209 results about "Cognitive training" patented technology

The invention discloses a cognitive impairment assessment system and method based on general artificial intelligence, and the method comprises the following steps: S1, collecting multi-modal data through a wearable device, a mobile application and an online tool; s2, carrying out preprocessing on the multi-modal data; s3, comprehensively analyzing the preprocessed data, evaluating cognitive competence, and identifying a cognitive impaired field; s4, a rehabilitation training plan is generated through a neural evolution algorithm, and the training content, sequence, difficulty and type are dynamically adjusted; s5, providing cognitive training and adjusting tasks in real time through virtual reality and augmented reality technologies; s6, predicting cognitive load and psychological state, and dynamically adjusting the intervention plan; and S7, protecting data privacy by using a block chain technology, monitoring a training effect, and generating a progress report. According to the method, the intervention plan and the privacy protection technology are dynamically adjusted through multi-modal data analysis based on general artificial intelligence, and a personalized and real-time cognitive impairment assessment and intervention scheme is provided.

The invention discloses a wireless high-density electroencephalogram and myoelectricity hybrid synchronous acquisition and monitoring system, and belongs to the field of human-computer interaction. The wireless high-density electroencephalogram and myoelectricity mixed synchronous collecting and monitoring system is composed of three parts, namely a high-density electroencephalogram and surface myoelectricity signal collecting system, a base station system and an upper computer system. The high-density electroencephalogram and surface electromyogram signal acquisition system is responsible for acquisition and primary processing of signals, and the base station system performs data interaction with the high-density electroencephalogram and surface electromyogram signal acquisition system in a wireless transmission mode and transmits the processed signals to the upper computer system for further analysis and display. According to the invention, a wireless and distributed architecture and a high-channel-number data acquisition scheme are integrated, the problems of efficient acquisition and synchronous processing of electroencephalogram and myoelectricity mixed signals are emphatically solved, and the application range in the fields of brain-computer interfaces, virtual reality, neural rehabilitation, cognitive training and the like is widened.

The invention relates to the technical field of child cognitive training, and discloses an ADHD child cognitive training system. The system comprises a multi-modal sensing module, an attention evaluation module, a dynamic task generation module, a behavior feedback module and a self-adaptive adjustment module. The multi-modal perception module collects multi-dimensional behavior data, the attention evaluation module extracts attention fluctuation features, the dynamic task generation module generates a cognitive training task sequence, the behavior feedback module performs emotion state classification processing to generate feedback signals, and the self-adaptive adjustment module generates personalized training difficulty steps. According to the system and the method, through comprehensive data acquisition, precise attention assessment, dynamic task generation, real-time emotion feedback and difficulty adaptive adjustment, personalized and precise cognitive training of ADHD children is realized, the training effect is effectively improved, and the problems of lack of personalization, insufficient state monitoring, unscientific difficulty adjustment and the like of an existing training method are solved.

The invention discloses a mild cognitive impairment brain rehabilitation training device and system in the technical field of cognitive nerve rehabilitation, and the device comprises a multi-modal data fusion module, a personalized training task generation module, a multi-sensory stimulation presentation module and a real-time adaptive regulation and control module. And the personalized training task generation module is used for dynamically generating a personalized narrative training task fusing the user interest theme and the cognitive training target by utilizing a reinforcement learning algorithm based on the user cognitive weak domain evaluation result and the user personal interest and life narrative content obtained through natural language processing. Clinical data of a patient and real-time electroencephalogram and behavior data are fused, a narrative training task deeply fused with life experience and interest of the patient is dynamically generated, the difficulty of the training task is automatically adjusted according to real-time physiological indexes, meanwhile, seamless connection with a medical system is achieved through digital biomarkers, and the training efficiency is improved. And the precision and compliance of rehabilitation training are obviously improved.

The invention relates to the technical field of test question generation, in particular to an intelligent test question generation method and system based on learning behavior analysis. The method comprises the following steps: acquiring interactive behavior data and score data of learners in a user online learning platform in real time; inputting the interactive behavior data and the score data into a pre-trained knowledge state analysis model to generate a user knowledge state matrix; based on the knowledge state matrix and in combination with a preset teaching target library, identifying a target knowledge point set which needs to be strengthened currently and a corresponding cognitive training type; according to the target knowledge point set needing to be strengthened and the corresponding cognitive training type, a test question element combination algorithm is called, question stems, interference items and question solving path prompts are dynamically assembled, and personalized test questions are generated. The method has the advantages that full-closed-loop intelligent teaching from behavior analysis of the user to targeted training is achieved, and personalized test questions adaptive to individual cognitive vulnerabilities are dynamically generated.

