108 results about "Elderly health" patented technology

The invention relates to the technical field of health management and artificial intelligence, in particular to an old people health analysis system and method based on combination of medicine and nursing. The method comprises the steps of collecting and processing multi-modal health data, and generating a health data vector set; mapping the vector set to a standardized health knowledge ontology, constructing a health map initial structure and generating a map node vector; generating a health portrait and an evolution prediction result based on time sequence modeling; identifying risk features according to the health portrait and the prediction result, and generating a medical care service strategy set; and issuing the strategy set to an execution unit and collecting feedback, and finally updating a graph structure and optimizing model parameters based on feedback data. According to the invention, multi-modal data-driven old people health dynamic evolution modeling and personalized service strategy closed-loop optimization are realized, and the intelligent level and response efficiency of medical and nursing services are improved.

The invention is suitable for the technical field of fall detection and help calling, and provides a fall detection and help calling method for the elderly at home, and the method comprises the steps: collecting the multi-source health monitoring data of the elderly through a monitoring camera and a sensor, and carrying out the preprocessing based on the collected data; respectively extracting walking posture features, getting-up and sitting-down posture features, daily activity posture features, motion features, acceleration features, gyroscope features and heart rate features of the elderly; inputting the extracted features into a trained abnormal action detection model for action detection; when the old people have abnormal behavior actions, performing multi-dimensional analysis on the abnormal behavior actions of the old people by utilizing a clustering algorithm; and feeding back the analysis result of the abnormal behavior action of the old person in real time according to a preset help calling rule. According to the invention, the aims of comprehensively monitoring the health state of the elderly, timely discovering abnormity, deeply analyzing reasons and quickly responding to rescue can be fulfilled.

The invention relates to the field of intelligent health situation monitoring, in particular to an elderly health situation monitoring and early warning system and device based on digital twinning, and the system comprises a data collection module, a digital twinning module, a risk prediction module and an early warning module. Wherein the data acquisition module acquires physiological and environmental data in real time; the digital twin module constructs an environment and individual model which dynamically reflects the physical state of the old people, predicts the environment risk and adjusts the state of the model; the risk prediction module evaluates health risks according to the vital sign data and a twinborn model; and the early warning module customizes a health management scheme or sends early warning to nursing personnel according to the evaluation result. The system has the advantages of real-time performance and accuracy, realization of personalized health management, effective prediction of environmental risks, timely early warning and presentation of technical advantages. Meanwhile, physiological and environmental factors are comprehensively considered, comprehensive health management support is provided for old people, and health monitoring and risk early warning efficiency is remarkably improved.

The invention discloses an internet-of-things senile disease nursing system supporting equipment state monitoring, and relates to the technical field of internet-of-things senile nursing. An acquisition module realizes multi-index monitoring by using a flexible sensor and a non-invasive technology; the edge computing unit fuses the neuromorphic architecture and federal learning; the equipment monitoring module predicts faults in combination with acoustic emission and thermal imaging technologies; the health assessment engine carries out disease early warning through causal reasoning and a knowledge graph; the early warning system realizes hierarchical response and multi-terminal linkage; and the block chain platform ensures data security and sharing. Through multi-module collaborative innovation, precise collection of elderly health data and real-time monitoring of equipment states are realized, diseases and equipment faults are early warned in advance, an intelligent evaluation engine can predict complications, multi-modal early warning improves response efficiency, a block chain technology guarantees data security, medical resource sharing is supported, and the system is suitable for popularization and application. And the safety, timeliness and intelligent degree of senile disease nursing are comprehensively improved.

The invention relates to the technical field of health management of old people, and discloses a method and a system for predicting multiple diseases of old people. The method comprises the following steps: acquiring multi-modal health monitoring data of a target old person in a preset time period, wherein the multi-modal health monitoring data comprises physiological index time sequence data, a medication record sequence and a daily activity ability evaluation result; and performing cross-modal correlation analysis on the multi-modal health monitoring data to generate a disease interaction characteristic matrix containing metabolic disease correlation degree, circulatory system disease coordination index and neurodegenerative disease progress rate. And performing hierarchical clustering processing on the feature matrix by adopting a dynamic weight distribution algorithm, and outputting potential common disease combinations of the target old people and a priority score of each common disease combination. And generating a personalized intervention strategy set including a drug interaction avoidance scheme, a rehabilitation training intensity adjustment scheme and a nutrition intake ratio scheme according to the priority score.

