Interactive personal health management system based on artificial intelligence and operation method thereof

Abstract

The invention discloses an interactive personal health management system based on artificial intelligence and an operation method. Different from a part of existing modes, limited health data and brief basic information which are acquired by a single acquisition device and serve as a unique health information source of a user are not limited, but only serve as health basic information, and a concept and an implementation scheme of'health supplement information 'are provided. On the basis of obtaining the health basic information, through alternate or simultaneous use of multiple types of collection devices and multiple collection ways and modes, more health supplement information of the user is obtained, and a comprehensive AI health information source of the user is jointly constructed. The AI health information source is analyzed and calculated through an artificial intelligence health algorithm, once the AI health information source changes, the AI health assessment result is adjusted accordingly, an infinite loop mechanism is formed, the user health assessment result is promoted to be infinitely close to precision, and health information is interacted with the user in real time through the AI health digital human in a natural language.

Description

Technical Field

[0001] The present invention is in the technical field at the intersection of artificial intelligence and health management. Specifically, it is an innovative design of applying artificial intelligence (AI) technology to a health management system and its operation method. This system integrates artificial intelligence algorithms, natural language processing technology, machine learning technology in the field of computer science and professional knowledge in the field of health management.

[0002] In the health data collection link, with the combination of various sensor technologies integrated in the collection device and machine learning algorithms, the collected data is preliminarily processed and analyzed. Natural language processing technology plays a role in the interaction between users and the system, enabling users to conveniently input and obtain health information. In the health analysis and evaluation stage, artificial intelligence algorithms and machine learning technology jointly conduct in-depth mining and analysis of a large amount of health data, and combined with professional health knowledge, generate accurate evaluation results. Finally, in the health management advice generation link, considering the user's personalized information and analysis and evaluation results comprehensively, natural language processing technology is used to provide users with multi-dimensional and interactive health management advice in an easy-to-understand manner. The whole process involves the coordinated operation of hardware devices (such as collection devices and operation terminal devices) and software systems (including AI health agents, AI health digital humans and related management systems), aiming to provide users with personalized, multi-dimensional and interactive health management services. Background Art

[0003] In the development process of the health management field, the early stage mainly relied on the traditional medical model, focusing on disease treatment. With the improvement of people's health awareness and the pursuit of quality of life, the focus of health management has gradually shifted to disease prevention and health promotion, and modern technology has also begun to be integrated. People's needs for health management are becoming increasingly complex and diverse, and more effective health protection methods are being explored at each stage. However, both traditional medical health management methods, emerging wearable intelligent device health management applications, and current artificial intelligence health management systems have many limitations in different aspects.

[0004] (I) Deficiencies of Traditional Medical Health Management Methods

[0005] Insufficient personalized health services: In the traditional medical system, due to the imbalance between the supply and demand of medical resources and the impact of the medical system on doctors' working modes, ordinary doctors usually have to face a large number of patients at the same time, resulting in insufficient time and meticulous care for each patient in their busy work. The large number of patients makes it difficult for doctors to fully and deeply understand the specific situation of each patient, and finally the health advice provided is not accurate enough to meet the needs of patients for personalized health services.

[0006] Limited health service time: The working and service hours of traditional general doctors are generally fixed. When patients encounter health problems outside of working hours, they often cannot obtain professional doctor guidance in a timely manner, which may delay the condition. Although some hospitals have on-duty doctors, due to the large number of patients and limited understanding of patient information faced by on-duty doctors, this dilemma cannot be well solved. Moreover, the communication between doctors and patients is often short and superficial, making it difficult to comprehensively understand the special circumstances and needs of each patient, and unable to provide long-term, personalized health management services for patients.

[0007] Lag in health assessment results: When faced with a large amount of monitoring data accumulated by patients over a long period of time, the speed of traditional general doctors in processing and analyzing data is relatively slow, and sometimes even multi-department consultations are required. Because traditional medicine lacks efficient data processing tools and algorithms, manual data analysis is prone to errors and omissions. In this case, patients may need to wait a long time to obtain diagnostic results and suggestions, affecting the timeliness of health management.

[0008] Difficulty in popularizing exclusive doctors: Although special personal or family exclusive health doctors can overcome the deficiencies of ordinary medical methods, considering the current medical resource situation in society and the economic level of the public, it is difficult to popularize personal or family exclusive health doctors. This makes it impossible for the public to obtain continuous, personalized health management services, which may lead to the failure to prevent and control some chronic diseases in a timely and effective manner, having an adverse impact on the public's health management.

[0009] Lack of timely knowledge update and service adjustment: Due to their busy work and limited information acquisition channels, general doctors have difficulty in keeping up with a large amount of the latest medical and health knowledge and research results in real time, and it is difficult to quickly adapt to the progress of medical research and changes in users' health needs. For example, in terms of health management, some new health risk assessment indicators or healthy lifestyle suggestions cannot be conveyed to patients in a timely manner, which may affect patients' accurate understanding of their own health status and the adoption of reasonable health management measures.

[0010] (2) Deficiencies of general wearable intelligent devices in health management

[0011] With the rise of current wearable intelligent devices, the emergence of new technology sensors and the improvement of their accuracy, health monitoring devices have entered thousands of households from the traditional medical field, opening a new era of personal health management, which is of great significance to the promotion and popularization of the health management cause. However, the current general wearable intelligent devices have the following deficiencies in health management:

[0012] Incomplete acquisition of health information: Generally, wearable intelligent devices usually rely only on the limited physiological data they monitor themselves. They are relatively weak in collecting basic health-related information of users (such as medical and physical examination reports, user emotion and ability evaluations, etc.), and do not achieve information interaction similar to doctor consultations. Therefore, the sources of their health information lack systematicness and comprehensiveness, thus affecting the accuracy of health assessments.

[0013] The health assessment results lack reference value: Generally, wearable intelligent devices often only count and list the health monitoring data for users to view and analyze by themselves, without achieving the effect of intelligent health management. Even if individual devices can provide certain health assessment results, they are only calculated based on simple physiological characteristic data models, not based on artificial intelligence large models. In addition, their health assessment results lack a systematic and comprehensive health information source foundation and ignore user individual differences. Therefore, such health assessment results do not have reference value.

[0014] The user interaction method is single: Generally, wearable intelligent devices mostly only display health monitoring data or health assessment results in the corresponding interface window, and their systems lack user interactivity and participation. Users often can only passively receive health suggestions and lack a real-time and in-depth communication and feedback mechanism with the health management system or professionals. This single interaction method cannot meet the needs of users for real-time communication and feedback during the health management process. For example, when users have questions about health suggestions or encounter difficulties during implementation, they cannot obtain targeted answers and guidance in a timely manner, affecting the effective implementation of the health management plan.

[0015] Lack of health management collaboration ability: Generally, wearable intelligent devices are usually used independently and cannot achieve the following functions in the cluster user mode: manage supplementary health information for other users (such as establishing a basic health file, uploading medical and physical examination reports, conducting relevant ability and emotion evaluations, etc.), perform device proxy binding operations, and establish attention and collaborative management of health information among different users. This limitation makes it difficult for them to meet the complex needs of multi-person health management. In real life, scenarios such as family health management and enterprise employee health management have high requirements for collaboration ability. For example, when healthy users are unable to complete relevant operations alone due to old age or physical defects, or for group, family, or even family users, general wearable intelligent devices cannot meet the needs and scenarios of such cluster health management.

[0016] (III) Deficiencies of existing artificial intelligence in personal health management

[0017] With the development of artificial intelligence technology, some application explorations have emerged in the field of health management. Some systems use machine learning algorithms to analyze massive medical data to assist doctors in disease diagnosis, but most are limited to specific disease categories or single medical procedures and have not been able to build a comprehensive system that comprehensively covers all dimensions of personal health management. In practical application scenarios such as chronic disease management, lifestyle and psychological factors of patients cannot be comprehensively considered.

[0018] In addition, with the progress of artificial intelligence natural language processing technology, artificial intelligence language models or intelligent chatbots such as Doubao, Kimi, and iFlytek Spark AI have emerged and become important tools in people's daily lives and work. However, these general-purpose intelligent chatbots cannot independently obtain users' health monitoring data. Usually, users need to actively provide health information sources and then the chatbots will interpret and reply, and they are not professional health management systems. Health management APPs such as "iFlytek Xiaoyi" support users to upload medical reports, but they also cannot automatically obtain users' health monitoring data or more health information sources, and their nature is similar to that of general-purpose intelligent chatbots.

[0019] Considering the above situation, by consulting patent documents on the application of artificial intelligence in health management, no solution has been found that takes personal health as the core and can solve the deficiencies of traditional medical models and health consultations as well as the shortcomings of general wearable intelligent devices in health management.

[0020] For example, the patent application number is 202110414313.1, and the name is Artificial Intelligence Multidisciplinary Expert Collaboration Health Management System and Method. This invention discloses an artificial intelligence multidisciplinary expert collaboration health management system. A health monitoring chip is provided inside the artificial intelligence health management device. The health monitoring chip is electrically connected to a display screen, a palm sensing area, and a sole sensing area through wires respectively. A cloud storage module and an information receiving module are arranged in parallel inside the health monitoring chip. A health management module is provided inside the client module. A pending consultation module and a completed consultation module are arranged in parallel inside the doctor end module; this artificial intelligence multidisciplinary expert collaboration health management system enables patients to timely master their physical health conditions, has a good treatment effect on existing chronic diseases, has a good preventive effect on possible chronic diseases, comprehensively evaluates health and chronic diseases, and launches a "evaluation - follow-up - re-evaluation - follow-up" health management spiral rising full health management cycle closed-loop system to achieve full-life-cycle health management.

[0021] The above-mentioned invention discloses a health management system and method. Although the invention is called a management system, it is actually designed around specific health management-related devices, mainly collecting body data through specific hardware structures such as a foot sole sensing area and a palm sensing area. This system is not a person-centered artificial intelligence health management system. Although it has launched a closed-loop system of the entire health management cycle with a spiral upward of "assessment - follow-up - re-assessment - follow-up" in health management, the format of its health information source is relatively fixed and limited. Besides the user's basic information, it fails to comprehensively collect various other health supplementary information of the user, such as medical and physical examination reports, emotional and ability evaluation results, lifestyle information, etc. In terms of health management, due to the lack of comprehensive integration of health information, it is unable to provide users with accurate personalized health management solutions. For example, in formulating health risk assessments and preventive healthcare measures, it is difficult to be accurate and personalized due to the lack of key factors such as lifestyle information. At the same time, there are deficiencies in the integration of health information for long-term health management, and it cannot make full use of multiple health information sources to optimize health management strategies. Therefore, this system is limited to specific disease categories or single medical links and has not yet constructed a comprehensive and constructive system covering all dimensions of health management.

[0022] Another example is the invention with the application number 201910062638.0 and the name of a personalized physical health terminal service system based on artificial intelligence. This invention belongs to the field of artificial intelligence health management systems and particularly relates to a personalized physical health terminal service system based on artificial intelligence. This invention collects parameters such as health indicators related to the user's physique, including heart rate, blood pressure, body temperature, and pulse information, then analyzes the collected parameters, and compares the parameters with the pre-stored physique model in the system to give accurate health guidance information to the user. At the same time, it structures the periodic physique parameters of the user into data problems, and the physique health management AI conducts data analysis by asking and answering questions for the user. For the question points that the user often answers wrongly and the problem points that have not been improved, chart analysis and warning are carried out in the system blind area warning module. Through the feedback of the physique health management AI of personalized display information and warning information, the interactivity of the system is improved, and the user can be detected and actively reminded to monitor and improve their own physique, enabling the user to have a better understanding of their own physique and improvement in the long term.

[0023] The above-mentioned invention discloses a personalized physical health terminal service system. Although it belongs to the field of artificial intelligence health management systems and also enables an intelligent management robot, which is a virtual robot, to be carried on the system terminal, it has some obvious limitations. This system mainly focuses on the physical health management of students, designs around the collection of specific physical health-related indicators (such as heart rate, blood pressure, body temperature, and pulse information, etc.), and then compares them with the pre-stored physical models in the system to provide health guidance. It is not for the comprehensive health management of ordinary individuals and lacks the collection of other important health supplementary information, such as medical and physical examination reports, emotion and ability evaluation results, lifestyle information, etc., and cannot comprehensively understand the health status of users. The interaction between the users and the system of this invention mainly conducts questions and answers through the physical health management AI, but the questions are limited to physical-related parameters and the questions generated based on these parameters. The feedback forms are mainly rewards or prompt information for the users' correct or incorrect answers, as well as warnings for the error-prone question points of the users, and do not fully utilize the experience characteristics of natural language understanding and interaction of artificial intelligence. This interaction method is relatively limited and lacks more user-friendly and diverse methods such as natural language interaction to meet the different health consultation and communication needs of users.

[0024] For another example, the application number is 202410789753.9, and the name is a health record tracking and feedback system based on artificial intelligence and machine learning technologies. This invention discloses a health record tracking and feedback system based on artificial intelligence and machine learning technologies, including a data collection module, a data processing module, a health assessment module, a feedback generation module, a prediction module, and a user interface module. It can collect users' physiological data in real time through biosensors, generate personalized health assessments and suggestions by processing and analyzing the data, the system can predict future health conditions, provide timely health intervention suggestions, and the user interface is friendly and intuitive to help users understand health data and suggestions.

[0025] However, although the above-mentioned invention adopts artificial intelligence and machine learning technologies, its technical application is mainly limited to the data collection and processing level, which has similarities and limitations with ordinary wearable intelligent devices. This invention only has improvements in data processing and algorithms due to the use of artificial intelligence technologies. For example, the data processing module uses specific deep neural network structures and algorithms for data cleaning, modeling, etc. operations, and constructs functions applicable to the health record data set. However, its "health record data set" is actually only limited to the health monitoring data of the collection module and does not fully consider other key health information outside the users' physiological data, such as the users' basic health records, medical and physical examination reports, emotion and ability evaluation results, and lifestyle information, etc. This single-dimensional data source makes the system unable to comprehensively evaluate and manage the users' health status from multiple perspectives, and may thus affect the accuracy, comprehensiveness, and effectiveness of health management.

[0026] Although the above-mentioned invention mentions that the user interface is friendly and intuitive and helps users understand health data and suggestions, it lacks specific explanations. It only gives a simple scheme idea without elaborating on specific implementation plans in detail. Moreover, it does not clarify whether the interactive interface has a mechanism to obtain users' health supplement information. At the same time, it does not mention whether there are AI health agents and AI health digital humans trained based on artificial intelligence, nor does it explain their working methods and interaction mechanisms. Although it mentions "helping users understand health data and suggestions", it does not indicate whether it supports users to actively supplement health information or conduct real-time health consultations or medical inquiries. This situation makes users in a relatively passive health management mode similar to ordinary wearable smart devices during the health management process and cannot meet the more actual needs of users to actively participate in health management.

[0027] (IV) Innovative Measures and Practical Significance of the Present Invention

[0028] In summary, the present invention fully considers the defects and deficiencies of traditional medical health management methods, wearable smart devices, and existing artificial intelligence health management systems. In response to these problems, the present invention carefully launches a brand-new artificial intelligence-based interactive health management system and its operation method, which is abbreviated as the "AI Health Management System". The present invention has a design concept centered on personal health and conducts systematic design around the overall health status of individuals. This concept not only focuses on the root causes of diseases but also emphasizes disease prevention and health promotion, aiming to provide users with comprehensive and personalized health management services.

[0029] The personal health management system involved in the present invention collects users' health information through various channels to build a complete health information source. Firstly, it uses collection devices to collect basic health monitoring data and information, which cover many key health indicators, such as data on health signs (heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc.), health behavior data (sleep status, exercise conditions, etc.), and health stress data, and analyzes them through professional algorithms to obtain preliminary health monitoring information. Secondly, it uses the health supplement information management system to gather more detailed health information of users, including users' basic health records, medical and physical examination reports, and users' emotion and ability evaluation results, etc., and organically integrates this information with the previously obtained health monitoring information to build a relatively comprehensive user health information source.

[0030] In addition, the present invention deploys an AI health digital human, which, during the process of providing health consultations to users, can further collect users' supplementary health information and feedback in a manner similar to that of ordinary doctors' consultations, making the users' health information sources more complete. On this basis, the AI health management system of the present invention uses an AI health intelligent agent trained in artificial intelligence and health systems to comprehensively and deeply analyze and calculate the users' comprehensive health information sources, and then provide users with accurate health assessment results. At the same time, with the natural language interaction function of the AI health digital human, it can respond 24 hours a day, 7 days a week, and meet the users' health consultation demands through a natural language multi-modal interaction mode, answering various consultation questions of users regarding health or the use of system devices. In short, the present invention is committed to obtaining the most comprehensive health information sources of users and using cutting-edge artificial intelligence technologies for analysis and calculation, aiming to provide users with highly valuable assessment results and health suggestions.

[0031] Moreover, the present invention fully considers the general needs of special groups (such as the elderly or people with physical disabilities) for health trusteeship, and innovatively creates a group cluster health management mode and a family cluster health management mode, and supports application scenarios of mutual health concern and health trusteeship among users, greatly meeting the intelligent health management needs of special groups and the needs of multi-user centralized intelligent health management. Further, the health management system involved in the present invention and the deployed AI health digital human also have functions of intelligent reminder and guidance for users' supplementary health information, health matters, and abnormal use of health devices, and act as the customer service staff of the system and devices, greatly enhancing the autonomy and user-friendly experience of users' intelligent health management. In addition, this system also supports a single user to use multiple collection terminal devices simultaneously, making the users' health collection data and information more comprehensive and diversified; the system also supports multiple operation terminal devices, and users can conduct health consultations and communications with the AI health digital human on any operation terminal; the system also supports the export of users' personal health data for reference by third-party medical institutions, making up for the lack of long-term health monitoring data of patients in general medical institutions. The numerous innovative measures of the present invention have achieved major breakthroughs at multiple levels, aiming to fully meet the diverse, user-friendly, and individualized needs of users for health management, helping users achieve more comprehensive, accurate, and convenient intelligent health management, and bringing users an unprecedented health management experience. Summary of the Invention

[0032] In view of the problems appearing in the above-mentioned background technology, the present invention aims to fully meet the diverse, user-friendly, and individualized needs of users for health management, and help users achieve more comprehensive, accurate, and convenient intelligent health management. Specifically, the following technical solutions are adopted:

[0033] Provided is an artificial intelligence-based interactive personal health management system and its operation method, which is abbreviated as the "AI Health Management System" in the specification of the present invention. It includes two key and interrelated parts: basic equipment (hardware) and basic framework (software), jointly constructing a complete and efficient health management system. Specifically, the following technical solutions are adopted:

[0034] (I) System Hardware Architecture

[0035] 1. Overview of Hardware Composition

[0036] As shown in Figure 01 [Schematic Diagram of Basic Equipment for System Composition - Equipment Components], the basic equipment, namely the equipment components, serves as the hardware carrier and environmental conditions for the system operation. The system operation depends on a powerful hardware foundation, mainly composed of a collection terminal device, an operation terminal device, and the hardware system of the AI Health Cloud Service Platform. Among them, the operation terminal device is a general term for the main operation terminal device (such as a smart phone, a tablet computer, etc.) and the secondary operation terminal device (such as a smart speaker, a smart robot, etc.). These hardware components work together to provide a stable operation environment and a physical carrier for data interaction for the system.

[0037] 2. Collection Device Types and Function Integration

[0038] The collection devices supported by the AI Health Management System of the present invention have diversity, which is the key to achieving comprehensive health data collection. For example, wearable intelligent devices (such as smart rings, smart bracelets, smart watches, etc.) integrate a series of advanced sensor technologies, such as optical heart rate sensors (PPG), electrode electrocardiograms (ECG), blood pressure detection sensors, thermometers, acceleration sensors, gyroscopes, etc. Through these sensors, it is possible to collect real-time a wide range of health sign data of users, such as heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc., as well as health behavior data that deeply reflects the living habits and physical activity status of users, such as sleep status, exercise conditions, etc. Household medical detection devices (such as electronic blood pressure monitors, blood glucose meters, body fat scales, etc.) focus on the accurate measurement of specific health indicators, further supplementing the overall health data.

[0039] Different from some existing health management methods that only obtain limited health monitoring data of users through specific collection channels (such as a single collection device), the collection device of the present invention greatly broadens the breadth and depth of data collection. At the level of collection device categories, it includes, but is not limited to, general wearable smart devices without medical device certification, similar wearable health data collection devices with medical device certification, personal or household medical devices and health detection devices with medical device certification, work and living environment monitoring data monitoring devices with professional certification or without professional certification, etc., and the above-mentioned health supplementary information directly or indirectly related to the health of users that can be collected by such collection devices; at the level of the usage mode of collection devices, it includes, but is not limited to, a single specified type of collection device, multiple collection devices of multiple types used alternately, and multiple collection devices of multiple types used simultaneously to collect health supplementary information directly or indirectly related to the health of users, etc.

[0040] At the level of collection device categories, it includes, but is not limited to, general wearable smart devices without medical device certification, similar wearable health data collection devices with medical device certification, personal or household medical devices and health detection devices with medical device certification, work and living environment monitoring data monitoring devices with professional certification or without professional certification, etc., and the above-mentioned health supplementary information directly or indirectly related to the health of users that can be collected by such collection devices, and acoustic collection devices with professional certification or without professional certification.

[0041] The collection device uses built-in professional algorithms to preliminarily process the original sensor data. For example, it removes noise interference through a filtering algorithm and uses a calibration algorithm to ensure the accuracy of the data, so as to obtain more reliable health monitoring information. Then, with the help of wired connection conditions or wireless connection technologies (such as Bluetooth, WiFi, etc.), the processed data is transmitted to the paired operation terminal device (such as a smart phone, etc.), realizing the timely transmission and integration of the data, and further uploading it to the AI health cloud service platform.

[0042] 3. Characteristics of the operation terminal device

[0043] The diversified design of the operation terminal device meets different user scenarios and needs. Main operation terminal devices such as smart phones and tablet computers are equipped with high-performance processors, sufficient memory, and high-resolution displays, run intelligent operating systems, have high openness and compatibility, and support users to install application programs or related APPs of the "main operation terminal (system)". Users can view health data, conduct health consultations, etc. on the operation terminal through touch operations, providing a convenient and intuitive interaction experience.

[0044] Significantly different from general health management methods, secondary operation terminal devices such as smart speakers and smart robots have audio input and output (including microphones and speakers) and network connection functions. Some MCU solutions with non-intelligent operating systems are combined with real-time operating systems (RTOS) to execute the software programs of "secondary operation terminals". At the user level, the operation terminal is mainly used to receive data from collection devices and transmit them to the AI health cloud service platform. At the same time, users can interact with the AI health digital human in the terminal through voice commands for health consultation or Q&A.

[0045] A user can use the primary operation terminal device and the secondary operation terminal device simultaneously; at the same time, the system also supports one user using the primary operation terminal device and another user using the secondary operation terminal device, and the two work together to achieve a health management mode of health trusteeship.

[0046] 4. Hardware Composition of AI Health Cloud Service Platform

[0047] The hardware system of the AI health cloud service platform is the core operation and data storage center of the entire system. It is a powerful integrated software and hardware comprehensive service system, and its important feature is the integration of the AI health intelligent body cloud service end system.

[0048] Its hardware architecture includes high-performance AI computing servers with powerful computing capabilities, capable of quickly processing massive amounts of health data. Large-capacity storage devices (such as hard disk arrays, distributed storage systems, etc.) are used to store users' health information sources, health assessment results, and various data required for system operation, ensuring the secure storage and ready access of data. High-speed network connection devices (such as 10 Gigabit Ethernet, Fibre Channel, etc.) ensure the rapid transmission of data within the platform and the efficient interconnection with external devices and systems.

[0049] In terms of computing resources, the platform can parallelly process the health data operation tasks of multiple users, meeting the needs of a large number of users using the system online simultaneously. In terms of storage resource characteristics, data redundancy technology and efficient data management strategies are adopted to ensure data security and scalability. For example, regular backups of users' health data are performed to prevent data loss.

[0050] (2) System Software Architecture

[0051] 1. Overview of Software System Composition

[0052] As shown in Figure 02 [Schematic Diagram of the Basic Architecture of System Composition - Software System], in terms of the software system, the basic architecture of the AI Health Management System consists of four subsystems: the AI Health Intelligent Agent, the Acquisition Terminal, the Operation Terminal, and the AI Health Cloud Service Platform. These subsystems cooperate closely to jointly achieve the intelligent health management function of the system. Among them, the AI Health Intelligent Agent is divided into a client system and a cloud server system, which are respectively embedded in the operation terminal and the AI Health Cloud Service Platform, and at the same time integrate cloud computing capabilities and mobile terminal interaction functions, providing core support for the intelligent operation of the system.

[0053] As shown in Figure 02 [Schematic Diagram of the Basic Architecture of System Composition - Software System], in addition to including the above-mentioned core secondary subsystem, the AI Health Intelligent Agent Client System, the main operation terminal also covers other secondary subsystems: The Health Monitoring Information Management System is responsible for collecting, organizing, and analyzing users' health monitoring data and information, providing a basis for subsequent evaluation; The Health Supplementary Information Management System supports users to manage their personal health supplementary information and integrates it with health monitoring information to form the AI health information source of users; Other management systems of the main operation terminal are responsible for ensuring the normal operation of the device and realizing function expansion, covering multiple aspects such as device settings and permission management.

[0054] As shown in Figure 02, other management systems of the secondary operation terminal and the AI Health Intelligent Agent Client System jointly form a complete secondary operation terminal; Other management systems of the cloud service platform and the AI Health Intelligent Agent Cloud Server System form a complete AI Health Cloud Service Platform; The Health Data Acquisition Management System and other management systems of the acquisition terminal form a complete acquisition terminal.

[0055] 2. Composition of Function Modules of Each Subsystem

[0056] As shown in Figure 03 [Schematic Diagram of Deployment of Main Function Modules of the System - AI Health Intelligent Agent], the AI Health Intelligent Agent Client System includes the following main function modules: AI Audio-Visual Dialogue Window Interaction Module, AI Audio Dialogue Interaction Module, AI Health Information Source Acquisition Module (Client), AI Health Assessment Result Display Module, AI Health Assessment Result (Ⅰ) Output Module, AI Health Assessment Result (Ⅱ) Output Module; The AI Health Intelligent Agent Cloud Server System includes the following main function modules: AI Health Information Source Acquisition Module (Cloud Server), Medical and Physical Examination Report AI Analysis Module, AI Health Information Source Processing Module, AI Health Intelligent Agent Initial Calculation Module, AI Health Intelligent Agent Precise Calculation Module, AI Health Assessment (Ⅰ) Generation Module, AI Health Assessment (Ⅱ) Generation Module.

[0057] As shown in Figure 04 [Schematic Diagram of the Deployment of the Main Functional Modules of the System - AI Health Cloud Service Platform], in addition to the main functional modules of the AI Health Agent Cloud Server System, the subsystem "Other Management System of the Cloud Service Platform" includes the following main functional modules: System User Management Module (Cloud Server), Data Synchronization and Storage Module (Cloud Server), Network Communication and Protocol Service Module, Instruction Parsing and Execution Service Module, AI Health Agent Development Module, Platform System (Other) Management Module.

[0058] As shown in Figure 05 [Schematic Diagram of the Deployment of the Main Functional Modules of the System - Main Operation Terminal], in addition to including the subsystem AI Health Agent Client System and its main functional modules, the secondary subsystems of the main operation terminal, namely the Health Monitoring Information Management System, the Health Supplementary Information Management System, and the Other Management System of the Main Operation Terminal, each have their main functional modules.

[0059] Among them, the main functional modules included in the Health Monitoring Information Management System are: Health Monitoring Data Cleaning Module, Health Monitoring Information Review Module; the main functional modules included in the Health Supplementary Information Management System are: User Health Basic File Management Module, User Medical and Physical Examination Report Management Module, User Emotion and Ability Evaluation Module, User Health Other Information Management Module.

[0060] Among them, the main functional modules included in the Other Management System of the Main Operation Terminal are: User Management Module (Client), Personal Device Binding Module (Client), Data Synchronization and Storage Module (Client), Network Communication and Protocol Terminal Module, Instruction Parsing and Execution Terminal Module, Group Cluster Management Module (Client), Family Cluster Management Module (Client), Cluster Device Binding Module (Client), Terminal Device System Resource Invocation Module, Main Operation Terminal (Other) Application Module, Main Operation Terminal (Other) Management Module.

[0061] As shown in Figure 06 [Schematic Diagram of the Deployment of the Main Functional Modules of the System - Secondary Operation Terminal], in addition to including the subsystem AI Health Agent Client System and its main functional modules, the Other Management System of the Secondary Operation Terminal has some functional modules in common with the Other Management System of the Main Operation Terminal. In addition, the Other Management System of the Secondary Operation Terminal may have the Secondary Operation Terminal (Other) Interaction Module and the Secondary Operation Terminal (Other) Management Module.

[0062] 3. Collaboration Mechanism of the Important Functional Modules of the System

[0063] Specifically, the AI health management system deploys AI health digital humans, which are virtual digital humans in the "AI audio-visual dialogue window interaction module" and "AI audio dialogue interaction module" of the operation terminal, and are special system programs for the function module and interaction module of the operation terminal. The AI health digital human is also the interface and carrier for the AI health intelligent agent to interact with users. It presents itself to users in a digital human-like image and communicates with users through natural language processing technology to answer users' health questions and provide health knowledge and advice.

[0064] The health monitoring information management system of the operation terminal focuses on collecting, organizing, and analyzing real-time health monitoring data from the acquisition terminal, including key indicators such as health sign data (such as heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc.), health behavior data (such as sleep status, exercise situation, etc.), health stress data, as well as the health conclusions obtained by the acquisition device through preliminary calculations. After cleaning (removing noise and outliers) and reviewing (checking data rationality, consistency, and integrity) the data, the system uploads the data to the AI health cloud service platform and also transfers some data to the AI health intelligent agent client system to provide the latest monitoring information in a timely manner when users query.

