181 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 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 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.

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.

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.

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 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.

The invention discloses a cognition training adjustment method, device and system based on physiology and performance. The method comprises the steps that performance data and physiological data of a user when the user participates in a target cognition game are obtained; inputting the expression data and the physiological data into a game adaptation analysis model to obtain an analysis result; if the analysis result is that the game is not matched, the target cognitive game is updated, and the step of obtaining the performance data and the physiological data when the user participates in the target cognitive game is executed again according to the updated target cognitive game; and if the analysis result is game adaptation, generating a cognitive training report according to the performance data, the physiological data and the analysis result. When the user participates in the target cognitive game, the performance data and the physiological data are obtained, whether the target cognitive game needs to be updated or not is determined based on the analysis result obtained by the performance data and the physiological data, the best challenge can be continuously provided, and the cognitive training effect is improved.

1. Name of the design product: cognitive training record board (visual feedback type). 2. Use of the design product: the design product is used for the record board of children's cognitive training. 3. Design points of the design product: in shape. 4. Picture or photo best indicating the design points: perspective view 1.

The application discloses a kind of cognitive promotion method and system based on multi-modal data.The cognitive promotion method includes: obtaining the first multi-modal data before treatment of patient;Amyloid load grouping is carried out to patient based on the amyloid load in the brain of patient, to obtain the initial cognitive training scheme corresponding;Cognitive training is carried out based on initial cognitive training scheme during the treatment of patient, and the second multi-modal data during treatment is collected;Based on multi-modal data before and after treatment of patient, in combination with brain network group atlas, obtain the multi-modal change data of patient;The multi-modal change data of patient is input into preset model, to output the cognitive promotion scheme that cognitive index of patient is most improved, to push to patient and carry out cognitive training.The method will be integrated by A beta-PET data, functional nuclear magnetic resonance imaging data and event-related potential data, real-time evaluation of the neuroplasticity change of patient, to dynamically generate personalized cognitive promotion scheme.

The utility model discloses a rehabilitation training device. The rehabilitation training device comprises a base, a stand column and a plurality of sets of rotating discs. The lower end of the stand column is connected to the base, the rotating discs sequentially sleeve the stand column from bottom to top and rotate around the stand column, and object mounting positions are arranged on the peripheral sides of the rotating discs. The rotating disc comprises an adapter and a holding ring, the lower end of the adapter is provided with a sleeve rotationally connected with the upper end of the stand column in a sleeving mode, and the upper end of the adapter is provided with a connecting shaft rotationally connected and matched with the sleeve in a sleeving mode. A plurality of supports are arranged on the inner side of the holding ring in the circumferential direction, limiting grooves are formed in the ends, close to the center of the holding ring, of the supports, and L-shaped protruding blocks matched with the limiting grooves in a clamped mode are arranged on the outer side of the adapter seat in the circumferential direction. The number of the rotary tables is three, the sizes of the three rotary tables are sequentially decreased from bottom to top, the upper portion of the rotary table located on the uppermost side is connected with a decorating part, and the decorating part is an LED lamp in a five-pointed star shape. The rehabilitation training device not only can be used for basic training of upper limbs, but also can be used for cognitive training, and meets all-around rehabilitation requirements of old people.

The invention relates to the technical field of cognitive training, in particular to a cognitive ability training method and system based on virtual reality. The method comprises the steps that a training mode selected by a user is obtained, a corresponding virtual scene is loaded according to the training mode, and the training mode comprises a grabbing training mode, a balance training mode and a racing training mode; acquiring training data when a user performs training in the virtual scene; determining an error rate, response time and continuous success times of the user based on the training data, and matching an adjustment rule according to the error rate, the response time and the continuous success times; and adjusting and outputting the corresponding training difficulty according to the adjustment rule, so that the user performs training under the adjusted training difficulty. The cognitive ability training effect can be improved.

The invention discloses a brain machine training system and method based on electroencephalogram attention assessment, and the system comprises an electroencephalogram data collection module which is used for collecting the electroencephalogram data and behavior data of a target user during the training period in real time, meanwhile, electroencephalogram data of the attention concentration state and the relaxation state of the target user within the preset duration are collected to serve as individual baseline data; the electroencephalogram data real-time processing module is used for analyzing the electroencephalogram data, and based on the analyzed electroencephalogram data and the individual baseline data, a standardized electroencephalogram attention score and neural processing efficiency are obtained through calculation; the data analysis and result visualization module is used for generating a behavior characteristic analysis report and an electroencephalogram attention analysis report of the target user; and the AI-based attention evaluation and suggestion module is used for generating an attention evaluation report according to a predefined report specification. And the practicability and the intelligent level of the brain-computer interface in cognitive training are improved.

The application discloses a kind of fusion training method and system for multiple cognitive abilities.The fusion training method includes: obtaining the cognitive evaluation result of user for attention, inhibition and memory;Based on the cognitive evaluation result, obtain the first training parameter related to attention and inhibition;Based on the first training parameter, obtain the second training parameter related to memory;Based on the first training parameter and the second training parameter, configure the cognitive training task of corresponding difficulty level and training duration for user;Push the cognitive training task to user for cognitive training, for simultaneously training the attention, inhibition and memory of user;Obtain the cognitive training data of user, and feedback the current cognitive training result to user.The fusion training method can integrate multidimensional cognitive ability training into one, break the common single cognitive ability training form, and help to improve and transfer the comprehensive ability of user.