The invention relates to the technical field of medical or health data information, in particular to an intelligent health old-age care safety monitoring system, which comprises an old-age information acquisition module for acquiring face and basic information; the body health monitoring module predicts health parameters through LSTM, and if the health parameters exceed a threshold value or change abnormally, one is added to the alarm frequency; the psychological health monitoring module uses a StyleGAN to generate an enhanced data set and performs emotion classification through a convolutional neural network, and if the emotion deviates from a baseline, one is added to the alarm frequency; the tumble posture monitoring module judges tumble through posture estimation, and if tumble is detected, one is added to the alarm frequency; the position anomaly monitoring module identifies abnormal movement or residence, and if an anomaly is detected, the number of alarms is increased by one. And guardians and medical staff can obtain alarm information and monitoring reports in time according to the alarm times, so that the efficiency of monitoring the health and safety of the elderly is improved.

The invention relates to the field of community old-age care, and discloses a community old-age care-oriented medical-care-and-care-combined data intercommunication and service coordination system, which comprises a sensing module used for acquiring physiological data of old people, old-age care service data, environment data and service demand information to form multi-modal information; the network module is used for carrying out multi-modal information transmission, protocol conversion and edge calculation preprocessing to obtain processed data; and the data module is used for constructing a standardized data lake according to the processed data by adopting a unified data standard and a main data management technology, and carrying out fusion storage, treatment and safety protection to obtain multi-source information. Multi-modal information is collected to provide a data basis for cross-mechanism cooperation, data transmission and preprocessing are performed, and a standardized data lake is constructed through a unified data standard and main data management, so that medical institutions, pension institutions and community grids can share global data such as health states, service records and the like of old people in real time.

The invention relates to the technical field of intelligent medical monitoring, in particular to a personalized health monitoring and early warning system for elderly people living alone fused with multi-dimensional data, and the system comprises a data collection and preprocessing module which collects multi-dimensional physiological parameter signals of a user and converts the multi-dimensional physiological parameter signals into multi-dimensional medical features; the health prediction module performs health category prediction on the multi-dimensional medical features of the current time node based on a pre-trained deep learning model, generates a data graph under each time node, and stores the data graph and a corresponding health category prediction result in a specified directory; the early warning module analyzes whether the multi-dimensional physiological parameter signals under each time node are abnormal or not in a mode of combining a hard threshold value and a soft threshold value, and if yes, an alarm is given out; and the abnormity output module calls and outputs the data maps of the preset duration before and after the abnormity alarm time node and the corresponding health categories. According to the invention, personalized monitoring and risk early warning of the health state of the elderly can be realized more accurately from multiple dimensions.

The invention provides an old people body health early diagnosis and risk assessment system based on artificial intelligence, and relates to the technical field of old people health monitoring and assessment. Old people health parameters are collected in real time according to a set time interval, and a statistical method is used to calculate a mean value and a standard deviation of cardiovascular parameters; then, based on acceleration data, heart rate change, blood pressure fluctuation and position change information, sleep, movement and resting states of the old people are judged, and the day and night blood pressure change rate, the sleep state heart rate standard deviation, the movement state pulse wave conduction speed change quantity and the resting state heart stroke output average value are calculated; four risk assessment formulas of blood pressure risk, heart rate risk, pulse wave conduction velocity risk and heart stroke output quantity are constructed according to the data, a comprehensive health risk value is calculated through weighted merging, and the health state of the old people is judged to be healthy, medium-low risk or high risk according to a set threshold value.

The invention discloses a smart old-age service platform based on Internet of Things big data, and belongs to the technical field of Internet of Things old-age care, and the platform specifically comprises a voice instruction collection module which is used for collecting the interaction voice data of an old person and smart home equipment in real time; the voice feature extraction module is used for carrying out feature separation processing on the collected original voice data and extracting quantized instruction indexes; the baseline model construction module is used for establishing a voice health baseline model based on user characteristics and generating a personalized voice index reference interval according to the historical voice data of the old; the voice instruction comparison module is used for dynamically comparing the real-time instruction index with the baseline model, generating a voice health deviation degree curve, and triggering early warning when curve fluctuation exceeds a preset morphological characteristic; the interaction mode adjusting module is used for adjusting the interaction mode of the smart home equipment according to the voice health deviation degree; the health of the elderly is judged through the voice index change, and the smart home service quality is improved.

