40 results about "Exercise prescription" patented technology

The invention provides a body function evaluation method and device based on multi-modal sensing fusion. Real-time detection and analysis of human motion and postures are achieved through a multi-modal sensing technology. According to the method, the test process is standardized, operation is automatic, scoring is objective, the accuracy and repeatability of the test are improved, and manual intervention is reduced. Through visualization and voice guidance, action demonstration and prompts are provided on a large screen, it is ensured that a testee completes a test autonomously, and the operation burden of workers is reduced. Meanwhile, the system automatically calculates scores and generates reports according to a standard SPPB scoring rule, provides result interpretation and rehabilitation suggestions, and remarkably improves the evaluation efficiency and practicability. In addition, a personalized video exercise prescription is generated according to the test score, so that the testee can track the training progress conveniently. The closed loop of detection and intervention services is ensured, and the rehabilitation effect is improved.

The invention relates to an exercise prescription generation method and device, equipment and a storage medium, and the method comprises the steps: obtaining target input information of a user, and achieving the standardization of the input information; on the basis of the target input information, retrieval is performed in the plug-in knowledge base to obtain the retrieval result matched with the target input information, so that the retrieval result is professional, and the retrieval accuracy is improved; the target input information and the retrieval result are input into the trained retrieval generation model, the exercise prescription is output, the retrieval generation model is iteratively trained according to the marked fine adjustment data set, compared with traditional medical consultation, the exercise prescription is output through the trained retrieval generation model, the generation time of the exercise prescription is shortened, and the user experience is improved. Compared with general artificial intelligence model interaction, the exercise prescription generated by the method is combined with the retrieval result of the plug-in knowledge base, and the method is more professional.

The invention discloses a personalized exercise prescription generation method fusing deep learning, learnable similarity and multi-modal time sequence analysis. The method comprises the steps that firstly, static signs and health risk labels of a user and dynamic signals such as the heart rate, the HRV and the step number collected by wearable equipment in real time are integrated, and unified modeling is conducted through a multi-modal encoder to form individual state vectors; then outputting a preliminary motion scheme by a BERT-Transform text generation model, mapping a user to a hidden space taking a historical execution effect as supervision by using a comparative learning network, and accurately inferring an FITT core parameter through approximate nearest neighbor retrieval and effect weighting; performing consistency optimization on texts and parameters through a large language model, completing risk verification under a safety barrier constructed by a medical rule base, ensuring that output meets clinical taboo and individual tolerance, and finally continuously optimizing long-term health income under medical constraints in combination with an offline reinforcement learning strategy, and cooperating with meta-learning cold start and uncertainty estimation, so as to achieve the purpose of improving the safety of the health management system. Safe, accurate, self-adaptive and explainable personalized exercise prescription generation for new and old users is realized, and the method can be widely applied to intelligent fitness, chronic disease exercise intervention and digital health management scenes.

The invention discloses a skeletal muscle repair method and system based on muscle satellite cell regulation and control. The method comprises the following steps: performing proliferation and differentiation correlation analysis on satellite cell steady state data and aerobic exercise intensity data to establish a proliferation regulation and control map; determining a collaborative repair time window according to the atlas, extracting difference response deviation correction parameters to form an activity correction factor, and performing repair intensity correction on the collaborative repair time window to generate a self-adaptive repair window; carrying out exercise prescription adaptation on the self-adaptive repair window, identifying a satellite cell activation regulation and control channel, obtaining activation delay time through activation efficiency mapping, and delimiting a response level according to the activation delay time to generate layered repair configuration; activation delay evaluation is conducted on layered repair configuration to determine a preferred activation mode, dynamic activation characteristics are extracted based on optimal activation time window data to form an intervention execution sequence, a skeletal muscle repair execution instruction is output in combination with an exercise prescription parameter table, and dynamic collaborative adaptation of satellite cell repair state monitoring and training scheme parameters is achieved.