The embodiment of the invention provides a cognitive training method and system based on an eye movement tracking control technology, and relates to the field of eye movement tracking, and the method comprises the steps: obtaining test data, corresponding to a plurality of eye movement test tasks, of a tested person; wherein the various eye movement test tasks comprise eye movement test tasks corresponding to each cognitive ability to be evaluated, aiming at each cognitive ability, according to eye movement test data, related to the cognitive ability, of the testee, index values of various ability evaluation indexes, corresponding to the cognitive ability, of the testee are determined; and determining the ability score corresponding to the cognitive ability, and determining a matched target cognitive training game according to the ability scores corresponding to various cognitive abilities of the testee. According to the method, the cognitive competence is evaluated based on the eye movement data of the testee, and the matched game is selected according to the evaluation result to train the cognitive competence, so that the interestingness of cognitive training is enhanced, and the training effect of cognitive training is remarkably improved.

The invention discloses a cognitive improvement method and system based on multi-modal data. The cognition improvement method comprises the following steps: acquiring first multi-modal data of a patient before treatment; carrying out amyloid protein load grouping on the patients on the basis of amyloid protein loads in the brains of the patients so as to obtain corresponding initial cognitive training schemes; performing cognitive training based on the initial cognitive training scheme during the treatment period of the patient, and collecting second multi-modal data during the treatment period; based on the multi-modal data before and after the treatment of the patient, acquiring multi-modal change data of the patient in combination with the brain network group atlas; and inputting the multi-modal change data of the patient into a preset model to output a cognition improvement scheme for improving the cognition index of the patient to the greatest extent, and pushing the cognition improvement scheme to the patient for cognition training. According to the method, by integrating A beta-PET data, functional nuclear magnetic resonance imaging data and event-related potential data, the neuroplasticity change of a patient is evaluated in real time, so that a personalized cognition improvement scheme is dynamically generated.

The invention provides a construction method of a brain rehabilitation cognitive training effect prediction model. The method improves the accuracy and individuation level of cognitive training effect prediction. Firstly, state data of a subject is obtained and preprocessed; thirdly, obtaining unified features by adopting an extraction layer, carrying out combined modeling of a spatial topological relation and dynamic time sequence evolution by adopting a fusion layer based on the unified features and generating spatio-temporal features, and adjusting model parameters by adopting an adaptation layer according to baseline features of a subject to ensure personalized prediction; and finally, in a model operation process, triggering online updating through concept drift detection, and generating a confidence interval and an interpretability score of a prediction result based on Bayesian reasoning. According to the method, through state data processing, personalized adaptation, dynamic adaptation and Bayesian reasoning, the precision, stability and interpretability of brain rehabilitation cognitive training effect prediction are remarkably improved, and powerful support is provided for personalized treatment and clinical decision making.

The invention discloses a cognitive enhancement training method and system based on brain signal pattern recognition. The method comprises the following steps: acquiring offline brain signal data of a user, preprocessing the offline brain signal data, and inputting the preprocessed offline brain signal data into a pre-selected decoding model for model training so as to construct a decoding model for the user; based on multiple preset cognitive states, constructing task adjustment logic to perform bidirectional adjustment on the cognitive training task for each cognitive state; in the cognitive training process of the user, on-line brain signal data of the user is decoded based on the decoding model so as to obtain the current cognitive state of the user, and the next cognitive training test is adjusted in real time according to task adjustment logic so as to perform EEG neural regulation and fNIRS neural regulation on the user and further perform cognitive enhancement on the user. According to the method, the current cognitive state of a user is recognized in real time by pre-constructing a decoding model, and bidirectional adjustment is performed on a task according to preset task adjustment logic, so that cognitive enhancement is performed on the user.