The invention provides a graded early warning method and system for a home health risk event of the aged, and the method comprises the steps: 1, obtaining health risk index data of the aged at home through intelligent monitoring equipment, carrying out the classification and summarization of the obtained index data according to a home health risk scene, and determining a home health risk monitoring index; 2, identifying home health events of the monitored person by detecting the change of the monitoring indexes, and classifying the events into different grades according to the event types and degrees; and step 3, performing graded early warning according to different grades, namely performing pop-up warning on the corresponding terminal according to the identified monitoring information when the health event reaches the triggering condition of the corresponding early warning grade. According to the invention, through classification and grading of the monitoring data, possible health problems of the elderly can be identified in an early stage, timely alarm can be given for sudden health events, and the life quality and survival opportunities of the elderly are improved.

The invention relates to the technical field of medical health, in particular to an old people health monitoring robot system for an old people institution based on cloud intelligent control. The system comprises a health monitoring management generation module, a health monitoring execution acquisition module, a health activity abnormity analysis module and a remote monitoring alarm module. Historical physiological health data and historical daily activity data can be acquired, and a health monitoring management scheme is generated by using a cloud control platform. A cloud control platform is utilized to send a health monitoring task instruction to a corresponding health monitoring robot and execute navigation to the position of the old in an old-age care institution, meanwhile, medicine delivery and meal delivery tasks are executed, body recognition inquiry and physiological health signal collection are carried out, and meanwhile, health signal abnormity positioning and early warning response are carried out. And generating a health abnormity early warning signal corresponding to the elderly in the pension institution, and timely sending early warning information to medical personnel or family members corresponding to the pension institution. The health monitoring management efficiency of the old-age care institution can be improved.

The invention discloses a tumble early warning system based on multi-dimensional feature fusion and a hierarchical trigger mechanism, and the system integrates the data of seven dimensions: traditional Chinese medicine diagnosis features (face image, eye diagnosis, tongue image, ear image and pulse condition), western medicine clinical indexes (electronic medical record and past medical history), posture behaviors, environment monitoring, inquiry semantics, voice voiceprint and psychological state. And accurate fall risk assessment is realized. The system adopts a three-stage trigger mechanism: a first-stage trigger module independently scores traditional Chinese medicine and western medicine features, and preliminarily quantifies the falling risk; the secondary trigger module independently scores the seven-dimensional features and outputs a multi-modal risk assessment result; and the third-level trigger module performs weighted fusion on the scores of all dimensions based on medical priori knowledge to generate low-risk, medium-risk and high-risk third-level early warning signals. Through multi-source data collaborative analysis and hierarchical decision making, the accuracy and clinical applicability of fall early warning are remarkably improved, and the method is suitable for old people health monitoring and medical aid decision making.

The invention discloses a multi-dimensional health state assessment method for an old-age care robot, and relates to the technical field of old-age health monitoring, and the method comprises the steps: collecting the physiological parameters of a cared old person through a built-in multi-sensor module of the old-age care robot, and forming a physiological parameter set; on the basis of the physiological parameter set, combining a preset physiological parameter threshold value, and performing weighted fusion on standardized numerical values of various physiological parameters to obtain a physiological health index through calculation; analyzing facial expressions and voice features of the cared old people by adopting an emotion recognition algorithm, and extracting psychological state data of the cared old people; and inputting the physiological health indexes and the psychological state characteristic parameters into a health state evaluation model to generate a health state evaluation report. Potential health risks can be found in time, a scientific decision basis can be provided for medical staff and family members, and the health management level and life quality of old people are effectively improved.

The invention provides an old people health management detection method and system, and the method comprises the steps: obtaining behavior task data and physiological data of old people through a scale or a non-invasive device, extracting data features, carrying out the fusion, building a cognitive state evaluation model set through combining an integrated learning model, a deep learning model and a statistical learning model, and carrying out the detection of the health management of old people. Training a cognitive state evaluation model set by adopting a differentiated learning strategy, constructing a dynamic evaluation system based on cognitive competence scores, determining evaluation frequency, determining evaluation items by adopting a correlation priority strategy of data features, establishing a nonlinear mapping rule, setting training reference parameters according to the cognitive competence scores, and evaluating the cognitive competence scores according to the training reference parameters. And making a personalized cognitive training scheme based on the dynamic evaluation system and the individual data characteristics of the elderly. The method is high in individuation degree and simple to operate, has continuous and comprehensive data, and can capture dynamic changes of cognitive competence, know differences of old people in real time and provide a timely and effective feedback mechanism.