[0065] The health supplementary information management system of the operation terminal provides a platform for users to comprehensively manage their personal health supplementary information. Users can establish a health basic file in this system and enter in detail personal basic information (such as gender, age, height, weight, etc.), work-related information (such as work nature, work schedule, whether there are night shifts and overtime, etc.), lifestyle information (such as exercise situation, bad habits, etc.), physical condition (such as whether often catching colds, allergic substances, etc.), basic medical history (such as whether there are basic diseases, whether having had surgeries, etc.), and female-specific information (such as menstrual time, whether pregnant, etc.). Users can also upload medical and physical examination reports, and the system will analyze the reports, extract key information, and integrate it into the user's health information source. In addition, users can conduct emotion and ability evaluations, and the system provides personalized health management suggestions based on the evaluation results.

[0066] 4. Explanation of the innovation of the system architecture

[0067] Different from some existing health management methods that are composed of only specified single acquisition devices, operation terminal devices, ordinary cloud database servers and other software and hardware components in a traditional fixed mode. For example, in some existing health management methods, due to the single acquisition device, only limited health data can be obtained, which cannot meet the users' needs for comprehensive health monitoring; at the same time, its operation terminal is fixed and difficult to adapt to the usage habits and scenario changes of different users.

[0068] The health management system involved in the present invention can obtain more comprehensive health monitoring data and health supplement information of the same user through one or more collection devices and various channels and methods. The software architecture of this system consists of components such as a collection terminal, an operation terminal, and an AI health cloud service platform. Among them, the system has developed an AI health intelligent agent and an AI health digital human through comprehensive training based on artificial intelligence technology and health professional knowledge. The AI health intelligent agent client and the AI health digital human are deployed on the operation terminal, and the AI health intelligent agent cloud server is deployed on the AI health cloud service platform. The operation terminal of the system is divided into a main operation terminal and a secondary operation terminal.

[0069] In addition to the above software system, the health management system of the present invention also includes the following hardware systems: collection devices, operation terminal devices, and the hardware system of the AI health cloud service platform. Among them, the operation terminal devices are further divided into main operation terminal devices and secondary operation terminal devices. The collection terminal is installed inside the collection device, the main operation terminal is installed on the main operation terminal device for user health management (such as a smart phone, etc.), and the secondary operation terminal is installed on the secondary operation terminal device for user health management (such as a smart photo frame or a smart robot, etc.), serving as an auxiliary tool for user health management.

[0070] In the health management system of the present invention, the collection device is connected to the operation terminal device for transmitting the user's health monitoring data and information; the operation terminal device can communicate bidirectionally with the AI health cloud service platform to achieve the upload of the user health information source, the comprehensive analysis and operation of the AI health intelligent agent, and the reception and output of the AI health assessment results. The AI health digital human, as a part of the AI health intelligent agent, is an intelligent health advisor for natural language interaction between the system and the user, and the AI health intelligent agent provides data and decision support for the AI health digital human. Each component of the system works together to jointly promote the operation of the health management work.

[0071] A typical collection device of the health management system of the present invention is similar to a common wearable intelligent device, integrating multiple sensors and technologies, including but not limited to an optical heart rate sensor (PPG), an electrode electrocardiogram (ECG), a blood pressure detection sensor, a thermometer, an acceleration sensor, a gyroscope, etc. Through the interaction with these sensors and the application of professional algorithms, the collection device can drive the sensors in real time to collect the user's health monitoring data, thereby obtaining key health indicators of the wearer user, including but not limited to heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc., health behavior data (including but not limited to sleep status, exercise conditions, etc.), health stress data, and preliminary health monitoring information obtained through professional algorithm analysis.

[0072] The acquisition device of the health management system described in the present invention transmits health monitoring data and information to the paired and bound operation terminal device through wired or wireless connection. The operation terminal device then transmits it to the AI health cloud service platform as the basic data of the user's AI health information source. This health management system supports the timed automatic measurement mode of the acquisition device or the user can actively initiate the measurement of relevant data at any time. As the user cooperates with the continuous normal operation of the acquisition device, the user's health monitoring data will continue to accumulate and update, and be recorded in the user's AI health information source in chronological order.

[0073] In the health management system of the present invention, health monitoring data and health supplement information complement each other to jointly constitute the user's complete AI health information source. Health monitoring data provides the basic data support for the real-time evaluation of the system, while health supplement information enriches the data dimension. The two work together under the comprehensive analysis and operation of the AI health agent, making the AI health evaluation result more accurate and comprehensive, and further achieving the purpose of providing personalized health evaluation and suggestions for users, further reflecting the innovation of the present invention in the field of health management.

[0074] (III) System Data Management and Security Mechanism

[0075] 1. Application of System Data Transmission Technology and Communication Protocol

[0076] Multiple wireless transmission technologies are used for data transmission in the system to meet the requirements of different scenarios. Bluetooth is suitable for short-distance and low-power data transmission scenarios, such as the data transmission between the acquisition device and the operation terminal device. It is convenient to connect and has high stability, but the transmission speed is relatively slow. It is suitable for transmitting health monitoring data with high real-time requirements but small data volume, such as real-time data like heart rate and blood oxygen saturation. This targeted application of transmission technology is not available in traditional health management methods, and traditional methods may not have such refined data transmission strategies. WiFi is suitable for transmitting a large amount of data in an indoor environment, such as the data transmission between the operation terminal device and the AI health cloud service platform. It has the characteristics of fast transmission speed and wide coverage, and can quickly upload the user's health data and download health evaluation results, health suggestions and other information. Mobile networks (such as 4G, 5G) provide data transmission guarantee for users in outdoor areas or areas without WiFi coverage, ensuring that users can be connected to the system in real time, such as receiving health reminders in real time, and ensuring that users can interact with the system for data in different environments.

[0077] In terms of communication protocols, the HTTP / HTTPS protocol is commonly used for regular data interaction between the operating terminal and the cloud service platform, such as user login, information query, data upload and download, etc. This protocol is based on the request-response model to ensure the reliable transmission of data over the network. The HTTPS protocol adds an SSL / TLS encryption layer on top of HTTP to guarantee the confidentiality and integrity of data transmission, preventing data from being stolen or tampered with during transmission. Traditional health management systems may not have such perfect security measures for data transmission. The MQTT protocol is mainly applied to message pushing between devices, such as the acquisition device pushing real-time monitoring data to the operating terminal or the cloud service platform. It has the characteristics of being lightweight, low-power, highly reliable, and can ensure the accurate transmission of messages in an unstable network environment.

[0078] 2. Data Fusion of System's Multi-Terminal Devices

[0079] The AI health management system of the present invention supports the simultaneous use of the main operating terminal device and the secondary operating terminal device, as well as the alternating or simultaneous use of multiple types of acquisition devices. Therefore, it ensures the strict corresponding management between the user's health data and the devices, as well as the data processing of multiple devices.

[0080] To ensure the strict corresponding management between the user's health data and the devices, the system of the present invention adopts an advanced data management strategy. At the acquisition device end, the data collected by each device carries unique identification information, such as device serial number, sensor number, etc. This information is transmitted to the operating terminal device together with the collected data. After receiving the data, the operating terminal device associates the data with the corresponding user account and device information through built-in intelligent recognition and matching algorithms. For example, when a smart bracelet and an electronic sphygmomanometer transmit data to a smartphone at the same time, the system can accurately identify which data comes from the bracelet (such as the number of steps and heart rate data), and which data comes from the sphygmomanometer (such as blood pressure value), and integrate them into the user's personal health record to ensure the accuracy and integrity of the data.

[0081] The system also implements a dynamic data update and synchronization mechanism. When the user collects health data at different times using different devices, the system can update the user's health information source in real time and ensure that the health data displayed on each operating terminal device (whether it is the main operating terminal or the secondary operating terminal) is the latest. For example, when the user uses a smart watch to monitor exercise data outdoors and then uses a body fat scale to measure body composition data at home, these data will be synchronized to the AI health cloud service platform in a timely manner, and the updated comprehensive health information will be displayed on the user's smartphone and tablet.

[0082] The system also has intelligent data fusion and analysis capabilities. It can fuse data from different types of collection devices, explore the internal relationships between the data, and thus generate more valuable health assessments and suggestions. For example, by combining the exercise data, sleep data of a smart bracelet and the blood glucose data of a home blood glucose meter, the system can analyze the impact of the user's lifestyle on blood glucose fluctuations and provide personalized exercise and diet suggestions for the user.

[0083] In summary, for the AI health management system framework, through the innovative design of the above system hardware architecture, software architecture, and data processing and security mechanisms, the AI health management system of the present invention is significantly superior to the existing general health management methods. The innovation of the AI health management system of the present invention in supporting multi-terminal and multi-device collaborative work is not only reflected in the diversified integration of hardware devices and the collaborative operation of software systems, but more importantly in the intelligence and precision of data management and processing mechanisms. Through these innovations, the system can provide users with comprehensive and personalized health management services, realizing the transformation of health management from the traditional fragmented and single-mode to the intelligent and integrated mode. This technological innovation is of great significance in enhancing the user's health management experience and improving the health management effect, and is expected to lead the development trend of the future health management field and provide a more powerful guarantee for people's healthy life.

[0084] 3. System Data Transmission and Storage

[0085] In this system, the operation terminal mainly serves as an application computing tool and program. The collection device and the operation terminal device not only act as collection or operation tools, but also play the role of network data transmission tools. When the user's health monitoring data is successfully transmitted to the AI health cloud service platform, the user profile and health information are disassociated from the operation terminal and the device. This means that even if the same user replaces the collection device or the operation terminal device again and reinstalls the terminal program, it will not affect the user's AI health information source and AI health assessment results. However, it should be noted that if the user does not fully synchronize the local data to the system before replacing the collection device or the operation terminal device, it may cause some data loss.

[0086] Collection devices usually temporarily store health monitoring information within a certain period of time, and the temporary storage duration varies for different devices. When the system detects the absence of user health monitoring data and information, the AI health digital human will promptly guide the user to troubleshoot the reasons and remind them to upload data as soon as possible, thereby reducing the risk of data loss. When the operation terminal is connected to the network and in the working state, the health monitoring information and health supplement information will be quickly synchronized and transmitted to the AI health cloud service platform, and the health supplement information updated by the operation terminal in the connected state will also be transmitted synchronously. The AI health cloud service platform provides stable and reliable guarantees for aspects such as data storage, backup, system security, and maintenance.

[0087] In addition, considering the special needs of some users or the restrictions of certain regional policies, health data may be restricted from leaving the country or transmitted to the cloud platform (such as the aforementioned AI health cloud service platform). In this case, the health management system can deploy the AI health intelligent agent cloud service end system to the operation terminal in an optimized configuration and reduced installation volume. Although this deployment method will affect the accuracy of the AI health assessment results to a certain extent, it can still basically achieve the closed-loop process of health management. This implementation method is within the innovation scope of the present invention.

[0088] For example, in some regions with strict regulatory requirements for data transmission, the system can flexibly adjust the deployment method according to local policies to ensure that as perfect a health management service as possible is provided to users on the premise of compliance. At the same time, for those users who are concerned about data security, this localized deployment method also provides an option, enabling users to use the health management system with more confidence.

[0089] 4. System Data Management and Security Protection

[0090] In terms of data encryption transmission safeguard measures, the system uses a variety of encryption algorithms to ensure data security. For user-sensitive information (such as personal identity information and medical records in the health file), the AES (Advanced Encryption Standard) encryption algorithm is used for encrypted storage to ensure the security of data in the storage medium. Traditional health management systems may not be able to achieve such encryption intensity in data storage security. During the data transmission process, the RSA (Rivest–Shamir–Adleman) algorithm is used for key exchange to establish a secure encryption channel, and then the AES algorithm is used to encrypt the transmitted data to prevent the data from being intercepted and stolen during network transmission. In terms of key management, the system adopts a centralized key management system to update keys regularly to ensure the security and effectiveness of the keys.

[0091] At the same time, the system also has perfect security protection measures. In terms of the identity authentication mechanism, when users register and log in, the system verifies through the username and password, and also supports biometric technologies such as fingerprint recognition and facial recognition as auxiliary authentication means to ensure the authenticity of user identities. Traditional health management may only rely on simple account password verification, with relatively low security. For device access, when the acquisition device and the operation terminal device are connected to the system, device authentication is required. Identity recognition is carried out through information such as the device serial number and MAC address to prevent illegal devices from accessing the system. In terms of access control policies, the system sets different access levels according to user roles and permissions. For example, ordinary users can only access their own health data, while administrators can access and manage the health data of users within a certain range. Corresponding access permissions are also set for different functional modules and data resources. For example, only authorized professionals or system algorithms can operate the health assessment result generation module to prevent unauthorized access and data tampering. Traditional health management systems may not be as refined and strict in permission management. In terms of data storage encryption, in addition to encrypting the storage of sensitive information, encryption technology is also adopted for the entire database to ensure the security of data in the storage medium and prevent data leakage incidents.

[0092] (4) System User and Device Management

[0093] In the current field of digital health management, the user management and interaction mechanism is a key link for the system to operate effectively and meet user needs. Traditional health management systems often have many deficiencies in user management, such as chaotic user information management, single and not very intelligent interaction methods, and inflexible and not very refined permission settings. The present invention is committed to solving these problems and has constructed a comprehensive and innovative user management and interaction mechanism, aiming to provide users with a more convenient, secure and personalized health management experience.

[0094] 1. User Management System

[0095] User registration and login process (including multiple identity verification methods): When using this system, users first need to open the AI health management system application on the main operation terminal device (such as a smartphone, tablet, etc.). After entering the registration interface, fill in basic information such as username, password, and contact information (such as mobile phone number or email). The system will send a verification code to the contact information filled in by the user, and the user needs to enter the correct verification code to complete the preliminary verification. During the login process, the user enters the registered username and password, and the system verifies. At the same time, to improve security, the system supports multiple identity verification methods, such as biometric technologies like fingerprint recognition and facial recognition as auxiliary verification means. For example, when logging in, the user can choose to use fingerprint recognition. Just place the finger on the device fingerprint recognition area, and the system can quickly verify and log in, ensuring the authenticity and security of the user identity.

[0096] User Information Management (Classification Management and Update Methods of Personal Basic Information and Health Records): User information management covers personal basic information and health record management. Personal basic information includes name, gender, age, height, weight, occupation, etc. These information are filled in by users during registration and can be modified and improved in the system later. Health records are comprehensive records of users' health conditions, including basic health records, medical and physical examination reports, emotional and ability evaluation results, etc. Basic health records include work-related information (such as nature of work, work schedule, whether there are night shifts and overtime, etc.), lifestyle information (such as exercise situation, bad habits, etc.), physical condition (such as whether often catch colds, allergic substances, etc.), basic medical history (such as whether there are basic diseases, whether had surgeries, etc.), and female-specific information (such as menstrual time, whether pregnant, etc.). Users can enter basic health record information in the corresponding module of the operation terminal, and the system stores it classified. Medical and physical examination reports can be uploaded by users, supporting multiple formats (such as PDF, JPEG, etc.). The system will automatically identify and parse the formats, extract key information and integrate it into the health records. Emotional and ability evaluation results are provided by the system with corresponding evaluation tools (such as intelligence tests, emotional control tests, etc.). After users complete the evaluations, the results are automatically stored in the health records. Users can view and update their health records at any time, and the system will record the update history to facilitate users to trace and manage their health information.

[0097] Multiple Interaction Modes between Users and the System (Interaction Scenarios and Implementation Technologies such as Health Consultation, Information Query, Operation Instruction Input, etc.): The interaction modes between users and the system are rich and diverse. In terms of health consultation, users can ask health questions to the AI health digital human through text input or voice commands, such as "I always have headaches recently. What could be the reasons?" The AI health digital human uses natural language processing technology to understand users' questions and then provides corresponding answers and suggestions based on system knowledge and users' health information sources. When querying information, users can query their health monitoring data (such as real-time heart rate, blood pressure, blood sugar, etc.), health assessment results, health record content, etc. on the operation terminal. The system quickly retrieves and displays relevant information through the database query function. In terms of operation instruction input, users can perform various operations on the operation terminal through touch operations (such as clicking, swiping, etc.), such as setting health reminders, adjusting parameters of collection devices, participating in health activity registrations, etc. For example, if a user wants to set a daily morning 8 o'clock exercise reminder, they only need to perform corresponding operations in the reminder setting interface of the operation terminal. The system ensures that users can interact with the system conveniently, obtain the required information and services through user-friendly interface design and efficient interaction technologies.

[0098] 2. User Permission Management

[0099] Specific permission settings for different types of users (individual users, cluster administrators, custodians, ordinary cluster members, etc.) in different application modes (individual mode, group cluster mode, family cluster mode): In the individual mode, individual users have full access to their own health data, including viewing and editing health basic files (such as modifying personal basic information, updating lifestyle changes, etc.), viewing health monitoring data (such as real-time viewing of heart rate, blood pressure, etc.), viewing health assessment results and detailed reports, conducting health consultations (freely communicating with AI health digital humans about health problems), formulating and implementing personalized health management plans according to system suggestions (such as adjusting diet and exercise plans), etc. Individual users can also apply for or cancel health concerns for other users (including individual users and cluster users), but the health supplement information of the concerned objects will not be aggregated into their own health information sources.

[0100] In the group cluster mode, enterprise administrators have the highest permissions. They can view the summary of the health data of all employees in the company (such as overall health indicator statistics, disease distribution, etc.), formulate enterprise health management policies (such as stipulating the physical examination cycle of employees, health activity arrangements, etc.), organize company-wide health activities (such as group physical examinations, health lectures, health competitions, etc.), and allocate and manage the permissions of subordinate department administrators and employees (such as setting the permission scope of department administrators, enabling or restricting certain operation permissions of employees). Department administrators can view the detailed health data of employees in their departments (including personal health files, monitoring data, assessment results, etc.), organize health activities within their departments, review the health supplement information of employees in their departments (such as verifying the authenticity and validity of medical reports uploaded by employees), and conduct health concerns and health custody for employees in their departments (with the authorization of employees). The permissions of ordinary employee members mainly focus on viewing their own health data and assessment results, participating in health activities organized by the enterprise or department (such as signing up for physical examinations, participating in health lectures, etc.), modifying their own health supplement information within a certain range (such as updating personal lifestyle changes, etc.), and consulting health problems with the system or administrators.

[0101] In the family cluster mode, the family administrator is responsible for the custody of the health information of family members, including the custody of supplementary health information for family members (such as establishing basic health files, uploading medical and physical examination reports, and conducting emotional and ability assessments, etc.), managing the binding of family members' collection devices and auxiliary operation terminal devices (performing device binding and unbinding operations), viewing family members' health data summaries and analysis reports (understanding the overall health status of the family), and paying attention to the health of family members (actively obtaining the health status of family members and the working status of collection devices). The permissions of ordinary family members include viewing their own health data and evaluation results, consulting with AI health digital people, modifying their own supplementary health information within a certain range (such as updating changes in personal living habits, etc.), and viewing some family members' health information (such as immediate family health information) with authorization.

[0102] Permission change mechanism (trigger conditions, approval process, etc.): There are various trigger conditions for permission changes. In an enterprise or organization, position change is one of the common trigger factors. For example, when an employee is promoted to a department administrator, the system will automatically trigger the permission change process and grant him the corresponding management authority. When the health custody relationship changes, such as the replacement of the custodian or the adjustment of the custody object, the corresponding change of permissions will also be triggered. In addition, according to the adjustment of the company's health management policy, such as temporary changes to employee health data access rights during certain special periods, the administrator can also manually trigger the permission change process. In terms of the approval process, permission changes caused by position changes are usually approved by the company's human resources department or higher-level administrators. The approval steps include submitting an application for permission change (including information such as the reason for the change, comparison of permissions before and after the change, etc.). After receiving the application, the approver will review it according to the company's regulations and actual situation. If the approval is passed, the system will automatically update the user's permissions; if not, the applicant will be notified and the reason will be explained. For permission changes caused by changes in health custody relationships, the original custodian or the object of custody shall submit an application, and after confirmation by the relevant parties (such as the object of custody agrees to the new custodian's custody application, or the original custodian agrees to terminate the custody relationship), the system will update the permissions. Permission change approval generally has a time limit, such as completing the approval within 3-5 working days after the application is submitted, to ensure the timeliness and effectiveness of system permission management, and avoid delays in permission changes that affect normal user use or the implementation of corporate health management.

[0103] Associations and Restrictions among Permissions (Collaborative Control of Data Access Permissions and Operation Permissions): There are close associations and restrictions among the permissions in the system. The data access permissions and operation permissions are collaboratively controlled. For example, ordinary employees only have the permission to view their own health data. Therefore, in terms of operation permissions, they cannot perform operations such as modifying or deleting the health data of other employees, which ensures the privacy and security of employees' health data. Although department administrators can view the health data of employees in their department, their operation permissions are restricted to a certain extent. For example, they cannot randomly modify the core health data of employees (such as medical diagnosis results), and can only modify some updatable information (such as contact information in the basic health file of employees), and the modification operations will be recorded by the system for traceability and auditing. Enterprise administrators have higher data access and operation permissions, but when performing some sensitive operations (such as deleting a large amount of employees' health data), they need to go through a higher-level approval process (such as approval by senior enterprise leaders or joint approval by multiple people) to prevent abuse of permissions. This restrictive relationship among permissions effectively guarantees the security of the system and the accuracy and integrity of the data, ensures that users use the system legally and compliant within their permissions, and at the same time provides an effective permission management mechanism for the health management work of enterprises or organizations, promoting the orderly development of health management work.

[0104] 3. System User and Device Management Mechanism

[0105] Given the diverse number and complex usage methods of the collection devices (and extended monitoring devices) for health monitoring data and health supplement information, to ensure the accurate correspondence between data and users, the health management system of the present invention sets up the following user management system, device binding module, and their related system operation mechanisms.

[0106] The user management system of this system consists of an operation terminal user management module, a group-style cluster management module, a family cluster management module, and a system user management module of the AI health cloud service platform. These modules work together to provide corresponding operation and function permissions for users in different health management scenarios.

[0107] The system automatically generates a "unique user account identification code" and a "user identity ID number" for each registered user, which are in one-to-one correspondence to represent a user, ensuring the uniqueness and clear identification of each user in the entire health management system. The name of the user is only used as a basic information attribute and is not used for unique identification. It is normal for there to be multiple users with the same name in the system.

[0108] The system can automatically generate a "user identity QR code" for each user's "unique user account identification code" to facilitate interactive operations between users. For example, a user can use the built-in scanning tool of the system or a third-party scanning tool to scan another user's "user identity QR code" to apply for health attention; or enter another user's "user identity ID number" in the health attention window to apply for health attention by searching and selecting.

[0109] A user can simultaneously apply the individual user health management mode, the group-based cluster health management mode, and the family-based cluster management mode. The use of each mode will be clearly marked in the user application file, and their roles in the relevant cluster health management mode will also be clearly marked in the user application file.

[0110] When a user establishes a health attention relationship with another user, whether they are the health attention giver or the health attention recipient in this relationship will also be clearly marked in the user application file. In addition, the same principle applies to more other operations and settings performed by the user using this health management system.

[0111] With the help of the system data synchronization storage module (including the client and the cloud server), the latest user application file information is saved. At the same time, through the system communication protocol and instructions, the user management modules of the main operation terminal and the secondary operation terminal and the AI health cloud service platform are prompted to synchronously update the user application file information, so as to ensure the consistency and integrity of the configuration and data of the entire system, and the system operates or manages according to the updated configuration conditions.

[0112] The device binding module of the health management system is divided into a personal device binding module and a cluster device binding module, aiming to realize the device management, use and maintenance of system users in various health management application scenarios.

[0113] When a user registers a user account using the main operation terminal device, the system will automatically read the "device serial number" and "MAC address" of the main operation terminal device, and then generate a "unique machine identification code for the main operation terminal device", and use this code as the code of the user's main operation terminal device in the system and record it in the user's device file. When the user binds the acquisition device or the secondary operation terminal device, similarly, the system will automatically read the "device serial number" and "MAC address" of the corresponding device, generate a "unique machine identification code for the acquisition device" or "unique machine identification code for the secondary operation terminal device", and use this identification code to represent the user's acquisition device or secondary operation terminal device in the system and record it in the user's device file.

[0114] The corresponding unique machine identification code of the device is associated one-to-one with the user's "unique identity identification code of the user account" to ensure that the main operation terminal device is used by the associated user, to ensure that the health monitoring data and information obtained by the acquisition device belong to the health information source of the associated user himself / herself, and to ensure that the user of the secondary operation terminal device is the associated user.

[0115] The system can automatically generate a "device QR code" for the unique machine identification code of each device, which is convenient for users to perform on-site binding operations or remote binding operations. For example, a user can use the built-in scanning tool of the system or a third-party scanning tool to scan the "device QR code" of an acquisition device to achieve binding, or can also perform binding by searching and selecting through Bluetooth device pairing.

[0116] A user's account is unique and can only be logged in and used on one main operation terminal device. When the user changes the main operation terminal device and logs in on the new device, the account on the original main operation terminal device will automatically log out. At the same time, a user can enable multiple acquisition devices, which can be used alternately or simultaneously to collect more health monitoring data of the user. In addition, a user can also enable two or more secondary operation terminal devices. Similarly, different secondary operation terminal devices can be used at different times to conduct health consultations with the AI health digital human or for other applications, or two or more secondary operation terminal devices can be used simultaneously at the same time to interact with the AI health digital human.

[0117] With the help of the system data synchronization storage module (including the client and the cloud server), the latest user device profile information is saved. At the same time, through the system communication protocol and instructions, the device management modules of the main operation terminal and the secondary operation terminal and the AI health cloud service platform are prompted to synchronously update the user device profile information to ensure the consistency and integrity of the configuration and data of the entire system, and the system operates or manages according to the updated configuration conditions.

[0118] (V) System user health management interaction

[0119] System user health management interaction refers to the process of collection, transmission, processing, feedback and operations based on different permissions and roles around health information between users and various components of the system (including acquisition devices, operation terminal devices, AI health agents, AI health cloud service platforms, etc.) in the AI health management system, covering various modes such as individual user's own health management, health concern between users, and health trusteeship for cluster users, aiming to achieve personalized, precise and systematic health management services.

[0120] 1. Basic mode of health management

[0121] Such as Figure 15As shown in [Schematic Diagram of System User Health Management and Interaction - Basic Health Management Mode], the basic operations of a general individual user for health management and the system workflow include a closed-loop process of health information collection, transmission, processing, and feedback of evaluation results.

[0122] Network interconnection (such as Figure 15 shown by connection ④): The user's collection device and the main operation terminal device remain in a bound state (such as Bluetooth, WiFi, etc.). The main operation terminal device is wirelessly interconnected with the AI Health Cloud Service Platform to achieve data transmission or related control.

[0123] Health information collection and transmission (such as Figure 15 shown by connection ②): The user normally wears (or uses) the collection device to obtain health monitoring data and health monitoring information, and transmits it to the main operation terminal. At the same time, the user inputs health supplementary information in the health supplementary information management system of the main operation terminal, and after comprehensively forming the health information source, it is transmitted to the AI Health Cloud Service Platform.

[0124] Data processing and health assessment: In the AI Health Cloud Service Platform, the data synchronization storage module manages data storage. Multiple functional modules of the AI Health Intelligent Agent Cloud Server System process the health information source, including operations such as acquisition, parsing, preliminary calculation, and accurate calculation, to generate health assessment results.

[0125] Feedback of health assessment results and user interaction (such as Figure 15 shown by connection ③): The AI Health Cloud Service Platform feeds back the health assessment results to the main operation terminal. The user can view the results on the relevant interface of the main operation terminal (such as Figure 23 shown), and interact with the AI Health Digital Human in the main operation terminal to obtain health advice, etc. (such as Figure 25 shown).

[0126] 2. Health Concern Mode

[0127] Such as Figure 16 As shown in [Schematic Diagram of System User Health Management and Interaction - Health Concern Mode], it shows the interaction process of health concern between two users, which is an important application mode of the system user health management interaction. One user's concern for another user's health is mainly reflected in that on their own operation terminal, they can consult the AI Health Digital Human about the health status and the working status of the collection device of the other user.

[0128] In this application mode, this user is the "concerned person", and the other user is the "object of concern". (Such as Figure 16 shown by connection ④): User is the object of concern, and User is the concerned person.

[0129] As a follower, the user can follow multiple follow-up objects simultaneously, and the list of follow-up objects will be automatically listed in the AI Health Digital Human dialogue window (such as Figure 25 shown in ①) and can be switched at any time. If no key object is selected, it is considered that the user is consulting the AI Health Digital Human about their own health information.

[0130] It should be noted that due to system permission restrictions, if the follower informs the AI Health Digital Human of the health supplement information of the follow-up object, it is regarded as invalid information, and the AI Health Intelligent Agent will ignore this information and will not collect it into the health information source of the follow-up object. As Figure 16 shown, when the user communicates with the AI Health Digital Human in the "AI Audio-Visual Dialogue Window" of the operation terminal, although the connection ② is used in the illustration, it only indicates that the user is consulting the AI Health Digital Human about the health problems of their follow-up object (only for special cases for special explanation).

[0131] 3. Health Trusteeship Mode

[0132] As Figure 17 [Schematic Diagram of System User Health Management and Interaction - Health Trusteeship Mode] shows the interaction process of health trusteeship between two users, which is an important application mode of system user health management interaction. One user uses the main operation terminal device to enable the cluster user mode and becomes the cluster administrator to exercise the health trusteeship authority (as Figure 33 shown), becoming the trustee; another user uses the secondary operation terminal device to become the object of their health trusteeship, and the two parties establish a "health trusteeship" relationship (as Figure 17 shown by the connection ⑤).

[0133] The user and the other user cooperate to jointly complete the health trusteeship work and the health management work of the user. The specific operations are as follows:

[0134] The user exercises the health trusteeship authority to bind the acquisition device to the secondary operation terminal device (or remotely), and the user wears (or uses) the acquisition device and works normally. As Figure 17 shown by the connection ⑥, ensure that the secondary operation terminal device is connected to the network so that it can maintain data transmission and control with the AI Health Cloud Service Platform.