This invention relates to the field of exercise prescription generation and recommendation technology, and discloses an LLM-based generative recommendation method for exercise prescriptions. The method involves acquiring and preprocessing data, constructing a knowledge graph based on the preprocessed data (S1), pre-training the LLM model, inputting the constructed knowledge graph into the LLM model, and optimizing it through reinforcement learning. The PPO algorithm is used to optimize the LLM model's output strategy. Based on the optimized LLM model, the exercise prescription is derived and generated in natural language using FITT parameters. This method combines user characteristics and scenario information to generate high-quality, personalized exercise prescriptions. The invention utilizes a multi-dimensional reward function framework to quantify prescription quality and optimize the generation strategy, ensuring that the generated exercise prescriptions are not only scientifically sound but also conform to the user's actual situation and preferences. Synthetic data is generated through a user simulator, achieving an upgrade from static recommendation to dynamic adaptation, improving user experience and the level of intelligence in exercise and health management.

The invention belongs to the technical field of information processing and artificial intelligence, and discloses an exercise prescription generation method, device and system based on clinical data, a medium and equipment, and the method comprises the steps: obtaining the clinical data of a test object; joint physiological features are extracted from the clinical data based on a multi-source heterogeneous data fusion model; inputting the extracted combined physiological features into a dynamic randomization engine, and grouping the combined physiological features based on the dynamic randomization engine; and constructing and training a health state prediction model, inputting the grouped combined physiological features into the trained health state prediction model, outputting a health state level of the test object and a physiological state evolution track under different exercise interventions, and generating a personalized exercise prescription. According to the method, accurate prediction of the individual health state and personalized generation of the intelligent exercise prescription can be realized, and scientificity, pertinence and practicability of health management of the test object are effectively improved.

The invention discloses a lung cancer patient home exercise rehabilitation training system based on a severe game, and the system comprises a patient terminal device which is used for operating a severe game application and collecting exercise behavior data and physiological signals; the medical care terminal management interface is used for medical care personnel to log in and check patient information and training execution conditions; and the server / cloud platform comprises an exercise prescription engine module which is used for generating an individualized exercise prescription based on the baseline evaluation data of the patient. Through a virtual game scene and a hierarchical breakthrough and reward mechanism, the originally boring respiratory training, resistance training and walking training are integrated into a severe game with the sense of sexuality and goals, the participation interest and the sense of achievement of a patient are stimulated, and the possibility of long-term persistence is remarkably improved.

The present application relates to a kind of children's physical health exercise guidance method and system based on intelligent algorithm, personal physical data and physical activity data are collected using acquisition equipment, then the physical data and physical activity data collected are matched database, generate personal record.Intelligent algorithm analyzes personal record, automatically analyzes basic body data, automatically classifies, generates personalized exercise prescription.Personalized exercise prescription is pushed to user in real time in system front end, user continues to exercise according to personalized prescription.Subsequently, motion data in the exercise process are collected by acquisition equipment and are transmitted to cloud, the exercise prescription and data of this time are stored by cloud using big data, in combination with artificial correction error prescription mechanism, the wisdom algorithm model is nibbled optimization, overcome the technical defects that existing method lacks systematicness and integrity, lacks curative effect evaluation and quality control, detection result is not accurate and system automation degree is low.

This application discloses an exercise prescription generation device, method, equipment, and medium, relating to the field of sports health management technology and applied to computer devices. It includes: a feature extraction module that simultaneously collects body composition and muscle strength data from obese subjects, and obtains body composition and muscle strength features through preprocessing and feature extraction; a preliminary generation module that performs hierarchical judgment on the two types of features to determine the obesity type and muscle strength level, and generates a preliminary exercise prescription based on the combination results; a prescription generation module that uses the body-muscle combination index to determine aerobic exercise parameters and determines resistance training parameters based on the muscle strength level, generating a target exercise prescription for the current execution cycle; an exercise review module that obtains the review results after the subject executes the prescription; and a prescription adjustment module that adjusts the prescription based on the review results to obtain the target exercise prescription for the next execution cycle. This effectively solves the problems of single-dimensional exercise prescription assessment, insufficient personalization, inaccurate intensity matching, and lack of quantitative decision-making and dynamic adjustment.