The invention discloses a cognitive training system and method, electronic equipment and a storage medium, and the system comprises an electroencephalogram signal collection module which uses a high-sensitivity non-invasive electroencephalogram sensor to collect an electroencephalogram signal of a user in real time; the signal processing module is used for preprocessing the collected electroencephalogram signals by using a deep learning algorithm, removing noise and extracting useful features; the training strategy optimization module is used for analyzing the electroencephalogram signals of the user based on a game theory model and formulating a personalized cognitive training strategy; and the feedback control module is used for feeding back the optimized training strategy to the user, and improving the cognitive participation degree and the training effect of the user through multi-sensory stimulation such as visual sense and auditory sense. According to the cognitive training system and method, the electronic equipment and the storage medium, the game theory is applied to the BCI system, and the cognitive training effect can be enhanced through strategy optimization.

The invention discloses a cognitive training emotion interaction method and system based on a large model. The method comprises the following steps: acquiring a cognitive evaluation result of a patient, and pushing a corresponding cognitive training scheme to the patient; before cognitive training, acquiring the current emotional psychological state of the user to judge whether the cognitive training requirement is met or not, and if not, performing emotion regulation until the cognitive training requirement is met; during cognitive training, acquiring multi-modal data of the patient and inputting the multi-modal data into a preset large model to perform emotion calculation, so as to identify the current emotional psychological state of the patient again; and based on the current emotional psychological state of the patient, carrying out interaction feedback of a corresponding mode on the patient so as to carry out personalized emotional interaction with the patient. According to the method, the emotional state of the user is recognized in advance before cognitive training, emotion feedback of different modes can be performed according to the current emotional psychological state of the patient in the cognitive training, so that the training compliance of the patient is improved, and the cognitive training effect is improved.

The invention relates to the field of virtual reality, in particular to an adaptive virtual reality cognitive training method and system. The method comprises the steps of obtaining a user individual information set and a real-time multi-modal physiological data stream, performing real environment three-dimensional reconstruction and relative and friend face modeling based on the user individual information set, and generating an individual virtual training scene; based on the real-time multi-modal physiological data flow and the individualized virtual training scene, nerve-behavior feature extraction and digital twinning dynamic modeling are carried out, and a user cognitive state evaluation information set is generated; based on the user cognitive state evaluation information set, training task parameter real-time optimization and virtual scene element dynamic adjustment are carried out through an adaptive strategy, and a cognitive enhancement intervention instruction set is generated; and based on the cognitive enhancement intervention instruction set, performing neural regulation intervention and training data closed-loop feedback, and generating and outputting an individualized cognitive training report. According to the method and the device, accurate self-adaptive intervention is realized in a virtual reality cognitive training process.

The invention discloses a two-dimensional cognitive training system and method integrating attention and an execution function, relates to the field of medical rehabilitation, and is used for ensuring comprehensiveness, scientificity, pertinence and long-term effectiveness of cognitive function training. According to the method, a concentrated attention training task, a continuous attention training task, a selective attention training task, an alternate attention training task and a decentralized attention training task are sequentially carried out; the training task of each dimension comprises multiple levels of sub-training tasks with gradually increased difficulty; in the training tasks of each dimension, at least a suppression control task and a memory task are fused; the training tasks of each dimension respectively collect training data to evaluate training indexes. According to the method, the cognitive function training task is more scientific, comprehensive and effective.

The invention discloses a brain small vascular disease lower limb dysfunction self-adaptive electrical stimulation auxiliary rehabilitation system in the technical field of medical instruments, and the system comprises a data collection module which is used for obtaining the multi-modal data of a patient in real time; the decision regulation and control module is used for generating dynamically optimized electrical stimulation parameters and rehabilitation task instructions based on a deep reinforcement learning algorithm and patient individualized pathological characteristics according to the multi-modal data; the electrical stimulation execution module is used for synchronously regulating and stimulating nerve targets according to the optimized electrical stimulation parameters; and the interactive virtual reality module is used for combining immersive gait training and cognitive training. By detecting the multi-modal physiological data of the patient, combining the deep reinforcement learning model to dynamically optimize the electrical stimulation parameters, and coupling VR exercise training and cognitive training, the three-in-one collaborative rehabilitation mode of electrical stimulation-physical treatment-cognitive intervention is realized, the rehabilitation training efficiency is improved, the relapse risk of the patient is reduced, and the rehabilitation training experience of the patient is enhanced.

