Cognitive function rehabilitation training system and method based on virtual reality

Abstract

The invention discloses a cognitive function rehabilitation training system and method based on virtual reality, and the system comprises a cognitive function test unit which is used for carrying out the cognitive impairment test evaluation of a patient based on a virtual reality module, and generating a cognitive function evaluation report of the patient; the cognitive training unit is used for generating a personalized cognitive training scheme based on the cognitive function evaluation report, carrying out targeted cognitive training in a virtual reality environment, and collecting physiological data and training performance data of the patient in the cognitive training process; the feedback unit is used for comprehensively analyzing the physiological data and the training performance data and generating a staged feedback report; and the rehabilitation effect tracking unit is used for analyzing rehabilitation effects of the patient in different time periods based on the periodic feedback report and optimizing a subsequent cognitive training scheme based on an analysis result. And the interestingness and interactivity of rehabilitation training are improved.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality (VR) technology, and in particular to a cognitive function rehabilitation training system and method based on virtual reality. Background Art

[0002] With the acceleration of the aging process of the global population, health problems related to cognitive dysfunction have gradually become prominent, especially common neurodegenerative diseases and brain damage such as Alzheimer's disease (AD) and sequelae of stroke, which have become the main factors affecting the quality of life of patients. These cognitive dysfunctions not only seriously affect the daily living ability of patients, but also increase the care burden on families and society. Therefore, how to effectively improve the cognitive level of patients with cognitive dysfunction and help them restore their ability to live independently is an important research direction in the current field of medicine and rehabilitation.

[0003] At present, rehabilitation training for cognitive dysfunction mainly relies on traditional offline training methods. These methods usually include individual guidance from specialists or rehabilitation therapists, and the main content includes training in memory, attention, spatial cognition, problem-solving ability, etc. These methods mainly stimulate patients' cognitive functions through paper-and-pencil tests, tabletop games, puzzles, and other basic activities. In addition, some clinical institutions also use computer-assisted cognitive training software to improve patients' cognitive abilities through simple human-computer interaction. However, these traditional methods and systems have significant limitations.

[0004] Traditional rehabilitation training methods are often standardized training models, which are difficult to customize according to individual differences of patients (such as the degree of cognitive impairment, specific damaged areas, etc.). Due to the different rehabilitation needs and progress speeds of each patient, the lack of personalized rehabilitation programs will lead to unsatisfactory training results and may even make patients feel bored and frustrated, further reducing their enthusiasm for participation; existing rehabilitation training methods, especially those based on paper and pen or simple computer software, are often monotonous and lack the motivation to attract patients to participate in the long term. This boring training content will cause patients to feel tired and bored easily, thereby reducing the continuity and effectiveness of their training. The rehabilitation of cognitive function is essentially a long-term process, so it is crucial to maintain the patient's sense of participation and enthusiasm; traditional rehabilitation training mostly relies on manual observation and recording, and it is difficult to evaluate the patient's progress in a timely and accurate manner. Doctors and therapists usually need to judge the rehabilitation effect based on the patient's subjective feedback and limited test results. There is a lack of systematic quantitative data support, which not only leads to delays in the adjustment of rehabilitation programs, but also easily ignores some subtle but important changes.

[0005] Therefore, there is an urgent need for a cognitive function rehabilitation training system and method based on virtual reality. Summary of the invention

[0006] The present invention provides a cognitive function rehabilitation training system and method based on virtual reality to solve the above problems existing in the prior art.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] The cognitive function rehabilitation training system based on virtual reality includes:

[0009] A cognitive function testing unit, which is used to test and evaluate the patient's cognitive dysfunction based on a virtual reality module and generate a cognitive function evaluation report for the patient;

[0010] The cognitive training unit is used to generate personalized cognitive training programs based on cognitive function assessment reports and carry out targeted cognitive training in a virtual reality environment. During the cognitive training process, the patient's physiological data and training performance data are collected;

[0011] Feedback unit, used to comprehensively analyze physiological data and training performance data and generate periodic feedback reports;

[0012] The rehabilitation effect tracking unit is used to analyze the patient's rehabilitation effects in different time periods based on periodic feedback reports, and optimize subsequent cognitive training programs based on the analysis results.