[0135] As Figure 30 shown, the user exercises the health trusteeship authority to register a user account for the user, and the AI Health Management System will automatically establish a health trusteeship relationship and record for the user and the other user, support the user to enjoy the subsequent health trusteeship work and rights for the other user, and at the same time the user automatically has the right to pay attention to the health of the other user.

[0136] As Figure 33As shown, the user manages the health supplementary information for the user, that is, establishing a basic health record for the entrusted object, uploading the medical and physical examination reports of the entrusted object, evaluating the emotions and abilities of the entrusted object, etc.

[0137] The user can turn on or wake up the AI Health Digital Human by voice on their secondary operation terminal, and consult their own health problems through conversation, or obtain health reminders from the AI Health Digital Human, or answer the medical questions of the AI Health Digital Human. As one of the AI health information sources for the user, it enables the AI health management system to make a more accurate health assessment result for the user.

[0138] As the health trustee of the user, in addition to having the right to pay attention to the user's health, the user can also consult the AI Health Digital Human about the user's health status and the usage of related devices on their primary operation terminal. The user can entrust multiple entrusted objects at the same time, and the list of entrusted objects will be automatically listed in the AI Health Digital Human dialogue window (such as Figure 25 shown in ① in the figure) and can be switched at any time. Since the user can also pay attention to multiple health care objects at the same time, their entrusted objects and care objects will be distinguished by different labels.

[0139] Particularly, when consulting the health status of the entrusted object with the AI Health Digital Human, the user can also actively provide the health supplementary information of the entrusted object (such as the user), which will become one of the user's health information sources; however, if it is for the user's health care object, the user has no right to provide the health supplementary information of the care object, and even if provided, it will be automatically regarded as invalid by the system.

[0140] If other users want to pay attention to the user's health, the user can view the application information of the other party on their primary operation terminal device and choose "agree or refuse" according to the situation.

[0141] If the user wants to pay attention to the health of other users, the user can apply to the other party on behalf of the user on their primary operation terminal device. Once the other party agrees, the user can enjoy the right to pay attention to the health of other users. At this time, the user can directly tell the AI Health Digital Human "Please help me switch the care object *** (name or relationship)", and at this time, the user and the AI Health Digital Human are consulting the health of the care object. If the user wants to switch back to consulting their own health, tell the AI Health Digital Human "Please help me switch to pay attention to myself (or similar natural language expression)".

[0142] If the user's health custody rights are transferred to other users, the user can apply to transfer this right to other users through relevant permission operations. If other users agree to accept it, the other users and the user will enter into a new health custody relationship. The custody relationship between users will be terminated and the user will no longer have the right to pay attention to the user's health (unless a normal application is made to pay attention to the user's health and the consent of the custodian is obtained).

[0143] This application mode can be used in the family, where the elderly may not be proficient in the operation of smart devices and cannot independently complete the settings related to health management. For example, young family members can act as custodians and use their own main operating terminal devices to manage health information for the elderly (custodian objects). Young family members can register accounts for the elderly, establish basic health files, upload medical and physical examination reports, conduct emotional and ability assessments, etc. At the same time, bind the collection devices (such as smart bracelets) and secondary operation terminal devices (such as smart speakers) used by the elderly. The custodian can also use the AI ​​health digital person to pay attention to the health status of the custodian and the working status of the collection equipment, and promptly discover and take measures when the elderly have physical abnormalities. In addition, the elderly can also consult and communicate with the AI ​​health digital person through secondary operation terminal devices (such as smart speakers).

[0144] This application mode is also applicable to remote operations, such as remote registration of user accounts, remote binding of user devices, remote health management operations, and remote attention to the health of others. It adapts to more application scenarios and needs of current health management users.

[0145] (VI) System workflow of AI health management

[0146] like Figure 18 [AI Health Management - System Workflow Diagram] shows the workflow steps of the AI ​​health management system and its interaction with users when users are actually applying AI health management.

[0147] First, the collection terminal obtains the user's health monitoring information to form an AI health information source and transmits it to the AI ​​health cloud service platform. The platform stores, parses and processes the AI ​​health information source, and the AI ​​health intelligent body preliminary calculation module performs preliminary calculations based on this to generate AI health assessment results (Ⅰ), which mainly reflect the status under basic health monitoring data. If the user does not complete the health supplementary information or does not communicate with the AI ​​health digital person and supplement the health information, the health assessment result will be based on this.

[0148] Next, the system may prompt the user to supplement health information based on the results. After the user performs relevant operations, the operating terminal transmits and updates the AI health information source again. The platform reprocesses, and the AI health intelligent agent actuarial module conducts precise calculations by integrating more factors to generate the AI health assessment result (II). As the user continuously supplements information and the device continuously collects data, this process loops. Each loop may involve additional processing such as information source verification and adjustment of the calculation basis. Through this loop-dynamic process, the health assessment result is continuously updated and optimized, approaching accuracy and comprehensiveness, which reflects the core mechanism of the entire AI health system.

[0149] It should be particularly noted that the AI health management system differentiates between the AI health assessment result (I) and the AI health assessment result (II), mainly based on the consideration of computing power costs in the actual project commercial operation. The two assessment results are generated by the AI health intelligent agent preliminary calculation module and the actuarial module respectively. Relatively speaking, the computing power cost adopted by the actuarial module is significantly higher than that of the preliminary calculation module. Specifically, when the system provides the AI health assessment result (I), since the user has not provided supplementary health information, the system only has the user's basic health data, such as the limited health monitoring data obtained by a single collection device and the brief user basic information. These data lack comprehensiveness and have a unified format and templatization, and the health information source is relatively simple. In this case, whether using the AI health intelligent agent preliminary calculation module or the actuarial module of this system, the generated AI health assessment results and their accuracies do not differ significantly, and the accuracies are both relatively low. From the perspective of the actual project commercial operation, it is a more sensible choice to use the AI health intelligent agent preliminary calculation module with a lower computing power cost to generate the AI health assessment result (I). However, if cost factors are not considered, or for the sake of simplifying the system, this system can also uniformly use the AI health intelligent actuarial module to generate the AI health assessment result, that is, no longer differentiate between the AI health assessment result (I) and the AI health assessment result (II). Under the premise of no creative labor, the embodiments obtained by ordinary technical personnel in this field in this situation all fall within the protection scope of the present invention.

[0150] To better understand the working process steps of the AI health management system and its interaction with users, we first make the following explanations for three important special terms: "AI health consultation", "AI health information source", and "AI health assessment result":

[0151] 1. AI health consultation

[0152] In the AI health management system, AI health consultation refers to the process in which the user conducts natural language interaction with the AI health digital human through the operating terminal to obtain professional health advice, AI health assessment results, and comprehensive health assessment reports (or special contents).

[0153] During the AI health consultation process, the AI health digital human may adopt an "inquiry" method to ask the user questions related to the user's health behaviors (generally information unknown to the AI health information source), such as "How do you feel about your mental state recently?", "Have you often had constipation recently?", "Are you pregnant and how long is the pregnancy?", etc., which are questions that may be related to the user's current health status or information that needs to be supplemented for the customer consultation content, so that the AI health digital human can more accurately analyze and evaluate the user's health.

[0154] At the same time, during the AI health consultation process, the AI health digital human may also remind the user of the abnormal situation report of the acquisition device, the operation problems of the materials that the user may fill in or upload in the "Health Supplementary Information Management System" (such as missing, abnormal, expired, etc.), and the medical appointment event reminder (such as postoperative review reminder, medication reminder, etc., which requires the user or the custodian to upload relevant medical documents in the Health Supplementary Information Management System).

[0155] In addition, the custodian in the cluster user mode can conduct health consultations for the custodial object with the AI health digital human and answer the inquiries of the AI health digital human on its behalf.

[0156] 2. AI Health Information Source

[0157] The AI health information source refers to all the information sets related to the user's health comprehensively obtained through various channels in the AI health management system, which is in contrast to the original data source for AI analysis by the AI health intelligent agent. The AI health information source is a comprehensive and systematic health original information database, providing a data basis for the system to conduct accurate health analysis, risk assessment, formulation of personalized health management plans, and decision-making of the AI health intelligent agent. The comprehensiveness and quality of the AI health information source depend on the different types of health data that different acquisition devices can collect, as well as the integrity or authenticity of the information filled in or uploaded by the user in the AI health supplementary information management system.

[0158] 3. AI Health Assessment Results

[0159] In the AI health management system, the AI health assessment result is also called the "health assessment result". The AI health assessment result is a conclusive report based on the system's comprehensive analysis of all the user health information sources it can obtain, and at the same time, it also covers the abnormal situation report of the user's use of the acquisition device, the problem report of the materials that the user may fill in or upload in the "Health Supplementary Information Management System" (such as missing, abnormal, expired, etc.), and the management report of the user's medical appointment events obtained by parsing, etc.

[0160] Part of the content of this assessment result will be presented at the relevant interface positions of the "Health Information Display Interface Interaction Module" (such asFigure 23 as shown in ①②③ in the figure), as an AI health analysis report or advice; and present relevant reminder information on the relevant reminder interface, such as abnormal collection devices, abnormal health supplement information, medical appointment events, etc. (as shown in ① in the figure). Figure 24 During the process of AI health consultation with users, the AI health digital human will summarize or extract answers to users' consultation questions based on the "AI health assessment results" (as shown in ⑧ in the figure), or further explain and give suggestions to users, or provide the above-mentioned relevant reminder information to users. Figure 25

[0161] The generation of AI health assessment results depends on AI health information sources, and the comprehensiveness and quality of AI health information sources depend on different types of health monitoring data that different collection devices can collect, as well as the integrity and authenticity of the information filled in or uploaded by users in the AI health supplement information management system.

[0162] AI health assessment results are divided into two natures: AI health assessment results (Ⅰ) and AI health assessment results (Ⅱ) due to different AI health information sources or whether there is additional health supplement information.

[0163] AI health assessment results (Ⅰ) are defined in the AI health management system as: health assessment results obtained when users have not performed any operations on health supplement information. Specifically: ⑴ No operations are performed in the health supplement information management system (such as establishing a user's health basic file, uploading the user's medical and physical examination reports, evaluating the user's emotions and abilities, etc.); ⑵ The user or the custodian has not had a dialogue with the AI health digital human or provided any information related to the user's own health to the AI health digital human. In this case, the health assessment results obtained by the user or the custodian are AI health assessment results (Ⅰ).

[0164] AI health assessment results (Ⅱ) are defined in the AI health management system as: health assessment results obtained when users have performed certain update operations on health supplement information. Specifically: ⑴ Initially operate or update health materials for the second time in the health supplement information management system (such as establishing a health basic file, uploading the user's medical and physical examination reports, evaluating the user's emotions and abilities, etc.); ⑵ The user or the custodian has had a dialogue with the AI health digital human and provided one or some information related to the user's own health to the AI health digital human. In this case, the subsequent health assessment results obtained by the user are AI health assessment results (Ⅱ).

[0165] 4. AI health management operation process

[0166] such as Figure 18 ​As shown in the [AI Health Management - System Workflow Schematic Diagram], during the process of the AI health management system obtaining the absolute AI health assessment result (I), there is a rigorous working mechanism and process sequence, following the three - stage principle of "data input, data operation, and result output". First, on the operation terminal, data is obtained through the acquisition module, and after being processed by the cleaning, review, and storage modules, it is transmitted to the cloud platform. After receiving it, the cloud platform obtains, stores, and processes the data, which is calculated by the preliminary calculation module, and then the result is obtained by the generation module. Finally, the result output module transmits it back to the operation terminal, and the supplementary information reminder module determines whether supplementary information is required. The relevant module then reminds the user on the operation terminal. Each step is closely connected to form a complete process. Specifically as follows:

[0167] (1) Related working steps of the operation terminal (inputting AI health information source to the cloud platform)

[0168] Step (1), AI health information source acquisition module (client): After the data synchronization between the customer collection device and the operation terminal is updated, this module is responsible for obtaining the data related to the user's health monitoring information, providing the raw data basis for subsequent processing. These data may come from the information collected by various sensors in the collection device.

[0169] Step (2), Health management data cleaning and management module: Clean the obtained raw health monitoring information, which includes removing noise and outliers in the data, handling possible missing values, and standardizing the data to meet the requirements of subsequent system processing and improve data quality.

[0170] Step (3), Health monitoring information review and management module: Review the health monitoring information from multiple dimensions, including checking the rationality of the information, such as whether the monitored physiological indicators are within a reasonable range; the consistency of the information, that is, whether the information from different sources matches each other; and the integrity of the information to ensure that key information is not missing, preparing for integrating the health information source.

[0171] Step (4), Data synchronization and storage module (client): Locally store the health monitoring information that has been cleaned and reviewed, and at the same time prepare for transmitting data to the AI health cloud service platform, ensuring the security and integrity of the data locally and being able to transmit it to the cloud platform in a timely and accurate manner.

[0172] (2) Related working steps of the AI health cloud service platform (AI health operation)

[0173] Step (5), AI health information source acquisition module (cloud server): Obtain the health information source data transmitted from the operation terminal on the cloud server. These data contain the health monitoring information that has been preliminarily processed by the client, providing the data basis for further processing on the cloud platform.

[0174] Step (6), Data Synchronization and Storage Module (Cloud Server): Manage the storage of the obtained health information source data. Adopt efficient data storage technologies and algorithms to ensure the security, integrity, and accessibility of the data. At the same time, classify and index the data for subsequent processing and querying.

[0175] Step (7), Medical and Physical Examination Report AI Analysis Module: In this step, analyze the uploaded medical and physical examination reports, including operations such as format recognition, content extraction, semantic understanding, and standardization processing, to provide data support for subsequent evaluations. However, if the customer obtains the AI health assessment result (I) with an absolute definition, this step is skipped because no relevant operations are involved (the user has not uploaded medical and physical examination reports, etc.).

[0176] Step (8), AI Health Information Source Processing Module: Further process the obtained health information sources. Use advanced algorithms and technologies to deeply clean, organize, and standardize the data, and extract key information to provide a more accurate and standardized data foundation for AI operations.

[0177] Step (9), AI Health Agent Initial Calculation Module: Based on the processed health information source data, perform preliminary calculations using AI large models and related machine learning algorithms. This calculation mainly conducts a preliminary assessment of the user's health status based on basic health monitoring data. Since no health supplement information and interaction with the AI health digital human are involved, the assessment is relatively basic and preliminary.

[0178] Step (10), AI Health Assessment (I) Generation Module: According to the preliminary calculation results, this module generates the AI health assessment result (I). This result mainly reflects the health status assessment of the user based on basic health monitoring data, including some basic health indicator analyses and risk warnings, etc.

[0179] ⑶ Related Working Steps of the Operating Terminal (Receiving the AI Health Assessment Result Output by the Cloud Platform)

[0180] Step (11), AI Health Assessment Result (I) Output Module: Responsible for receiving the AI health assessment result (I) generated by the AI health cloud service platform and transmitting it to the relevant display and interaction modules of the operating terminal to ensure that the assessment result can be accurately transmitted to the operating terminal.

[0181] Step (12), AI Health Supplement Information Reminder Module: According to the obtained AI health assessment result (I), this module determines whether the user needs to supplement health information. If so, it will trigger subsequent reminder operations to prompt the user to perform relevant operations in the health supplement information management system to improve the health information.

[0182] Step (13), The operating terminal reminds the user to supplement health information in the following management module

[0183] AI Health Assessment Result Display Module: Display relevant content of the AI health assessment result (Ⅰ) on the operation terminal (such as Figure 23 shown in ①②③), including but not limited to health indicators, risk assessment and other information, enabling users to intuitively understand the preliminary assessment results of their health status, and at the same time reminding users that they may need to supplement health information. AI Audio-Visual Dialogue Window Interaction Module, that is, on the main operation terminal, the AI health digital human conducts AI health consultation interaction with the user, reminding the user to supplement health information (such as Figure 24 shown in ①). AI Audio Dialogue Interaction Module, that is, generally on the secondary operation terminal, the AI health digital human conducts AI health consultation interaction with the user through audio dialogue, or reminds the user to supplement health information.

[0184] 5. AI Health Management System Joint and Progressive Mechanism and Process

[0185] Such as Figure 18 [AI Health Management - System Workflow Schematic Diagram] shows that in the AI health management system, the mechanism of the AI health assessment result (Ⅰ) is a preliminary assessment based on basic health monitoring data. And the mechanism of the AI health assessment result (Ⅱ) is based on this. When the user operates on the health supplementary information or communicates with the AI health digital human and additional health supplementary information is added, a further health assessment result is generated. The joint and progressive mechanism of the AI health assessment result (Ⅰ) and the AI health assessment result (Ⅱ) aims to make the system's health assessment result of the user infinitely tend to be accurate and comprehensive through an infinite loop process as the user's health supplementary information and the data collected by the device are updated. The specific joint and progressive mechanism and process are as follows:

[0186] ⑴ The first ⑴ - ⒀ steps of the workflow for operating on the AI health assessment result (Ⅰ)

[0187] Step ⒁, the user operates to supplement health information in the following management modules

[0188] User Health Basic File Management Module: The user operates on the personal health basic file in this module, including supplementing or correcting personal basic information (such as age, gender, occupation, etc.) and family medical history and other content, providing more comprehensive and accurate background information for subsequent assessments.

[0189] User Medical and Physical Examination Report Management Module: The user uploads medical and physical examination reports, which contain detailed physical examination data (such as various physiological indicators, disease diagnosis results, etc.) and doctor's diagnosis suggestions and other information, providing key basis for the system's precise assessment.

[0190] User Situation and Ability Evaluation Module: Users perform evaluation operations on their own situations and abilities, such as evaluating aspects such as mental state (e.g., anxiety, depression levels), living abilities (e.g., self-care ability, motor ability), etc., enabling the system to understand the user's health status from multiple dimensions.

[0191] AI Audio-Visual Dialogue Window Interaction Module (i.e., AI Health Digital Human Dialogue Window): Through this module, users have AI health consultation dialogues with the AI health digital human, providing additional information related to their own health. This information may be a further explanation of the previously uploaded materials or supplementary details of new health conditions.

[0192] ⑵ Related Working Steps of AI Health Management System (Repeat steps ⑴ - ⑻ and execute steps A1 and A2)

[0193] Repeat steps ⑴ - ⑻: This part of the process is similar to steps ⑴ - ⑻ when obtaining the AI health assessment result (Ⅰ). It includes operations such as the operation terminal obtaining, cleaning, reviewing, and storing health monitoring information, and the AI health cloud service platform obtaining, storing, and processing health information sources, providing an accurate data basis for subsequent actuarial calculations.

[0194] Step A1, AI Health Agent Actuarial Module: Based on the processed and supplemented health information sources, this module uses more complex AI algorithms and models for actuarial calculations. It comprehensively considers various factors such as the medical and physical examination reports uploaded by users, the information obtained from dialogues with the AI health digital human, and basic health monitoring data, and conducts a more in-depth and accurate assessment of the user's health status.

[0195] Step A2, AI Health Assessment (Ⅱ) Generation Module: According to the actuarial results, this module generates the AI health assessment result (Ⅱ). This result is more comprehensive and accurate than the AI health assessment result (Ⅰ), including more detailed health indicator analysis, risk assessment, and personalized suggestions for the user's health status, etc.

[0196] ⑶ Related Working Steps of the Operation Terminal (Receiving the AI Health Assessment Result Output by the Cloud Platform)

[0197] Step A3, AI Health Assessment Result (Ⅱ) Output Module: Responsible for receiving the AI health assessment result (Ⅱ) generated by the AI health cloud service platform and transmitting it to the relevant display and interaction modules of the operation terminal, ensuring that the assessment result can be accurately transmitted to the operation terminal.

[0198] Step A4, Users obtain the assessment result (Ⅱ) in the following management module or receive a reminder of further health supplement information. AI Health Assessment Result Display Module: Display relevant content of the AI health assessment result (Ⅱ) on the operation terminal (such as Figure 23as shown in ①②③ in the figure, including but not limited to information such as health indicators and risk assessments, enabling users to intuitively understand the preliminary assessment results of their health status and at the same time reminding users that they may need to supplement health information. The AI audio-visual dialogue window interaction module, that is, on the main operation terminal, the AI health digital human interacts with the user for health consultation or further reminds the user to supplement health information (such as Figure 24 as shown in ① in the figure). The AI audio dialogue interaction module, that is, generally on the secondary operation terminal, the AI health digital human conducts AI health consultation interaction with the user through audio dialogue or reminds the user to further supplement health information.

[0199] such as Figure 18 [Schematic Diagram of the System Workflow of AI Health Management] As shown, through the above detailed introduction and description of the user obtaining AI health assessment results (Ⅰ) and AI health assessment results (Ⅱ), as well as the relevant work processes and steps of the system, combined with Figure 18 the "Process Description" in the lower left corner, we know that:

[0200] The first health management work process: paragraphs (1 - 13) (or step 7 may not exist)

[0201] That is, when the user performs health management operations, they obtain AI health assessment results (Ⅰ), and the entire process of the relevant work of the AI health management system (which has been introduced in detail before and will not be repeated here). If the user obtains absolute-defined AI health assessment results (Ⅰ) at this step, this step is skipped because no relevant operations are involved (the user has not uploaded medical and physical examination reports, etc.).

[0202] The second health management work process: step (14) + repeat paragraphs (1 - 8) + paragraphs (A1 - A4)

[0203] That is, when the user performs health management operations, they obtain AI health assessment results (Ⅱ), and the entire process of the relevant work of the AI health management system (which has been introduced in detail before and will not be repeated here).

[0204] The third health management work process: repeat step (14) + repeat paragraphs (1 - 8) + paragraphs (B1 - B4); The fourth health management work process: repeat step (14) + repeat paragraphs (1 - 8) + paragraphs (C1 - C4); and so on, in an infinite loop.

[0205] That is, it represents the combined and progressive mechanism of AI health assessment results (Ⅰ) and AI health assessment results (Ⅱ). Through an infinite loop process, as the user's health supplementary information and the data collected by the device are updated, the system's health assessment results for the user will infinitely tend to be accurate and comprehensive. Although Figure 18The specific segments (B1 - B4) and (C1 - C4) are not marked. However, from the illustrative example of the segment (A1 - A4) and the operating mechanism of "and so on, in an infinite loop", an ordinary person can infer from the principle that it follows a pattern similar to the second - time health management workflow.

[0206] (VII) Acquisition and Collection Expansion of AI Health Information Sources

[0207] Different from some existing health management methods that only obtain limited health monitoring data and brief personal basic information (such as a small amount of information like gender, age, height, weight, etc.) of users through specific collection channels (such as a single collection device), and use simple data models or individual applications of artificial intelligence to obtain a rough health assessment result of the user; the present invention is applicable to multiple collection devices, channels, and methods to obtain more health supplementary information of the same user, and jointly constructs a comprehensive AI health information source for the user with the health monitoring data and brief personal basic information obtained through the above - mentioned specific collection channels. Using artificial intelligence health algorithms to comprehensively analyze and calculate this AI health information source, quickly obtain the AI health assessment result of the user, and this result information can be fed back to the user through ways such as page display on the operation terminal, intelligent reminder, and AI health digital human answering the user's health consultation. Once the AI health information source of the user changes, its AI health assessment result will also be adjusted accordingly, and through this loop mechanism, precise and comprehensive personalized health assessment and suggestions are provided for the user.

[0208] The health supplementary information includes, but is not limited to, from the content level: the health basic file information, medical and physical examination report information, emotion and ability evaluation results and other user health information completed by the user on the operation terminal device (such as a smart phone, etc.) of this system; the health supplementary information of the user obtained by the AI health digital human deployed on the operation terminal of this system during the process of health consultation or medical inquiry with the user; obtaining more health monitoring data of the above - mentioned user by alternately or simultaneously using more collection devices; information such as the user's daily meal records, work and living environment monitoring data, social activity records obtained through special collection devices or monitoring devices, algorithms or other means; and the user's medical record conditions and health - related information obtained from the relevant management systems of one or more third - party diagnosis and treatment or physical examination institutions through data interfaces and communication protocols.

[0209] The health basic file is the health information file filled in by the above-mentioned user (or health custodian) on the operation terminal according to the system questionnaire, covering information directly or indirectly related to the user's health, including but not limited to the user's basic information (such as gender, age, height, weight, etc.), work-related information (such as work nature, work and rest, whether there are night shifts and overtime, etc.), eating habits (such as food types, intake, food preferences, etc.), lifestyle information (such as exercise situation, bad habits, etc.), physical condition (such as whether often having colds, allergic substances, etc.), basic medical history (such as whether having basic diseases, whether having surgeries, etc.), female-specific information (such as menstrual time, whether pregnant, etc.).

[0210] The medical and physical examination reports are the report documents generated after the formal hospital conducts medical examinations and evaluations on the physical conditions of the above-mentioned users, and then uploaded to the system by the users (or health custodians) through the operation terminal, covering information directly or indirectly related to the users' health, including but not limited to blood test reports, urine test reports, various imaging examination reports (such as X-ray, CT reports, etc.), pathological examination reports, microbial culture reports, drug concentration detection reports, etc., as well as electrocardiogram reports, echocardiogram reports, endoscopy reports, surgery reports, diagnosis reports, treatment reports, follow-up reports and health assessment reports, medication guides, relevant pre-operative and post-operative notices, reexamination notice documents, etc.

[0211] The emotion and ability evaluation is the relevant evaluation results obtained by the system through the questionnaire feedback of the above-mentioned users on the operation terminal by borrowing various scientific evaluation models widely recognized in the medical and health fields, including but not limited to the relevant evaluation results or conclusions obtained through intelligence tests (such as Wechsler Adult Intelligence Scale, etc.), emotion control tests (such as Emotion Regulation Questionnaire, etc.), cognitive ability tests (such as Montreal Cognitive Assessment Scale, etc.), personality trait test results (such as Big Five Personality Inventory, etc.), memory tests (such as Wechsler Memory Scale, etc.), attention tests (such as Attention Network Test, etc.), language ability tests (such as Boston Naming Test, etc.).

[0212] The daily meal record is the daily meal record of the above-mentioned user obtained by the system through special collection devices, algorithms or other means, including but not limited to meal time, food types, intake, dining environment and other information.

[0213] The work and living environment monitoring data is the environmental monitoring data of the above-mentioned user obtained by the system through special collection devices, algorithms or other means, including but not limited to environmental air pressure, temperature, humidity, light intensity, ultraviolet intensity, noise intensity, air quality and other information, as well as information on environmental safety and comfort.

[0214] In addition, the present invention further expands the scope of the health supplement information, including but not limited to:

[0215] At the level of the collection approach, it expands from only through specific collection approaches to not limiting the collection approaches and methods, without specifying dedicated or specific collection devices, and collecting health supplement information directly or indirectly related to the user's health;

[0216] At the level of the categories of collection devices, it includes but not limited to health supplement information directly or indirectly related to the above-mentioned user's health that can be collected by collection devices such as ordinary wearable intelligent devices not certified as medical devices, similar wearable health data collection devices certified as medical devices, personal or household medical devices and health detection devices certified as medical devices, and work and living environment monitoring data monitoring devices with or without professional certification;

[0217] At the level of the usage methods of collection devices, it includes but not limited to collecting health supplement information directly or indirectly related to the user's health when using a single specified type of collection device, alternating the use of multiple quantities and types of collection devices, or using multiple quantities and types of collection devices simultaneously;

[0218] At the level of the data information collection method, it expands from collecting health data through collection devices to directly or indirectly obtaining medical record conditions and health-related information of the above-mentioned user from the relevant management systems of one or more third-party diagnosis and treatment or physical examination institutions through data interfaces and communication protocols;

[0219] In summary, the present invention has achieved major breakthroughs and innovations in the field of health management. By comprehensively expanding the scope of health information collection, diverse collection approaches, and device usage methods, combined with advanced artificial intelligence algorithms, a comprehensive and accurate user health portrait is constructed, continuously optimizing the health assessment results, providing highly personalized and dynamic health management services for users, leading health management into a new era of AI intelligence and precision, and strongly promoting the development and progress of the health industry.

[0220] (VIII) Multi-form Output of AI Health Assessment Results

[0221] Such as Figure 21 [Schematic Diagram of AI Health Management - Output of AI Health Assessment Results] shows that the AI health agent is in a core position in the health management system and serves as the operation and processing center for health analysis. The figure systematically and comprehensively displays its operation output results, that is, the types and output methods of AI health assessment results, specifically including but not limited to the following:

[0222] Relevant health assessment results that can be obtained during the health consultation and dialogue between the user and the AI digital human (such as Figure 21 shown in ⑥⑦⑧ inFigure 25 as shown in ③ below, the system will automatically convert to the user's question form (such as Figure 25 as shown in ⑧ below). In addition, the system should cooperate with the user's needs to connect to the third-party health or medical institution system to obtain health data or evaluation results (such as Figure 21 as shown in ⑨ below).

[0223] such as Figure 21 as shown in ⑥ below and Figure 25 as shown in ③ and ⑧ below, which show the specific forms and classifications that the health assessment results of AI health consultation include but are not limited to in the form of a structural and interaction schematic diagram. The following are common forms of health assessment result output.

[0224] Comprehensive Health Assessment Report: One of the forms of AI health assessment results that is comprehensive, systematic, and individualized, issued by the AI health intelligent agent to the user by comprehensively analyzing the user's health information sources for the "Comprehensive Health Assessment Report" required by the user (such as Figure 21 as shown in ⑥ below). The comprehensive health assessment report includes but is not limited to health index, health risk, physiological indicators, sleep quality, daily routine insights, stress measurement, aging trend, health advice, etc.

[0225] Health Index: A comprehensive quantitative indicator used to comprehensively evaluate an individual's health status in the AI health management system. It is the result obtained by analyzing and weighted calculating health information sources from multiple dimensions. These health information sources include but are not limited to physiological indicators, lifestyle factors, medical history, etc. The health index aims to convey the general situation of the user's health level to the user in a simple and intuitive way, providing a reference basis for the user to quickly understand the overall situation of their own health.

