177 results about "Functional disability" patented technology

A programmatically generated AI avatar includes a customizable personality module, acting as the embodied interface for a powerful AI “mind” that delivers personalized coaching to improve user health, well-being, and longevity. The system uses machine learning, large language models, and biometric modeling to synthesize real-time, multi-modal health data—including sleep, nutrition, glucose, mood, and activity—and generate forward-prescribed KHAs. Unlike human coaches, it continuously adapts based on context and behavior, targeting the root cause: metabolic dysfunction—namely by restoring healthy, sustainable body composition through the preservation or building of lean muscle mass and reduction of excess fat. KHAs can also be shared with friends or programmatically generated AI avatars, allowing for coordinated action, emotional support, and accountability through social connection—further reinforcing positive behavior and adherence. The system's reinforcement learning engine incorporates both individual response data and anonymized population-level insights to optimize recommendations over time, learning which interventions are most effective for users with similar physiological and behavioral profiles. First validated with Olympic athletes—resulting in measurable improvements and medal-winning outcomes—this system offers a scalable, emotionally intelligent coaching engine that exceeds human capability, designed for the ultimate purpose of supporting sustainable health, resilience, and human thriving.

A programmatically generated AI avatar includes a customizable personality module, acting as the embodied interface for a powerful AI “mind” that delivers personalized coaching to improve user health, well-being, and longevity. The system uses machine learning, large language models, and biometric modeling to synthesize real-time, multi-modal health data—including sleep, nutrition, glucose, mood, and activity—and generate forward-prescribed KHAs. Unlike human coaches, it continuously adapts based on context and behavior, targeting the root cause: metabolic dysfunction—namely by restoring healthy, sustainable body composition through the preservation or building of lean muscle mass and reduction of excess fat. KHAs can also be shared with friends or programmatically generated AI avatars, allowing for coordinated action, emotional support, and accountability through social connection—further reinforcing positive behavior and adherence. The system's reinforcement learning engine incorporates both individual response data and anonymized population-level insights to optimize recommendations over time, learning which interventions are most effective for users with similar physiological and behavioral profiles. First validated with Olympic athletes—resulting in measurable improvements and medal-winning outcomes—this system offers a scalable, emotionally intelligent coaching engine that exceeds human capability, designed for the ultimate purpose of supporting sustainable health, resilience, and human thriving.

A programmatically generated AI avatar includes a customizable personality module, acting as the embodied interface for a powerful AI “mind” that delivers personalized coaching to improve user health, well-being, and longevity. The system uses machine learning, large language models, and biometric modeling to synthesize real-time, multi-modal health data—including sleep, nutrition, glucose, mood, and activity—and generate forward-prescribed KHAs. Unlike human coaches, it continuously adapts based on context and behavior, targeting the root cause: metabolic dysfunction—namely by restoring healthy, sustainable body composition through the preservation or building of lean muscle mass and reduction of excess fat. KHAs can also be shared with friends or programmatically generated AI avatars, allowing for coordinated action, emotional support, and accountability through social connection—further reinforcing positive behavior and adherence. The system's reinforcement learning engine incorporates both individual response data and anonymized population-level insights to optimize recommendations over time, learning which interventions are most effective for users with similar physiological and behavioral profiles. First validated with Olympic athletes—resulting in measurable improvements and medal-winning outcomes—this system offers a scalable, emotionally intelligent coaching engine that exceeds human capability, designed for the ultimate purpose of supporting sustainable health, resilience, and human thriving.

The invention discloses a multi-mode brain dysfunction auxiliary diagnosis method based on a dynamic function connection network. A two-stage collaborative learning framework from an individual brain graph to a group relation graph is constructed. Firstly, an individual multi-modal fusion brain map is constructed, node features of the individual multi-modal fusion brain map are obtained through node regularization regression analysis of an rs-fMRI time sequence, an adjacent matrix is obtained through calculation of the brain interval grey matter volume difference of a T1 image, and individual enhancement characterization is obtained through map convolutional network fusion. And then constructing a group relationship enhancement graph, taking individual representation as node features, constructing a dual-channel adjacency relationship for distinguishing homologous / heterologous connection according to age and gender, obtaining final discriminative representation through dual-channel graph attention network aggregation, and performing classification diagnosis according to the final discriminative representation. According to the method, deep fusion of multi-modal information and explicit modeling of key biological variables are realized, and an effective tool is provided for accurate and explainable auxiliary diagnosis of brain diseases.