The invention relates to a meta-cognition real-time training method based on electroencephalogram data and a machine learning model. The meta-cognition real-time training method comprises the steps that current brain cognition information data of trainees are collected and preprocessed; transferring the obtained original electroencephalogram data to a preset frequency domain wave band through Fourier transform to obtain an energy value, and calculating a time sequence energy value to obtain brain cognition information data; marking the brain cognition information data, establishing a tag set for the brain cognition information data according to categories, and establishing a brain cognition feature set according to preset selected features; the method comprises the following steps: acquiring brain cognition information data in a training class stage in real time, performing timely voice reminding on trainees by a trainer according to training conditions, and marking the training data to obtain a training set for model training; performing verification and model correction on the training model obtained in the training class stage through a verification class until the training requirements are met; and in the teaching class stage, the machine learning model outputs real-time guidance information to guide trainees to carry out meta-cognitive training.

The invention discloses an fNIRS adaptive feedback emotion cognition cooperative training device and method, and relates to the technical field of emotion disorder cognition training. The device comprises a data acquisition module used for acquiring an original dual-wavelength light intensity signal from a brain; the data processing module is used for performing multi-stage preprocessing on the original dual-wavelength light intensity signal; the neural feedback module is used for calculating a multi-dimensional evaluation index according to the hemoglobin concentration data and adjusting a difficulty level and a feedback threshold value of a training task by using a dynamic threshold value control algorithm; the training module is used for training participants based on the emotion stimulation task and the cognitive training task; and the evaluation module is used for performing training evaluation according to the comparison result of the comprehensive performance score and the feedback threshold. Brain function equipment is closely combined with cognitive training and emotion stimulation tasks, dynamic evaluation and real-time feedback are added for traditional tasks, and through the brain network analysis technology, accurate evaluation of the user training effect is achieved.

The invention relates to the technical field of medical health and artificial intelligence, in particular to a system and method for improving the cognitive function of old people based on emotion voice perception training. Comprises: a voice stimulation presentation module for controlling playing of target voice stimulation and masking voice; the training program control module is used for controlling and adjusting the voice stimulation presentation module; the reaction collection module collects the reaction of the patient and outputs the reaction to the feedback and enhancement module; the feedback and strengthening module is used for providing training feedback according to the input of the reaction acquisition module; the data processing and evaluation module is used for processing the input of the feedback and enhancement module; and the user interface and visualization module is used for providing operation and result display for patients and researchers. According to the method, emotional voice perception training and voice recognition training in a noise environment are combined for the first time, a comprehensive cognitive intervention mode based on acoustic signal processing and emotional rhythm recognition is established, and the limitation that a traditional cognitive training visual channel is poor in dependence and migration effect is broken through.

The invention discloses a virtual supermarket construction and cognitive training method for old people based on a VR technology, and relates to the technical field of virtual scene psychological assessment, and the method comprises the steps: presetting continuous multi-task execution setting in a virtual supermarket scene; then, synchronously acquiring behavior data, voice data, expression / emotion information and physiological data of the elderly during completion of each task in a process of completing preset continuous multi-task execution setting by the elderly; mapping the acquired multi-modal data to a psychological characteristic index; scoring and summarizing are carried out according to the task stages based on the psychological characteristic indexes, and psychological characteristic index ability scores and psychological ability scores of the task stages are formed; comprehensively evaluating the psychological state of the elderly according to the formed psychological characteristic index capability score and the psychological capability score of each task stage, and judging the overall psychological risk type of the elderly after completing the preset continuous multi-task execution setting of the virtual supermarket to obtain the current psychological risk condition of the elderly.

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 provides a group multi-scene cognitive training method and device based on MR and a multi-modal brain-computer interface, and relates to the technical field of cognitive training. The method comprises the following steps: performing cognitive competence evaluation based on a cognitive competence evaluation scale to obtain a cognitive competence evaluation result; based on a cognitive ability database, a preset group number of people and a candidate group database, performing cognitive ability matching according to a cognitive ability evaluation result; based on a cognitive task library, performing task matching according to the group cognitive ability vector; under the MR scene, based on the cooperative training group, the competition training group and the matched cognition task, group cognition training is carried out, signal collection is carried out, and multi-modal physiological signals are obtained; and performing cognitive competence evaluation by using the cognitive competence evaluation model to obtain a trained cognitive competence evaluation result. The group cognition training method based on the BCI multiple scenes is high in training efficiency, large in generalization degree and high in applicability.