[0226] Health Risk: Health risk refers to the possibility that an individual user will develop a certain disease or health problem in a future period of time. In the AI health management system, by analyzing the user's health information sources, risk prediction models and algorithms are used to evaluate the potential occurrence risks of different diseases. For example, for cardiovascular disease risk assessment, multiple factors such as age, blood pressure, blood lipid, smoking history, etc. may be considered, and corresponding risk levels such as low risk, medium risk, high risk, etc. will be given to help users understand their potential health threats in a timely manner and take corresponding preventive measures.

[0227] Physiological indicators: Physiological indicators refer to the objective data reflecting the physiological state of the human body measured through various physiological detection means. In the AI health management system, common physiological indicators include basic vital signs such as heart rate, blood pressure, body temperature, and blood oxygen saturation, as well as more complex professional indicators such as electrocardiogram, electroencephalogram, and blood biochemical indicators (such as blood sugar, blood lipids, and liver function indicators). These physiological indicators can reflect the physiological function state of the human body in real time or regularly, and are of great significance for disease diagnosis, monitoring, and health assessment.

[0228] Sleep quality: It is a comprehensive evaluation of the individual's sleep condition. In the AI health management system, the evaluation of sleep quality is usually based on data from multiple aspects, including sleep duration, sleep depth, sleep stage distribution (such as light sleep, deep sleep, rapid eye movement period, etc.), and the number of awakenings during sleep. At the same time, it may also combine the user's self-statement information in the AI health consultation dialogue, such as whether they feel sleepy and their mental state, to comprehensively judge the quality of sleep.

[0229] Routine insight: It refers to the in-depth understanding and analysis of the individual's daily routine. By collecting and analyzing the user's routine-related information, such as wake-up time, bedtime, working time, rest time, exercise time, etc., the system can insight whether the user's routine pattern is regular and reasonable. In the AI health management system, routine insight helps to discover possible problems in the user's routine, such as staying up late for a long time and irregular routine, which may have a negative impact on health, so as to provide targeted routine adjustment suggestions for the user to maintain a good health state.

[0230] Stress measurement: In the AI health management system, it is a quantitative assessment of the stress level borne by an individual. The AI health agent uses specific algorithms and models for the AI health information sources and health stress data obtained from the user, and converts the analysis result data into a quantifiable stress value to help the user understand their stress status and take corresponding mitigation measures.

[0231] Aging trend: It is the targeted health guidance provided for the user in the AI health management system based on the user's health assessment results, health information sources, and individual characteristics. It covers multiple aspects such as lifestyle adjustment, disease prevention, and treatment suggestions. For example, for users with hypertension, it may be recommended to control salt intake, maintain appropriate exercise, and measure blood pressure regularly; for users with poor sleep quality, it may be recommended to improve the sleep environment and establish a regular bedtime. Health advice aims to help users improve their health status and prevent the occurrence and development of diseases.

[0232] such as Figure 21As shown in "Free Q&A with AI Health Digital Human"⑦, users can consult the AI Health Digital Human about personal health-related questions in natural language (either in text or voice form) (as mentioned above, not limited to health indexes, health risks, physiological indicators, sleep quality, etc.). Users can also conduct secondary consultations on the answers provided by the AI Health Digital Human, asking for further explanations or explanations in an easy-to-understand manner (if the user's health supplement information is sufficient, the AI Health Digital Human will also automatically communicate with the user in an appropriate expression and language). Users can also ask the AI Health Digital Human about the statistical data and information of a certain period of the user's health monitoring data, or the comparison, change, trend, etc. of the data between certain periods. During the health consultation process, the system supports multi-round conversations and mutual Q&A. Just like having a normal conversation with an ordinary doctor, users can correct and supplement their questions, and the AI Health Digital Human will automatically judge and organize them and give relevant answers to the users.

[0233] As Figure 21 As shown in "Free Q&A with AI Health Digital Human"⑦, users can also consult the AI Health Digital Human about health knowledge questions. Based on the health professional knowledge learned by the AI Health Digital Human from the AI large model, the health professional knowledge trained by the AI Health Intelligent Agent, and the relevant health information retrieved, it answers the users' questions in an easy-to-understand manner and provides professional health popular science answering services for the users.

[0234] In short, relying on its advanced intelligent technology and comprehensive evaluation system, the AI Health Management System provides users with accurate, efficient, and personalized health protection. It not only makes health data visual and problem diagnosis intelligent, but also makes health advice customized, greatly improving users' control and management level of their own health. In the future, with the continuous iteration and improvement of technology, it is expected to become an indispensable health guard and personal family doctor for everyone's healthy life.

[0235] (IX) Artificial Intelligence Functions and Features of the AI Health Management System

[0236] 1. Intelligent Consultation Function of the AI Health Digital Human

[0237] The AI Health Digital Human deployed in the AI Health Management System has an intelligent consultation function and can ask users about behavior questions or subjective self-feelings related to the users' health.

[0238] The questions asked by the AI health digital human to users are not a questionnaire with a fixed format and content. When users ask health consultation questions, if it is found that there is information that should be supplemented but is not reflected in the user's AI health information source, the AI health digital human will ask questions, such as "How do you feel about your mental state recently?" "Have you often had constipation recently?" "Are you pregnant and how long is your pregnancy?" etc.

[0239] The intelligent consultation of the AI health digital human has a scientific strategy mechanism. Based on the user's comprehensive AI health information source, a fusion analysis algorithm based on the artificial intelligence deep learning framework is used to extract features through a neural network model and conduct correlation analysis to determine the consultation strategy. Specifically, centered around the user's health consultation questions, it is carried out in the order from the important factors to the secondary factors, and from the direct factors to the indirect factors of the user's relevant health problems. At the same time, the user's health portrait is updated according to the user's answers, and the consultation process and words are adjusted in real time to achieve personalized consultation, ensuring the smooth acquisition of key health supplement information and providing users with more accurate health assessments and suggestions.

[0240] Once the user answers the consultation questions, the AI health digital human will immediately clean, filter, organize and standardize the answer content, extract key information and supplement it to the user's AI health information source in a timely manner. With the continuous progress of the question-and-answer between the two parties, an infinite loop update of the AI health information source is realized.

[0241] The intelligent consultation of the AI health digital human has a self-learning and optimization mechanism. Based on multi-source data such as consultation records, health assessment feedback, and changes in health conditions, deep learning algorithms such as recurrent neural networks or long short-term memory networks are used to learn the user's response patterns, and reinforcement learning is used to optimize the consultation strategy. New risk patterns and group characteristics are discovered through unsupervised learning, and the knowledge base and strategy are updated in a timely manner.

[0242] 2. Intelligent reminder function for health supplement information of AI health digital human (or system)

[0243] The AI health management system has an intelligent reminder function for health supplement information. This function helps to ensure that the user's AI health information source always remains relatively complete and accurate, provides more comprehensive basic data for the system, so that the system can provide users with more accurate health assessments and more targeted health suggestions.

[0244] The system summarizes the interactive records of the health consultation conversations with users, judges the relevant health problems that users relatively focus on, or analyzes the possible relevant health problems of users. If it is found that these health problems are closely related to the content missing in the user's health information source, the system will then activate the intelligent reminder mechanism and program.

[0245] The reminder content of this reminder function mainly focuses on the missing parts of the health information in the health supplement information management system of the operation terminal, including but not limited to the filling of relevant important information that the user has not completed in the health basic file management module of the system, the relevant important evaluations that the user has not completed in the emotion and ability evaluation module of the system, and the relevant important medical or physical examination reports that the user has not uploaded in the medical and physical examination report management module of the system, etc.

[0246] The implementation methods of this intelligent reminder function include but are not limited to informing the user through the AI health digital human in its dialogue window, popping up a reminder window or reminder label on the relevant display interface of the operation terminal, sending text messages or push notifications to the contact information registered by the user, etc. The reminder content clearly points to the category of health information that the user needs to supplement and the supplement entry. For example, it reminds the user to fill in relevant important information items in the health basic file management module of the system. At the same time, the reminder content may mention that the health information items to be supplemented are related to a certain health problem that the user is concerned about or a health problem that may occur to the user's body.

[0247] This intelligent reminder function is dynamic and timely. As the system continuously analyzes the user's health information source and the user's health status changes, once a new health information supplement requirement appears, the system can start the reminder in a timely manner.

[0248] The intelligent reminder function can be optimized by combining the user's usage habits and behavior patterns. If the system finds that the user is usually more likely to respond to reminders and supplement health information at a specific time period or in a specific scenario, the system will give priority to sending reminders at the corresponding time or in the corresponding scenario to improve the efficiency and enthusiasm of the user to supplement health information.

[0249] 3. Intelligent reminder function for the health matters of AI health digital human (or system) users

[0250] The AI health management system has an intelligent reminder function for health matters. When the system learns from the user's health information source that the user has a medical appointment event, a review event, or a medication event, the system will start the intelligent reminder mechanism for health matters and timely remind the user to pay attention to the relevant event content and suggest taking corresponding measures. Or, when the system comprehensively analyzes the user's health information source and finds that the user may have corresponding health risks, the system will also start the reminder mechanism. For example, when it is found that there are potential serious risks brought about by abnormal changes in certain physiological indicators, it is recommended that the user go to a relevant professional institution for a physical examination or to a medical institution for an examination, etc.; when it is detected that the user should pay attention to relevant work and rest, it reminds the user to adjust the work and rest, etc.

[0251] One way for the system to remind users of health matters is through the AI Health Digital Human. The AI Health Digital Human will remind users of health matters in its dialogue window. This kind of notification is proactive and not only made in response to users' health consultations. At the same time, the system can also remind users of health matters by popping up reminder windows and displaying reminder labels on relevant display interfaces of the operation terminal.

[0252] The intelligent reminder function of the system is dynamic and timely. As the system continuously monitors and analyzes users' health information and the users' health conditions change continuously, once there are new health matters that need to remind users, the system can quickly respond and start the reminder in a timely manner to ensure that users can understand their health conditions and the actions they need to take in the first place.

[0253] 4. Automatic Communication Mode Adjustment Function of the AI Health Digital Human

[0254] The AI Health Digital Human deployed in the AI Health Management System can automatically adjust the communication mode, such as a professional mode or a popular mode. Whether it is a professional mode or a popular mode, it aims to provide a better and more suitable health management interaction experience for different users.

[0255] For users with a professional background, the AI Health Digital Human will adopt a relatively professional communication mode, using professional terms and in-depth medical knowledge to communicate in order to discuss health problems more efficiently and provide professional advice. The background information of users can be obtained from the users' health basic files. If it shows that the user has a medical-related educational background or is engaged in the medical industry, the system will mark this user as having a professional background; at the same time, if the user frequently uses professional terms or shows a relatively high degree of familiarity with professional medical knowledge, the AI Health Digital Human will also judge that the user has a certain professional background.

[0256] For ordinary users without a professional background, the AI Health Digital Human switches to a popular mode for communication. It uses easy-to-understand language and avoids using complex professional terms to ensure that users can more easily understand health information and advice.

[0257] 5. Reminder of Equipment Abnormal Conditions by the AI Health Digital Human (or System)

[0258] The AI Health Digital Human deployed in the AI Health Management System can remind users of abnormal problems in the use of collection devices or operation terminal devices and put forward guiding suggestions. Through the timely reminder and effective guidance of the AI Health Digital Human on abnormal problems in the use of users' collection devices and secondary operation terminal devices, users can timely discover and solve equipment problems, ensure the stable operation of the health management system, guarantee the accurate collection and transmission of health data, and thus improve the health management effect and experience of users.

[0259] When the user's health monitoring data or information is missing or abnormal for a long period, or when data transmission interruptions, delays, or losses occur between the user's collection device and the operation terminal, the AI Health Digital Human will remind the user of the relevant phenomena and suggest that the user check whether the connection between the collection device and the terminal is stable, or ask whether the user is using the collection device properly, or check whether the battery of the relevant device is sufficient, or provide detailed troubleshooting steps based on possible reasons, etc.

[0260] When the health monitoring data collected by the sensors of the collection device (such as optical heart rate sensors, etc.) shows abnormal fluctuations or significantly deviates from the user's normal range, the AI Health Digital Human will issue a timely reminder and provide targeted troubleshooting suggestions based on the characteristics and common problems of different types of sensors. If it is confirmed with the user that the data abnormality is not a device problem, it will be converted to a user health problem, reminding the user to pay attention, or suggesting that the user consult a professional doctor or seek medical treatment in a timely manner.

[0261] 6. The AI Health Agent has an optimization mechanism and adaptive learning ability

[0262] The AI Health Management System and the AI Health Agents deployed therein have an optimization mechanism and adaptive learning ability. The AI Health Agent is trained based on the AI large model and has the ability to acquire and learn health knowledge. It continuously scans and collects the latest and most comprehensive medical and health knowledge across the country and even the world by establishing a connection with a professional medical database, including information such as cutting-edge health research results, the latest disease treatment methods, and advanced health management concepts. Through this mechanism, the AI Health Agent can continuously update and improve its own knowledge system to provide users with the most cutting-edge and accurate health advice and services.

[0263] Based on the continuously accumulated user health data and user feedback information, developers can use the AI Health Agent development module of the system to debug and optimize the AI Health Agent.

[0264] The learning content of the AI Health Agent covers multiple aspects. From the perspective of health data, the system will learn the correlations between different health indicators; from the perspective of user behavior patterns, the system will learn the acceptance and implementation of health management suggestions by users; from the perspective of user feedback information, the system will adjust its own evaluation methods and management strategies based on the user's satisfaction with the health assessment results and improvement suggestions. At the same time, the AI Health Agent itself has the ability of self-adjustment and can automatically adjust its own algorithms and model parameters to better adapt to the health conditions and needs changes of different users, thus significantly improving the accuracy of health assessment and management. (X) System Customer Service Work of the AI Health Digital Human

[0265] The AI health digital human deployed by the AI health management system can assume the role of the customer service staff of this system. When users have questions about the use of this system and related devices, the AI health digital human can promptly provide users with accurate usage instructions and professional guidance suggestions. Whether it is the functional operation process of the operation terminal or the correct wearing method and daily maintenance points of the acquisition device, the AI health digital human can answer in a clear and easy-to-understand manner. In this way, the AI health digital human helps users better master the usage methods of the system and devices, and enhances the user experience and convenience in the process of health management.

[0266] 1. AI customer service in the form of an AI health digital human

[0267] Users can directly ask questions in the dialogue window of the AI health digital human. Similar to consulting health problems, except that at this time, the AI health digital human does not answer the user's health problems, but the operation questions encountered by the user in using this system or the usage problems of related devices.

[0268] For example, a user newly purchased a body fat scale, an acquisition device, and wanted to know the precautions when using it. The user asked the AI health digital human: "I just bought a body fat scale. Is there anything special I need to pay attention to when using it?" The AI health digital human replied: "When using the body fat scale, please make sure to place it on a hard and flat ground, and avoid using it on a carpet or uneven ground to avoid affecting the measurement accuracy. Before measurement, please take off your shoes and socks, stand steadily on the scale surface with both feet, and try to keep your body balanced without shaking. In addition, to obtain more accurate measurement results, it is recommended to measure at the same time every day on an empty stomach." After understanding these precautions, the user used the body fat scale correctly and obtained more reliable body fat data.

[0269] 2. AI customer service in the form of adding friends through a chat tool

[0270] On the customer service contact interface of the operation terminal, the AI customer service page will display the QR code for adding friends of the AI customer service instant chat tool (taking the WeChat QR code as an example). The WeChat account of this AI customer service added by the user is actually the WeChat account of the AI health digital human. However, it should be noted that the act of privately simulating a WeChat account number poses a risk of violating the WeChat platform regulations and laws and regulations. In actual applications, it is recommended to actively communicate with the WeChat official to explore legal and compliant cooperation channels and technical solutions to ensure the sustainable development of the business and the protection of user rights and interests.

[0271] If you want to enable the AI digital human to have a WeChat account number, automatically pass the friend application and provide customer service, the following technical steps need to be taken (for reference only, actual operations need to ensure legal compliance):

[0272] WeChat ID Simulation Registration and Login: Use automated scripts and simulation software to build an account system similar to WeChat IDs. During the process, it is necessary to ensure compliance with the relevant platform usage rules and laws and regulations, and not violate the privacy policy and service terms. This link involves simulating the real user registration process, such as generating virtual mobile phone numbers (if permitted by the platform) or using legally obtained test numbers, filling in the necessary registration information, so as to complete the account creation and login operations.

[0273] Automatic Processing of Friend Requests: Write a program to monitor WeChat friend request notifications. When a user sends a friend request, automatically accept the request by leveraging the WeChat API (if there are legal and available interfaces) or simulating click operations. This requires in-depth understanding of the WeChat client working mechanism and communication protocol, accurately identifying and responding to friend request events, while also taking into account security and stability to prevent misoperations or being detected as abnormal by the WeChat platform.

[0274] Integration of Customer Service: Connect the AI customer service function module with the WeChat account, enabling the AI digital human to receive user messages in the WeChat chat window and intelligently reply based on the preset knowledge base and conversation logic. This requires developing a message sending and receiving processing system that can convert WeChat messages into a format understandable by the AI digital human and convert its replies into WeChat messages to be sent to users. At the same time, based on the positioning and training of the AI healthy digital human customer service role, continuously optimize the AI customer service conversation ability, covering aspects such as natural language understanding, semantic analysis, question classification, and answer generation, so as to provide a high-quality customer service experience.

[0275] Security and Compliance Assurance: Throughout the entire process, security and compliance issues are of utmost importance. It is necessary to ensure the confidentiality and security of user data and prevent the leakage of any user privacy information. At the same time, strictly follow the WeChat platform usage specifications and relevant laws and regulations to prevent account bans or legal risks caused by violations. Regularly conduct system security audits and vulnerability detections, and promptly repair potential security hazards to ensure the stable and reliable operation of the service.

[0276] 3. AI Customer Service Management Mechanism

[0277] ⑴ Basic Learning and Summary of Common Problems

[0278] The AI customer service will first conduct in-depth learning on detailed product or service manuals, which cover core information such as the system's functional architecture, operation process, technical parameters, and various business rules. Through natural language processing technology and text analysis algorithms, the AI extracts, classifies, and structurally stores the key knowledge points in the manual, building a preliminary knowledge system.

[0279] Meanwhile, comprehensively sort out and analyze historical customer consultation data, and use data mining techniques to identify frequently occurring problem types and patterns. For example, in a health management system, common problems may include device connection failures, data interpretation confusion, functional operation steps, etc. For these problems, the AI customer service will generate standard answer templates and associate them with corresponding question keywords to enable quick and accurate responses in subsequent conversations.

[0280] ⑵ Problem reporting and manual guidance

[0281] When the AI customer service encounters a problem that it cannot answer during a real-time conversation with a user, first it will politely apologize to the user, admit that the problem mentioned by the user temporarily exceeds its ability to solve, inform the user that it will feedback to the development team and seek a solution, and hope that the user can come back to consult relevant issues after some time.

[0282] The AI customer service will use the built-in problem identification and classification model to extract and describe the detailed features of the problem. These problem descriptions will be organized into structured data reports and submitted to the system's management background.

[0283] After receiving the report, the administrator will conduct an in-depth analysis of the problem based on their professional knowledge and experience. For some complex technical problems or problems involving ambiguous areas of business rules, the administrator will directly intervene in the conversation and provide accurate answers to the user in the form of manual guidance, ensuring that the user's problems are solved in a timely manner and providing learning examples for the AI customer service at the same time.

[0284] ⑶ Autonomous decision-making support in the mature stage

[0285] As the AI customer service continuously accumulates conversation experience and knowledge and gradually enters the mature stage, it can conduct a more in-depth analysis and understanding of newly emerging problems. When encountering problems that have not been solved before, the AI will use its learned knowledge reasoning and language generation capabilities to generate multiple possible reference answers.

[0286] These answers will be generated based on the problem-solving ideas of past similar problems, knowledge in related fields, and semantic understanding models. For example, for a compatibility problem of a new health monitoring device, the AI may generate answer suggestions from different angles according to the device's technical specifications, common compatibility solutions, and the specific situation provided by the user, such as checking software version updates, trying specific connection settings, etc., for the administrator to select the optimal solution according to the actual situation, further improving the ability and efficiency of the AI customer service to handle complex problems.

[0287] ⑷ Feedback on difficult problems and R & D collaboration

[0288] For questions that the AI customer service fails to answer after multiple attempts, the system will record the questions in detail and feedback them to the R & D team. The R & D team will analyze and research the questions from multiple perspectives such as technical implementation and product design, which may involve operations such as checking system code, query optimization of the database, and expansion and improvement of the knowledge graph.

[0289] After finding a solution, the R & D team will feedback the answer to the AI customer service system, and at the same time update the knowledge base and relevant model parameters, so that the AI customer service can learn new knowledge and coping strategies, so as to independently provide accurate responses to users when encountering similar problems in the future, continuously improve the intelligence level and service quality of the entire customer service system, realize the closed-loop optimization process from problem discovery to solution, and provide users with a more high-quality and efficient customer service experience.

[0290] 4. Features and Effects of AI Health Digital Human Customer Service

[0291] In traditional health management services, when users encounter problems and consult the customer service, they often need to queue up on the artificial customer service hotline, wasting a lot of time. The AI health digital human customer service has the advantages of instant response and all-weather service guarantee, completely avoiding this situation. Whether it is during the busy hours of weekdays or during non-working hours such as holidays or late at night, as long as users have questions, they can ask the AI health digital human at any time.

[0292] Traditional artificial customer service often needs to keep asking and eliminating to find the problem points. As a customer service staff, the AI health digital human itself is part of the system and can quickly discover abnormal problems through system monitoring, thus improving the work efficiency of the customer service.

[0293] The AI health digital human performs customer service work, can process multiple users' questions in parallel, improve the overall service efficiency, and reduce the customer service cost. In actual application scenarios, especially when the health management service faces a large number of users, traditional artificial customer service often faces problems such as queuing and low service efficiency. Each user's question needs to be processed by the artificial customer service one by one, and the time to process a question is relatively long, resulting in other users having to wait a long time to get a response. The AI health digital human can process multiple users' consultation requests at the same time and will not reduce the service quality due to the increase in the number of users.

[0294] As the customer service staff of the AI health management system, the AI health digital human plays an important role in helping users solve problems related to system and equipment usage, effectively improving the user experience, promoting users' active participation in health management, being an important part of the system, and providing strong support for the wide application of the system and the improvement of the user health management effect.

[0295] (XI) Group-style Cluster User Management and Application

[0296] A family (clan) or a group (organization) uses an AI health management system and devices. Such a group is called a cluster, and the users in the cluster are all members of this cluster. This user module is called the cluster user mode, which is further divided into the group cluster mode and the family cluster mode. The two cluster modes coexist compatibly. A user can either use the group cluster mode or the family cluster user mode simultaneously.

[0297] 1. Management mechanism of the group cluster

[0298] A cluster is the original unit of the group cluster structure newly created by individual users. The health management object of the cluster administrator is its natural cluster members, and at the same time, it can also admit more individual users to join and become its cluster members. Cluster members are directly subordinate to the administrator and are managed by it. The cluster administrator may also merge other clusters and their sub-clusters. The direct members of other clusters will be directly subordinate to this administrator, and the sub-clusters of other clusters will also be transferred and become the sub-clusters of this cluster (their establishment remains unchanged). Cluster members have the right to create a first-level sub-cluster downward and manage the members of the sub-cluster. Sub-cluster members are not directly subordinate members of the cluster administrator. The cluster administrator can only conduct health management on its directly subordinate cluster members, while the health management of sub-cluster members can only be implemented by the sub-cluster administrator.

[0299] A cluster member can create a first-level sub-cluster downward and manage the members of the sub-cluster. There is a superior-subordinate relationship between the sub-cluster and the cluster. The cluster is divided into first-level sub-clusters, second-level sub-clusters downward, and so on. Sub-cluster members are only directly subordinate members of that sub-cluster, and only the sub-cluster administrator can exercise the right of health management.

[0300] A combined cluster is an associated framework. A combined cluster has no directly subordinate cluster members; a cluster and a sub-cluster have their own directly subordinate cluster members. A cluster administrator can apply to "combine" with another cluster to become a first-level combined cluster. The cluster administrator of the party that agrees to the combination becomes the first-level combined cluster administrator. He can then apply to combine with other first-level combined clusters to become a second-level combined cluster, and so on. The highest-level combined cluster is relatively called the "top-level combined cluster".

[0301] After an individual user newly creates a group cluster, he naturally becomes the cluster administrator of this cluster. The cluster administrator has the right to conduct health management on other secondary operation terminal users, and this user is one of the natural cluster members of this cluster. The cluster administrator can enjoy the right to pay health attention to the directly subordinate members of this cluster and the members of the lower-level sub-clusters (without the consent of the cluster members).

[0302] A cluster member can create a first-level sub-cluster downward and manage the sub-cluster members. This cluster member is the administrator of the created first-level sub-cluster. There is a superior-subordinate relationship between the sub-cluster and the cluster. The cluster is divided into first-level sub-clusters, second-level sub-clusters downward, and so on. The sub-cluster administrator is a general term for administrators at all levels of sub-clusters. Sub-cluster members are only the direct members of that sub-cluster, and only the sub-cluster administrator can exercise the right of health custody.

[0303] A cluster administrator can apply to "unite" with another cluster to become a first-level united cluster. The cluster administrator who agrees to the union becomes the administrator of the first-level united cluster. He can then apply to unite with other first-level united clusters to become a second-level united cluster, and so on. The highest-level united cluster is relatively called the "top-level united cluster". The united cluster administrator is a general term for administrators at all levels of united clusters.

[0304] Users in a cluster or sub-cluster are all members of this cluster or sub-cluster, that is, they are called cluster members. The cluster administrator also belongs to one of the cluster members. Cluster members can view all cluster members of the entire cluster or the top-level united cluster and submit applications for health concern to them. Cluster members are divided into direct members (directly affiliated members of the cluster) and non-direct members (members of its lower-level sub-clusters). The administrator can only provide health custody for direct members. Cluster members are naturally under the health concern of the sub-cluster administrators (cluster administrators) at higher levels.

[0305] As Figure 34 shown, the cluster is a basic unit system. There are directly affiliated cluster members under the cluster, including roles such as cluster administrators, first-level sub-group administrators, and cluster members. The first-level sub-cluster is a branch of the cluster. The first-level cluster also has its own directly affiliated cluster members, including roles such as first-level sub-cluster administrators, second-level sub-cluster administrators, and first-level sub-cluster members. Thus, it can be seen that the first-level sub-group cluster administrator is both a directly affiliated member of the cluster and a directly affiliated member of the second-level sub-cluster he created. The same mechanism applies to lower-level branches.

[0306] As Figure 34 shown, the united cluster forms a tree-like structure. We call this system the "united cluster tree-like system". A cluster unites with other clusters to become a first-level united cluster. The cluster administrator who agrees becomes the administrator of the first-level united cluster, and so on for the second-level united cluster until the relatively top-level united cluster is reached. As Figure 34 shown by the connection ⑵, before the second-level associated cluster (A) unites with the second-level associated cluster (B), the second-level associated cluster (A) is the top-level united cluster of this system; after the second-level associated cluster (A) unites with the second-level associated cluster (B), the upper-level united cluster formed becomes the top-level united cluster of this system.

[0307] As Figure 34As shown, the combined cluster is just a framework and has no direct cluster members; the cluster and sub-clusters have their own direct cluster members. The cluster, as a basic unit system and the grass-roots unit of the combined cluster, is as shown in Figure 32 connection ⑴.

[0308] 2. Principles Followed by the Group-style Cluster

[0309] Combination Principle: All combined clusters, clusters, and sub-clusters within the top-level combined cluster cannot be combined again; all combined clusters and clusters within the top-level combined cluster can be combined with other top-level combined clusters (or clusters). After combination, the other party becomes a part within this top-level combined cluster (its establishment remains unchanged).

[0310] Merger Principle: All clusters (sub-clusters) of the same level within a top-level combined cluster can be merged. The administrators and cluster members of the merged clusters (sub-clusters) become the members of the newly merged cluster; all clusters (sub-clusters) of different levels within a top-level combined cluster can be merged. The administrators and cluster members of the lower-level sub-clusters become the members of the higher-level cluster (or sub-cluster); all clusters (sub-clusters) of the same level within a tree-type system can merge with external independent clusters (i.e., those in a non-combined state). After merger, the administrators and cluster members of the external cluster become the members of the newly merged cluster (sub-cluster), and the sub-clusters of the external independent cluster are also transferred together (its establishment remains unchanged).

[0311] Sharing Principle: All lower-level cluster members within the top-level combined cluster can view and apply for health concerns for any cluster member within the system of the top-level combined cluster (different from individual users. Individual users need to separately request the other party's identity ID number or scan the ID QR code to conduct inquiries or concerns).

[0312] It should be reminded that the administrator is only an identity for management responsibilities. In essence, the administrator is also an individual user. The administrator is only its management permission identity. An individual user can "hold multiple positions", that is, can hold any position without conflict with each other.

[0313] As an individual user, the cluster administrator can conduct health concern activities with other users in his / her own name, can also join other clusters or sub-clusters, and can also create more clusters or sub-clusters. As the cluster administrator, he / she exercises relevant cluster management permissions, including but not limited to agreeing to others joining the cluster, inviting others to join the cluster, health trusteeship, cluster combination, cluster merger, transferring the cluster administrator permission, dissolving the cluster, etc.