[0013] Among them, the patient's cognitive function assessment report is generated, including:

[0014] The VR module presents the patient with initial cognitive function test tasks based on the patient's personalized adjustment dimensions, which include cognitive development history, cultural background, lifestyle habits, and current health status;

[0015] Determine the patient's completion results of the current cognitive test task and the scores and emotional tone of the completion results, including correct completion results and incorrect completion results;

[0016] Based on the patient's completion results and the personalized adjustment dimensions, multiple new cognitive test tasks are determined and output, and scores and emotional intonations regarding the completion results of each new cognitive test task are determined, until the consecutive number of new incorrect completion results reaches a preset number threshold, or the current cognitive test task is determined to be the last test task;

[0017] Generate and output the patient's cognitive function assessment report based on each completed result, the score and emotional tone of the completed result. The cognitive function data includes multiple cognitive indicators of memory, attention, and executive function;

[0018] The patient's cognitive dysfunction level is set based on preset conditions, which include the patient's total score in cognitive test tasks, reaction time, accuracy of completion results, emotional tone, and one or more of the personalized adjustment dimensions.

[0019] Among them, generate personalized cognitive training programs, including:

[0020] Generate a personalized cognitive training program based on the cognitive function assessment report. The personalized cognitive training program sets different training tasks and difficulties according to the user's cognitive function level;

[0021] Introducing a variety of different VR scenarios, including social interactions in daily life, travel, and family activities, allowing users to interact and compete with other patients;

[0022] Conduct targeted cognitive training in a virtual reality environment, using VR headsets, handheld controllers, and motion capture equipment to provide an immersive experience for users;

[0023] During cognitive training, the patient's physiological data and training performance data are collected in real time. The physiological data include heart rate and brain waves, and the training performance data include reaction time and task completion.

[0024] Adjust the difficulty and context of cognitive training tasks based on physiological data and training performance data;

[0025] If the training effect reaches the preset standard, a prompt message is output to remind the staff that the current training plan is effective;

[0026] If the training effect does not meet the preset standard, the personalized cognitive training program will be updated and subsequent cognitive training will be carried out in a new virtual reality scenario.

[0027] Among them, the generation of periodic feedback reports includes:

[0028] Based on the physiological data of the subjects, a physiological state change curve is established to analyze the fluctuation of physiological state before, during and after training;

[0029] Based on the training performance data of the subjects, generate training performance trend charts to evaluate the dynamic performance of reaction time, task completion and error rate as the training tasks change;

[0030] Combine the physiological state change curve and training performance trend chart to generate a phased feedback report.

[0031] Among them, the subsequent cognitive training program is optimized based on the analysis results, including:

[0032] Based on the periodic feedback report, generate the rehabilitation effect evaluation of the tested subjects in different training cycles;

[0033] Provide improvement suggestions for different stages of physiological status and training performance in the periodic feedback report, including recommended training content, optimized training situation and suggested physiological status regulation methods;

[0034] Generate optimization strategies for subsequent training tasks based on periodic feedback reports, including task goal adjustment and situation optimization;

[0035] Generate optimization strategies for subsequent training tasks, including generating more difficult training tasks based on current feedback when comprehensive evaluation indicators show excellent status, and adjusting key parameters of training tasks, including increasing task operation complexity, shortening reaction time limits, and raising task completion requirements;

[0036] When the comprehensive evaluation indicators show an abnormal state, new adaptive training tasks are generated based on the current feedback, the difficulty of the training tasks is reduced, and the task situations are adjusted, including increasing the task rest interval, extending the operation time, or reducing task interference.