The invention relates to the technical field of intelligent control, and discloses a power-assisted control method of a lower limb pneumatic flexible exoskeleton and a lower limb pneumatic flexible exoskeleton system.The method comprises the steps that healthy side plantar pressure data are obtained, healthy side key gait event nodes are recognized, and the power-assisted control method of the lower limb pneumatic flexible exoskeleton is obtained according to the healthy side key gait event nodes and ankle joint angle data; estimating an uninjured side continuous gait phase, and calculating an affected side target gait phase according to the uninjured side continuous gait phase; according to the target gait phase of the affected side, auxiliary torque and tension are determined; according to the auxiliary torque and the pulling force, target air pressure for supporting the airbag and shrinking the airbag is determined, an electromagnetic valve is controlled to execute deflation or inflation operation according to the target air pressure, and the internal pressure of the airbag is controlled within a target range. The invention aims to provide flexible assistance conforming to the biomechanical characteristics of the ankle joint of a human body for people with ankle joint dysfunction, improve the walking ability and improve the safety and comfort of rehabilitation training.

A programmatically generated AI avatar includes a customizable personality module, acting as the embodied interface for a powerful AI “mind” that delivers personalized coaching to improve user health, well-being, and longevity. The system uses machine learning, large language models, and biometric modeling to synthesize real-time, multi-modal health data—including sleep, nutrition, glucose, mood, and activity—and generate forward-prescribed KHAs. Unlike human coaches, it continuously adapts based on context and behavior, targeting the root cause: metabolic dysfunction—namely by restoring healthy, sustainable body composition through the preservation or building of lean muscle mass and reduction of excess fat. KHAs can also be shared with friends or programmatically generated AI avatars, allowing for coordinated action, emotional support, and accountability through social connection—further reinforcing positive behavior and adherence. The system's reinforcement learning engine incorporates both individual response data and anonymized population-level insights to optimize recommendations over time, learning which interventions are most effective for users with similar physiological and behavioral profiles. First validated with Olympic athletes—resulting in measurable improvements and medal-winning outcomes—this system offers a scalable, emotionally intelligent coaching enginethat exceeds human capability, designed for the ultimate purpose of supporting sustainable health, resilience, and human thriving.

The invention relates to the technical field of artificial intelligence and big data, and discloses a learning disorder assessment and adaptive training system and method based on multi-dimensional behaviors, and the system comprises a multi-modal assessment module, a path generation module, a nerve regulation and control module and an adaptive engine module. By fusing multi-modal data features of language behaviors, electroneurographic signals and task response behaviors and combining a cross-modal attention mechanism to dynamically construct a cognitive state recognition model, learning disorder typing accuracy is improved, multi-dimensional ability defects such as attention, memory, language understanding and execution control are quantified based on a three-dimensional cognitive map, and learning disorder typing accuracy is improved. It is ensured that the assessment result comprehensively covers the core dimension of cognitive impairment; transcranial direct current stimulation is synchronously triggered in the cognitive task starting stage, space-time precise matching of task state nerve regulation and brain region activation is achieved, stimulation target point coordinates and current intensity are dynamically adjusted according to real-time nerve feedback, and the neuroplasticity reconstruction efficiency is improved.

The invention discloses a daily life activity ability assessment method and system based on a multi-branch space-time fusion network. The method comprises the steps of collecting motion data of a to-be-evaluated object, performing segmentation, noise reduction and standardization preprocessing, and extracting time-frequency domain features and motion deviation degree, motion similarity index and bilateral symmetry index provided by the invention; obtaining a uniform Bhattacharyya index scale score; and taking the motion feature data set and the clinical score as input, performing training based on a multi-branch space-time fusion algorithm, constructing a multi-task prediction model, and realizing automatic evaluation of the ADL. According to the method, the multi-branch space-time fusion network is innovatively introduced, the relevance between tasks is fully utilized, the spatial feature extraction capability is enhanced in combination with the graph neural network, adaptive fusion of the features is realized through a cross-layer interactive attention mechanism, the model prediction precision and evaluation reliability are remarkably improved, and the method is suitable for large-scale popularization and application. And an effective technical support is provided for rehabilitation evaluation and personalized treatment of patients with dyskinesia and disability and dementia.