The application relates to the technical field of obesity exercise analysis, and discloses a method for generating age-section personalized obesity prescriptions based on deep learning, which comprises the following steps: acquiring metabolic data of target objects in different age sections within 24 hours after exercise in real time, analyzing the metabolic data, obtaining metabolic phase angle maps of different age sections, and taking the target objects as obese people; through age-section analysis of 24-hour metabolism and multi-organ data after exercise, a personalized exercise prescription is generated, from a metabolism phase angle map to a rhythm step-out amount, to a metabolism resonance factor and a target direction amount, each link focuses on age differences, accurately captures metabolic fluctuation characteristics of young and middle-aged obese people, and finally, the prescription is combined with a resonance sensitive period, a metabolic elasticity interval and the like, dynamic adaptation of intensity, time length and time period is realized, the problem that a traditional prescription is disconnected with actual metabolism is effectively solved, and the accuracy and effect of obesity intervention are greatly improved.

The invention relates to the technical field of exercise health big data processing and personalized exercise prescription generation, and discloses a personalized prescription generation method based on exercise big data. The method covers the whole process of motion data acquisition, time sequence standardization, feature extraction, grading judgment and prescription output. By collecting continuous heartbeat, displacement and time consumption information, an equal-interval heartbeat sequence is reconstructed and normalized, frequency domain transformation and integral analysis are combined, and physiological and behavioral characteristics of a sporter are accurately obtained. And on the basis of low-frequency and high-frequency energy integrals, a training intensity index is constructed in combination with an average speed, and a grading threshold value is set, so that automatic personalized exercise prescription output is realized. The whole process supports historical data archiving and trend analysis. According to the method, the problem that fine evaluation is difficult due to the fact that traditional methods depend on single indexes and subjective experience is solved, and the scientificity, pertinence and intelligent level of exercise prescriptions are improved.

The invention discloses a digital health management system and method based on cardiopulmonary fitness analysis, and belongs to the technical field of artificial intelligence and digital health. The method comprises the following steps: collecting and preprocessing physiological features and motion data of a user; constructing a data set containing the actually measured maximum oxygen uptake; introducing a sparrow search algorithm to optimize hyper-parameters of the multi-layer perceptron model, and training to obtain a high-precision maximum oxygen uptake prediction model; predicting by using the model; generating a correlation analysis heat map based on the physiological features of the user and the maximum oxygen uptake predicted value; generating a personalized exercise prescription based on the prediction result and an FITT-VP rule base; the maximum oxygen uptake is re-predicted regularly, the change trend is tracked, and the exercise prescription is automatically adjusted; and finally, all information is fed back through a visual interface. The method has the technical advantages of accuracy, robustness and closed loop, breaks through the limitation of a traditional health management mode, and provides a one-stop active health management service for a user.

This invention provides an intelligent exercise intensity assessment system and method. The intelligent exercise intensity assessment system includes: an exercise testing machine, a physiological information sensor, a signal transmitter connected to the physiological information sensor, a central control unit connected to the signal transmitter, and a cloud database connected to the central control unit. The physiological information sensor detects the exerciser's physiological information before and after operating the exercise testing machine. The signal transmitter transmits the physiological information to the central control unit, which then transmits it to the cloud database. The cloud database analyzes the physiological information and obtains its corresponding wattage value. Based on the wattage value, the cloud database obtains the resistance coefficient of different fitness equipment. Therefore, the intelligent exercise intensity assessment system of this invention can track and record the exerciser's data and calculate a suitable exercise prescription based on the exerciser's physiological information.