[0037] Among them, based on the patient's personalized adjustment dimension, the virtual reality module presents the patient with initial cognitive function test tasks, including:

[0038] Obtain the patient's personalized adjustment dimension data, which includes the patient's cognitive development history, cultural background, living habits and current health status;

[0039] According to the personalized adjustment dimension data, the virtual reality module generates cognitive function test tasks and presents the initial cognitive function test tasks to the patient through the virtual reality display device;

[0040] Obtain patient test feedback data from initial cognitive function test tasks;

[0041] Update the patient's personalized adjustment dimensions based on test feedback data, including: adjusting the difficulty of test tasks based on cognitive development history, optimizing task content based on cultural background, adjusting task rhythm based on living habits, and adjusting task duration based on current health status;

[0042] The updated personalized adjustment dimensions are input into the virtual reality module to generate subsequent cognitive function test tasks, which are presented to the patient for the next round of cognitive training;

[0043] Based on the patient's feedback, continue to optimize the personalized adjustment dimensions until the patient's cognitive function test tasks reach the preset rehabilitation standards;

[0044] Build a data analysis model to perform cluster analysis on the cognitive function test results of patients in different time periods, generate cognitive function change trends, and adjust subsequent cognitive training programs based on the change trends;

[0045] Ultimately, a personalized cognitive function rehabilitation report is generated for the patient, and the report is integrated with the patient's virtual reality training data to optimize the rehabilitation effect and improve cognitive function.

[0046] Among them, determine the patient's completion results of the current cognitive test task, as well as the scores and emotional tone of the completion results, including:

[0047] Obtain the patient's response behavior data and reaction time in the current cognitive test task. The reaction time is the time from the output of the current cognitive test task to the acquisition of the response behavior.

[0048] Determine the completion result and emotional tone of the current cognitive test task based on the response behavior data, the completion result includes a correct completion result and an incorrect completion result;

[0049] If the completion result is a correct completion result, determining a first score of the correct completion result based on the reaction time and the response behavior data;

[0050] If the completion result is an erroneous completion result, the second score of the erroneous completion result is determined to be 0.

[0051] Among them, different training tasks and difficulties are set, including:

[0052] Based on the cognitive function assessment report, obtain the user's cognitive function level data, which includes the user's cognitive function indicators of memory, attention, executive function and language ability;

[0053] According to the cognitive function level data, a personalized cognitive training program is generated. The personalized cognitive training program sets different training tasks and difficulties according to different cognitive function indicators, including:

[0054] When the memory index is low, set tasks that require patients to recall daily life events, and adjust the complexity of the tasks by increasing difficulty, from simple object memory to complex event recall;

[0055] When the attention index is low, the patient is required to concentrate on completing tasks in a distracting situation, and the difficulty of the task is gradually switched from single attention to multi-tasking.

[0056] When executive function is low, set training tasks that require patients to plan and perform multi-step operations, and dynamically adjust the difficulty of the task based on the accuracy and time of execution;

[0057] When language ability is low, set training tasks based on language comprehension and expression, with tasks gradually upgrading from simple word selection to complex dialogue construction;

[0058] Among them, a variety of different virtual reality scenarios are introduced, including:

[0059] Social interaction situations in daily life, allowing users to communicate with virtual characters or other patients, improving language skills and social interaction skills through conversation tasks;

[0060] In a virtual travel scenario, users need to complete relevant tasks during the trip, including sense of direction tests and object identification tasks, to improve memory and executive function;

[0061] Virtual family activity scenarios simulate daily affairs management in the family, including cooking, housework planning and time management, to enhance users' executive functions and planning abilities.

[0062] Among them, the cognitive function rehabilitation training methods based on virtual reality include:

[0063] S101: Based on the virtual reality module, the patient's cognitive dysfunction test is evaluated and a cognitive function assessment report is generated;

[0064] S102: Generate a personalized cognitive training program based on the cognitive function assessment report, and carry out targeted cognitive training in a virtual reality environment. During the cognitive training, collect the patient's physiological data and training performance data;

[0065] S103: Comprehensively analyze physiological data and training performance data and generate a phased feedback report;

[0066] S104: Based on the periodic feedback report, analyze the patient's rehabilitation effects in different time periods, and optimize the subsequent cognitive training program based on the analysis results.