[0314] As shown in Figure 35 continuously shown as ①②, a cluster administrator ⑴ conducts interactive operations of mutual health concern with an individual user outside the cluster. As shown in Figure 35As shown in Continuous ③, it is a schematic diagram of an individual user applying to the cluster administrator ⑴ to join the cluster and getting approval. As Figure 35 As shown in Continuous ④, it is a schematic diagram of the cluster administrator ⑴ sending an invitation to join the group to the individual user. As Figure 35 As shown in Continuous ⑤, it is a schematic diagram of another cluster administrator ⑵ applying to the cluster administrator ⑴ to join the cluster under its jurisdiction and getting approval. As Figure 35 As shown in Continuous ⑥, it is a schematic diagram of the cluster administrator ⑴ sending an invitation to join the group to another cluster administrator ⑵. As Figure 35 As shown in Continuous ⑦⑧, it is a schematic diagram of the interactive operation of the cluster administrator ⑴ and the cluster administrator ⑵ for cluster union. 3. Related permission operations and processes for health trusteeship

[0315] Device binding and permission activation: As Figure 36 As shown by the connections ②③, in terms of health trusteeship, the administrator performs device binding operations on the specified trustee object on the main operation terminal. After the AI health cloud service platform obtains the relevant information, it verifies the identity of the cluster administrator. Once the verification is passed, the system will establish a file for the trustee object, and at the same time automatically generate a [unique user account identification code] for the trustee object and establish a one-to-one association relationship with the [unique user account identification code] of the cluster administrator, thereby activating the trusteeship permission of the cluster administrator for the trustee object.

[0316] Trusteeship operations and the rights of the trustee object: After that, the administrator can carry out health trusteeship behaviors on the trustee object in the capacity of a health trustee during the management process. At the same time, the trustee object itself also retains the right to conduct normal health management, such as being able to conduct operations such as health consultations with the AI health digital human.

[0317] 4. Permission interaction process among cluster members and users

[0318] Permission protocol setting and communication: As Figure 36 As shown in Continuous ④⑥, among cluster members or users inside and outside the cluster (such as A, B, C), they perform interactive settings through their own permission settings and operations, or through the permission "protocols" with other users. These operations will be communicated to the AI health cloud service platform in the form of application instructions or confirmation instructions.

[0319] Platform verification and adjustment execution: After receiving the relevant instructions, the AI health cloud service platform will verify the identity of single-party users or multi-party users. After the verification is passed, the system will review the permission "protocols" reached by the users or between users, re-archive them, and execute the corresponding adjustment operations, as shown by the platform process steps g and h.

[0320] Information Update and System Execution: After the above process, the system will save the latest user profile information and synchronize and update it with the user management modules of the main operation terminal and the secondary operation terminal through communication protocols and instructions, as shown in Figure 36 continuously shown as ⑤⑦⑧⑨ in. After the update is completed, the AI health management system and each operation terminal will perform management operations according to the new "agreement" of permissions among users.

[0321] (XII) Family-style Cluster User Management and Application

[0322] When a family (clan) or a group (organization) uses the AI health management system and devices, such a group is called a cluster, and the users in the cluster are all members of this cluster. This user module is called the cluster user mode, which is further divided into the group-style cluster mode and the family-style cluster mode. The two cluster modes coexist compatibly. A user can either use the group-style cluster mode or the family-style cluster user mode at the same time.

[0323] 1. Management Mechanism of Family-style Cluster

[0324] A family refers to a social group composed of people with blood relationships (including direct and collateral blood relatives) or marital relationships. Family members usually share a surname or the origin of the surname, have a common ancestor, and continue the family's culture, values, and traditions in family inheritance. The scope of a family can extend from a nuclear family (parents and children) to a large family including grandparents, uncles, aunts, cousins, and other relatives. It is a form of social organization based on kinship bonds and plays an important role in social structure and cultural inheritance.

[0325] A family tree, also known as a genealogy or clan tree, is a special document that records the family's lineage and the deeds of its important figures in written form. It details the origin, migration, branches of the family, the names, styles, birth and death dates, marital status, children's information of family members, as well as relevant information such as family rules and precepts, family property, and ancestral halls. The family tree is an important carrier of family history and culture. Through it, the development context of the family can be traced, the blood relationships and inheritance order among family members can be understood, the cohesion and sense of identity of the family can be maintained, and at the same time, it provides rich materials for the study of history, demography, sociology, folklore, etc.

[0326] The AI health management system, from the construction and application of the cluster mode, cleverly utilizes the group nature, structural characteristics of the family, various scenario requirements of family health management, and characteristics such as family marriages being similar to cluster alliances, and innovatively designs the family-style cluster health management mode.

[0327] In the family cluster mode, the operation and interaction methods of the system take into account the behavior habits and communication methods of the native family. Family members can conveniently perform operations such as creating a family cluster, inviting others to join the family, and kicking others out of the family. These operations are similar to the organizational and management behaviors within the family. At the same time, the sharing and exchange of health information among family members also follow the communication mode within the family, making the health management operations more natural and smooth.

[0328] The family cluster mode is a health management mode with family members as the unit. A family is similar to a cluster, a family is similar to a sub-cluster, and the marriage between families is similar to a combined cluster, but there are slight differences. There are two roles in the family cluster: the family tree creator (default family tree administrator) and family members. The family tree creator is only limited to family tree management. Any family members (or other individual users) can pay health attention to each other; families are defined within the family according to certain rules, and each family member automatically enjoys the right to health care for other family members.

[0329] 2. Related role definitions of the family cluster

[0330] Family tree creator: The first family member to create a family tree in any family is the family tree creator. This family member is responsible for maintaining and modifying the family tree and can also assign permissions to other family members for division of labor management. For example, Figure 37 As shown in ⑤ of [Family cluster structure - User roles], "A male 2" has an administrator label, which is the family tree creator of this family and is also the default administrator of the family tree.

[0331] Family lineage person: The family lineage person determines their position in the family based on blood relationship. Each family lineage person carries the transmission of family genes and is a link in the family reproduction chain. (Such as father and son in the paternal family, mother and son in the maternal family). For example, Figure 37 As shown in "G male 1", "A male 1", "B male 1", etc. are family lineage persons.

[0332] Family member: All members of a family are family members, including all family members within their family line. A family member is also one of the members of the paternal family and one of the members of the maternal family, and also becomes one of the members of the spouse's family after marriage.

[0333] Family: In the AI health management system, "family" refers to a relative unit within a family or family tree, consisting of parents and children (and their spouses) as a family. According to the actual application of the AI health management system, it is mainly for the health management of family members with relatively close blood relationships, so there are certain differences from the traditional meaning of the family tree. We call the highest-level family lineage person in the family tree built in the AI health management system the "branch ancestor", such as Figure 37The family shown in ① is the "family branch ancestor family", which is also the primary family in the family. For example, Figure 37 As shown, in the AI health management system, the family cluster presents a tree-like branch structure. Below the "family branch ancestor family", according to the genealogy, it can be called the primary sub-family, the secondary sub-family, and so on. For example, Figure 37 In ② is the primary sub-family, ③ and ⑨ are the secondary sub-families, ③ is the tertiary sub-family, and ④ is the quaternary sub-family.

[0334] Family members: The family members of a family include the people in the family genealogy and their spouses, children and their spouses. For example, Figure 37 In ⑤, the father, ⑥ the mother, ⑦ the son, and ⑧ the daughter-in-law form the "⑨-A male 2" family.

[0335] 3. Other explanations of the family-based cluster

[0336] It is worth emphasizing that, as Figure 37 shown, in the family cluster mode, the family, as a concept of member composition, has non-complete fixity, and it presents the characteristics of relativity and overlap in actual situations. Specifically, the four dotted-line frames ①, ②, ③, and ④ in the figure respectively correspond to four families, and there is an overlapping phenomenon among these four dotted-line frames, which is a normal situation. Taking the family member ⑤ "A male 2" in the family genealogy as an example, he and his spouse, son, and daughter-in-law together form a family; at the same time, as the son of "G male 3", he also forms a family with his parents and brothers; in addition, he and his wife and his wife's parents also form a family. In the family-based cluster mode of the AI health management system, ⑤ "A male 2" has corresponding rights related to the health concern and health trusteeship of family members in these three families.

[0337] In the family cluster mode of the AI health management system, it strictly follows the family structure principle based on the blood relationship of father-son or mother-son relationship. In terms of family member identification and related permission management, it breaks through the limitation of traditional families that only focus on the male family tree and implements the equal concept of treating male and female members equally. Specifically, regardless of male or female members, even after a woman gets married, in the family-based cluster mode of this system, her family relationship still continues in the original family tree, which is different from some concepts of traditional family trees.

[0338] Normally, when a user is unmarried, according to the principle of family blood belonging, he / she belongs to both the paternal family and the maternal family at the same time. After the user gets married, the spouse's family will be added. For Figure 38Taking a certain "user" in the [Family Cluster Structure - Tripartite Marital Relationship among Family Members] as an example, where connection ① is used to represent the marital relationship of the user's parents, and connection ② shows the positions of the user's father in the paternal family and the maternal family; connection ④ reflects the marital relationship between the user and their spouse, and connections ③ and ⑤ display the positions of the user in the paternal family, the maternal family, and the spouse's family. Additionally, as Figure 39 shown, based on the genealogy structure, taking this user as an example and from the perspective of the user as the center, the standard appellations for the members of the three families are referred to, so as to reflect the characteristic mechanism of family cluster management.

[0339] If the above-mentioned user also has adoptive parents with legal relationships, this situation is also applicable to the family cluster mode of the AI health management system. In this case, the user can correspondingly add the adoptive father's family and the adoptive mother's family, and its management mechanism is the same as that of the biological parents' family line.

[0340] Any member of the family who creates the family tree for the first time (and is responsible for maintaining and modifying it) is the creator and administrator of this family's family tree, and can also be managed by assigning permissions to family members for division of labor. As Figure 40 shown in ⑦, the family member ⑴, as the creator of the family tree, assigns the family tree management permission to the family member ⑵, generally divided into full-family management or partial branch management. When creating the family tree, the birthday and gender of family members must be indicated (the system automatically generates family relationships and mutual appellations, as Figure 39 shown).

[0341] It should be emphasized that after the family tree is created, the AI health management system will automatically generate a [unique user account identification code] for each family member, and at the same time will automatically mark the position of each family member in the family and the family tree, and clarify their relative relationships with other family members or family members.

[0342] Under the family cluster management mode, the AI health management system defaults that family members automatically have the right to pay mutual health attention to each other, and can also, according to the actual situation and needs, actively choose to cancel the attention by the health attention party or the attention object. To pay attention to other family members of the family, the consent of the person himself or the custodian must be obtained, as Figure 40 shown in ③ and ④.

[0343] Under the family cluster management mode, the AI health management system defaults that family members have the right to health custody of another family member in the same family; if a child has health custody of their parents, it can be lifted or transferred to a sibling for custody; to custody other family members, the entrustment of the family member who has the right to custody of him must be obtained.

[0344] As Figure 41As shown in the [Family Cluster User Permission Management Mechanism], in the family cluster user mode, the "agreement" reached among the family tree creator, family tree administrator, family members, and family members through relevant management permission operations will be re-filed and executed by the AI Health Cloud Service Platform system to ensure the accuracy and effectiveness of the permission settings.

[0345] 4. Health Custody Related Permission Operations and Processes

[0346] Device Binding and Permission Activation: As Figure 41 shown by the connection ②③ in the figure, in terms of health custody, a family member A binds a device with another family member C in the same family on the main operation terminal. After the AI Health Cloud Service Platform obtains the relevant information, it verifies the identities of family members A and C. Once the verification is passed, the system will establish a health custody file for family members A and C, and then activate the custody permission of the cluster administrator for the custody object.

[0347] Custody Operations and the Rights of the Custody Object: After that, family member A can implement health custody behaviors on the custody object family member C in the capacity of a health custodian during the management process. At the same time, the custody object family member C also retains the right to conduct normal health management, such as being able to consult the AI Health Digital Human for health advice and other operations.

[0348] 5. Permission Interaction Process among Family Members and Users

[0349] Permission Agreement Setting and Transmission: As Figure 41 shown by the continuous ④⑥ in the figure, family members or users inside and outside the cluster (such as A, B, C) interactively set through their own permission settings and operations, or the permission "agreement" with other users. These operations will be transmitted to the AI Health Cloud Service Platform in the form of application instructions or confirmation instructions.

[0350] Platform Verification and Adjustment Execution: After receiving the relevant instructions, the AI Health Cloud Service Platform will verify the identities of single or multiple users. After the verification is passed, the system will review the permission "agreement" reached among users or users, and re-file and execute the corresponding adjustment operations, as shown by the platform process steps g and h.

[0351] Information Update and System Execution: After the above process, the system will save the latest user file information and synchronously update it with the user management modules of the main operation terminal and the secondary operation terminal through communication protocols and instructions, as Figure 40 shown by the continuous ⑤⑦⑧⑨ in the figure. After the update is completed, the AI Health Management System and each operation terminal will perform execution management operations according to the new permission "agreement" among users.

[0352] In addition to the above features, all family members of a user's own family enjoy the rights of default health concern and health trusteeship among themselves (the relevant right mechanisms are the same as those of the group cluster mode), unless the concerned party cancels the corresponding concerned person; a user can directly view all family members (except for members of his own family) in the family tree to which he belongs and submit requests for health concern or health trusteeship to them (different from individual users, individual users need to separately request the other party's identity ID number or scan the ID QR code to conduct inquiries or concerns).

[0353] It should be reminded that the family tree creator and administrator are only identities for family tree management responsibilities. In essence, the administrator is also an individual user. The administrator is only the identity for his management authority over the family tree. As an individual user, any family member can, in addition to participating in the family cluster health management, also conduct health concern activities with individual users who are not family members, such as Figure 40 shown by the connecting lines ①② in. If the individual user is a family member who has not joined the family cluster, he can also apply to a family member with family tree management rights to join the family tree, or be invited to join the family tree, such as Figure 40 shown by the connecting lines ⑤⑥ in.

[0354] A user can enable the health management applications of both the group cluster mode and the family cluster mode at the same time, and naturally enjoy the relevant permissions of the group cluster mode and the family cluster mode.

[0355] (13) Diversification of the acquisition devices of the AI health management system and expansion to third-party data access methods

[0356] The expansion and compatibility capabilities of the AI health management system are crucial. It not only determines whether the system can adapt to diverse user needs and complex health management scenarios, but also concerns the practicality and sustainable development of the system. By docking and integrating with various types of devices and third-party systems, the system can obtain more comprehensive health data and provide more accurate health assessment and management services for users. The ways of expansion and compatibility cover the docking with wearable intelligent devices, personal household medical devices, and the systems of third-party diagnosis and treatment or physical examination institutions. Each method adopts specific technical means and standard protocols to ensure the accurate transmission of data and the stable operation of the system. This all-round expansion and compatibility aims to break information silos, realize the interconnection and interoperability of health data, and ultimately focus on users to enhance the user's health management experience and promote the development of the health management field towards a more efficient and intelligent direction.

[0357] 1. The expansion and compatibility of the acquisition devices are reflected in, but not limited to, the following aspects

[0358] Wearable Smart Devices: The AI health management system is committed to being compatible with more types of wearable smart devices. Whether it is common smart bracelets, smart watches, or emerging smart rings, smart ankle bracelets, etc., the system can be compatible with them. These wearable smart devices integrate a variety of sensors, such as optical heart rate sensors, electrode electrocardiogram sensors, blood pressure detection sensors, thermometers, acceleration sensors, gyroscopes, etc. The system can accurately obtain the health data collected by these devices, including information such as heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, and exercise status, providing users with comprehensive health monitoring services.

[0359] Personal Home Medical Devices: The acquisition devices of the system not only include wearable smart devices but also cover personal home medical devices. The system can be compatible and integrated with a variety of personal home medical devices. For example, common home medical devices such as electronic blood pressure monitors, blood glucose meters, and body fat scales can be connected to the system. When users measure relevant health indicators using these devices, the data can be transmitted to the system in real time. This integration allows the system to collect more comprehensive health data for more accurate health assessments.

[0360] Special Acquisition Devices for Healthy Diet: That is, the system obtains the above-mentioned daily meal records of users through special acquisition devices, algorithms, or other means, including but not limited to information such as meal time, food types, intake, and dining environment.

[0361] Work and Living Environment Monitoring Devices: That is, the system obtains the environmental monitoring data of users through special acquisition devices, algorithms, or other means, including but not limited to information such as environmental air pressure, temperature, humidity, light intensity, ultraviolet intensity, noise intensity, air quality, etc., as well as information such as environmental safety and comfort.

[0362] Acoustic acquisition equipment: The user's own and surrounding people's voice information and the acoustic environment in which they are located are recorded in high fidelity. Then, the cutting-edge audio processing algorithm and professional emotion recognition model are used to accurately extract voice features from the recorded audio data, and based on the emotion analysis algorithm constructed by deep training of the AI ​​large model, the speaker's emotional state and emotional tendency are accurately judged. At the same time, the health monitoring data such as physiological indicators that are indirectly related to the user's emotions monitored by other acquisition devices in the system are integrated to carry out a comprehensive and comprehensive analysis, so as to obtain scientific and objective evaluation results. For example, it can accurately identify whether the emotional expression is aggressive and vicious, or whether it shows a gentle and friendly attitude, so as to achieve a deep insight into the emotional dimension of voice and the purpose of accurate quantitative analysis. On this basis, the system will present a detailed and comprehensive analysis reference report to the user or his guardian, and propose corresponding adjustment measures in a targeted manner. These measures not only play a key role in protecting the personal safety of users, but also have positive value and important significance in maintaining the mental health of users and promoting social health.

[0363] 2. Expand the scope of health supplement information, including but not limited to the following aspects

[0364] From the perspective of collection channels, the collection of supplementary health information directly or indirectly related to the user's health is expanded from only using specific collection channels to unlimited collection channels and methods, without specifying dedicated or specific collection equipment;

[0365] From the perspective of the types of data collection equipment, it includes but is not limited to ordinary wearable smart devices that have not been certified as medical devices, wearable health data collection devices that have been certified as medical devices, personal or home medical devices and health testing equipment that have been certified as medical devices, data collection equipment such as work and living environment monitoring equipment that have been professionally certified or not, and acoustic collection equipment that have been professionally certified or not, which can collect the above-mentioned supplementary health information that is directly or indirectly related to the health of the user;

[0366] From the aspect of the use of collection equipment, including but not limited to a single designated type of collection equipment, the alternating use of multiple types of collection equipment, and the simultaneous use of multiple types of collection equipment to collect supplementary health information directly or indirectly related to the user's health;

[0367] From the perspective of data information collection methods, it has expanded from collecting health data through collection equipment to directly or indirectly obtaining medical records, conditions and health-related information about the above-mentioned users from the relevant management systems of one or more third-party diagnosis or physical examination institutions through data interfaces and communication protocols.

[0368] 3. Interface with the systems of third - party medical diagnosis or physical examination institutions, expanding the concept of acquisition devices to system data access

[0369] System interface implementation: The system can be extended to interface with the systems of third - party medical diagnosis or physical examination institutions. This interface is achieved through standardized data interfaces. We use encryption technology to protect the privacy and security of data. For example, HL7 (Health Level 7) or other relevant data exchange standards can be used to ensure accurate and secure data transmission between different systems. At the same time, encryption technology is used to protect the privacy and security of data during transmission.

[0370] Enriching the health information source: The data obtained from third - party institutions is diverse. It includes but is not limited to historical diagnosis results, treatment plans, disease progression records, laboratory test reports (such as blood test, urine test results), and imaging examination materials (such as X - ray films, CT scan results). These data enrich the system's health information source and provide important references for health assessment.

[0371] Improving the accuracy of health assessment: When assessing a user's health status, data from third - party institutions plays a crucial role. For example, when assessing a user's risk of cardiovascular disease, in addition to considering the current health monitoring data (such as heart rate, blood pressure) obtained from acquisition devices and the user's health supplement information (such as lifestyle, family medical history), the system will also refer to the historical diagnosis results of cardiovascular disease, the use of medications in the treatment plan, and the changes in blood pressure and blood lipid levels in the disease progression records from third - party institutions. By comprehensively considering these aspects, the system can more comprehensively analyze the user's disease risk factors and develop a more personalized health management plan.

[0372] Disease monitoring and tracking applications: For users with chronic diseases, data from third - party institutions is valuable for disease monitoring and tracking. The system can obtain the disease progression of users at different time points, such as the blood sugar control of diabetic patients, the changes in renal function indicators of chronic kidney disease patients, and the symptom improvement information after drug treatment. Based on this information, the system can timely adjust the health management strategy and provide more timely and effective health intervention measures to help users better control the disease development and improve the quality of life.

[0373] Enhancing the user - centered experience: By interfacing with the systems of third - party medical diagnosis or physical examination institutions, the system realizes a user - centered experience and service that integrates health information and health management. Users do not need to frequently switch between different systems to obtain comprehensive health information and personalized health management services. This one - stop service model improves user satisfaction and convenience of use.

[0374] Expansion and Optimization of System Functions: From the perspective of system functions, this docking expands the function categories of the acquisition terminal, making it not limited to obtaining data from acquisition devices. At the same time, it also optimizes the health assessment and management capabilities of the entire AI health management system. The system can use richer information sources for more accurate analysis and decision-making, providing better health management services for users. (14) Diversification of the Sub-operation Terminal of the AI Health Management System

[0375] In the field of modern health management, people increasingly focus on using diverse intelligent devices to conveniently manage personal health. The AI health management system aims to achieve compatibility with multiple types of sub-operation terminal devices through innovative design, such as intelligent robots, smart speakers, digital photo frames and other intelligent devices. These sub-operation terminal devices can be developed based on the communication protocol of this health management system, or the system can actively be compatible with common intelligent devices on the market. Users can purchase newly the sub-operation terminal devices supporting the system, or make full use of the resources of the original sub-operation terminal devices. After simply installing the operation terminal program of this system, they can use the relevant functions and services of this health management system. In special cases, the sub-operation terminal device can also integrate some functional modules of the acquisition terminal. At this time, the sub-operation terminal device combines the functions of the operation terminal and the acquisition terminal into one. The user health monitoring data or environmental monitoring information collected by it can be directly transmitted to the AI cloud health service platform.

[0376] 1. Smart Speaker as a Sub-operation Terminal Device

[0377] Health Information Query and Voice Interaction: If the smart speaker is connected to the AI health management system as a sub-operation terminal device, users can interact with the smart speaker through voice commands to query health information. For example, the user says, "Xiaokang Doctor, query my steps yesterday." After receiving the voice command, the smart speaker transmits the command to the AI health cloud service platform through its connection with the AI health management system. The cloud service platform identifies the relevant health data according to the user account, and then feeds back the query result (such as "Your steps yesterday were 8,000 steps") to the user in voice form through the smart speaker. Users can also ask other health information, such as "What is the average value of my blood pressure in the past week?" etc. The smart speaker can accurately understand and obtain the system feedback, providing the information required by the users.

[0378] Health Reminders and Push: The system, based on the user's health management plan and set reminder rules, pushes health reminders to the user through the smart speaker. For example, at 7:00 every morning, the smart speaker will automatically announce "Good morning. You need to take antihypertensive medicine today. Please remember to take the medicine on time." If the user has a physical examination appointment on the same day, the smart speaker will remind the user before the appointment time: "You have a physical examination appointment at 10:00 this morning. Please make preparations in advance and bring relevant documents to the physical examination center." These reminder messages help users develop good health habits and ensure that they do not miss important health matters.

[0379] Emergency Response (Special Function Integration): In special cases, if the smart speaker integrates some function modules of the acquisition terminal, such as being equipped with a simple electrocardiogram monitoring sensor (implemented through an external device or an internal sensor). When the user suddenly feels unwell in the heart at home, the user can activate the electrocardiogram monitoring function on the smart speaker, collect the user's electrocardiogram data, and transmit it to the AI Cloud Health Service Platform in real time. After receiving the data, the AI Health Intelligent Agent quickly analyzes the data to judge the user's heart health status. If an abnormality is found, the system automatically triggers an emergency rescue mechanism. On the one hand, it provides emergency response guidance to the user through the smart speaker (such as "Please stay calm, sit down and rest, and avoid strenuous exercise"), and on the other hand, it immediately sends an alarm message to the preset emergency contacts (such as family members, doctors or the emergency center), informing them of the user's location and health status for timely rescue measures.

[0380] 2. The intelligent robot as a secondary operation terminal device

[0381] Health Information Query and Voice Interaction: If the intelligent robot is connected to the AI Health Management System as a secondary operation terminal device, the user can interact with the intelligent robot through voice commands to query health information. For example, the user says "Doctor Xiaokang, query my steps yesterday." After receiving the voice command, the intelligent robot, through its connection with the AI Health Management System, transmits the command to the AI Health Cloud Service Platform. The cloud service platform identifies the relevant health data based on the user's account, and then feeds back the query result (such as "Your steps yesterday were 8000 steps") to the user in voice form through the intelligent robot. The user can also ask other health information, such as "What is the average value of my blood pressure in the past week?" etc. The intelligent robot can accurately understand and obtain the system feedback to provide the information required by the user.

[0382] Health companionship and interaction services: In daily life, intelligent robots interact with users as health companions. For example, when the user is sitting in the living room resting, the robot actively approaches the user and asks, "How do you feel today? Do you need a health check?" The user can communicate with the robot via voice, such as answering, "I'm a bit tired today." Based on the user's answer, the robot may reply, "You can take a proper rest, drink some water, and relax. If you want to know more ways to relieve fatigue, I can provide you with relevant information." The robot can also recommend suitable health activities or entertainment content according to the user's health condition and interests, such as "According to your physical condition, it's suitable to do some gentle yoga exercises today. I can play yoga music for you," to encourage the user to actively participate in health management.

[0383] Health data collection and transmission (function integration): Assume that this intelligent robot integrates an environmental monitoring function module (such as air quality sensors, temperature and humidity sensors, etc.). During its daily activities, the intelligent robot can collect real-time information on the air quality index, temperature, humidity, etc. of the surrounding environment and automatically transmit it to the AI cloud health service platform, providing data support for the system to analyze the user's health condition and environmental impact.

[0384] 3. Digital photo frame as a secondary operation terminal device

[0385] Health information query and voice interaction: If the digital photo frame is connected to the AI health management system as a secondary operation terminal device, the user can interact with the digital photo frame via voice commands to query health information. For example, the user says, "Doctor Xiaokang, query my steps yesterday." After receiving the voice command, the digital photo frame transmits the command to the AI health cloud service platform through its connection with the AI health management system. The cloud service platform identifies the relevant health data based on the user's account and then feeds back the query result (such as "Your steps yesterday were 8000 steps") to the user in voice form through the intelligent robot. The user can also ask other health information, such as "What is the average value of my blood pressure in the past week," etc. The digital photo frame can accurately understand and obtain the system feedback to provide the information needed by the user.

[0386] Visual display of health data: Digital photo frames are mainly used to display the user's health data and related information in an intuitive and beautiful way. For example, on the screen of the digital photo frame, the user's weight change trend, blood pressure fluctuation curve and other physiological indicators in the past month are displayed in the form of charts, allowing users to understand the changes in their health status at a glance. At the same time, the photo frame will also display the health assessment results generated by the system based on the user's health data, such as health risk level prompts, health advice summaries and other information. For example, when the system analyzes the user's weight data and finds that the user's weight has increased recently, the photo frame will display prompts such as "Your weight has increased recently, please pay attention to controlling your diet and increasing your exercise" to remind users to pay attention to health issues.

[0387] Health knowledge push and education: The system regularly pushes health knowledge and popular science articles to the digital photo frame, which are displayed on the photo frame screen in the form of pictures and texts. The content covers disease prevention, healthy diet, sports and fitness, mental health and other aspects, such as "How to prevent cardiovascular disease", "Summer diet precautions", "Simple exercises suitable for office workers", etc. When users browse the digital photo frame in their spare time, they can easily obtain this health knowledge and improve their health awareness and self-care ability.

[0388] 4. The secondary operation terminal device may integrate some functional modules of the acquisition terminal

[0389] In special cases, the secondary operation terminal device can also integrate some functional modules of the collection terminal. In this case, the secondary operation terminal device integrates the two-in-one functions and properties of the operation terminal and the collection terminal, and the collected user health monitoring data or environmental monitoring information can be directly transmitted to the AI ​​cloud health service platform. In this case, the secondary operation terminal can not only collect user health monitoring data or environmental monitoring information, but also the user can directly consult with the AI ​​health digital person through the secondary operation terminal.

[0390] (XV) Layered architecture and special compatibility mode of AI health management system

[0391] In today's digital health management field, with the rapid development of technology and the increasing diversification of user needs, AI health management systems are facing the challenge of how to achieve efficient operation, wide compatibility and provide high-quality services in a complex equipment environment. In order to meet these challenges, the present invention innovatively proposes a layered architecture and a special compatibility mode, aiming to further optimize the system design, improve system performance, expand the scope of system application, and bring users a more convenient, comprehensive and personalized health management experience. This architectural model not only reflects the deep integration and innovation of the system at the technical level, but also reflects the in-depth thinking on the applicability of health management services in different devices and user scenarios. It is an important exploration and breakthrough of the present invention in solving practical health management problems.

[0392] 1. Architecture Layering Principle

[0393] In the development and compatibility aspect of the AI health management system, in order to adapt to diverse device environments and enhance the flexibility and scalability of the system, a layered architecture design is adopted, which is mainly divided into the host computer and the "AI health management system (without host computer)" in the narrow sense. The host computer plays a key role as the device coordination and communication hub in the entire system. It focuses on handling complex tasks such as communication protocol adaptation and control instruction interaction between the acquisition devices and the secondary operation terminal devices. By parsing and converting the communication protocols of various acquisition devices (such as smart bracelets, smart watches, home medical detection devices, etc.) and secondary operation terminal devices (such as smart speakers, smart robots, etc.), the host computer ensures the accurate transmission and effective control of data between different devices. For example, when the acquisition device uses the Bluetooth Low Energy (BLE) protocol to transmit health monitoring data, the host computer can accurately identify and receive the data, and then convert it according to the unified data format within the system for subsequent processing. At the same time, the host computer is also responsible for sending control instructions to the acquisition devices, such as starting specific sensors for data acquisition, adjusting the acquisition frequency, etc., as well as managing the connection status and function calls of the secondary operation terminal devices.