The invention discloses an oxygen uptake cardiopulmonary endurance testing method based on load turn-back walking and a human brain structure, and relates to the technical field of exercise physiology and biomedicine detection.The method comprises the steps that progressive load turn-back walking exercise data and a high-resolution brain structure image of a subject are obtained; extracting key brain region parameters such as the thickness of the anterior cinerary cortex, the grey matter density of island leaves and the signal intensity of brainstem respiratory center; normalizing the motion features and brain structure parameters and then constructing a 12-dimensional multi-modal fusion feature vector; and inputting a deep feedforward neural network model to predict the maximum oxygen uptake, and performing five-level cardiopulmonary endurance evaluation according to an age and gender correction result. According to the method, quantitative association between peripheral exercise performance and a central nervous anatomy basis can be realized, the heart and lung endurance evaluation precision of old people and individuals with abnormal neurological functions is remarkably improved, and rapid screening and personalized exercise prescription making are supported.

The invention belongs to the field of health screening instruments, and particularly relates to an exercise prescription health screening system based on pulse rest. The system comprises an acquisition module, a processing module and a regulation and control module. The acquisition module comprises a hanging ring, and the hanging ring is made of a silica gel material; a pulse sensor is arranged in the hanging ring, and the pulse sensor is a piezoelectric sensor; a plurality of airflow sensors are fixedly arranged on the right side of the pulse sensor in the hanging ring, and the airflow sensors are MEMS microphones; pressure sensors are evenly distributed on the surface, making contact with the neck, of the hanging ring. A gyroscope for collecting three-axis acceleration is arranged in the hanging ring, and the pulse sensor is used for collecting pulse data of the neck of a user. According to the scheme, the collection module, the processing module and the regulation module cooperate, the limitation of the prior art is broken through, and the problem that exercise prescription health screening is inaccurate due to the fact that physiological signals are easily disturbed by behaviors of a user when collected at the neck part is solved.

1. The name of the design product: a graphical user interface for prescribing exercise for pregnant women for electronic devices. 2. The use of the design product: for an electronic device. 3. The design features of the design product: the content of the graphical user interface. 4. The picture or photo that best shows the design features: front view. 5. The use of the graphical user interface: the front view is the main interface for prescribing exercise for pregnant women, clicking the "doctor's order" in the menu bar on the left side of the front view enters the interface change state diagram 1, clicking the "add doctor's order" in the lower left corner of the interface change state diagram 1 enters the interface change state diagram 2, clicking the triangle symbol in the box in the upper left corner of the interface change state diagram 2 enters the interface change state diagram 3, selecting the patient "Zhang Li" in the interface change state diagram 3 enters the interface change state diagram 4, clicking the plus sign in the upper right corner of the "exercise prescription" in the interface change state diagram 4 enters the interface change state diagram 5, checking the "dynamic electrocardiogram" in the lower right corner of the interface change state diagram 5 enters the interface change state diagram 6, checking the "oximeter" in the lower right corner of the interface change state diagram 6 enters the interface change state diagram 7, clicking "lying power car" in the interface change state diagram 7 enters the interface change state diagram 8, clicking the point on the coordinate axis on the left side of the interface change state diagram 8 enters the interface change state diagram 9, clicking "confirm" below the interface change state diagram 9 enters the interface change state diagram 10, clicking "save" below the interface change state diagram 10 enters the interface change state diagram 11, and clicking "OK" in the interface change state diagram 11 enters the interface change state diagram 12.

The invention discloses a multi-modal heart rate index-based exercise state monitoring and exercise prescription adjusting method, which comprises the following steps of: preprocessing multi-modal heart rate index data of a user, and calculating a data quality score based on a signal-to-noise ratio and an exercise artifact degree of the processed heart rate index data; extracting a heart rate mean value, a heart rate variability index and a heart rate recovery index from the processed heart rate index data, inputting the heart rate mean value, the heart rate variability index and the heart rate recovery index into an individualized adaptive model, and determining a physiological load index and risk classification; calculating a recovery prediction window according to the heart rate recovery index and the historical recovery data; and generating an exercise prescription adjustment instruction based on the data quality score, the physiological load index, the risk classification and the recovery prediction window, and dynamically adjusting the exercise intensity. The problems that the traditional technology is difficult to adapt to individual differences and dynamic changes, is easily interfered by motion artifacts, lacks multi-modal fusion and is rough in feedback mechanism are solved, and the motion state monitoring accuracy and the refinement level of motion prescription adjustment are improved.