[0067] Compared with the prior art, the present invention has the following advantages:

[0068] The cognitive function rehabilitation training system based on virtual reality includes: a cognitive function test unit, which is used to test and evaluate the patient's cognitive dysfunction based on the virtual reality module and generate a cognitive function assessment report for the patient; a cognitive training unit, which is used to generate a personalized cognitive training program based on the cognitive function assessment report, and carry out targeted cognitive training in a virtual reality environment, and collect the patient's physiological data and training performance data during the cognitive training process; a feedback unit, which is used to conduct a comprehensive analysis of the physiological data and training performance data and generate a phased feedback report; a rehabilitation effect tracking unit, which is used to analyze the patient's rehabilitation effect in different time periods based on the phased feedback report, and optimize the subsequent cognitive training program based on the analysis results. Virtual reality technology improves the fun and interactivity of rehabilitation training through immersive experience, thereby improving the patient's sense of participation and compliance. Patients can participate in rehabilitation training more actively in a virtual environment, which helps to improve rehabilitation efficiency.

[0069] Other features and advantages of the present invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the present invention.

[0070] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0072] Figure 1 is a structural diagram of a cognitive function rehabilitation training system based on virtual reality in an embodiment of the present invention;

[0073] Figure 2 Flow chart of a cognitive function rehabilitation training method based on virtual reality in an embodiment of the present invention. DETAILED DESCRIPTION

[0074] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0075] The embodiment of the present invention provides a cognitive function rehabilitation training system based on virtual reality, which is characterized by comprising:

[0076] A cognitive function testing unit, which is used to test and evaluate the patient's cognitive dysfunction based on a virtual reality module and generate a cognitive function evaluation report for the patient;

[0077] The cognitive training unit is used to generate personalized cognitive training programs based on cognitive function assessment reports and carry out targeted cognitive training in a virtual reality environment. During the cognitive training process, the patient's physiological data and training performance data are collected;

[0078] Feedback unit, used to comprehensively analyze physiological data and training performance data and generate periodic feedback reports;

[0079] The rehabilitation effect tracking unit is used to analyze the patient's rehabilitation effects in different time periods based on periodic feedback reports, and optimize subsequent cognitive training programs based on the analysis results.

[0080] The working principle of the above technical solution is as follows: the cognitive function test unit conducts a comprehensive test and evaluation of the patient's cognitive function through a virtual reality environment, and generates a cognitive function evaluation report for the patient. Cognitive function mainly refers to human memory, attention, executive ability, spatial perception ability, etc. VR scene design: The system designs a realistic virtual environment, such as a supermarket shopping scene, and the patient needs to complete the shopping task according to the prompts, such as remembering the list of items to be purchased, finding the corresponding items on the shelf, and completing the payment process. Collecting data: During the task, the system records the patient's behavioral data, such as the time of task completion, the number of errors (such as missing items in the shopping list or taking the wrong items), and the efficiency of path planning. Generate an evaluation report: The system analyzes the patient's cognitive ability based on the data. For example: If the patient forgets the items to be purchased many times during the shopping task, it indicates that his short-term memory is weakened. If the patient cannot find the target item or deviates from the route many times, it indicates that the spatial perception ability is reduced.

[0081] For example, a patient with mild cognitive impairment was asked to buy five items in a virtual supermarket: milk, bread, eggs, apples and biscuits. If he missed the eggs and his route planning efficiency was low, the system would record these behaviors and point out in the evaluation report that the patient's short-term memory and executive function needed to be strengthened.

[0082] Based on the evaluation report, the cognitive training unit generates a personalized cognitive training program and conducts targeted cognitive training in a virtual reality environment. Personalized training program generation: Based on the test results, the system designs specific training content for the patient's weak links. If the patient's short-term memory is poor, the system designs a memory training game, such as asking the patient to remember a set of randomly appearing object names and then recall them within a specified time. If the patient's attention or executive ability is weak, the system can arrange attention training that requires the patient to respond quickly, such as quickly pressing a button when the target object appears in a virtual environment. Physiological data and training performance collection: During the training process, the system collects the patient's physiological data, such as heart rate, brain wave activity, etc., through supporting equipment (such as heart rate monitors, eye trackers, EEG equipment, etc.). At the same time, the patient's performance in training, such as accuracy, reaction time, completion time, etc., is recorded.