The invention relates to the technical field of elderly health monitoring, in particular to an elderly health condition prediction method based on a wearable device, and the method comprises the steps: data collection, data analysis, health condition prediction and evaluation, alarm intervention and personalized suggestion. According to the scheme, the context attribute information of the monitoring data in the user wearing equipment is extracted, and the human behavior model and the time relation model are constructed; an LSTM model combined with a multi-scale attention module is adopted to analyze data of a human behavior model and a time relation model, and subtle and complex mode changes in daily activities of a user are captured; according to the method, abnormal behaviors and abnormal data deviating from a normal mode are inferred, found and explained by combining an ASP efficient common sense inference mechanism based on probability, so that the health condition of a user is predicted and evaluated, and corresponding early warning measures are triggered according to different types of abnormal data to help to prevent potential health risks in advance.

The invention discloses an intelligent robot system integrating health monitoring and cleaning functions for old people, and belongs to the technical field of intelligent old people nursing auxiliary equipment. According to the system, through cooperative work of the health monitoring module, the cleaning module, the interaction module, the control module and the communication module, health monitoring, intelligent cleaning and convenient interaction of old people in a family scene are achieved. The health monitoring module integrates the functions of blood pressure detection, medicine taking reminding and fall detection, and supports multi-dimensional health data acquisition and cloud transmission; the cleaning module realizes an efficient cleaning task through dual-mode control and intelligent path planning; the interaction module adopts a voice recognition mode and a touch control operation mode and adapts to the use habits of the old. And the control module dynamically coordinates health monitoring and cleaning functions through a multi-modal data fusion algorithm and a priority scheduling strategy, and preferentially processes emergency health requirements. The communication module supports dual-network encryption transmission, and collaborative management of local equipment and a cloud is realized. The system breaks through the bottleneck of function isolation of traditional equipment, improves the life safety and convenience of old people through an intelligent algorithm and an aging-suitable design, and has the advantages of high integration level, high adaptability and remote management capability.

The invention discloses a remote health monitoring system and method, a medium and equipment. The remote health monitoring system comprises a medicine taking reminding module, an AI accompanying chat module, a health early warning module, a remote unlocking module and a walking reminding module. The health monitoring module is used for monitoring the health condition of the old in real time; the medicine taking reminding module is used for regularly sending medicine taking reminding to the old; the AI chat accompanying module is used for realizing man-machine conversation with old people; the health early warning module is used for giving an alarm for abnormal health data; the remote unlocking module is used for remotely controlling the intelligent door lock to be unlocked; the walking reminding module is used for carrying out voice reminding on obstacles or water stains encountered by the old people in the walking process, and the display module is in signal connection with the health monitoring module, the medicine taking reminding module and the walking reminding module; according to the health monitoring overall technical scheme, the functions of health monitoring, medicine taking reminding, AI accompanying chat, health early warning, remote unlocking and the like are integrated, and all-around nursing of the old people is achieved.

The invention relates to a nursing home priority service response method, system and device based on digital twinning, and the method comprises the following steps: collecting health data of old people and state data of nursing personnel, and carrying out the preprocessing of the data; constructing an old people health state dynamic model, a nursing resource dynamic model and an environment path model; coupling the three models to form a digital twin model; calculating a service response priority based on the health score, the waiting time attenuation and the medical history characteristics of the elderly; according to the service response priority, scheduling the matched nursing personnel to carry out service response; and collecting a service execution result after the nursing personnel completes the task, updating the digital twinborn model based on the service execution result, and dynamically adjusting a scheduling strategy. According to the invention, real-time mapping and dynamic optimization of the health state of the elderly, the position of the nursing personnel and the environment path information in the nursing home are realized, and the service response efficiency, the resource scheduling accuracy and the nursing quality are remarkably improved.