The invention provides a schizophrenia early recognition and risk prediction method and system based on multi-mode speech analysis, and belongs to the technical field of medical artificial intelligence. The method comprises the following steps: prospectively acquiring natural voice data of an individual in a clinical high-risk period, performing clinical follow-up visit for two years, and constructing a first Chinese schizophrenia clinical high-risk voice longitudinal data set; based on the data set, audio and text features in the voice are extracted, a layered multi-mode integrated model is constructed, semantic coherence and acoustic features are fused, and early prediction of the schizophrenia transformation risk is achieved; through feature importance analysis, key voice marks closely related to negative symptoms, thinking disorder and cognitive impairment are recognized, and non-invasive, accurate and interpretable early recognition is achieved. According to the method, the technical blank of early screening tools for schizophrenia in Chinese context is filled, and the accuracy and stability of early recognition are remarkably improved.

The invention discloses a cerebral infarction swallowing dysfunction risk prediction method based on machine learning, and belongs to the technical field of risk prediction, and the method comprises the following steps: S1, retrieving and collecting a plurality of data sets related to cerebral infarction from an MIMIC IV database; s2, original data in the data set are preprocessed, clinical information is strictly verified, and data which does not conform to research standards are removed; s3, predicting the processed data through a plurality of models, and finding out the model with the best performance; and S4, continuously training the optimal model, constructing a swallowing function risk prediction model of the optimal model, deploying the optimal model to a webpage based on a Streamline framework, predicting the swallowing disorder risk of the patient, and generating a personalized SHAP force field graph. According to the method, a plurality of machine learning models are constructed, the model with the optimal performance is selected, and the cerebral infarction dysphagia risk is accurately predicted in combination with clinical data.

A programmatically generated AI avatar includes a customizable personality module, acting as the embodied interface for a powerful AI “mind” that delivers personalized coaching to improve user health, well-being, and longevity. The system uses machine learning, large language models, and biometric modeling to synthesize real-time, multi-modal health data—including sleep, nutrition, glucose, mood, and activity—and generate forward-prescribed KHAs. Unlike human coaches, it continuously adapts based on context and behavior, targeting the root cause: metabolic dysfunction—namely by restoring healthy, sustainable body composition through the preservation or building of lean muscle mass and reduction of excess fat. KHAs can also be shared with friends or programmatically generated AI avatars, allowing for coordinated action, emotional support, and accountability through social connection—further reinforcing positive behavior and adherence. The system's reinforcement learning engine incorporates both individual response data and anonymized population-level insights to optimize recommendations over time, learning which interventions are most effective for users with similar physiological and behavioral profiles. First validated with Olympic athletes—resulting in measurable improvements and medal-winning outcomes—this system offers a scalable, emotionally intelligent coaching engine that exceeds human capability, designed for the ultimate purpose of supporting sustainable health, resilience, and human thriving.

1. Name of the product in this design: Cognitive Impairment Assessment and Training Equipment. 2. Purpose of this design: For the assessment and training of mild cognitive impairment. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

This utility model discloses a rehabilitation device for lower limb dysfunction with adjustable angle, relating to the field of rehabilitation technology. It includes a base frame and a computer operating unit. The computer operating unit is installed on the top of the base frame, which has an adjustable support unit on top and a body support unit on top of the adjustable support unit. The device utilizes four square blocks on both sides inside the foot pedal. Two of the blocks have Velcro fasteners (first type) on top, and the other two have Velcro fasteners (second type) on top. During use, the patient places their foot on the foot pedal, and the Velcro fasteners (first and second types) securely fix the foot to the pedal. This effectively prevents the foot from slipping or becoming unstable on the foot pedal due to weakened muscle strength or poor balance during rehabilitation training, thus ensuring the smooth progress and safety of rehabilitation training.

The invention relates to the technical field of intelligent monitoring of mental health, and discloses a social function prediction system for teenager patients with depression. The system comprises a multi-source data acquisition module, a psychological feature fusion module and a prediction engine module. The multi-source data acquisition module is used for acquiring social interaction records of patients, constructing behavior dynamic characteristics, performing mode recognition and generating behavior mode data. And the psychological feature fusion module performs difference comparison on the behavior data and a healthy group benchmark, screens key behavior indexes, and calculates correlation degree values of the key behavior indexes and psychological assessment parameters in real time. The prediction engine module evaluates the social function degradation type based on the correlation degree, locates vulnerable nodes in the development process, and identifies specific dysfunction points. According to the system, continuous dynamic monitoring of social function states is realized, early warning of degradation risks and accurate positioning of weak links are realized through behavior-psychological correlation analysis, and technical support is provided for targeted intervention.