The present application relates to the technical field of treadmills, and particularly relates to an intelligent treadmill based on heart rate and a training method, which comprises the following steps: S1, acquiring instantaneous heart rate data of a runner at the moment when a preset cardiopulmonary endurance test prescription is completed, and calculating maximum oxygen uptake by combining the instantaneous heart rate data and basic information of the runner; S2, obtaining an oxygen uptake percentage by comparing the maximum oxygen uptake with an oxygen uptake percentage table, and calculating a target heart rate interval by combining the oxygen uptake percentage, gender and age; S3, executing a movement prescription based on the target heart rate interval of step S2 and acquiring an actual heart rate during the movement, and adjusting the movement intensity to maintain the actual heart rate within the target heart rate interval when the actual heart rate deviates from the target heart rate interval. The present application can avoid excessive movement or insufficient movement intensity, obtain the best movement prescription suitable for the runner, and thus help to improve the user experience of the runner when using the treadmill.

The invention discloses a postpartum rehabilitation management method and system fusing weakness assessment and pain prediction, and relates to the field of postpartum management, and the method comprises the steps: classifying a puerpera into a preset rehabilitation classification matrix according to weakness degree classification and pain risk classification, and generating a corresponding rehabilitation classification code; according to the rehabilitation classification code, a personalized initial rehabilitation scheme is called and combined from a preset modular intervention scheme library, and the initial rehabilitation scheme at least comprises one or more of a targeted exercise prescription, a nutrition prescription, a pain pre-rehabilitation intervention measure and a psychological social support plan. According to the invention, through pain risk prediction based on multi-dimensional postpartum weakness quantitative evaluation and multi-factor fusion, postpartum rehabilitation classification precision is realized, and intervention pertinence is improved. A modular intervention scheme is called based on the rehabilitation classification code, a personalized rehabilitation scheme matched with individual differences is generated, and the rehabilitation requirements of lying-in women with different weakness degrees and pain risks are met.

This application belongs to the field of information processing and artificial intelligence technology, and discloses a method, device, system, medium, and equipment for generating exercise prescriptions based on clinical data. The method includes: acquiring clinical data of test subjects; extracting joint physiological features from the clinical data based on a multi-source heterogeneous data fusion model; inputting the extracted joint physiological features into a dynamic randomization engine, and grouping the joint physiological features based on the dynamic randomization engine; constructing and training a health status prediction model; inputting the grouped joint physiological features into the trained health status prediction model; outputting the health status level of the test subject and the physiological status evolution trajectory under different exercise interventions; and generating a personalized exercise prescription. This application can achieve accurate prediction of individual health status and personalized generation of intelligent exercise prescriptions, effectively improving the scientific, targeted, and practical nature of health management for test subjects.

The invention provides an exercise prescription recommendation system and method for health data management. The system comprises a search space construction module used for obtaining exercise prescription index data, performing exhaustion combination on the exercise prescription index data, and constructing a search space based on the exercise prescription index data after exhaustion combination; the fitness function acquisition module is used for acquiring the real-time physical index data from the intelligent terminal and designing a fitness function of a particle swarm algorithm according to the real-time physical index data; and the exercise prescription recommendation module is used for searching an optimal solution in the search space by using a particle swarm algorithm based on the fitness function, and recommending an exercise prescription corresponding to the searched optimal solution. According to the method, the search space is constructed through exhaustion combination, potential effective exercise prescriptions cannot be missed when the particle swarm optimization is used for searching in the search space, and the exercise prescription found based on the search space and the fitness function is the optimal exercise prescription obtained according to real-time physical indexes and exercise prescription index data.