The invention discloses a question and answer type elderly health management method and device, and relates to the technical field of elderly health management. The method comprises the steps of constructing an old people group cognitive feature database, constructing a dynamic question and answer strategy library, collecting physiological, cognitive and sensory parameters in the daily activity peak period of the old people, calculating health degree coefficients corresponding to all dimensions, outputting comprehensive health scores by using a nerve attention mechanism technology, and determining the health degree of the old people according to the health degree coefficients. Dividing health levels and feeding back reports to update the strategy library; the device comprises a dynamic question and answer module, a rhythm perception scheduling module, a multi-modal data acquisition module, a health degree coefficient calculation module, a self-adaptive fusion calculation module, a health level judgment module and a closed-loop feedback optimization module. According to the invention, the accuracy of health assessment is improved, and the technical problems that traditional elderly health management lacks pertinence, multi-source data cannot be fully utilized and a management strategy cannot be dynamically adjusted are effectively solved.

The utility model discloses a community standardization elderly health screening device, and relates to the elderly health technology field, the community standardization elderly health screening device comprises a bottom plate, the upper end of the bottom plate is fixedly connected with a placing box, the placing box is internally provided with a detection computer, the right end of the placing box is fixedly connected with a corrugated wire, and the corrugated wire is connected with the detection computer. The lower end of the corrugated wire is fixedly connected with an operation pen, the right end of the placement box is fixedly connected with a placement box, the placement box is matched with the clamping rod, a clamping groove is formed in the operation pen, the right end of the placement box is fixedly connected with an air cylinder, the output end of the air cylinder is fixedly connected with the clamping rod, and the clamping rod is matched with the clamping groove. The clamping rod can enter the clamping groove formed in the operation pen, and the position of the operation pen can be fixed.

The utility model discloses a passive exoskeleton robot for health and emergency rescue escape of old people, which is detachable and comprises two protective arms, a robot body and a robot body. The back shell comprises two back supporting rods, a supporting column and two reinforcing plates, the two back supporting rods are detachably arranged on the two protective arms in the vertical direction, the supporting column is located between the two back supporting rods, and the two reinforcing plates are arranged at the upper ends and the lower ends of the two back supporting rods in the horizontal direction; the waist and back support comprises a back protection pad, a safety air bag and an equipment fixing device, the safety air bag is arranged between the back protection pad and the two back supporting rods, the equipment fixing device comprises two straps pulled to the lower portion of the equipment fixing device through the back shell, and a heat insulation part is arranged in the safety air bag; and each leg guard is provided with a heat absorption part and a hook. The passive exoskeleton device is convenient for old people to wear, has advanced functions of climbing stairs, escaping from fire disasters and the like, provides a comfortable passive exoskeleton device for the old people, and has a wide market prospect.

1. The name of the product of this design: Top (one-piece woven intelligent vital signs monitoring suit). 2. Purpose of this design product: This design product is a smart wearable device and can be used for sports vital signs detection, elderly health monitoring, fire emergency vital signs detection, and individual combat armaments. 3. The design key point of this appearance design product lies in the combination of shape and pattern. 4. The picture or photo that best illustrates the design key points: rear view. 5. The top view and bottom view of this design product can be seen from other views, so the top view and bottom view are omitted.

This invention discloses a question-and-answer-based elderly health management method and apparatus, relating to the field of elderly health management technology. The method includes constructing a cognitive characteristic database of the elderly population, building a dynamic question-and-answer strategy library, collecting physiological, cognitive, and sensory parameters during peak daily activity periods of the elderly, calculating health coefficients corresponding to each dimension, outputting a comprehensive health score using neural attention mechanism technology, classifying health levels, and providing feedback reports to update the strategy library. The apparatus includes a dynamic question-and-answer module, a rhythm perception scheduling module, a multimodal data acquisition module, a health coefficient calculation module, an adaptive fusion calculation module, a health level determination module, and a closed-loop feedback optimization module. This invention improves the accuracy of health assessment and effectively solves the technical problems of traditional elderly health management lacking specificity, failing to fully utilize multi-source data, and being unable to dynamically adjust management strategies.

The present invention relates to the field of health monitoring technology, and specifically to a method and system for recommending health and wellness knowledge for the elderly, comprising: obtaining a final confidence level of heart rate signal data based on the difference between data in a heart rate data sequence of a target frequency, the difference between adjacent elements in a time interval sequence, and the energy distribution of all reference frequencies; obtaining the degree of heart rate abnormality in each group of reference heart rate data sequences based on the difference between the trend distribution of data in each group of reference heart rate data sequences and the heart rate data sequence of the target frequency, the difference between the trend distribution of the heart rate signal data of the elderly and the consumed energy signal data, and the final confidence level of the heart rate signal data; and recommending health and wellness knowledge for the elderly based on the degree of heart rate abnormality in all groups of reference heart rate data sequences. The present invention improves the accuracy of detecting heart rate abnormalities in the elderly and improves the accuracy of recommending health and wellness knowledge for the elderly.