The invention discloses lower limb dyskinesia adjusting equipment and a gait adjusting method, and the equipment comprises a wearing part which comprises a housing matched with a lower limb; the projection module comprises a projector arranged on the shell, and the projection angle of the projector is adjustable; the control unit comprises a control mainboard arranged in the shell and an acquisition module communicating with the control mainboard, and the acquisition module is configured to acquire gait data of the wearing piece in real time; the projector communicates with the control mainboard, and the control mainboard is configured to control and adjust the projection angle of the projector based on the gait data acquired by the acquisition module. The lower limb dyskinesia adjusting device prompts gait disorders by using vision, and the mechanism is that the lower limb dyskinesia adjusting device can provide external sensory cues for the patient and stimulate the visual system of the patient, so that neural activity of the premotor area is activated. Visual information is used for guiding gaits, and the deficiency of internal movement rhythm caused by basal ganglion dysfunction is made up.

To provide compositions and methods for treating and preventing cognitive impairment, movement disorders, chronic pain, depression, decreased appetite, and addiction.SOLUTION: Also provided are methods for the diagnosis and monitoring of cognitive impairment, movement disorders, chronic pain, depression, decreased appetite, addiction, and other conditions such as convulsion or seizure. These compositions comprise fatty acid compounds and salts thereof which may be administered either alone, in combination with other medicaments, or as part of various treatment regimens. The provided compositions are effective for modulating markers, including, but not limited to, behavior associated with cognitive impairment, movement disorders, chronic pain, depression, decreased appetite, opiate addiction, and other related conditions. Methods for administering the compositions are also provided.SELECTED DRAWING: Figure 1

The present invention relates to a donepezil and tadalafil combination therapy for the prevention, treatment or amelioration of Alzheimer's disease or cognitive dysfunction. The combined administration of donepezil and tadalafil according to the present invention has an improvement effect on Alzheimer's disease or cognitive impairment superior to that of the individual administration of donepezil, and thus can be effectively used as a therapeutic or complexing agent or the like for Alzheimer's disease or cognitive impairment.

The system according to the embodiment aims to appropriately grasp the toilet timing of people with dementia or higher brain dysfunction, thereby reducing the burden on caregivers. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, and a calling unit. The collection unit collects data on the subject using a motion sensor, a heart rate sensor, and a body temperature sensor. The analysis unit understands the subject's condition based on the data collected by the collection unit and predicts when the subject will need to go to the toilet. The calling unit uses a caregiver avatar to call out to the subject and guide them to the toilet based on the analysis results obtained by the analysis unit.

The invention provides an augmented reality postoperative cognitive impairment risk prediction method and system, and relates to the technical field of wisdom medical treatment, and the prediction method comprises the steps: obtaining medical monitoring data and an AR interaction behavior type corresponding to a feasibility label, and inputting the AR interaction behavior type into a pre-trained XGboost model when it is determined that the cognitive function is allowed to be evaluated according to the feasibility label, determining a target AR scene in the multiple types of AR test scenes; acquiring test data of the patient in the target AR scene, wherein the test data comprises equipment position information of the image acquisition equipment, a test picture tested by the patient and AR behavior interaction data; picture features of a test picture are recognized through an image recognition module, equipment position information is mapped through a linear transformation layer and activated through a rectification linear unit, a view angle weight vector matched with picture feature channel dimensions is generated, and the view angle weight vector and the picture features are fused to obtain calibrated picture features.

The invention provides a traditional Chinese medicine preparation for improving or treating cognitive impairment, and relates to the technical field of traditional Chinese medicine pharmacy, and the traditional Chinese medicine preparation is prepared from morinda officinalis, eclipta, semen boitae, fructus alpiniae oxyphyllae, bighead atractylodes rhizome, valerian, turmeric, rhizoma acori graminei, leech, rhizoma anemarrhenae, dendrobium officinale, endothelium corneum gigeriae galli, hematoxylon and honey-fried licorice root. The traditional Chinese medicine preparation shows remarkable neuroprotection and cognition improvement effects on the cell level and the animal level, in the cell level, the preparation can effectively resist Abeta1-42 induced cell damage, and the protection effect is achieved through multiple ways of improving the cell activity, enhancing the oxidation resistance, inhibiting neuroinflammation and the like; in animal experiments, the preparation can comprehensively improve cognitive impairment of APP / PS1 model mice, including relieving behavioral abnormality, improving spatial learning and memory ability, enhancing new object recognition ability, and effectively reducing deposition of A beta in hippocampus on a molecular level. The invention provides a new thought for improving or treating cognitive impairment.