[0394] Corresponding to it is the "AI health management system (without host computer)", which is a client AI health management system at the pure software system level in the form of H5. This design makes the system have higher independence and portability at the software level. The H5 technology is based on Web standards and can run on multiple operating systems and devices without the need for native development for specific platforms. The "AI health management system (without host computer)" utilizes the cross-platform characteristics of H5 to build core functional modules such as user interface display, health data display and preliminary analysis, and user interaction. For example, users can access the H5-form AI health management system through browsers on devices such as mobile phones and tablets to view the trends of their health monitoring data, receive health reminder notifications, and conduct simple health consultation interactions with the AI health digital human.

[0395] 2. Embedding Mechanism with Ordinary Wearable Smart Device APPs

[0396] Nested implementation method: The nesting between the H5 integration system of the "AI Health Management System (without host computer)" and the APP of ordinary wearable intelligent devices is achieved through carefully designed technical means. Among them, the implementation of communication protocols and control is crucial. A common method is to develop and dock protocols through software development kits (SDKs) or application programming interfaces (APIs). Taking the SDK as an example, developers of wearable intelligent device APPs can integrate the SDK provided by the AI Health Management System into their own applications. The SDK contains a series of predefined functions and interfaces for communicating with the H5 integration system. For example, through the data transmission interface in the SDK, the APP can send the collected health data (such as heart rate, number of steps) to the H5 integration system in a specified format; at the same time, using the control interface, the APP can receive instructions sent by the H5 system, such as adjusting collection parameters, starting specific health function modules, etc. The application method of the API is similar. It provides a set of callable methods, enabling data interaction and functional collaboration between the APP and the H5 integration system.

[0397] Function integration and expansion: After completing the nesting and implementing the communication protocol and control, the APP of ordinary wearable intelligent devices will have some core functions of the AI Health Management System, such as preliminary analysis and display of health data, some health consultation services based on natural language processing, and health reminder functions. In terms of health data management, the APP can use the functions of the H5 integration system to conduct more in-depth analysis and visual display of the collected health data. For example, the heart rate data over a period of time can be displayed in the form of a chart for the user to more intuitively understand their heart rate change trend. In terms of user interaction, the APP can integrate some functions of the AI health digital human to provide users with health consultation services based on natural language processing. The AI health digital human in the H5 integration system will analyze based on the existing health data and knowledge base and try to answer users' questions and provide preliminary health suggestions. In addition, the APP can also use the H5 system to implement health reminder functions, such as reminding users to take medicine and exercise on time, to improve users' compliance with the health management plan.

[0398] 3. Significance and value of special forms in the system

[0399] Enhance system compatibility: This special form greatly enhances the compatibility of the AI health management system with existing devices. The market for ordinary wearable intelligent devices is diverse, and devices of different brands and models vary in terms of hardware configuration, operating system, and communication protocol. By nesting the H5 integrated system into its APP, partial function docking with the AI health management system can be achieved without large-scale modification of the hardware and underlying software of each device. This means that more existing wearable intelligent devices can be connected to the AI health management system, expanding the potential user group of the system and improving its applicability in the market.

[0400] Accelerate the promotion and application of functions: For developers, using the APP of ordinary wearable intelligent devices as a carrier to promote some core functions of the AI health management system can speed up the popularization of the functions. Users do not need to specifically download and install an independent AI health management application. They can experience the new health management functions directly in the familiar wearable device APP. This reduces the threshold for users to obtain health management services and increases their willingness to try the system functions. At the same time, since wearable devices are usually closely integrated with users' daily lives, users can obtain health data and related services more conveniently, thereby enhancing their attention and participation in health management and helping to cultivate users' health management habits.

[0401] Enrich the system ecosystem and data sources: From the perspective of the overall system, this special form enriches the ecosystem of the AI health management system. The connection of more wearable intelligent devices means more diverse data sources. These data can further enrich the system's health information database, providing support for more accurate health assessment and the formulation of personalized health management plans. For example, different brands of wearable devices may collect health data from different dimensions (such as some devices focus on sleep monitoring, while others focus on sports analysis). Integrating these data into the AI health management system can enable the construction of a more comprehensive health profile, enhancing the system's understanding of users' health conditions and thus providing users with better and more personalized health management services.

[0402] 4. Synergy with the overall invention

[0403] Following the system design concept: This special form fully adheres to the design concept of this invention, which is user-centered and provides comprehensive and accurate health management services. By nesting with the APP of ordinary wearable intelligent devices, the system can be closer to the daily usage scenarios of users and integrate health management services into the existing device usage habits of users. Whether during exercise (such as obtaining exercise-related health advice through the smart bracelet APP) or in daily life (such as receiving health reminders through the smart watch APP), users can obtain the support of the system at any time and place, further reflecting the original design intention of the system to care for users' health in all aspects and scenarios.

[0404] Enhancing the system function system: It complements the function modules described in other parts of the invention content and jointly constructs a more powerful health management system. For example, in terms of obtaining health information sources, the data collected and transmitted after the ordinary wearable intelligent device APP nests the H5 integration system becomes part of the overall health information source of the system. Combined with other collection devices (such as household medical testing devices) and the health supplement information input by users at the operation terminal (such as health basic files, medical and physical examination reports), it provides a richer data basis for the AI health intelligent body of the system, thus making the health assessment results more accurate and comprehensive. At the same time, at the user interaction level, the realization of the interaction function with the AI health digital person in the wearable device APP enriches the channels and methods of user interaction with the system, forming a multi-dimensional interaction mode with the interaction on the main operation terminal (such as the independent application on a smart phone) and the secondary operation terminal (such as a smart speaker), meeting the needs of users in different scenarios.

[0405] Expanding the system application scope: From the perspective of the system application scope, this special form further expands the application boundary of the AI health management system. It enables the system to not only run on specially equipped hardware devices (such as collection devices and operation terminals deeply integrated with the system), but also extend health management services to a wider user group by leveraging the existing platforms of ordinary wearable intelligent devices. This helps improve the adaptability of the system in different user groups and usage scenarios. Whether it is users with strong health awareness who pursue professional health management or ordinary users with initial health management needs who rely on daily wearable devices, they can all benefit from the AI health management system of this invention on the devices they are familiar with and convenient to use, thus realizing the effective expansion of the system application scope from the professional field to the mass consumption field.

[0406] 5. The key significance of the hierarchical architecture and special compatibility mode within the scope of patent protection

[0407] Uniqueness and Protectability of the Innovative Architecture: The hierarchical architecture proposed in this invention divides the AI health management system into a host computer and the "AI health management system (without a host computer)" in the form of H5, which is a unique design and has significant innovation in the field of health management technology. The host computer focuses on the functions of processing device communication protocols and control, and the way the H5 integrated system constructs client function modules using cross-platform characteristics is completely different from traditional single architectures or simple integration methods. This unique architecture combination has not been widely applied in the industry and constitutes a significant feature that differentiates it from the prior art. According to the requirements of patent law for the inventiveness of an invention, that is, the invention has prominent substantive features and significant progress, this hierarchical architecture clearly meets this standard. It solves problems such as multi-device compatibility and flexible function expansion through a brand-new design concept, provides a unique technical path for the development of the health management system, meets the basic conditions for obtaining patent protection, and can stand out among many similar technologies, becoming one of the core protection points of this invention.

[0408] Technical Contribution and Protection Value of the Special Compatibility Mode: In the special compatibility mode, the nested mechanism between the H5 integrated system of the "AI health management system (without a host computer)" and the ordinary wearable intelligent device APP to achieve communication and function integration through the SDK or API development docking protocol is another important innovation point of this invention. This compatibility mode greatly expands the application scope of the system, enabling the AI health management system to quickly promote some of its core functions by leveraging the existing wearable device ecosystem, which is of great significance in both technical implementation and market application. From the perspective of technical contribution, it overcomes the compatibility problems faced by traditional health management systems when integrating with different types of wearable devices, and realizes efficient collaborative work between different software systems through a standardized docking method, improving the overall flexibility and adaptability of the system. Within the scope of patent protection, this special compatibility mode belongs to a non-obvious technical improvement and has a positive promoting effect on the development of the industry's technology, and should be protected by patent law. It not only protects the innovative achievements of this invention in specific technical means, but also prevents other competitors from using the same or similar compatibility methods without authorization, thus maintaining the technical advantage of this invention in market competition.

[0409] The close association between the overall architecture and the invention objective ensures protection integrity: The hierarchical architecture and the special compatibility mode are closely associated with the overall health management objective of the present invention, jointly constituting a complete technical solution. Through this architecture and compatibility mode, the entire system realizes the full-process innovation from device data collection, transmission, processing to providing personalized health management services for users. The collaborative work of the host computer and the H5 integrated system ensures the accurate acquisition, efficient transmission and intelligent analysis of health data, while the compatibility with the wearable device APP seamlessly integrates the health management service into the user's daily device use, improving the user experience and the convenience of health management. This close association makes the entire invention form an organic whole technically, meeting the requirements for the integrity and consistency of the technical solution in patent applications. During the process of patent right protection, this integrity helps to ensure the comprehensive and effective protection of the entire invention, preventing others from circumventing patent infringement liability by imitating or improving some technical features. Any act of attempting to destroy this architectural integrity or replicate the special compatibility mode will be regarded as an infringement of the patent right of the present invention, thus ensuring that the innovative achievements of the present invention in the field of health management can obtain full legal protection, encouraging inventors to continuously invest in innovative R & D and promoting the continuous progress of the industry technology.

[0410] (XVI) Self-learning mechanism of the AI health management system

[0411] The self-learning mechanism of the AI health management system is one of the core advantages of the system. This mechanism is based on the collaborative work of multiple components of the system, covering hardware devices and software systems. The various health data collected by the acquisition terminal, the user's health supplementary information and feedback obtained by the operation terminal provide rich materials for learning. The system can learn the associations between health data, user behavior patterns and feedback information, and can also involve new knowledge, theories and methods in the field of health. Based on these learning contents, the system continuously adjusts the algorithm and model parameters, improves the accuracy of predicting the user's health status, provides more effective suggestions in disease prevention and management, and improves user satisfaction by comprehensively learning user feedback information, thus fully demonstrating the intelligence and adaptability of the system and reflecting the innovation and superiority of the present invention.

[0412] 1. Learning basis at the system level

[0413] The AI health management system is a complex whole, covering multiple components such as hardware devices (such as acquisition terminal devices, operation terminal devices) and software systems (such as AI health intelligent agents, etc.). These components all play an indispensable role in the self-learning mechanism.

[0414] The data collection terminal device continuously collects various health data, including but not limited to health sign data (such as heart rate, blood pressure, body temperature, etc.), health behavior data (such as sleep, exercise conditions), and through system learning, more extensive factors related to health, as well as further expansion of the system, such as possibly monitoring data related to the user's work and living environment (such as air quality, noise level, etc.). These data provide the basic materials for the system's learning.

[0415] The operation terminal device is not only the interface for users to interact with the system, but also can collect health supplement information input by users (such as medical reports, lifestyle descriptions, emotional states, etc.). At the same time, the feedback of users on the health assessment results and management suggestions given by the system on the operation terminal device is also an important basis for the system's learning.

[0416] The hardware system of the AI health cloud service platform provides strong support for the storage and processing of data. Its high-performance computing power and large-capacity storage devices ensure that a large amount of health data can be effectively processed and saved, providing a material basis for the system's self-learning.

[0417] 2. Synergy in the learning process

[0418] During the self-learning process, different components work together. The data collected by the data collection terminal device is first transmitted to the operation terminal device, and after preliminary processing, it is uploaded to the AI health cloud service platform.

[0419] The AI health agent runs on the AI health cloud service platform. It uses its own algorithms and models to analyze the uploaded data. At the same time, it adjusts its algorithm and model parameters according to the user feedback obtained from the operation terminal device. Here, the AI health agent development module of the AI health cloud service platform plays a key role. This module provides an efficient algorithm development and optimization environment for the AI health agent, enabling it to better process and analyze data and more accurately adjust algorithm and model parameters.

[0420] For example, if the user feedback indicates that a certain health assessment is inaccurate, the system will retrieve the detailed data for the relevant time period from the data collection terminal device, combine other health supplement information input by the user on the operation terminal device, and use the computing power of the AI health cloud service platform to re-analyze these data and adjust the relevant algorithm and model parameters of the AI health agent.

[0421] 3. Learning based on multiple data types

[0422] The content learned by the system includes not only the health data itself, but also the user's behavior patterns and feedback information.

[0423] From the perspective of health data, the system will learn the correlations between different health indicators. For example, through long-term observation, it is found that elevated blood pressure may be related to decreased sleep quality, reduced physical activity, and certain eating habits.

[0424] From the perspective of user behavior patterns, the system will learn the acceptance and implementation of health management suggestions by users. For example, if the system suggests that a user increase their physical activity, the system will observe whether the user actually increases their physical activity and the impact on health indicators after the increase in physical activity.

[0425] From the perspective of user feedback information, the system will adjust its own assessment methods and management strategies based on the user's satisfaction with the health assessment results and improvement suggestions.

[0426] 4. Learning new theories, knowledge, and methods

[0427] The AI health agent also has the ability to learn new theories, knowledge, methods, etc. continuously introduced in the health field. It can quickly cover new knowledge in related fields, learn and understand new health theories, and through verification and integration with its existing knowledge system and data, continuously improve its algorithms and models to better meet the development needs of health management. The AI health agent development module also provides support for this process, enabling the agent to better integrate new knowledge and optimize its algorithms and models.

[0428] 5. Comprehensive learning of feedback information to improve satisfaction

[0429] The feedback information obtained through interaction with users, including the accuracy of responses, the monitoring of device operation, and the general evaluation and trust of users, can all be worthy of comprehensive learning by the AI agent.

[0430] Regarding the accuracy of responses, if a user points out that the answers to certain health consultations are inaccurate, the AI health agent can use the AI health agent development module to re-analyze relevant data and knowledge and improve its response strategy.

[0431] Regarding the monitoring of device operation, if a user reports a device failure or abnormal situation, the system can use the development module to analyze relevant data and take corresponding measures for improvement.

[0432] Regarding the general evaluation and trust of users, if users have a high overall satisfaction with the system, the system can analyze the reasons and continue to maintain and optimize relevant aspects; if users have a low satisfaction, the system needs to understand the reasons for the dissatisfaction and make targeted improvements to achieve the best user satisfaction.

[0433] 6. Embodiment and application of learning outcomes

[0434] As the system continues to learn, its prediction accuracy of the user's health status continues to improve.

[0435] In terms of disease prevention, the system can more accurately predict the risk of a user contracting a certain disease and give preventive suggestions in advance. For example, for users with a family history of cardiovascular diseases, by learning information such as their family medical history, personal health data, and lifestyle, the system can more accurately predict their risk of developing cardiovascular diseases and give targeted suggestions for diet, exercise, and lifestyle adjustments.

[0436] In terms of disease management, the system can adjust the management plan in a timely manner according to the development of the user's condition. For example, for diabetic patients, the system will continuously adjust the diabetes management plan based on information such as the changes in the patient's blood sugar level, diet and exercise, and the effect of drug treatment to improve the treatment effect.

[0437] In addition, the learning achievements of the system are also reflected in the improvement of the user experience. Through more accurate health assessments and more reasonable management suggestions, users' trust in the system increases, and they are more willing to interact with the system, further promoting the learning and optimization of the system.

[0438] By elaborating on the self-learning mechanism of the AI health management system from multiple aspects, the role of the system can be more comprehensively demonstrated, reflecting the innovation and superiority of the present invention.

[0439] (XVII) Export and Sharing of Health Information Source Data of the AI Health System

[0440] In the field of modern health management, the effective utilization and sharing of data are crucial for providing comprehensive and accurate health services. As an advanced health management tool, the function of exporting and sharing the health information source data of the AI health management system has important significance and purpose. This function not only concerns the user's independent management and use of their own health data but also involves the collaborative cooperation between the system and third-party diagnosis and treatment or physical examination institutions to achieve better quality health care services. The methods cover the user's independent export and download as well as the system's docking and sharing with third-party institutions based on security protocols. Through these methods, it aims to break down data barriers, promote the circulation of health information, improve the accuracy and effectiveness of health assessments and medical services, and ultimately enhance the user's health management experience and health level.

[0441] 1. User's Independent Export and Download of Data

[0442] Such as Figure 21As shown in ⑨, the AI health management system fully embodies the user-centered design concept. Users have control over their own health data or information in the system and can export and download relevant health data according to their own needs. The system will organize these data into files in a certain format, such as the common CSV format, for easy reading and analysis by third-party institutions. This function of users' independent export and download of data not only gives users greater autonomy but also facilitates the use of users in different health management scenarios, enabling users to better participate in their own health management process.

[0443] 2. System connection and data sharing with third-party institutions

[0444] At the same time, as Figure 21 shown in ②, the AI health management system has strong scalability and compatibility and can achieve the sharing of health data or information by docking with the information systems and protocols of third-party diagnosis and treatment or physical examination institutions. With the explicit authorization of users, the relevant health systems of third-party diagnosis and treatment or physical examination institutions can access the relevant health data or information of the user's AI health management system for reference.

[0445] This way of docking and sharing data is achieved based on strict network security and data protection protocols. For example, an encrypted network transmission channel is adopted to ensure the security and integrity of data during transmission. At the same time, the system will conduct strict identity verification and authorization management on the transmitted data to prevent data from being illegally obtained or tampered with.

[0446] After the third-party institution obtains the user's health data, it will combine its own professional knowledge and medical resources to provide relevant health care services for customers. For example, if the third-party institution is a professional cardiovascular disease diagnosis and treatment center, after obtaining the long-term monitoring data of the user's heart rate, blood pressure, etc. and other relevant health information, it will combine its own clinical experience and advanced diagnosis and treatment technologies to provide users with more accurate disease diagnosis, more personalized treatment plans, and more comprehensive health management suggestions. This cooperation model between the system and third-party institutions fully integrates the advantageous resources of both parties, provides users with a better quality health service experience, and further expands the application scope and value of the AI health management system in the field of health care. Description of the drawings

[0447] Figure 01 Schematic diagram of the basic equipment of the system composition - equipment components

[0448] Figure 02 Schematic diagram of the basic framework of the system composition - software system

[0449] Figure 03 Schematic diagram of the deployment of the main function modules of the system - AI health intelligent agent

[0450] Schematic Diagram of the Main Functional Module Deployment of System 04 - AI Health Cloud Service Platform

[0451] Schematic Diagram of the Main Functional Module Deployment of System 05 - Main Operation Terminal

[0452] Schematic Diagram of the Main Functional Module Deployment of System 06 - Sub - Operation Terminal

[0453] Schematic Diagram of the Basic Infrastructure of System Operation - Main Operation Terminal Mode

[0454] Schematic Diagram of the Basic Infrastructure of System Operation - (Main + Sub) Operation Terminal Mode

[0455] Schematic Diagram of the Basic Infrastructure of System Operation - Multi - Operation Terminal Interaction Mode

[0456] Figure 10 Schematic Diagram of System User Application Mode - Single - User Basic Application Mode

[0457] Figure 11 Schematic Diagram of System User Application Mode - Single - User Main - Sub Comprehensive Application Mode

[0458] Figure 12 Schematic Diagram of System User Application Mode - Dual - User Health Concern Application Mode

[0459] Figure 13 Schematic Diagram of System User Application Mode - Dual - User Health Trusteeship Application Mode (Cluster User Mode 1)

[0460] Figure 14 Schematic Diagram of System User Application Mode - Multi - User Comprehensive Management Application Mode (Cluster User Mode 2)

[0461] Figure 15 Schematic Diagram of System User Health Management and Interaction - Basic Health Management Mode

[0462] Figure 16 Schematic Diagram of System User Health Management and Interaction - Health Concern Mode

[0463] Figure 17 Schematic Diagram of System User Health Management and Interaction - Health Trusteeship Mode

[0464] Figure 18 AI Health Management - Schematic Diagram of System Workflow

[0465] Figure 19 AI Health Management - Schematic Diagram of AI Health - Related Data Input and Output

[0466] Figure 20 AI Health Management - Schematic Diagram of Obtaining AI Health Information Sources

[0467] Figure 21AI Health Management - Schematic Diagram of AI Health Assessment Result Output

[0468] Figure 22 Schematic Diagram of AI Health Management Interaction on the Main Operation Terminal - Basic Interface and Association

[0469] Figure 23 Schematic Diagram of AI Health Management Interaction on the Main Operation Terminal - AI Health Assessment Result Display Interface

[0470] Figure 24 Schematic Diagram of AI Health Management Interaction on the Main Operation Terminal - AI Health Digital Human Reminder Interface

[0471] Figure 25 Schematic Diagram of AI Health Management Interaction on the Main Operation Terminal - AI Health Digital Human Standard Dialogue Window

[0472] Figure 26 Schematic Diagram of AI Health Management Interaction on the Main Operation Terminal - AI Health Digital Human Audio-Visual Dialogue Window

[0473] Figure 27 Schematic Diagram of AI Health Management Interaction on the Main Operation Terminal - User Medical and Physical Examination Report Management Interface

[0474] Figure 28 Schematic Diagram of AI Health Management Interaction on the Main Operation Terminal - Operation Guide for Medical and Physical Examination Report Management

[0475] Figure 29 Schematic Diagram of User Registration and Device Binding Mechanism - Individual User Single Device Association Scenario

[0476] Figure 30 Schematic Diagram of User Registration and Device Binding Mechanism - Individual User Multiple Device Association Scenario

[0477] Figure 31 User Management - Schematic Diagram of Health Management Permissions

[0478] Figure 32 User Management - Schematic Diagram of Health Concern Permissions

[0479] Figure 33 User Management - Schematic Diagram of Health Custody Permissions

[0480] Figure 34 Schematic Diagram of Group-Type Cluster Structure

[0481] Figure 35 Schematic Diagram of Group-Type Cluster Permission Management

[0482] Figure 36 Schematic Diagram of Group-Type Cluster User Permission Management Mechanism

[0483] Figure 37 Schematic Diagram of Family-Type Cluster Structure - User Roles

[0484] Figure 38 Schematic diagram of family - style cluster structure - Three - family marriage relationship among family members

[0485] Figure 39 Schematic diagram of family - style cluster structure - Standard appellations of three families for family members (perspective)

[0486] Figure 40 Schematic diagram of family - style cluster permission management

[0487] Figure 41 Schematic diagram of family - style cluster user permission management mechanism Specific implementation manners

[0488] To make the objectives, technical solutions and advantages of the present invention clearer, the following further elaborates the present invention in conjunction with the accompanying drawings and embodiments. It should be noted that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention.

[0489] Therefore, the following detailed description of the embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely represents some embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0490] It should be noted that, without conflict, the embodiments in the present invention and the features and technical solutions in the embodiments may be combined with each other.

[0491] In the description of the present invention, it should be understood that if terms such as "upper", "lower", "left", "right", etc. are used to indicate the orientation or positional relationship, it is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the drawings are only for illustrative purposes and cannot be construed as a limitation of the present invention. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances. In addition, terms such as "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0492] It should be noted that similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0493] It should be noted that the specification of the present invention uses "special term codes" and "special term tables" as important auxiliary tools, aiming to provide a way for examiners or readers to understand the present invention, its solutions and embodiments as systematically as possible, so as to minimize misjudgment and ambiguity. The specification of the present invention involves professional expressions in multiple specific fields, and the special terms therein are key elements for conveying the core content of the present invention. However, it should be clear that the special terms and related descriptions only exist as a guiding tool. The core content of the present invention should not be unduly restricted by the naming method of the special terms or the completeness of the explanations. For those of ordinary skill in the art, based on their own professional knowledge and specific technical background, they can reasonably understand the specific meanings of the above special terms.

[0494] It should be noted that the specification of the present invention uses "function module codes" and "function module tables" as important auxiliary tools, aiming to provide a way for examiners or readers to understand the present invention and its embodiments as systematically as possible, so as to minimize misjudgment and ambiguity. The specification of the present invention involves professional expressions in multiple specific fields, and the names and related descriptions (brief introductions) of the function modules therein are key elements for conveying the core content of the present invention. However, it should be clear that the names and related descriptions (brief introductions) of the function modules only exist as a guiding tool. The core content of the present invention should not be unduly restricted by the naming method of the function modules or the completeness of the descriptions (brief introductions). For those of ordinary skill in the art, based on their own professional knowledge and specific technical background, they can reasonably understand the specific meanings of the above function modules.

[0495] This embodiment relates to an artificial intelligence-based interactive personal health management system and its operation method. It is an advanced health management system developed based on artificial intelligence technology and health professional knowledge, and is named "AI Health Management System" here (abbreviated as "system" in the specification of the present invention).

[0496] This specification aims to comprehensively and deeply introduce the AI Health Management System, which is one of the embodiments of the present invention. The AI Health Management System is a relatively complex whole, integrating advanced artificial intelligence technology and new health management concepts, covering multiple levels of technologies and functions, and involving all aspects from hardware devices to software systems, from individual user applications to cluster user management. To enable readers to clearly and accurately understand this system, we have organized the content in a systematic and logically coherent manner.

[0497] During the introduction, we will start with the basic architecture of the system and gradually go into the various functional modules and the collaborative relationships between them. For some key concepts and complex operation processes, we may first present their core points and overall logic, and some details and professional terms may not be immediately elaborated. This is because we hope that readers will first establish a macro understanding of the system and grasp the relationship and operation mechanism between the various parts. In this way, readers can form a preliminary understanding of the general functions and operation of the system based on the overall logic and contextual coherence.

[0498] As the content progresses, we will use a progressive approach to further explain and supplement the concepts and information mentioned earlier. This progressive presentation method can prevent readers from being confused by too many details at the beginning, and help guide readers to gradually go deeper into the details of the system, thereby strengthening their understanding and memory of the entire system.

[0499] We consider that the readers of this manual are diverse, including professional medical personnel, technical experts and ordinary people with health management needs. For professionals, they can understand and infer some contents that are not explained in detail with their own professional knowledge and experience. For non-professional readers, we are committed to using clear logical structure and easy-to-understand language to enable them to gradually understand the working principle and application method of the system during the reading process.

[0500] (I) System composition basic equipment (equipment components)

[0501] The system composition of the AI ​​health management system includes two key parts: basic equipment and basic framework. As shown in Figure 01 [System composition basic equipment diagram - equipment components], the basic equipment is the equipment component, which is the hardware carrier and environmental conditions for the operation of the system. It is mainly composed of acquisition terminal equipment, operation terminal equipment and AI health cloud service platform hardware system.

[0502] The acquisition device, short for "acquisition terminal device", is used to collect health data. It can be wearable smart devices (such as smart rings, smart bracelets, smart watches, etc.). These devices integrate advanced sensor technologies such as optical heart rate sensors (PPG), electrocardiogram (ECG) electrodes, blood pressure detection sensors, thermometers, acceleration sensors, gyroscopes, etc., and can collect various health data in real time. Through the cooperation of sensors and professional algorithms, key health indicators such as health sign data (such as heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc.), health behavior data (such as sleep status, exercise conditions, etc.), and health stress data can be monitored, and preliminary health monitoring information can be obtained. At the same time, using wireless connection methods such as Bluetooth or WiFi, the health monitoring data and health monitoring information are transmitted to the paired operation terminal device for subsequent AI operation and analysis. In addition, the acquisition device can also refer to all relevant devices such as other household or commercial medical devices and health detection devices that can provide health data.

[0503] The operation terminal device covers various smart terminal devices with intelligent operating systems (such as smart phones, tablets, etc.) or smart terminal devices with non-intelligent operating systems (such as smart speakers, etc.). The operation terminal device is a general term for the main operation terminal device and the secondary operation terminal device.

[0504] The main operation terminal device covers various smart phones, tablets, etc. with intelligent operating systems. In terms of hardware, the main operation terminal device is equipped with a high-performance processor, sufficient memory, and a high-resolution display screen, and can run various complex application programs smoothly. In terms of software, the operating system of the main operation terminal device has high openness and compatibility, and supports users to install application programs or related APPs of the "main operation terminal (system)".

[0505] The secondary operation terminal device is an intelligent terminal device with audio input and output (including microphone and speaker) and network connection functions. It has two types: one is with a display screen, such as a tablet computer, a digital photo frame, a smart robot with a screen, etc.; the other is without a display screen, such as a smart speaker, a smart robot without a screen, etc. Its operation solutions are twofold: one is to have an intelligent operating system that supports the installation of the "secondary operation terminal" application program; the other is to adopt the MCU solution of a non-intelligent operating system and combine it with a real-time operating system (RTOS) to execute the software program of the "secondary operation terminal". At the user usage level, the main application scenarios include receiving data from the acquisition device and transmitting it to the AI health cloud service platform, as well as the user having health consultation interactions or Q&A with the AI health digital human in it. Due to its particularity, in addition to being applicable to some individual users as an auxiliary device for the main operation terminal device, it is more suitable for the cluster user mode. For example, in a cluster, when the elderly are unable to use the main operation terminal device (such as a smart phone), family members can use their own mobile phones to install the main operation terminal, supplement the health information for the elderly (such as establishing a basic health file, uploading medical and physical examination reports, conducting emotion and ability evaluations, etc.), and bind the acquisition device and the secondary operation terminal device on behalf of the elderly (or remotely bind), and at the same time consult the AI health digital human on behalf of the elderly about the health status and the working status of the acquisition device.

[0506] The hardware system of the AI health cloud service platform specifically refers to all the hardware systems involved under the AI health cloud service platform system.

[0507] (2) System Composition Infrastructure (Software System)

[0508] As shown in Figure 02 [Schematic Diagram of System Composition Infrastructure - Software System], in terms of the software system, the infrastructure of the AI health management system usually refers to its software system. This system consists of four subsystems: the AI health intelligent agent, the acquisition terminal, the operation terminal, and the AI health cloud service platform. Among them, the AI health intelligent agent is divided into a client system and a cloud server system, which are respectively embedded in the operation terminal and the AI health cloud service platform, and at the same time integrates cloud computing capabilities and mobile terminal interaction functions. The whole system is an organic whole highly integrated in multiple dimensions and at multiple levels by these four subsystems, and each subsystem and each functional module cooperate with each other to provide users with comprehensive, personalized, and interactive health management services and experiences.