Provided in the present invention are a cognitive decision-making evaluation training system and method in instantaneous super-heavy and weightlessness states. The system comprises a multi-degree-of-freedom super-heavy and weightlessness simulation platform, a VR head-mounted display having an eye movement tracking function, a multi-mode controller, a gesture recognition sensor, a flight seat and frame structure, a super-heavy and weightlessness simulation platform module, and a cognitive decision-making evaluation training module. In super-heavy and weightlessness states of the system, the spatial perception capability, the attention, and the learning and memory capabilities of a person are affected to varying degrees. Therefore, by performing cognitive training in such a simulation scenario and by means of the acquisition and comprehensive analysis of real physiological parameters in a task stage, a more real and efficient training solution can be provided to people, thus helping people to better implement reinforcement training of cognitive behaviors.

A system, method, and computer platform product for an adaptive cognitive training platform. In accordance with various aspects of the present disclosure, an adaptive cognitive training platform is configured to process user activity data from one or more instances of a computerized cognitive training program to determine a baseline cognitive assessment for one or more cognitive abilities / skills of a user. The cognitive assessment model may be configured to further process the user activity data to predict a relative value or measure of efficacy for one or more computerized stimuli or interactions within the computerized cognitive training program. The adaptive cognitive training platform may be configured to configure, modify and / or present one or more graphical user interface elements for one or more subsequent instances of the computerized cognitive training program according to the predicted value or measure of efficacy of one or more cognitive training tasks.

The invention provides a jigsaw and music combined interactive training system and method, relates to the field of education and entertainment, and optimizes the training experience of a user by dynamically adjusting the difficulty and shape of a jigsaw task and music accompaniment and combining multi-dimensional physiological and psychological information of brain wave data, emotional state and cognitive load. The system comprises a brain wave acquisition module, an emotion recognition module, a puzzle generation module, a music generation module and a sensory feedback module. The jigsaw puzzle task and the music content are adaptively adjusted according to the real-time state of the user, so that the task is not too simple and not too difficult, and emotion fluctuation or cognitive fatigue of the user is effectively avoided. Through the combination of music and tasks, the emotion state of the user can be adjusted, the concentration and cognitive competence can be improved, the learning motivation of the user can be enhanced, the method can be widely applied to the fields of mental health, cognitive training and entertainment, the cognitive competence, emotion adjustment and task completion of the user are improved, and therefore the comprehensive psychological and cognitive improvement effect is achieved.

The invention discloses an optimization method for senile cognitive impairment intervention. The optimization method comprises the following steps: S1, a multi-modal evaluation stage: acquiring neurophysiology, behavior and language data of a patient through a multi-source sensing module; s2, personalized prescription generation: calculating a comprehensive cognitive impairment index (CCI), and generating a personalized cognitive training scheme; s3, the intervention module executes the steps that a virtual training scene is generated in the AR environment; and S4, effect verification and iteration: generating a neuroplasticity evaluation report after training, and quantifying the parahippocampal gyrus-prefrontal cortex function connection enhancement degree. Neurophysiology, behaviors and language data of a patient are synchronously collected by adopting a multi-source sensing module, and a personalized cognitive training scheme is generated based on a comprehensive cognitive disorder index. Meanwhile, a virtual scene is constructed to execute an intervention module, and the parahippocampal gyrus-prefrontal lobe function connection enhancement degree is quantitatively analyzed after intervention, so that an evaluation-decision-intervention-verification closed-loop system is constructed, and the intervention effect of the senile cognitive impairment is remarkably improved.

The invention discloses a cognitive training device and method for optimizing cognitive impairment of old people, and relates to the technical field of rehabilitation training.The body height adapting mechanism comprises a fixing plate and a fixing seat which are fixedly connected to a base, and a connecting seat and a connecting block which are fixedly connected to the bottom of a training box, and the front face of the fixing plate is fixedly connected with a motor; the front face of the fixing plate is rotationally connected with an adapter shaft, the surface of an output shaft of the motor is fixedly connected with a small gear, the surface of the adapter shaft is fixedly connected with a large gear and a transmission arm, the transmission arm is rotationally connected with a connecting arm, and the inner wall of the fixing base is rotationally connected with a first limiting strip. According to the training box, the height position of the training box can be adjusted according to the height and training requirements of old people through the arrangement of the height adapting mechanism, it is ensured that the old people keep the optimal height state in the training process, the old people do not need to stoop down or raise the head deliberately, and the discomfort of the old people is reduced.