The invention provides a VR-based exercise prescription rehabilitation guidance system and method, and relates to the technical field of medical rehabilitation, and the system comprises a patient terminal and a doctor terminal. The patient terminal comprises a personal information acquisition module, a rehabilitation process monitoring module, a first control module and a multi-stage VR virtual rehabilitation training module; the doctor terminal comprises an exercise prescription generation module, a second control module and an exercise scheme database module; according to the invention, accurate data intelligent creation of the exercise prescription is realized, the complex operation process of a doctor is simplified, the remote supervision efficiency and quality are effectively improved, and the utilization rate of medical resources is improved.

1. The name of the design product: body medical fusion center graphical user interface for electronic device. 2. The use of the design product: the design product is used to display information and human-computer interaction. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Other views are omitted. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: the user's body measurement device report is integrated to realize the platform to open complete exercise prescription and exercise energy consumption estimation according to the customer's multi-dimensional test index results. 8. The human-computer interaction mode of the graphical user interface: design 1 front view interface is a login interface, clicking "dietary intake suggestion" on design 1 front view enters design 1 interface change state diagram; design 2 front view interface is a login interface, clicking "body shape" on design 2 front view enters design 2 interface change state diagram; design 3 front view interface is a login interface, clicking "body function" on design 3 front view enters design 3 interface change state diagram; design 4 front view interface is a login interface, clicking "body quality" on design 4 front view enters design 4 interface change state diagram; design 5 front view interface is a login interface, clicking "exercise risk" on design 5 front view enters design 5 interface change state diagram; design 6 front view interface is a login interface, clicking "spiritual pressure and psychology" on design 6 front view enters design 6 interface change state diagram. 9. Other circumstances that need to be explained: in each view, the content of the blank filled frame can be replaced; the character represented by "X" can be replaced, and the number of "X" does not constitute a limitation on the number of replaced characters.

This invention belongs to the field of medical rehabilitation training and intelligent monitoring and control technology, specifically relating to a closed-loop regulation method, system, device, and storage medium for maintenance dialysis pulmonary hypertension exercise intervention. The method collects dialysis recovery data, pulmonary circulation tolerance data, exercise tolerance data, and historical training response data to construct dialysis recovery safety boundaries, pulmonary circulation tolerance boundaries, and exercise prescription boundaries, which are then fused to form the allowable domain for the current training session. During training, a comprehensive deviation index is calculated based on a rolling time window, and graded regression regulation is implemented. After training, the boundaries for the next training cycle are updated based on training completion, recovery achievement, and abnormal event penalty values. This scheme can improve the safety, completion rate, and individual adaptability of exercise intervention.

The invention discloses a full-time dual-module diabetes life intervention system and method. The system comprises a data acquisition module; a data management module; the algorithm module is used for analyzing and processing the collected data by applying a user portrait engine, a trend analysis engine and an intervention management engine; and the application module comprises a heavy intervention module and a light intervention module, and further comprises a module switching management unit which dynamically realizes switching and continuous management between the heavy intervention module and the light intervention module based on an evaluation report or trend chart analysis according to a preset rule or a manual instruction. In the re-intervention module, CGM data, point blood glucose data, user portraits and manual guidance are deeply integrated, and rapid and highly-targeted diet structure reconstruction, safe exercise prescription making and accurate monitoring point setting are achieved. In the light intervention module, a trend chart is formed based on user autonomous monitoring data, intelligent evaluation and early warning are achieved, and re-intervention is triggered or guidance is maintained according to needs.

A purpose is to provide a health management system that can support the health of each patient safely and continuously by collaborating with exercise and nutrition specialists. In a health management system, a service providing server, a doctor server, and a client terminal share information data via a network. The client terminal is provided with an identification information registration means, a medical interview information registration means, and an information transmission means. The service providing server is provided with a guidance instruction issuance request means for transmitting an issuance request for guidance instruction data regarding exercise prescription and nutrition prescription by a doctor to the doctor server. The doctor server is provided with a guidance instruction automatic creation means, a guidance instruction manual correction means, and a guidance instruction issuance means based on the information data obtained from the guidance instruction issuance request means.