[0509] The AI Health Agent, or "AI Health Agent (System)", is a first-level subsystem of the AI Health Management System. The AI Health Agent is jointly composed of the AI Health Agent cloud server system and the AI Health Agent client system. This system integrates advanced artificial intelligence technology, cloud computing capabilities, and mobile terminal interaction functions to provide users with comprehensive and personalized health management services. The AI Health Agent (System) is based on an AI computing server and an application program background server, which integrates an AI large model trained with professional health knowledge. It has powerful AI computing capabilities and data analysis capabilities, and can deeply analyze and quickly process a large amount of health data information from the operation terminal to provide users with individualized health assessments, predictions, and personalized health suggestions. At the same time, the AI Health Agent (System) also provides an "AI Health Digital Human" instant health dialogue mode to provide users with a more intuitive and vivid health interaction experience. The AI Health Agent System realizes the full-process service from health data collection, analysis to health management through the collaborative work of the cloud server and the client.

[0510] The collection terminal, which is a software system installed in collection devices (such as smart rings, smart bracelets, smart watches, etc.), is a first-level subsystem of the AI Health Management System. The collection terminal closely cooperates with the sensor technology integrated in the collection device, including optical heart rate sensors (PPG), electrode electrocardiograms (ECG), blood pressure detection sensors, thermometers, acceleration sensors, gyroscopes, etc. Through the interaction with these sensors and the application of professional algorithms, the collection terminal can drive the sensors in real time to collect user health monitoring data, thereby obtaining key health indicators such as users' health sign data (such as heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc.), health behavior data (such as sleep status, exercise conditions, etc.), health stress data, as well as preliminary health monitoring information obtained through professional algorithm analysis. At the same time, the collection terminal uses wireless connection technologies such as Bluetooth or WiFi to transmit the health monitoring data and health monitoring information to the operation terminal device paired and bound with it. The collection device can also be other household or commercial medical systems or health detection systems that can provide users with health data, or generally refer to all software systems that can provide users with health data.

[0511] The operation terminal, namely the "operation terminal system", is abbreviated as the "operation terminal" or called the "operation terminal (system)". It is a first-level subsystem of the AI health management system and is a collective term for the main operation terminal (system) and the secondary operation terminal (system). The application program (APP) of the operation terminal is downloaded and installed by the user on the user's operation terminal device (such as a smart phone). The user conducts personal health management through registration and login. The user can view AI health analysis information and AI health reminder information on the relevant interface of the operation terminal. At the same time, on the one hand, the operation terminal is responsible for obtaining the user's health supplement information (including basic health record information, medical and physical examination report information, emotion and ability evaluation information, etc.) and comprehensively processing it with the health monitoring information obtained by the collection terminal into the user's health information source; on the other hand, the operation terminal integrates the AI health intelligent agent client system and is equipped with the AI health digital human function module. The user can communicate with the AI health digital human in natural language in real time and reply to the questions raised by the AI health digital human in the way equivalent to a doctor's consultation, further supplementing the user's health information source so that the AI health management system can analyze the user's health status more accurately and comprehensively.

[0512] The AI health cloud service platform, or the "AI health cloud service platform (system)", is a first-level subsystem of the AI health management system. It is a software and hardware integrated service system that combines the AI operation server and the application program background server into one. The AI health cloud service platform integrates the server-side system of the AI health intelligent agent. The server-side of the AI health intelligent agent and the client-side of the AI health intelligent agent integrated in the operation terminal cooperate to execute AI health operations and AI health management work, and maintain and support the normal operation of the "AI health digital human". The AI health cloud service platform is also the management background of the system user operation permissions, strictly controlling the access and operation permissions of different users to the platform to ensure the security of user data and privacy. The AI health cloud service platform has a complete system software architecture, advanced hardware configuration and high-speed network configuration, with powerful computing, storage and servo capabilities, ensuring the ability to serve multiple users simultaneously.

[0513] (3) Second-level subsystems of the AI health management system

[0514] As shown in Figure 02 [Schematic diagram of the basic architecture of the system composition - software system], at the software level, the first-level subsystems of the AI health management system include: AI health intelligent agent, collection terminal, main operation terminal, secondary operation terminal, and AI health cloud service platform. Among them, the main operation terminal and the secondary operation terminal are collectively referred to as the operation terminal. The AI health intelligent agent is divided into a client system and a cloud server system. Its client system is embedded in the main operation terminal and the secondary operation terminal, and its cloud server system is organically embedded in the AI health cloud service platform, while integrating cloud computing capabilities and mobile terminal interaction functions. The second-level subsystems of the AI health management system are the second-level subsystems further subdivided from its first-level subsystems.

[0515] As shown in Figure 02, the AI Health Agent secondary subsystem includes the AI Health Agent client system and the AI Health Agent cloud server system. The client system is responsible for obtaining and preprocessing user information, and the cloud server system performs in-depth analysis and calculations. The two cooperate with each other in data processing, calculation evaluation, providing health advice and interaction, and also closely cooperate in aspects such as version control and maintenance support to jointly achieve the health management function.

[0516] The AI Health Agent client system, also known as the "AI Health Agent (system) client", is not only an important secondary subsystem of the AI Health Agent (system) but also the core secondary subsystem of the operating terminal. It is an organic combination of the AI Health Agent (system) and the operating terminal (system). It is integrated into the operating terminal system and then installed (or implanted) into the operating terminal device to work together with other management systems of the operating terminal. At the same time, it also works together with the AI Health Agent cloud server system, responsible for obtaining and preprocessing the user's health monitoring information and health supplement information, and at the same time transmitting the health assessment results obtained from the cloud server to the user through the window interface or the "AI Health Digital Human" dialogue. The AI Health Agent client system is also the AI interaction system between the "AI Health Service System" and the user (including the AI Health Digital Human, the AI Health dialogue window, etc.), supporting users to conduct AI health consultations. Users can interact with the "AI Health Digital Human" through natural language to obtain professional health advice, answers, and health reminders.

[0517] The AI Health Agent cloud server system, also known as the "AI Health Agent (system) cloud server", as the core secondary subsystem of the AI Health cloud service platform, carries powerful functions developed based on professional training of the AI large model. It uses advanced artificial intelligence algorithms and the AI large model to deeply analyze and calculate the user's health monitoring data and health monitoring information obtained from the operating terminal device. By working together with the AI Health Agent client system integrated in the operating terminal, it jointly executes AI health calculations and AI health management tasks, providing users with individualized health assessments, personalized health advice, and maintaining and supporting the "AI Health Digital Human". The AI Health Agent cloud server system continuously learns and optimizes from a large amount of health knowledge to improve its own analysis ability and service quality.

[0518] As shown in Figure 02, the health data collection and management system and other management systems of the collection terminal form a complete collection terminal. The health data collection and management system, namely the "health data collection and management system of the collection terminal", is one of the important subsystems of the collection terminal, mainly responsible for collecting and managing various health monitoring data of users. It is deeply integrated with the sensor technology integrated in the collection terminal device, including optical heart rate sensor (PPG), electrode electrocardiogram (ECG), blood pressure detection sensor, thermometer, acceleration sensor, gyroscope, etc. Through professional algorithms and driver programs, the sensors are activated in real time to collect health monitoring data, including key health indicators such as health sign data (such as heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc.), health behavior data (such as sleep status, exercise conditions, etc.), health stress data, and preliminary health monitoring information obtained through professional algorithm analysis.

[0519] Other management systems of the collection terminal are important subsystems of the collection terminal. It forms a complete collection terminal system with the health data collection and management system of the collection terminal. Other management systems of the collection terminal play a key role in the collection terminal, mainly responsible for various management tasks except for the collection of health monitoring data, including device setting management, wireless connection management, transmission control of health data and information, power management, etc.

[0520] As shown in Figure 02, in addition to including the above-mentioned core secondary subsystem AI health intelligent agent client system, the main operation terminal also includes other secondary subsystems, which cooperate with each other to jointly realize the system functions: the health monitoring information management system is responsible for collecting, sorting, and analyzing users' health monitoring data and information, providing a basis for subsequent evaluation; the health supplement information management system supports users to manage personal health supplement information, integrates it with monitoring information, and improves the accuracy of analysis; other management systems of the main operation terminal undertake the tasks of ensuring the normal operation of the device and function expansion, covering multiple aspects such as device setting and permission management.

[0521] The health monitoring information management system is a secondary subsystem of the main operation terminal. The health monitoring information management system focuses on the collection, sorting, and analysis of users' health monitoring data and health monitoring information. It closely cooperates with the collection terminal, receives real-time health monitoring data transmitted from the collection terminal (such as smart rings), including key health indicators such as health sign data (such as heart rate, electrocardiogram, blood pressure, blood oxygen saturation, body temperature, etc.), health behavior data (such as sleep status, exercise conditions, etc.), health stress data, and preliminary health monitoring information obtained through professional algorithm analysis, and then uploads these health monitoring data and health monitoring information to the AI health cloud service platform.

[0522] The Health Supplementary Information Management System is a secondary subsystem of the main operation terminal. The Health Supplementary Information Management System provides users with a platform for comprehensively managing personal health supplementary information. It supports users in establishing a basic health file, uploading important health documents such as medical and physical examination reports, and conducting operations such as emotion and ability evaluations. By integrating these health supplementary information and combining it with health monitoring information, it provides a richer and more comprehensive AI health data source for the AI health management system, thereby achieving more accurate health analysis and assessment. This system also supports the cluster user mode, allowing users with corresponding permissions to act as administrators to perform operations and health management of health supplementary information for another user.

[0523] Other management systems of the main operation terminal and other secondary subsystems of the main operation terminal form a complete main operation terminal. Other management systems of the main operation terminal play an important management role in the AI health management system, undertaking the important tasks of ensuring the normal operation and function expansion of the main operation terminal equipment. It includes multiple aspects such as device setting management, permission management, data storage and backup management, system update and maintenance, etc.

[0524] As shown in Figure 02, other management systems of the secondary operation terminal and the AI health intelligent agent client system form a complete secondary operation terminal. Other management systems of the secondary operation terminal play an important auxiliary management role in the AI health management system. This system is mainly responsible for the specific function management and operation guarantee of the secondary operation terminal equipment. In terms of function management, it includes audio input and output management to ensure that devices such as microphones and speakers can accurately receive user voice commands and provide clear voice feedback. For different types of secondary operation terminal equipment, this system is also responsible for coordinating their unique function characteristics, such as the movement control and interaction management of intelligent robots, etc. In terms of operation guarantee, it covers tasks such as power management and connection management of the equipment to ensure that the secondary operation terminal equipment can operate stably and efficiently.

[0525] As shown in Figure 02, other management systems of the cloud service platform refer to other management systems and hardware conditions in the AI health cloud service platform except for the AI health intelligent agent cloud service system. It and the AI health intelligent agent cloud service system form a complete AI health cloud service platform. Other management systems of the cloud service platform cover hardware devices and a series of management functions to ensure the normal and efficient operation of the AI health cloud service platform. In terms of hardware, it includes high-performance AI computing servers, application program background servers, reliable storage devices, and high-speed network connection devices, etc., providing a strong material basis for the stable operation of the entire platform system. In terms of management functions, it is responsible for important tasks such as user permission management, data storage and backup, network connection management, system monitoring and maintenance, etc.

[0526] (IV) Deployment of the Main Function Modules of the System

[0527] The first-level subsystem of the AI health management system is an important architectural level of the AI health management system. The second-level subsystem is a further subdivision of the first-level subsystem, and its functional modules are more focused on specific functional areas. Under the framework of the first-level subsystem, the functional modules of the second-level subsystem refine and deepen the relevant functions. They not only cooperate closely with the functional modules of other second-level subsystems within the same first-level subsystem, but also conduct data interaction and functional coordination with the relevant functional modules in other first-level subsystems, realizing data circulation and functional collaboration across subsystems, and jointly building a complete and efficient health management system.

[0528] 1. Deployment of the main functional modules of the AI health agent

[0529] As shown in Figure 03 [Schematic diagram of the deployment of the main functional modules of the system - AI health agent], the AI health agent (system) is divided into the AI health agent client system and the AI health agent cloud server system.

[0530] ⑴ As shown in Figure 03, the AI health agent client system includes the following main functional modules:

[0531] AI audio-visual dialogue window interaction module: As an important interaction interface between the user and the AI health agent client system, this module integrates natural language processing, speech recognition, and video display technologies. It can receive the user's voice commands and text inputs, perform real-time parsing and processing, and accurately convey the user's needs to the system. At the same time, it shows the system's feedback information to the user in an audio-visual combination way, such as showing the dialogue content in the image of an AI health digital human, providing an intuitive interaction experience.

[0532] AI audio dialogue interaction module: This module focuses on audio interaction. It uses speech recognition technology to recognize the user's voice commands, converts them into text information and then passes them to the system for processing. At the same time, it uses speech synthesis technology to convert the system's feedback information into voice output, realizing the voice dialogue between the user and the system's AI health digital human. This module can also provide a convenient interaction method for users on devices without visualization conditions (such as smart speakers).

[0533] It should be noted that the AI Health Digital Human refers to the virtual digital human in the "AI Audio-Visual Dialogue Window Interaction Module" and the "AI Audio Dialogue Interaction Module" of the operation terminal, which is a special system program of the operation terminal. It mainly communicates with the user about the health status of the owner (user) of the acquisition device. The AI Health Digital Human is the interface and carrier for the AI Health Intelligent Agent to interact with the user. It presents itself to the user in a digital human-like image and communicates with the user through natural language processing technology, answering the user's health questions and providing health knowledge and advice. The AI Health Digital Human converts the complex analysis results and professional suggestions generated by the AI Health Intelligent Agent into easy-to-understand language and forms, and conveys them to the user, thus realizing efficient interaction between the user and the system. It can be understood that the AI Health Intelligent Agent is a behind-the-scenes research team responsible for processing and analyzing a large amount of health data and information, while the AI Health Digital Human is the front desk attendant of this team, conveying the research results of the AI Health Intelligent Agent to the user. Due to the differences in the hardware configuration of the operation terminal device (such as whether it has a display screen and touch screen input operation) and the operating system (intelligent operating system or non-intelligent operating system), the interaction modalities of the AI Health Digital Human are different. Generally, in the case of an intelligent operating system with a screen (such as a tablet computer), the AI Health Digital Human in the "AI Audio-Visual Dialogue Window Interaction Module" can interact in the forms of text dialogue, voice dialogue, and video dialogue; while in the case of a non-intelligent operating system without a screen (such as a screenless smart speaker), the AI Health Digital Human in the "AI Audio Dialogue Interaction Module" can only conduct voice dialogue.

[0534] AI Health Information Source Acquisition Module (Client): This module is mainly responsible for acquiring health-related information of the user from the client. It collects the health supplementary information input by the user on the operation terminal device, such as the content of the health basic file filled in by the user himself / herself, the medical and physical examination report information uploaded, etc. At the same time, it also receives the health monitoring information transmitted by the acquisition device, integrates these information into the health information source of the client, and provides data support for subsequent health assessment.

[0535] AI Health Assessment Result Display Module: This module is used to display the assessment results of the AI Health Intelligent Agent on the user's health status. It presents them to the user in an intuitive way, such as displaying assessment contents such as health indexes, health risks, and physiological indicators through charts, text descriptions, etc. According to different types of assessment results (such as AI Health Assessment Result (Ⅰ) and AI Health Assessment Result (Ⅱ)), this module can accurately display the corresponding result information to help the user understand their own health status.

[0536] AI Health Assessment Result (I) Output Module: When the system generates the AI Health Assessment Result (I), this module is responsible for accurately outputting the result to the user. It ensures that the result information is presented in a suitable format and manner, such as displaying relevant physiological index data, health risk warnings, etc. in a specific interface area. This module follows relevant standards and specifications during the result output process to ensure the accuracy and readability of the result.

[0537] AI Health Supplementary Information Reminder Module: This module mainly reminds users of their health supplementary information. It monitors the user's operations in the health supplementary information management system, such as whether there are uncompleted contents in the health basic file, unuploaded medical and physical examination reports, etc. When such situations are found, this module will promptly remind the user to perform corresponding operations to ensure that the system can obtain complete health information and improve the accuracy of health assessment.

[0538] AI Health Assessment Result (II) Output Module: Similar to the AI Health Assessment Result (I) Output Module, when the system generates the AI Health Assessment Result (II), this module is responsible for accurately outputting the result to the user. It will display relevant information in a more detailed and accurate manner based on a more comprehensive health information source and a more precise assessment result, such as presenting a more comprehensive physiological index analysis, health risk assessment, etc., to help users better understand the changes and details of their own health status.

[0539] ⑵ As shown in Figure 03 [System Main Function Module Deployment Schematic - AI Health Agent], the AI Health Agent Cloud Server System includes the following main function modules:

[0540] AI Health Information Source Acquisition Module (Cloud Server): This module is mainly responsible for obtaining the user's health monitoring data and health monitoring information from the operating terminal device. It uses advanced communication technologies and network connections to ensure the stable transmission of data. By collaborating with the acquisition terminal and the operating terminal, it collects key health indicators such as health sign data, health behavior data, health stress data, etc. and preliminary health monitoring information to provide the raw data basis for subsequent analysis and processing.

[0541] Medical and Physical Examination Report AI Analysis Module: This module focuses on analyzing the medical and physical examination reports uploaded by users. It uses artificial intelligence technology to analyze and extract key information from various examination results (such as blood tests, imaging tests, etc.), test reports (such as pathological examinations, microbial cultures, etc.), as well as diagnosis reports, treatment reports, etc. included in the reports. These analyzed information will be integrated into the user's health information source to provide support for a more comprehensive and accurate health assessment.

[0542] AI Health Information Source Processing Module: This module processes the acquired health information sources. It adopts advanced algorithms and data processing technologies to clean, organize, and standardize health data from different channels. For example, it denoises health sign data, classifies and quantifies health behavior data to ensure the quality and consistency of the data. At the same time, it may also extract and select features from the data to better provide effective inputs for subsequent AI operations.

[0543] AI Health Agent Initial Calculation Module: Based on the processed health information sources, this module performs preliminary AI calculations. It uses large AI models and related machine learning algorithms to conduct a preliminary assessment and analysis of the user's health status. For example, it analyzes the user's basic vital signs to determine if there are any abnormalities; it performs pattern recognition on health behavior data to understand the user's lifestyle habits. The preliminary calculation results will serve as the basis for further refined calculations and provide a reference for generating more accurate health assessment results (Ⅰ).

[0544] AI Health Agent Refined Calculation Module: On the basis of the initial calculation module, this module performs more precise AI calculations. It comprehensively considers more factors, such as the analysis results of the user's medical and physical examination reports, the comprehensiveness and accuracy of the health information sources, etc. Through more complex algorithms and models, it conducts an in-depth assessment and prediction of the user's health status. For example, it more accurately predicts the user's disease risk and more finely customizes the health management plan, providing a more reliable basis for generating the final health assessment results (Ⅱ).

[0545] AI Health Assessment (Ⅰ) Generation Module: When the user has not performed specific operations on health supplementary information (such as not establishing a basic health record, not uploading medical and physical examination reports, etc.) or has not had sufficient dialogue and communication with the AI health digital human, this module generates AI health assessment results (Ⅰ) based on the existing health information sources and preliminary calculations. It mainly reflects the health status assessment of the user under the basic health monitoring data and provides the user with a preliminary health assessment conclusion.

[0546] AI Health Assessment (Ⅱ) Generation Module: When the user has updated operations on health supplementary information (such as establishing a basic health record, uploading the user's medical and physical examination reports, etc.) and has had dialogue and communication with the AI health digital human and provided relevant health information, this module generates AI health assessment results (Ⅱ) based on more comprehensive health information sources and more precise calculation results. It provides a more comprehensive and accurate health assessment conclusion, comprehensively considering various health-related factors of the user.

[0547] 2. Deployment of the Main Functional Modules of the AI Health Cloud Service Platform

[0548] As shown in Figure 04 [Schematic Diagram of the Deployment of the Main Functional Modules of the System - AI Health Cloud Service Platform], the AI Health Cloud Service Platform (system) is divided into the AI Health Agent Cloud Server System and other management systems of the cloud service platform. The main functional modules of the AI Health Agent Cloud Server System have been introduced and described in the AI Health Agent Functional Modules (not elaborated here), while the other management systems of the cloud service platform include the following main functional modules.

[0549] System User Management Module (Cloud Server): This module is mainly responsible for managing the users of the AI Health Management System. It covers functions such as user registration, login verification, and permission settings. By verifying user identities and allocating permissions, it ensures the reasonable access and use of platform resources by different users. At the same time, it is also responsible for maintaining the basic information and account status of users, ensuring the security and integrity of user data.

[0550] Data Synchronization and Storage Module (Cloud Server): This module focuses on data synchronization and storage. It ensures that users' health data, assessment results, and other relevant information can be synchronized in a timely and accurate manner between different devices and systems. Using efficient data storage technologies, it classifies and stores a large amount of health data for subsequent query, analysis, and use. At the same time, it also provides data backup and recovery functions to prevent data loss and damage.

[0551] Network Communication and Protocol Service Module: This module is responsible for establishing and maint...

Claims

1. An interactive personal health management system based on artificial intelligence, characterized by: Different from some existing health management methods, which only use specific collection channels, such as a single collection device to obtain users' limited health monitoring data and brief personal basic information, and use simple data models or individual artificial intelligence to obtain rough health assessment results for users; The personal health management system of the present invention is based on the above health management method and focuses more on using various types of collection devices or monitoring devices; as well as Multiple collection channels and methods to obtain more supplementary health information related to the user's health; and Together with the above brief personal basic information and health monitoring data, it forms the user's AI health information source; Then Artificial intelligence health algorithms are used to conduct in-depth comprehensive analysis and calculations on this AI health information source to provide users with accurate and comprehensive personalized health assessments and recommendations.

2. An interactive personal health management system based on artificial intelligence according to claim 1, characterized in that: Different from some existing health management methods, which only use specific collection channels, such as a single collection device to obtain users' limited health monitoring data and brief personal basic information, and use simple data models or individual artificial intelligence to obtain rough health assessment results for users; The present invention is applicable to a variety of collection devices, channels and methods to obtain more supplementary health information of the same user, and together with the health monitoring data and brief personal basic information obtained by the above-mentioned specific collection channels, construct a comprehensive AI health information source for the user; The AI ​​health information source is comprehensively analyzed and calculated using artificial intelligence health algorithms to quickly obtain the user's AI health assessment results. The result information can be fed back to the user through page display on the operation terminal, intelligent reminders, and AI health digital people answering user health consultations. Once the user's AI health information source changes, the AI ​​health assessment results will also be adjusted accordingly. Through this circular mechanism, users can be provided with accurate and comprehensive personalized health assessments and recommendations; The content of the health supplementary information includes but is not limited to the following: Health information of the user, such as basic health records information, medical and physical examination report information, emotion and ability assessment results, etc., completed by the user on the operating terminal device of the system; Supplementary health information of users obtained by the AI ​​health digital person deployed in the operating terminal of this system during health consultation or diagnosis with users; Obtain more health monitoring data of the above users by using more collection devices alternately or simultaneously; Information such as users' daily dining records, work and living environment monitoring data, social activity records, etc. obtained through special collection equipment or monitoring equipment, algorithms or other means; as well as Recording the user's and their surrounding voice environment with the help of specific collection and monitoring equipment; and obtaining the user's medical history and health-related information from the relevant management systems of one or more third-party diagnosis or physical examination institutions through data interfaces and communication protocols; Furthermore, the basic health file, i.e. the health information file filled in by the user or his / her health agent at the operating terminal according to the system questionnaire, covers information directly or indirectly related to the user's health, including but not limited to the user's basic information, work-related information, eating habits, lifestyle information, bad habits, physical condition, basic medical history, female-specific information, etc.; Furthermore, the medical and physical examination report is a report file generated by a regular hospital after a medical examination and assessment of the user's physical condition, and then uploaded to the system by the user himself or his health agent through an operation terminal, covering inspection reports including but not limited to blood tests, urine tests, various imaging examination reports, pathological examinations, microbial cultures, drug concentration tests, and electrocardiogram reports, echocardiogram reports, endoscopy reports, surgical reports, diagnosis reports, treatment reports, follow-up reports and health assessment reports, medication guidelines, relevant preoperative and postoperative notices, reexamination notice documents, and other information directly or indirectly related to the user's health; Furthermore, the emotion and ability assessment is to obtain relevant assessment results of the user through questionnaire feedback of the above-mentioned user on the operation terminal, including but not limited to obtaining relevant assessment results or conclusions of the user through intelligence test, emotion control test, cognitive ability test, personality trait test results, memory test, attention test, language ability test and other assessments; Furthermore, the daily dining record is the daily dining record of the user obtained by the system through special collection equipment, algorithms or other means, including but not limited to information such as meal time, food type, intake, dining environment, etc.; Furthermore, the work and living environment monitoring data is the environmental monitoring data of the above-mentioned users obtained by the system through special collection equipment, algorithms or other means, including but not limited to information such as ambient air pressure, temperature, humidity, light intensity, ultraviolet intensity, noise intensity, air quality, and information such as the safety and comfort of the environment; Furthermore, the recording of the user and the voice environment around the user is that the system uses an acoustic collection device to record the user's speech or activity sound, as well as the sound information of the user's surrounding environment; Furthermore, the present invention further expands the scope of the health supplement information, including but not limited to: From the perspective of collection channels, the collection of supplementary health information directly or indirectly related to the health of users is expanded from only specific collection channels to unlimited collection channels and methods, without specifying dedicated or specific collection equipment; From the perspective of the types of data collection equipment, it includes but is not limited to ordinary wearable smart devices that have not been certified as medical devices, wearable health data collection devices that have been certified as medical devices, personal or home medical devices and health testing equipment that have been certified as medical devices, data collection equipment such as work and living environment monitoring equipment that have been professionally certified or not, and acoustic collection equipment that have been professionally certified or not, which can collect the above-mentioned supplementary health information that is directly or indirectly related to the health of the user; From the aspect of the use of collection equipment, including but not limited to a single designated type of collection equipment, the alternating use of multiple types of collection equipment, and the simultaneous use of multiple types of collection equipment to collect supplementary health information directly or indirectly related to the user's health; From the perspective of data information collection methods, it has expanded from collecting health data through collection equipment to directly or indirectly obtaining medical records, conditions and health-related information about the above-mentioned users from the relevant management systems of one or more third-party diagnosis or physical examination institutions through data interfaces and communication protocols.

3. An interactive personal health management system based on artificial intelligence and its operation method according to claims 1-2, characterized in that: Different from some existing health management methods, which are only composed of designated single data collection equipment, operation terminal equipment, common cloud database server and other hardware and software components in a traditional fixed mode; The health management system involved in the present invention can obtain more and more comprehensive health monitoring data and health supplementary information of the same user through one or more collection devices and multiple channels and methods. The system software architecture is composed of collection terminals, operation terminals, AI health cloud service platforms and other components. The system develops AI health intelligent bodies and AI health digital people based on comprehensive training of artificial intelligence technology and health expertise, and deploys AI health intelligent body clients and AI health digital people in the operation terminals, and deploys AI health intelligent body cloud service terminals in the AI ​​health cloud service platform. The system's operation terminals are divided into main operation terminals and secondary operation terminals; Furthermore, in addition to the above-mentioned software system, the health management system of the present invention also covers a hardware system composed of multiple aspects including acquisition equipment, operation terminal equipment, and AI health cloud service platform, wherein the operation terminal equipment is further divided into a main operation terminal equipment and a secondary operation terminal equipment. The acquisition terminal is installed in the acquisition equipment, the main operation terminal is installed in the main operation terminal equipment of user health management, and the secondary operation terminal is installed in the secondary operation terminal equipment of user health management as an auxiliary tool for user health management; Furthermore, in the health management system of the present invention, the collection device is connected to the operation terminal device to transmit the user's health monitoring data and information; and The operating terminal device can communicate with the AI ​​health cloud service platform in a two-way manner to upload the user's health information source, perform comprehensive analysis and calculation of the AI ​​health intelligent body, and receive and output the AI ​​health assessment results; as well as As part of the AI ​​health agent, the AI ​​health digital human is an intelligent health consultant for the system to interact with users through natural language, while the AI ​​health agent provides data and decision support for the AI ​​health digital human; and All components of the system work together to promote the operation of health management; Furthermore, a typical data collection device of the health management system described in the present invention is similar to a common wearable smart device, integrating multiple sensors and technologies, including but not limited to an optical heart rate sensor, an electrode electrocardiogram, a blood pressure detection sensor, a thermometer, an acceleration sensor, a gyroscope, etc.; and Through interaction with these sensors and the use of professional algorithms, the collection device can drive the sensors in real time to collect user health monitoring data, thereby obtaining key health indicators such as the user's health signs data, health behavior data, health stress data, etc., and obtain preliminary health monitoring information through professional algorithm analysis; Furthermore, the collection device of the health management system of the present invention transmits the health monitoring data and information to the operation terminal device paired and bound thereto through a wired or wireless connection, and the operation terminal device then transmits it to the AI ​​health cloud service platform as the basic data of the user's AI health information source; and The health management system supports the automatic measurement mode of the collection equipment at a fixed time, or the user can actively initiate the measurement of relevant data at any time; As the user cooperates with the collection device to continue working normally, the user's health monitoring data will continue to accumulate and update, and will be recorded in the user's AI health information source in chronological order; In the health management system of the present invention, health monitoring data and health supplementary information complement each other and together constitute a complete AI health information source for the user.

