condition, continuously collecting information such as heart rate, steps taken, and sleep patterns. 【0859】 A "processing device for storing information in an information recording device" is a device that has the function of receiving collected biological information and saving it to an information recording device. 【0860】 An "analytical device that analyzes biological information to detect abnormalities" is a device that analyzes collected biological information and detects data that deviates from the normal range as an abnormality. 【0861】 An "analysis device that generates notification messages considering emotional state" is a device that, when an anomaly is detected, takes into account the user's emotional state and creates a notification message using the most appropriate expression. 【0862】 "Generative AI" is an artificial intelligence technology used to automatically analyze and make decisions based on biometric information, and to generate appropriate advice and notifications. 【0863】 A "system that considers the health status of the person receiving care and notifies third parties as needed" is a system that analyzes collected biometric information and automatically notifies third parties such as nurses and family members of the situation when necessary. 【0864】 This invention is a system for comprehensively monitoring the health and emotions of a person receiving care. This system utilizes "devices that collect personal biometric information," such as smartwatches and smartphones. These devices continuously acquire biometric information such as heart rate, steps taken, and sleep patterns. A server receives this data and operates as a "processing device that stores the data in an information recording device." 【0865】 The server incorporates a "generative AI" that analyzes biometric data. Specifically, it uses Python to analyze the data and executes the analysis on AWS. The analysis device has the function of "analyzing biometric data and detecting anomalies," detecting anomalies when the data deviates from the normal range. It also has the function of "generating notification messages considering emotional states," and performs emotion analysis using Google Cloud's Natural Language API. 【0866】 When an anomaly is detected, the server uses Firebase Cloud Messaging to send a notification message to the device. This message takes into account the emotional state of the person being cared for. For example, if the heart rate is abnormally high, a message such as "Your heart rate is above normal. Try some ways to relax" will be sent. 【0867】 Furthermore, this system also functions as a system that "considers the health status of the person receiving care and notifies third parties as needed." This ensures that the situation is communicated to nurses and family members in a timely manner, enabling a swift response. When sharing information with medical institutions, it is sent in a secure data format. 【0868】 For example, if the care recipient's sleep pattern is irregular, the system will send advice such as, "Your sleep is irregular. Try to set aside some time to relax before going to bed." The following prompt statements are used as input to the generative AI model. 【0869】 Consider how to respond when the care recipient's heart rate exceeds normal. Develop advice that takes their emotional state into account. 【0870】 This invention will realize a system that supports the health management of those receiving care from an emotional perspective as well. 【0871】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0872】 Step 1: 【0873】 The device continuously acquires biometric information such as heart rate, steps, and sleep patterns via a smartwatch or smartphone. At this point, the input is biometric information collected by sensors, and the output is biometric data that is updated in real time. The device prepares to transmit this data to a server using wireless communication technology. 【0874】 Step 2: 【0875】 The server receives biometric information transmitted from the terminal and stores it in the information recording device. The input is biometric data transmitted from the terminal. As output, the server stores the received data in a database in an organized format. The information is sorted chronologically so that it can be used for later analysis. 【0876】 Step 3: 【0877】 The analysis device on the server performs a process to detect anomalies using the received biometric information. A Python script analyzes the data and compares it to past normal data. The input for this step is stored biometric data, and the output is a dataset of data identified as abnormal. Specifically, it checks for things like abnormally high heart rates and disturbances in sleep patterns. 【0878】 Step 4: 【0879】 The analysis device uses a generative AI model to infer the emotional state after detecting an anomaly and generates an appropriate notification message. Sentiment analysis is performed using Google Cloud's Natural Language API. The input is biometric data corresponding to the anomaly, and the output is a notification message combined with the emotional state. 【0880】 Step 5: 【0881】 The server sends a notification message generated using Firebase Cloud Messaging to the device. The input here is the notification message generated by the analysis device, and the output is the warning message displayed on the device. The device receives this message and provides the user with health advice, such as stress management techniques. 【0882】 Step 6: 【0883】 If necessary, the server shares anomalous data and associated emotional information with third parties. Inputs are the data detecting anomalies and their analysis results. Outputs are notifications to relevant parties or information in an appropriate data format sent to healthcare institutions. Specifically, this is used when medical professionals need to intervene. 【0884】 Step 7: 【0885】 Ultimately, users assess their emotional state based on the displayed messages and take corrective actions if necessary. The input is the notification messages displayed on the device, and the output is feedback based on the user's actions. This process enables users to better manage both their physical and emotional well-being. 【0886】 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. 【0887】 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. 【0888】 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. 【0889】 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. 【0890】 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. 【0891】 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. 【0892】 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. 【0893】 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. 【0894】 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." 【0895】 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. 【0896】 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. 【0897】 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. 【0898】 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. 【0899】 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. 【0900】 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. 【0901】 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. 【0902】 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. 