Systems and methods for providing cognitive therapy to a patient are provided, which include a head mounted device wearable by the patient, a display configured to present one or more cognitive game scenes to the patient, one or more controllers for interacting with the cognitive training scenes, a cognitive engagement detection device configured to detect cognitive engagement of the patient and generate data indicative of the cognitive engagement of the patient, and a processor. The processor determines a level of cognitive engagement of the patient based at least in part on the data generated by the cognitive engagement detection device, determines performance of the patient interacting with the one or more cognitive training scenes based on information received from the one or more controllers, and determines cognitive improvement of the patient based on the cognitive engagement, cognitive medication taken, and the performance of the patient.

The invention relates to the technical field of data processing, and discloses a dynamic cognitive training method and system based on a large language model and multi-dimensional evaluation, which combines multi-dimensional input data such as standardized cognitive evaluation, demographic statistics, historical behaviors and real-time performance to construct a user cognitive portrait. The dynamic prompting engineering module and the content generation process of the large language model are integrated, so that the training content, the prompting mode, the interaction style and the like can deeply meet the individual differences and specific requirements of users, the fine-grained and deep personalized training process is provided, and through the dynamic prompting engineering module, the user experience is improved. According to the method, the fine cognitive state change of the user in each interaction and task can be captured in real time, the change is immediately converted into accurate control over large language model behaviors, training content and difficulty which are accurately matched with the current level of the user are generated, highly-dynamic and real-time adaptive cognitive training can be achieved, and the user experience is improved. The problems that a traditional cognitive training system is lagged in adjustment and insufficient in roughness are solved.

The invention relates to the technical field of artificial intelligence education, and discloses a personalized English grammar learning system based on artificial intelligence. Comprising a multi-modal data acquisition module, a deep user portrait construction module, a dynamic association knowledge graph module, a multi-modal intelligent diagnosis module, a meta-cognitive guide type learning path planning module, a personalized content generation module, an emotional real-time feedback module, a meta-cognitive training module, a social cooperation module and a closed-loop optimization module. The multi-modal data acquisition module is used for acquiring multi-dimensional and multi-modal data of a learner, and covering related data such as basic information. According to the personalized English grammar learning system and method based on artificial intelligence, by setting a multi-modal data acquisition module and a deep user portrait construction module, basic information, cognitive features, meta-cognitive levels and emotional preferences of learners are captured in all directions; and constructing a dynamically updated deep user portrait by means of a multi-dimensional data fusion algorithm and a time sequence analysis algorithm.

The invention discloses a brain-computer interaction system for cognitive-motion dual-task collaborative rehabilitation training. The brain-computer interaction system comprises a cognitive training interaction unit, an electroencephalogram signal acquisition unit, an electroencephalogram signal decoding unit and a motion training unit, according to the system provided by the invention, cognition-movement collaborative rehabilitation training is realized, compared with a single rehabilitation training mode, the rehabilitation efficiency is improved, a brain-computer interface technology is introduced, the attention and the movement intention of a subject are identified in real time, active movement rehabilitation is realized, the active participation degree of the subject in the rehabilitation training process is enhanced, a closed-loop system is established, and the rehabilitation training efficiency is improved. Mutual promotion of cognitive-motor function rehabilitation is enhanced, and induction of nerve recombination and reconstruction is enhanced.

The invention belongs to the technical field of cognitive power, and relates to a cognitive competence assessment method, training method, system, equipment and medium, the system comprises a data acquisition unit used for acquiring electrophysiological signal data and behavior data of a user; the evaluation unit is connected with the data acquisition unit and is used for executing a cognitive evaluation scale task and synchronously acquiring the electrophysiological signal data, the behavior data and the scale score of the user; the fusion analysis unit is connected with the data acquisition unit and the evaluation unit and is used for integrating the cognitive evaluation scale data, the electrophysiological signals and the behavior data and inputting the data into a multi-modal fusion evaluation model so as to output a cognitive load index and an emotional stability score; and the training unit is connected with the fusion analysis unit and is used for adjusting the VR training difficulty according to the cognitive load index and the emotion stability score. According to the scheme of the invention, the accuracy of cognitive ability evaluation and the applicability of cognitive training are effectively improved.