The invention discloses a knee joint postoperative exercise prescription generation system, belongs to the field of medical information health recovery, solves the problem that a personalized exercise prescription of a patient cannot be generated, and comprises a surgical data acquisition module for acquiring first surgical data of a knee joint surgery of the patient through an associated medical data system; the exercise prescription generation module is used for generating a personalized exercise prescription corresponding to the patient according to the first operation data; the exercise data acquisition module is used for acquiring exercise data when the patient executes the personalized exercise prescription through exercise data acquisition equipment worn by the patient, and performing analysis according to the exercise data to obtain physical sign data corresponding to the patient; and the exercise prescription updating module is used for updating the personalized exercise prescription according to the physical sign data. The individual condition of the patient is reflected through the first operation data, the personalized exercise prescription corresponding to the patient is generated, experience of doctors is not relied on any more, and the doctors can be prevented from neglecting some indexes due to subjective deviation.

The invention relates to the technical field of medical health data analysis, and discloses a motion and health index correlation analysis method for hyperlipidemia patients. The method comprises the steps of processing real-time health monitoring data of a patient, extracting a key index trend to construct a personalized health ground state vector, and realizing dynamic quantification of an individual health state. The core is to set up a plurality of motion intervention strategies, perform rehearsal in a simulation environment, and generate a health state evolution graph by mapping a rehearsal result to a health ground state vector. And the system analyzes key nodes of the atlas to determine the optimal intervention opportunity, and formulates a staged exercise prescription comprising specific monitoring points and an adjustment threshold value accordingly. The method has the advantages that individual differences are accurately quantified through vectorization modeling, intervention paths of different motion strategies are predicted through simulated rehearsal, and therefore the personalized level and the prospective decision-making ability of hyperlipidemia patient motion management are improved.

This application discloses a method, apparatus, device, and storage medium for pushing cardiac rehabilitation prescriptions to patients with stable angina pectoris. The method includes: acquiring original patient medical data from at least one external subsystem via an asynchronous parallel interface; determining snapshot information of the patient's status under various predefined cardiac rehabilitation rules based on the original patient medical data; correcting at least one of the exercise prescription parameters, medication prescription parameters, nutritional prescription parameters, psychological prescription parameters, and smoking cessation prescription parameters in the corresponding rehabilitation prescription based on the snapshot information of the patient's status, thereby determining rehabilitation prescription information; predicting the correction scheme and resource scheduling scheme for rehabilitation activities against preset long-term goals in the corresponding event nodes based on the original patient data and rehabilitation prescription information, thereby determining correction prescription information and resource scheduling prescription information; and pushing the rehabilitation prescription information, correction prescription information, and resource scheduling prescription information to multiple terminals for visual display.

The invention relates to the technical field of ankle sprain risk assessment and exercise rehabilitation, and discloses an ankle joint health management system based on exercise perception and an AI exercise prescription, and the system comprises a motion capture module which is used for collecting original exercise perception data when a user executes an ankle joint assessment motion; the analysis and evaluation module is used for performing joint point recognition and sequence extraction on the original motion perception data to obtain target joint motion data, and generating a risk level evaluation result of ankle joint sprain based on the target joint motion data and ankle joint related physiological information of the user; and the intelligent prescription module is used for calling a prescription generation model subjected to ankle joint rehabilitation knowledge training according to a risk level evaluation result, and outputting a personalized ankle joint rehabilitation exercise prescription for the user. According to the invention, the problems of strong subjectivity, non-uniform quantitative standards, feedback lagging and single rehabilitation scheme of traditional artificial evaluation are solved, and the quantitative precision and personalized guidance capability of ankle joint health management are improved.