【0903】 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. 【0904】 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. 【0905】 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. 【0906】 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 as being incorporated by reference. 【0907】 The following is further disclosed regarding the embodiments described above. 【0908】 (Claim 1) 【0909】 A terminal device for collecting personal biometric data, 【0910】 A server means that receives collected biometric data and stores it in a storage device, 【0911】 A generation AI means equipped with an analysis unit that analyzes biometric data to detect anomalies and generates a notification message when an anomaly occurs, 【0912】 A transmission unit means that sends a notification message to the terminal and warns the user, 【0913】 An advice unit means that generates and transmits personalized advice regarding anomalies, 【0914】 Means to authorize information sharing with medical institutions 【0915】 A system that includes this. 【0916】 (Claim 2) 【0917】 The system according to claim 1, further comprising a function that allows the analysis unit to determine an anomaly by referring to past biological data when detecting an anomaly. 【0918】 (Claim 3) 【0919】 The system according to claim 1, wherein the advice generated by the advice unit is adaptively updated based on user feedback. 【0920】 "Example 1" 【0921】 (Claim 1) 【0922】 A portable device for aggregating personal biometric information, 【0923】 Information processing means that receives aggregated biological information and stores it in a storage device, 【0924】 A generation algorithm means comprising an analysis unit that analyzes biological information to detect abnormalities and generates a notification signal in the event of an abnormality, 【0925】 A transmission unit means that sends a notification signal to a mobile device to warn the user, 【0926】 An advisory unit means that generates and transmits personalized advice regarding anomalies, 【0927】 Means to enable information sharing with medical facilities 【0928】 A system that includes this. 【0929】 (Claim 2) 【0930】 The system according to claim 1, further comprising a function that allows the analysis unit to determine an anomaly by referring to past biological information when detecting an anomaly. 【0931】 (Claim 3) 【0932】 The system according to claim 1, having a function that updates the advice generated by the advice unit in response to the user's response. 【0933】 "Application Example 1" 【0934】 (Claim 1) 【0935】 Devices and means for collecting personal biometric information, 【0936】 A computer means that receives collected biometric information and stores it in a storage medium, 【0937】 An artificial intelligence means comprising an analysis unit that analyzes biological information to detect anomalies and generates notification information when an anomaly occurs, 【0938】 A communication unit means that transmits notification information to a device and warns the user, 【0939】 An advisory unit means that generates and transmits personalized advice regarding anomalies, 【0940】 Means to authorize information sharing with medical institutions 【0941】 A system that includes this. 【0942】 (Claim 2) 【0943】 The system according to claim 1, further comprising a function that allows the analysis unit to determine an anomaly by referring to past biological information when detecting an anomaly. 【0944】 (Claim 3) 【0945】 The system according to claim 1, which has a function to adaptively update the advice generated by the advice unit in response to user input. 【0946】 "Example 2 of combining an emotion engine" 【0947】 (Claim 1) 【0948】 A device and means for collecting personal biometric data and transmitting it periodically in batches, 【0949】 Information processing device means for receiving collected biometric data and securely storing it in a database, 【0950】 A generative AI means that uses natural language processing to estimate emotions when analyzing biometric data, and generates anomaly detection and notification messages, 【0951】 A communication device means that sends notification messages and issues warnings using expressions based on the user's emotional state, 【0952】 An advice generation device means that generates personalized health improvement suggestions and transmits them to a user terminal, 【0953】 Authorizing information sharing with medical institutions and providing a secure means of information delivery 【0954】 A system that includes this. 【0955】 (Claim 2) 【0956】 The system according to claim 1, further comprising a function that, when an analysis device detects an anomaly, refers to historical biometric data and emotion analysis results to determine the anomaly. 【0957】 (Claim 3) 【0958】 The system according to claim 1, wherein the advice generated by the advice generation device has a function to adaptively update the advice based on the user's emotional feedback. 【0959】 "Application example 2 when combining with an emotional engine" 【0960】 (Claim 1) 【0961】 Devices and means for collecting personal biometric information, 【0962】 Processing means for receiving collected biological information and storing it in an information recording device, 【0963】 A generation AI means equipped with an analysis device that analyzes biological information to detect abnormalities and generates a notification message considering the emotional state when an abnormality occurs, 【0964】 A transmitting device means that sends a notification message to a device and warns the user, 【0965】 An advisory device means for generating and transmitting personalized advice regarding anomalies, 【0966】 A device to allow information sharing with medical facilities. 【0967】 A system that takes into account the health condition of the person receiving care and includes a system for notifying a third party as needed. 【0968】 (Claim 2) 【0969】 The system according to claim 1, which includes a function to determine an abnormality by referring to past biological information when the analysis device detects an abnormality. 【0970】 (Claim 3) 【0971】 The system according to claim 1, wherein the advice generated by the advice device is adaptively updated in consideration of the user's emotional state. [Explanation of Symbols] 【0972】 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

[Claim 1] A terminal device for collecting personal biometric data, A server means that receives collected biometric data and stores it in a storage device, A generation AI means equipped with an analysis unit that analyzes biometric data to detect anomalies and generates a notification message when an anomaly occurs, A transmission unit means that sends a notification message to the terminal and warns the user, An advice unit means that generates and transmits personalized advice regarding anomalies, Means to authorize information sharing with medical institutions A system that includes this. [Claim 2] The system according to claim 1, further comprising a function that allows the analysis unit to determine an abnormality by referring to past biological data when detecting an abnormality. [Claim 3] The system according to claim 1, wherein the advice generated by the advice unit is adaptively updated in response to user feedback.

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