The invention belongs to the technical field of biological medicines, and particularly relates to a composition for improving a cognitive function as well as a preparation method, a product and application of the composition. The composition is prepared by taking soybean meal, whey protein peptide powder and bovine bone collagen peptide powder in a mass ratio of 1: 3: 2 as peptide source raw materials, matching the peptide source raw materials with AMY001, lactobacillus plantarum LP-90 and clostridium butyricum (3: 1: 1) compound strains, and carrying out enzyme production self-hydrolysis by bacillus amyloliquefaciens, peptide-bacterium anaerobic synergistic fermentation and sodium alginate-HPMC-CPP composite carrier embedding. According to the present invention, the hippocampus Abeta1-42 protein can be cleared, the BDNF content can be increased, the IL-6 expression inhibition multi-mechanism synergistic effect can be achieved, the memory improvement rate and the Abeta1-42 clearance rate are high, and the cognitive impairment can be significantly repaired. The composition is high in stability and bioavailability, controllable in preparation process and suitable for development of food and health care products for improving the cognitive function and medicines for preventing or assisting in improving diseases related to cognitive impairment.

The invention discloses a lower limb rehabilitation auxiliary robot, which relates to the technical field of rehabilitation medical instruments and comprises a waist structure, a crotch structure, a leg structure, a knee joint structure, an ankle structure and a foot structure. The leg structure is provided with an upper plate, a lower plate and a leg limiting structure, the upper plate and the lower plate are arranged up and down, an inserting groove is formed in the lower end of the upper plate, the upper end of the lower plate is inserted into the inserting groove in a sliding fit mode, a clamping groove penetrating into the inserting groove is further formed in the upper plate, and the leg limiting structure is installed at the clamping groove and used for limiting relative sliding of the upper plate and the lower plate during locking. The leg structures and the waist structure have the functions of flexibly adjusting and locking the length and the width respectively, and SEA series elastic actuators in the knee joint structures provide an elastic receding interval within a certain range for a patient on the included angle parameters of the thigh structures and the shank structures. Full-parameter adaptation, safe elastic driving and efficient rehabilitation training of the body type of the patient can be achieved, and the device is suitable for full-process rehabilitation treatment of different dyskinesia patients.

The invention relates to the technical field of data processing, and discloses a vascular cognitive impairment assessment method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining diffusion tensor imaging data of a target object; calculating a target diffusion tensor parameter based on the diffusion tensor imaging data, and generating a target diffusion tensor parameter diagram; inputting the target diffusion tensor parameter map into a pre-constructed deep learning model to obtain a target significance weight map of the target object; based on the target saliency weight map and a pre-established mutual information atlas set, determining a structural similarity score between the target saliency weight map and each mutual information atlas in the mutual information atlas set; and based on the structural similarity score, determining a cognitive impairment risk level represented by the target neuropsychological scale. According to the method, the dysfunction of the patient in a plurality of cognitive fields can be accurately identified, and personalized cognitive disorder risk level evaluation is provided for each patient.

The application belongs to the technical field of traditional Chinese medicine preparation, and particularly relates to an acupoint sticking medicine for preventing and treating long-term postoperative cognitive impairment of elderly patients and a use method thereof. The traditional Chinese medicine composition of the acupoint sticking medicine comprises Huangrenshen, Baishao, Danggui, Guijianyu, Shichangpu, Yuanzhi, Tianzhuhuang, Longchi, Fushen, Mosha, Huoxiang and Pelian. Under the guidance of the traditional Chinese medicine meridian theory, the physiological characteristics of the elderly patients are combined with the long-term postoperative rehabilitation demand, so that the effective components of traditional Chinese medicine are absorbed through the skin and jointly play a superimposed treatment role. The acupoint sticking medicine has a definite effect on preventing and treating long-term postoperative cognitive impairment of elderly patients, can significantly improve the long-term postoperative cognitive function score of the elderly patients, improve the long-term postoperative life quality and sleep quality, and is beneficial to the long-term postoperative rehabilitation of the elderly patients.