The invention discloses an elderly assessment and nursing system and method based on the Internet of Things, and relates to the technical field of elderly care. The system comprises a health information collection module, a health data detection module, a health status assessment module, a nursing adjustment module and a nursing supervision module; the technical key points are: by real-time monitoring of changes in estimated values ​​of the health level of the elderly, timely discovering health risks and issuing alarm prompt signals, and continuing to observe on this basis, thereby ensuring the accuracy of subsequent judgment results, improving the accuracy and timeliness of elderly health monitoring, effectively preventing and handling health problems, executing regular accompanying strategies according to nursing adjustment instructions, adjusting the accompanying time of accompanying personnel, and supervising the regular taking of medicines, ensuring that the elderly receive timely and effective nursing and care, providing more personalized and accurate nursing services for the elderly, and improving nursing quality and effects.

The application discloses a kind of wisdom old-age service platform based on big data of thing association, belong to the technical field of Internet of Things old-age, specifically include: voice instruction acquisition module, for real-time acquisition old man and the interactive voice data of smart home equipment;Voice feature extraction module is used to carry out feature separation processing to the original voice data collected, extracts quantized instruction index;Baseline model construction module is used to establish the voice health baseline model based on user characteristics, generates personalized voice index reference interval according to old man historical voice data;Voice instruction comparison module is used to dynamically compare real-time instruction index with baseline model, generate voice health deviation curve, when curve fluctuation exceeds preset morphological characteristics, trigger early warning;Interaction mode adjustment module is used to adjust the interaction mode of smart home equipment according to the voice health deviation;The application realizes the health of old man by voice index change judgment and improves the quality of smart home service.

The invention discloses a CCRC-based health monitoring platform and application thereof, and belongs to the technical field of health monitoring, and the CCRC-based health monitoring platform comprises a data acquisition module, a monitoring item recommendation module, a CCRC management module, a CCRC management module, a CCRC management module and a CCRC management module, and the monitoring item recommendation module is used for establishing a monitoring item recommendation module to carry out detection items of health monitoring data based on personal preferences on the platform user so as to update health information. According to the invention, after the basic information of the user platform is acquired in real time through the data acquisition module, health monitoring can be carried out based on the user information, and preference pushing can be carried out on the information of the user to be subjected to health monitoring based on the personal information and the acquired user preference data; a health monitoring plan can be established according to the conditions and preferences of the user, the quality of pension service is improved, precise monitoring of the health of the elderly is expected to be realized, and the manpower and material resource cost is reduced.

The invention provides an information recommendation method and system based on artificial intelligence, and belongs to the technical field of information recommendation. Comprising the steps of 1, constructing a first data set; 2, constructing a second data set; step 3, based on the first data set, constructing a health knowledge preference coefficient of the ith old person; 4, constructing a health behavior adaptation coefficient and a participation depth coefficient of the ith old person based on the second data set; and step 5, associating the ith old people health knowledge preference coefficient with the ith old people health behavior adaptation coefficient and the participation depth coefficient, constructing a comprehensive health participation index, and performing evaluation and optimization. Through data analysis in which online health knowledge and offline medical lectures are combined, the health behavior tendency of the elderly user can be evaluated more accurately, and the optimized recommendation can help the user to obtain appropriate health knowledge.

The invention relates to the technical field of health risk assessment, and discloses an elderly health risk assessment method and system, and the method comprises the steps: collecting physiological parameter data and body function data of an elderly, and determining an initial health risk assessment value of the elderly; judging whether to adjust the initial health risk assessment value or not according to a comparison result of the collected real-time health data and a preset health threshold range; if yes, calculating a deviation value between the real-time health data and a preset health threshold range, and determining a final health risk assessment value according to the deviation value; according to a comparison result of the final health risk assessment value and a preset health risk range, judging whether potential risk analysis needs to be carried out or not; and if so, collecting psychological state data of the elderly to determine a potential risk value, and determining a health risk level according to a sum result of the potential risk value and the final health risk assessment value. Through multi-dimensional data integration, dynamic assessment adjustment and hierarchical risk analysis, systematic assessment of the health risk of the elderly is realized.