4. An interactive personal health management system based on artificial intelligence and its operation method according to claims 1-3, characterized in that: The health management system of the present invention is provided with a user management system and a device binding module, and related system operation mechanisms; The user management system of this system consists of an operation terminal user management module, a group cluster management module, a family cluster management module, and a system user management module of the AI ​​health cloud service platform; These modules work together to provide users with corresponding operations and functional permissions in different health management scenarios; Furthermore, the system automatically generates a "user account unique identification code" and a "user identity ID number" for each registered user, and the two correspond one to one to represent a user; Furthermore, the system can automatically generate a "user identity QR code" for each user's "user account unique identification code" to facilitate interaction between users; Furthermore, a user can simultaneously apply the individual user health management mode, the group cluster health management mode, and the family cluster management mode. The use of each mode will be clearly marked in the user application profile, and its role in the relevant cluster health management mode will also be clearly marked in the user application profile; Furthermore, when a user establishes a health concern relationship with another user, the role of the user as the health concern person or the health concern object in this relationship will also be clearly marked in the user application file, and other operations and settings performed by the user in applying the health management system also follow the same principle; Furthermore, with the help of the system client and cloud server data synchronization storage module, the user's latest application file information is saved; at the same time Through system communication protocols and instructions, the user management modules of the main operation terminal and the auxiliary operation terminal and the AI ​​health cloud service platform are prompted to synchronously update the user application file information; Furthermore, the device binding module of the health management system is divided into a personal device binding module and a cluster device binding module. The personal device binding module is used to bind the user's own devices, and the cluster device binding module is used for the user to bind the devices of its cluster members; Furthermore, when a user registers a user account using a primary operation terminal device, the system will automatically read the "device serial number" and "MAC address" of the primary operation terminal device, and then generate a "primary operation terminal device unique machine identification code", and record this code in the system as the user's primary operation terminal device code in the user's device file; and When the user binds a collection device or a secondary operation terminal device, the system will automatically read the "Device Serial Number" and "MAC Address" of the corresponding device, generate a "Collection Device Unique Machine Identification Code" or "Secondary Operation Terminal Device Unique Machine Identification Code", and use this identification code to represent the user's collection device or secondary operation terminal device in the system and record it in the user's device file; Furthermore, the corresponding device unique machine identification code is associated one-to-one with the user's "user account unique identification code" to ensure that the primary operation terminal device is used by the associated user, that the health monitoring data and information acquired by the collection device belongs to the associated user's own health information source, and that the user of the secondary operation terminal device is the associated user; Furthermore, the system can automatically generate a "device QR code" for each device's unique machine identification code, which is convenient for users to perform on-site or remote binding operations. A user can use the system's built-in scanning tool or a third-party scanning tool to scan the "device QR code" of a collection device to achieve binding, or can search and select to bind through Bluetooth device pairing; Furthermore, a user's account is unique and can only be logged in and used on one main operating terminal device; and When a user changes the primary operation terminal device and logs in on the new device, the account on the original primary operation terminal device will automatically log out; A user can enable multiple collection devices, which can be used interchangeably or simultaneously to collect more health monitoring data of the user; also A user can also enable two or more secondary operation terminal devices. Similarly, different secondary operation terminal devices can be used in different time periods to conduct health consultation or other applications with the AI ​​health digital person, or two or more secondary operation terminal devices can be used in the same time period to interact with the AI ​​health digital person at the same time; Furthermore, with the help of the system client and cloud server data synchronization storage module, the latest user device profile information is saved; at the same time Through system communication protocols and instructions, the device management modules of the main operation terminal and the auxiliary operation terminal and the AI ​​health cloud service platform are prompted to synchronously update the user device file information to ensure the consistency and integrity of the configuration and data of the entire system, and the system is operated or managed according to the updated configuration conditions.

5. An interactive personal health management system based on artificial intelligence according to claims 1-4, characterized in that: In this system, the operation terminal is mainly used as an application computing tool and program, and the acquisition device and the operation terminal device not only serve as an acquisition or operation tool, but also play the role of a network data transmission tool. When the user's health monitoring data is successfully transmitted to the AI ​​health cloud service platform, the user's profile and health information are disassociated from the operation terminal and device; The collection equipment usually temporarily stores health monitoring information for a certain period of time, and the temporary storage time of different devices varies. When the system detects that the user's health monitoring data and information are missing, the AI ​​health digital human will promptly guide the user to find out the cause and remind them to upload the data as soon as possible to reduce the risk of data loss; When the operating terminal is connected to the network and in working state, health monitoring information and health supplement information will be quickly and synchronously transmitted to the AI ​​health cloud service platform, which provides stable and reliable protection for data storage, backup, system security and maintenance. Taking into account the special needs of some users or policy restrictions in certain regions, health data may be restricted from leaving the country or being transmitted to the AI ​​health cloud service platform. In this case, the health management system can deploy the AI ​​health intelligent body cloud server system to the operating terminal in a way that optimizes the configuration and reduces the installation volume. Although this deployment method will affect the accuracy of the AI ​​health assessment results to a certain extent, it can still basically realize the closed-loop process of health management.

6. An interactive personal health management system based on artificial intelligence according to claims 1-5, characterized in that: The AI ​​health digital human deployed by the system has an intelligent consultation function, which can ask users behavioral questions or subjective self-perceptions related to their health; The questions that the AI ​​health digital person asks users are not questionnaires with fixed formats and contents. When users ask health consultation questions, if they find that there is information that is not reflected in the user's AI health information source but should be supplemented, the AI ​​health digital person will ask questions; Furthermore, the AI ​​health digital person's intelligent consultation has a scientific strategy mechanism. Based on the user's comprehensive AI health information source, it uses a fusion analysis algorithm based on an artificial intelligence deep learning framework to extract features through a neural network model and conduct correlation analysis to determine the consultation strategy. Furthermore, centering on the user's health consultation questions, the process is carried out in the order from important factors to minor factors, and from direct factors to indirect factors related to the user's health problems; at the same time Update the user's health profile based on their answers, adjust the consultation process and dialogue in real time, realize personalized consultation, ensure smooth acquisition of key health supplementary information, and provide users with more accurate health assessment and suggestions; Furthermore, once the user answers the questions, the AI ​​health digital human will immediately clean, filter, organize and standardize the answers, extract key information and add it to the user's AI health information source in a timely manner. As the two sides continue to ask and answer questions, the AI ​​health information source will be updated in an infinite cycle; Furthermore, the AI ​​health digital person's intelligent consultation has a self-learning optimization mechanism. Based on multi-source data such as consultation records, health assessment feedback, and changes in health status, it uses deep learning algorithms such as recurrent neural networks or long short-term memory networks to learn user response patterns, uses reinforcement learning to optimize consultation strategies, and discovers new risk patterns and group characteristics through unsupervised learning. Update the knowledge base and policies from time to time.

7. An interactive personal health management system based on artificial intelligence according to claims 1-6, characterized in that: The system has an intelligent reminder function for supplementary health information, which helps ensure that the user's AI health information source always remains relatively complete and accurate, providing the system with more comprehensive basic data, so that the system can provide users with more accurate health assessments and more targeted health advice; The system summarizes the interactive records of health consultation dialogues with users to determine the relevant health issues that users are relatively concerned about, or analyzes the relevant health issues that users may have. If it is found that these health issues are closely related to the missing content of the user's health information source, the system will activate the intelligent reminder mechanism and program; Furthermore, the reminder content of this reminder function mainly focuses on the missing parts of health information in the health supplementary information management system of the operating terminal, including but not limited to the user's incomplete filling of relevant important information in the system's basic health file management module, the user's incomplete relevant important assessments in the system's emotion and ability assessment module, and the user's incomplete upload of relevant important medical or physical examination reports in the system's medical and physical examination report management module. Furthermore, the implementation of the intelligent reminder function includes but is not limited to informing the user through the AI ​​health digital human in its dialogue window, popping up a reminder window or reminder label on the relevant display interface of the operation terminal, sending text messages or push notifications to the contact information registered by the user, etc.; and The reminder content clearly points to the category and entry point of the health information that the user needs to supplement, and the reminder content may mention that the health information item that needs to be supplemented is related to a health issue that the user is concerned about or a health issue that the user may have; Furthermore, this intelligent reminder function is dynamic and timely. As the system continuously analyzes the user's health information source and the user's health status changes, once there is a new need for supplementary health information, the system can initiate a reminder in a timely manner; Furthermore, the intelligent reminder function can be optimized based on user usage habits and behavior patterns. If the system finds that users are usually more likely to respond to reminders and supplement health information in specific time periods or in specific scenarios, the system will prioritize sending reminders at the corresponding time or in the corresponding scenario to improve the user's efficiency and enthusiasm for supplementing health information.

8. An interactive personal health management system based on artificial intelligence according to claims 1-7, characterized in that: The system has the function of providing intelligent reminders for users’ health matters; When the system learns from the user's health information source that the user has medical appointments, review events, or medication events, the system will activate the health event intelligent reminder mechanism to remind the user to pay attention to the relevant event content and suggest corresponding measures; Furthermore, one of the ways in which the system reminds users of health matters is through the AI ​​health digital person, which will remind users of health matters in its dialogue window. This notification is proactive, not just when the user is seeking health advice; and The system can also remind users of health matters by popping up reminder windows on the relevant display interface of the operation terminal, displaying reminder labels, etc.; Furthermore, the system's intelligent reminder function is dynamic and timely. As the system continuously monitors and analyzes the user's health information and the user's health status continues to change, once a new health issue arises that requires the user to be reminded, the system can respond quickly and initiate reminders in a timely manner, ensuring that the user can understand their health status and the actions they need to take at the first time.

9. An interactive personal health management system based on artificial intelligence according to claims 1-8, characterized in that: The AI ​​health digital person deployed by the system can automatically adjust the communication method and can communicate in a professional or popular way; For users with a professional background, AI health digital people will adopt a relatively professional communication method, using professional terminology and in-depth medical knowledge to communicate in order to discuss health issues more efficiently and provide professional advice; The user's background information can be obtained from the user's basic health profile. If it is shown that the user has a medical-related education background or works in the medical industry, the system will mark the user as having a professional background; If a user frequently uses professional terms or shows a high degree of familiarity with professional medical knowledge, the AI ​​health digital person will also judge that the user has a certain professional background; For ordinary users without professional background, AI health digital people switch to popular ways of communication, using easy-to-understand language and avoiding complex professional terms.

10. An interactive personal health management system based on artificial intelligence according to claims 1-9, characterized in that: The AI ​​health digital human deployed in this system can remind users of abnormal usage of data collection equipment or operation terminal equipment and provide guidance and suggestions; Through AI health digital human, users can be reminded of abnormal usage of data collection equipment and auxiliary operation terminal equipment in a timely manner and be effectively guided to promptly discover and solve equipment problems, thus ensuring the stable operation of the health management system; When the user's health monitoring data or information is missing or abnormal for a long period of time, or when the data transmission between the user's collection device and the operation terminal is detected to be interrupted, delayed or lost, the AI ​​health digital human will remind the user of the relevant phenomenon and provide reference troubleshooting steps based on possible causes; Furthermore, when the health monitoring data collected by the sensors of the collection equipment fluctuates abnormally or significantly deviates from the user's normal range, the AI ​​health digital human will issue a prompt reminder and provide targeted troubleshooting suggestions based on the characteristics of different types of sensors and common problems; Furthermore, if it is confirmed with the user that the data anomaly is not a device problem, it will be converted into a user health issue, and the user will be reminded to pay attention, or the user may be advised to consult a professional doctor or seek medical treatment in time.

11. An interactive personal health management system based on artificial intelligence according to claims 1-10, characterized in that: The AI ​​health digital person deployed in its system can assume the role of customer service staff of this system; When users have questions about the use of this system and related equipment, AI health digital human can provide users with accurate instructions and professional guidance and suggestions in a timely manner; Whether it is the functional operation process of the operating terminal, or the correct wearing method and daily maintenance points of the collection equipment, the AI ​​health digital human can answer them in a clear and easy-to-understand manner.

12. An interactive personal health management system based on artificial intelligence according to claims 1-11, characterized in that: The system and its deployed AI health agent have optimization mechanisms and adaptive learning capabilities; The AI ​​health agent is trained on the AI ​​big model and has the ability to acquire health knowledge and learn. It connects with professional medical databases to continuously scan and collect medical and health knowledge, health research results, and disease treatment methods across the country and even the world. Furthermore, the health management system can be based on the continuously accumulated user health data and user feedback information. Developers can use the system's AI health agent development module to debug and optimize the AI ​​health agent system; Furthermore, the learning content of the AI ​​health agent covers multiple aspects; Furthermore, from the perspective of health data, the AI ​​health agent will learn the relationship between different health indicators; Furthermore, from the perspective of user behavior patterns, the AI ​​health agent will learn the user's acceptance and implementation of health management suggestions; Furthermore, from the perspective of user feedback information, the AI ​​health agent will adjust its own assessment methods and management strategies based on the user's satisfaction with the health assessment results and improvement suggestions; Furthermore, the AI ​​health agent itself has the ability to self-adjust and can automatically adjust its own algorithms and model parameters to better adapt to the health conditions and demand changes of different users, thereby improving the accuracy of health assessment and management.

13. An interactive personal health management system based on artificial intelligence according to claims 1-12, characterized in that: The system supports the application mode of health care between users; In this application mode, when a user pays attention to the health of another user, the user who initiates the attention behavior is defined as the "follower" and the user being followed is the "followed object"; The object of interest can choose to use the primary operation terminal device or the secondary operation terminal device; The follower can only follow others by using the main operation terminal device, or the user's health agent can perform the operation of following others' health on his behalf; Furthermore, when a user has obtained the permission to pay attention to the health of another user, it is mainly reflected in that the user can consult the AI ​​health digital person about the health status of the other user and the working status of the collection equipment on his own operation terminal; and A user can follow multiple followers at the same time; Furthermore, when a user submits a health care application to another user and obtains the consent of the other user or the other user's health custodian, the health management system will determine that the two users have reached a health care agreement; at this time The system will establish a health care relationship profile for the two users in the user management module of the AI ​​health cloud service platform system, and synchronously update the relevant settings and permissions of the two users' operation terminals through communication protocols and instructions to ensure that all functions in the health care relationship between the two parties can operate normally; and The AI ​​health digital human dialogue window in the terminal device operated by the follower will automatically add new followees, making it convenient for the follower to quickly switch followees. When the follower switches followees, the AI ​​health digital human will automatically cooperate with the user and target the newly switched followees in the subsequent health consultation, including the followee's health information and problems, the working status of the followee's collection equipment, etc. Furthermore, due to system authority restrictions, if the follower informs the AI ​​health digital human that the health supplementary information of the followee is considered invalid, the AI ​​health intelligent body will ignore this information and will not collect it into the health information source of the followee, thereby ensuring the uniformity and traceability of the user's health information source.

14. An interactive personal health management system based on artificial intelligence according to claims 1-13, characterized in that: The system supports a single user to use the main operation terminal device and the auxiliary operation terminal device in a joint application mode at the same time; When a user has both a primary operation terminal device and a secondary operation terminal device, both can be bound to the collection device to obtain the user's health monitoring data and information, and the user can switch between the two modes at will; and There is no essential difference between the user health monitoring data and information obtained by the primary operation terminal device and the secondary operation terminal device, and both belong to the user's health data. The user can flexibly switch between different operation terminal devices to use the health management function; Furthermore, through the main operation terminal device, the user can view the health assessment results presented by the system in detail, the user can perform systematic and patterned health supplementary information operations, and can conduct health consultation with the AI ​​health digital person in a more intuitive way; Furthermore, due to its flexibility and particularity, the secondary operation terminal device can serve as an auxiliary device for the main operation terminal device. Without opening the main operation terminal device, the user can directly wake up the AI ​​health digital person of the secondary operation terminal by voice wake-up, so as to quickly conduct health consultation or handle other problems. The joint application mode of the main and auxiliary operation terminal devices is suitable for users to conveniently perform health management interactions in different scenarios.

15. An interactive personal health management system based on artificial intelligence according to claims 1-14, characterized in that: The system supports two users to use the main operation terminal device and the secondary operation terminal device respectively, and realizes the joint application mode of health hosting between the two users; In this mode, a user uses the primary operation terminal device to enable the cluster user mode and becomes a cluster administrator or family member to exercise health hosting rights and become the health custodian. Another user, as a cluster member or family member, uses the secondary operation terminal device to become the health hosting object, and the two parties establish a "health hosting" relationship. A user with escrow authority exercises health escrow authority in the relevant management module of his operation terminal to register an escrow object user account for another user. At this time, the system will establish a health escrow relationship file for the two users in the user management module of the AI ​​health cloud service platform system, and synchronously update the relevant settings and permissions of the operation terminals of the two users through communication protocols and instructions to ensure that all functions of both parties in the health escrow relationship can operate normally; Furthermore, in this mode, the cluster administrator manages the health of the managed object, which is mainly reflected in performing relevant management operations for the managed object on his own operation terminal; including but not limited to, Registering user accounts for managed objects; and Provide supplementary health information management for the custodian, i.e., establish basic health files for the custodian, upload medical and physical examination reports of the custodian, conduct emotional and ability assessments on the custodian, etc.; and Binding the collection equipment and the secondary operation terminal equipment for the managed object; Furthermore, in this mode, the cluster administrator, as the custodian, can use the device binding module of the main operation terminal to bind the collection device of the managed object and the secondary operation terminal device, and establish a correct association with the managed object by recording the device serial number, MAC address and other information to ensure that the device and the managed object accurately correspond to each other, so as to correctly obtain the health data of the managed object; Furthermore, this application mode is also suitable for remote operations, such as remotely registering the user account of the managed object, remotely binding the collection device of the managed object and the secondary operation terminal device, remotely performing health managed operations, and remotely paying attention to the health of the managed object; Furthermore, the health trustee user can start or wake up the AI ​​health digital person through voice on his / her secondary operation terminal, consult his / her health problems through dialogue, or obtain health reminders from the AI ​​health digital person, or answer the AI ​​health digital person's questions as supplementary health information; Furthermore, if the health escrow user wants to pay attention to the health of other users, the health escrow person can apply to the other party on his or her own main operation terminal device. Once the other party agrees, the health escrow user can enjoy the right to pay attention to the health of other users; and The health custodian user can consult the AI ​​health digital person on his / her main operation terminal about the health status of the custodian and the use of related equipment; and The health custodian user has the right to pay attention to the health of the custodian object. When the health custodian user consults the AI ​​health digital person about the health status of the custodian object, the health custodian user can actively provide supplementary health information of the custodian object; Furthermore, the health custodian user can manage multiple custodian objects at the same time, and the list of custodian objects will be automatically listed in the AI ​​health digital human dialogue window, so that the custodian user can choose to switch different custodian objects at any time; Furthermore, if the health custodian user wishes to transfer the health custodian rights of the custodian object to other users, the health custodian user can apply to transfer this right to other users through relevant permission operations. If other users agree to accept, that is, the other users and the custodian object will become a new health custodian relationship, and the custodian relationship between the original health custodian user and the original custodian object will be automatically terminated; Furthermore, when health custody relationships between users are established, transferred, or terminated, the system will conduct corresponding health custody relationship file management in the user management module of the AI ​​Health Cloud Service Platform system based on the authority agreement reached between the two relevant users, and will synchronously update the relevant settings and permissions of the operating terminals of the relevant users through communication protocols and instructions to ensure that the various health custody functions of the system can operate normally and orderly.

16. An interactive personal health management system based on artificial intelligence according to claims 1-15, characterized in that: The system supports multi-user group cluster health management mode and mechanism; After an individual user registers an account, when the user initiates an application to join a group cluster in the relevant management module of the main operation terminal, or upgrades to a group cluster administrator through relevant functional operations, the user operation terminal system will automatically load the functional modules or permissions related to group cluster health management; A cluster is the original unit of a group cluster structure newly created by an individual user. The cluster administrator manages the health of its natural cluster members and can also accept more individual users to join and become its cluster members. Cluster members are directly under the administrator and are managed by him; The cluster administrator may also merge other clusters and their subclusters. The direct members of other clusters will be directly subordinate to this administrator, and the subclusters of other clusters will also be transferred to and become subclusters of this cluster. Cluster members have the right to create one-level sub-clusters and manage sub-cluster members; Furthermore, in this mode, a cluster member can create a first-level sub-cluster and manage sub-cluster members. Sub-clusters and clusters have a hierarchical relationship. Clusters are divided into first-level sub-clusters, second-level sub-clusters, and so on. Subcluster members are only direct members of the subcluster, and health management rights can only be exercised by the administrator of the subcluster; When an individual user creates a new group cluster, he or she will naturally become the cluster administrator of the cluster; The cluster administrator may have the right to perform health management for other secondary operation terminal users, who are natural members of this cluster; According to the corresponding mechanism, cluster administrators can automatically enjoy the right to pay attention to the health of members directly under the cluster and members of subordinate sub-clusters without the consent of the cluster members being paid attention to; Furthermore, a cluster is a basic unit system, under which there are direct cluster members, including roles such as cluster administrator, first-level sub-group administrator, and cluster member; and The first-level sub-cluster is a branch of the cluster. The first-level cluster also has its own direct cluster members, including first-level sub-cluster administrators, second-level sub-cluster administrators, first-level sub-cluster members, and other roles; and The first-level subcluster administrator is a direct member of the cluster and a direct member of the second-level subcluster it creates. The mechanism is similar for lower-level branches. Furthermore, a cluster administrator can apply to "unite" with another cluster to form a first-level joint cluster. The cluster administrator who agrees to the union becomes a first-level joint cluster administrator, who can then apply to unite with other first-level joint clusters to form a second-level joint cluster, and so on. The federated cluster is an associated framework, and the federated cluster has no direct cluster members; Furthermore, in this mode, all federated clusters, clusters, and subclusters within the top-level federated cluster cannot be federated again; and All federated clusters and clusters within a top-level federated cluster can be federated with other top-level federated clusters or clusters, and after the federation, the other party becomes part of the top-level federated cluster; Furthermore, in this mode, all peer clusters within a top-level federated cluster can be merged, and the merged cluster administrators and cluster members become members of the newly merged cluster; and All different levels of clusters within a top-level federated cluster can be merged, and the lower-level sub-cluster administrators and cluster members become members of the upper-level cluster; and All clusters of the same level in a tree system can merge external independent clusters, that is, there is no joint state; and After the merger, the external cluster administrator and cluster members become members of the newly merged cluster, and the subclusters of the external independent cluster are also transferred in; Furthermore, in this mode, all lower-level cluster members within the top-level joint cluster can view and apply for health attention to any cluster member within the system within the top-level joint cluster; and The cluster member can also enter the other party's user ID number to search for a selection method or scan the other party's user ID QR code; Furthermore, in this mode, the cluster administrator is an identity with management responsibilities. The administrator is actually an individual user. The administrator is only an identity with management permissions. An individual user can have multiple roles, that is, he can work in any position without conflict. As an individual user, a cluster administrator can conduct health care activities with other users as an individual, join other clusters or sub-clusters, or create more clusters or sub-clusters; and As a cluster administrator, exercise relevant cluster management rights, including but not limited to agreeing to others to join the cluster, inviting others to join the cluster, health hosting, cluster union, cluster merger, transfer of cluster administrator rights, disbanding clusters and other management rights and responsibilities; Furthermore, in this mode, the system agreements reached between cluster administrators and cluster members through relevant management authority operations will be re-registered and executed through the AI ​​Health Cloud Service Platform system to ensure the accuracy and effectiveness of the authority settings.

17. An interactive personal health management system based on artificial intelligence according to claims 1-16, characterized in that: The system supports multi-user family cluster health management mode and mechanism; After an individual user registers an account, when the user initiates an application to join a family cluster in the relevant management module of the main operation terminal, or upgrades to a family tree creator through relevant functions, the user operation terminal system will automatically load the functional modules or permissions related to family cluster health management; The family cluster health management model refers to the construction and application of the group cluster health management model, and uses the group nature and structural characteristics of the family, various scenarios of family health management, and the characteristics of family marriage similar to cluster union to comprehensively design a multi-user health management model; In the family cluster mode, the system's operation and interaction methods take into account the behavior and communication methods of the original family; Family members can easily create family clusters, invite others to join the family, kick others out of the family, etc. Furthermore, the family-type cluster health management model is a health management model based on family members. The family is similar to a cluster, the family is similar to a sub-cluster, and the marriage between families is similar to a joint cluster; and There are two roles in the family cluster: the creator of the family tree and the family member. The creator of the family tree is limited to the management of the family tree. Moreover, any family member or other individual users can pay attention to each other's health. The family is defined by certain rules within the family, and each family member automatically has the right to take care of the health of other family members; Furthermore, under this model, the family cluster health management model has made specific definitions for relevant members, roles, and units. The creator of the family tree is any family member who creates the family tree for the first time. This family member is the creator of the family tree, who is responsible for maintaining and modifying the family tree, and can also assign permissions to other family members to share management; and A family lineage person is a person whose position in the family is determined by blood relationship. Each family lineage person carries the family gene and is a link in the family reproduction chain; and Family members are all members of a family, including all family members within its lineage; and In the AI ​​health management system, "family" refers to a relative unit in a family or family tree, consisting of parents, children, and their spouses; and The family lineage at the highest level of the family tree built in the AI ​​health management system is called the "branch ancestor", and the family it forms is the "family branch ancestor family", which is also the first-level family in the family; and The family cluster presents a tree-like branching structure. The "family ancestral family" can be called the first-level sub-family, the second-level sub-family, and so on according to the lineage. The family lineage members of a family and their spouses, children and their spouses are family members of the family. A family member is also a member of the paternal family and a member of the maternal family. If married, he or she will also become a member of the spouse's family. Furthermore, in the family cluster health management model, the family as a unit constitutes a concept that is not completely fixed, and in actual situations it presents the characteristics of relativity and overlap; Furthermore, in the family clustering model of the AI ​​health management system, it strictly follows the family structure principle of the father-son or mother-son relationship based on blood relationship. Regardless of male or female members, even after a woman gets married, under the family clustering model of the system, her family relationship still continues in the original family tree. Furthermore, if the above-mentioned user also has adoptive parents with whom he has a legal relationship, this situation is also suitable for the family clustering mode of the AI ​​health management system. In this case, the user can add the adoptive father family and the adoptive mother family accordingly, and their management mechanism is consistent with that of the biological parents family; Furthermore, any family member who first creates a family tree (and is responsible for maintaining and modifying it) is the creator and administrator of the family tree. The family tree can also be managed by assigning permissions to family members, generally divided into management of the entire family or management of some branches; and When creating a family tree, you must indicate the basic information of family members such as name, birthday, gender, etc. The system will automatically generate family relationships and mutual titles; and When creating a family tree, for each family member added to the family tree, the AI ​​health management system will automatically generate a "user account unique identification code" and "user identity ID number" for the family member, and will automatically mark the position of each family member in the family and family tree, and clarify the relative relationship between the family member and other family members or family members; Furthermore, in this mode, the AI ​​health management system assumes that family members automatically have the right to pay attention to each other's health. The concerned party or concerned object can also choose to cancel the attention according to the actual situation and needs. If paying attention to other family members, it must be agreed by the family member or the custodian. Furthermore, in this mode, the AI ​​health management system assumes that a family member can have the right to manage the health of another family member in the same family; and If a child has health conservatorship for his or her parents, he or she can terminate it or transfer it to a sibling; and To take care of other family members, the person must agree to it or be authorized by a family member who has the right to take care of him; Furthermore, in this mode, the creator and administrator of the family tree is only an identity with the responsibility of managing the family tree. The administrator is actually an individual user, and the administrator is only an identity with the authority to manage the family tree. As an individual user, any family member can participate in the family cluster health management and can also conduct health care activities with other individual users who are not family members as individuals; Furthermore, in this mode, the system agreements reached between the genealogy creator, genealogy administrator, family members, and family members through relevant management authority operations will be re-registered and executed through the AI ​​Health Cloud Service Platform system to ensure the accuracy and effectiveness of the authority settings.

18. An interactive personal health management system based on artificial intelligence according to claims 1-17, characterized in that: The system supports users to use individual health management mode, group cluster health management mode, and family cluster health management mode at the same time; The three modes operate independently and are not mutually exclusive. Users can freely combine them according to actual needs.

19. An interactive personal health management system based on artificial intelligence according to claims 1-18, characterized in that: The system is compatible with multiple types of secondary operation terminal devices, including smart robots, smart speakers, digital photo frames and other smart devices as secondary operation terminal devices of the system; These secondary operation terminal devices can be developed based on the communication protocol of the health management system, or the system can actively be compatible with common smart devices on the market; Users can purchase a new auxiliary operation terminal device that matches the system, or make full use of the original auxiliary operation terminal device resources. After simply installing the operation terminal program of this system, they can use the relevant functions and services of this health management system; Furthermore, in special cases, the secondary operation terminal device can also integrate some functional modules of the collection terminal. In this case, the secondary operation terminal device integrates the two-in-one functions of the operation terminal and the collection terminal. The collected user health monitoring data or environmental monitoring information can be directly transmitted to the AI ​​cloud health service platform; and The auxiliary operation terminal can not only collect user health monitoring data or environmental monitoring information, but also allow users to directly consult with the AI ​​health digital person for health through the auxiliary operation terminal.

20. An interactive personal health management system based on artificial intelligence according to claims 1-19, characterized in that: The system includes a host computer and a narrow "AI health management system without a host computer" at the development compatibility level, where the host computer is used to handle the communication protocol adaptation and control instruction interaction between the acquisition equipment and the secondary operation terminal equipment; This special architecture and compatibility mode make the system exist in an independent and unique form at the development compatibility level; The "AI health management system without a host computer" is in the form of H5 as a client at the pure software system level, and the H5 integrated system can be nested with the APP of ordinary wearable smart devices. Through the software development kit, namely SDK, or the application programming interface, namely API, communication protocols and control are implemented, so that the APP of ordinary wearable smart devices has some core functions of the AI ​​health management system, including preliminary analysis and display of health data, some health consulting services based on natural language processing, and health reminder functions.

21. An interactive personal health management system based on artificial intelligence according to claims 1-20, characterized in that: The health management system exports AI health information sources and AI health assessment results in a standard format, and supports users to provide them to third-party medical or health institutions that provide diagnosis and treatment services for data sharing and reference.

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