The invention provides application of hippophae rhamnoides fruit extract in preparation of products for preventing and treating cognitive dysfunction and / or emotional disorder and improving memory, and belongs to the technical field of biological medicine. The invention provides application of a sea-buckthorn extract or a product containing the sea-buckthorn extract in preparation of a product for preventing and treating cognitive dysfunction and / or mood disorder and improving memory. The sea-buckthorn extract comprises sea-buckthorn fruit oil, sea-buckthorn seed oil and / or sea-buckthorn fruit pulp. The hippophae rhamnoides extract is prepared from natural food hippophae rhamnoides rich in nutrient substances, has remarkable prevention and treatment effects on cognitive dysfunction and / or emotional disorder, has the effect of improving memory, can replace traditional medicine treatment, and has the advantages of being small in side effect, economical, practical, suitable for being taken for a long time and good in compliance.

This invention relates to the field of natural active ingredient research technology, specifically to the application of walnut peptides in the preparation of cognitive function improvers. The cognitive function improver is a core functional short peptide derived from walnuts, characterized by high bioactivity, non-toxicity, and favorable pharmacokinetic properties. Its amino acid sequence is AFVHWY. This short peptide is easily synthesized artificially and possesses characteristics such as easy oral administration, easy absorption, strong metabolic stability, and strong blood-brain barrier penetration, providing a novel solution for the prevention and improvement of cognitive impairment.

This invention belongs to the technical field of rehabilitation robots, specifically relating to a continuous phase control method for a lower limb rehabilitation exoskeleton that adapts to user gait. It employs a multi-task learning model, simultaneously outputting user identity probability and movement pattern probability to generate a probability map representing the similarity between the current gait and a certain movement pattern of a sample user in a sample database. A gait phase variable parameter prediction model is used to predict gait phase variable parameters, employing angular velocity data from the initial stage of the current gait cycle and the matched movement pattern to predict the gait phase variable parameters for the current cycle. Finally, a pre-constructed relational constraint model corresponding to the matched sample user and their movement pattern is used to obtain the desired joint angles from the real-time gait phase, and the exoskeleton is tracked and controlled via a PD controller. This invention can adaptively adjust the exoskeleton's motion assistance mode according to the user's gait characteristics, and is suitable for rehabilitation training of patients with lower limb motor dysfunction.

The invention discloses a method for evaluating cognitive impairment caused by micro-awakening increase, and relates to the technical field of influence of micro-awakening on cognitive function. The evaluation method comprises the following steps: inducing c-fos protein expression increase of para-brachial nucleus LPB and K-F subregions by micro-awakening, and evaluating cognitive impairment caused by micro-awakening increase according to the increase amount of the c-fos protein expression of the para-brachial nucleus LPB and K-F subregions. The invention relates to a method for evaluating cognitive impairment caused by increase of micro-awakening, and provides a novel marker for occurrence of micro-awakening, namely c-fos protein of para-arm nucleus LPB and K-F subregion. And the cognitive impairment caused by micro-awakening increase is expected to be evaluated by the increment of c-fos protein expression of para-arm nucleus LPB and K-F subregions.

The invention relates to the technical field of rehabilitation medical treatment and human-computer interaction, and discloses a rehabilitation method for senile osteoporosis with cognitive impairment based on augmented reality. The method comprises the steps that movement and physiological data of a patient are collected, a synchronous calibration signal is obtained through a fusion algorithm and Kalman filtering, and a virtual and real environment deviation value is determined in combination with the rehabilitation progress and pain feedback; optimizing response parameters and real-time force feedback parameters of the virtual scene through an adaptive adjustment mechanism, and extracting dynamic demand characteristics of the patient; fusing the dynamic demand features, audiovisual, tactile and interaction delay data through a convolutional neural network to obtain a virtual-real interaction feedback sequence; and generating virtual scene update data and an auxiliary device supporting force simulation value based on the sequence, and synthesizing a rehabilitation training output signal. According to individual requirements of patients, accurate virtual environments and interactive feedback are provided, dynamic accurate matching of virtual and real environments and real-time adaptation of multi-modal feedback in rehabilitation training are achieved, and the immersion feeling and rehabilitation effect of training are improved.