[0083] For example, a patient was diagnosed with poor short-term memory, and the system generated a "find the missing object" game. The patient observed the layout of a virtual room, and then some objects in the room were removed. The patient needed to recall and point out which objects had changed. During the training process, the system recorded the patient's accuracy and reaction time in real time, and observed his concentration through heart rate monitoring.

[0084] During the training process, the feedback unit will conduct a comprehensive analysis of the patient's physiological data and training performance data, and generate a phased feedback report. Comprehensive data analysis: The system analyzes the patient's training performance (such as accuracy, reaction time, etc.) and physiological data (such as heart rate changes, brain wave fluctuations, etc.) to evaluate the patient's current state. For example, if the patient's heart rate fluctuates greatly during certain training tasks, it may indicate that the patient feels anxious or nervous during training. Phased feedback report: The report summarizes the patient's performance over a period of time, indicating which cognitive abilities have been improved and which still need further training. For example: The reaction time of the attention task is shortened from an average of 5 seconds to 3 seconds, indicating that attention has improved. The deviation in path planning in spatial perception training has not been significantly improved, suggesting that this ability needs further optimization.

[0085] For example, after 10 memory training sessions, a patient's accuracy rate increased from 50% to 80%, but at the same time, his reaction time increased. System analysis shows that the patient's memory has improved, but the efficiency of task completion needs to be improved.

[0086] The rehabilitation effect tracking unit analyzes the patient's rehabilitation effects in different time periods based on the phased feedback report and optimizes the subsequent training plan. Effect analysis: The system compares the feedback data of different periods and analyzes the patient's rehabilitation trend. For example, whether the patient's short-term memory ability gradually improves with the increase in the number of training sessions. Optimize training plans: Adjust the difficulty or content of training according to the patient's progress. If the patient performs well in the current training task, the system will increase the difficulty of training, such as increasing the number of items to remember or shortening the reaction time. If some tasks are progressing slowly, the system will adjust the training content to focus more on the patient's weak links.

[0087] For example, after two months of training, a patient's accuracy in memory tests increased from 60% to 85%, but his path planning ability was still poor (for example, he often got lost). The system reduced the frequency of memory training and increased virtual navigation training, such as asking patients to plan an optimal route to their destination in a virtual city.

[0088] Virtual reality (VR): A three-dimensional simulation environment generated by computer technology. Users can interact with the virtual world by wearing headsets and other devices. Short-term memory: refers to the ability of humans to store and recall information in a short period of time, such as remembering a phone number. Physiological data: refers to data that reflects the state of the human body, such as heart rate, brain waves (EEG), etc., which are used to assess the patient's concentration or anxiety level.

[0089] The beneficial effects of the above technical solution are as follows: the system can generate a customized training program based on the cognitive dysfunction assessment of each patient. This personalized program ensures that the training of each patient can improve their specific cognitive function problems in a targeted manner, avoiding the "one-size-fits-all" limitations of traditional rehabilitation methods; the system can adjust the training content and difficulty in real time according to the patient's physiological data and training performance. This dynamic feedback mechanism can help patients train at an appropriate difficulty level, avoid excessive fatigue or overly simple tasks, and ensure the effectiveness and sustainability of the training; the system can effectively track the patient's rehabilitation progress through long-term data collection and analysis, which can not only provide patients with an intuitive display of rehabilitation effects, but also provide doctors with important clinical basis to help them better diagnose and adjust treatment; virtual reality technology improves the fun and interactivity of rehabilitation training through immersive experience, thereby improving patients' sense of participation and compliance. Patients can participate more actively in rehabilitation training in a virtual environment, which helps to improve rehabilitation efficiency.

[0090] In another embodiment, generating a patient's cognitive function assessment report includes:

[0091] The VR module presents the patient with initial cognitive function test tasks based on the patient's personalized adjustment dimensions, which include cognitive development history, cultural background, lifestyle habits, and current health status;

[0092] Determine the patient's completion results of the current cognitive test task and the scores and emotional tone of the completion results, including correct completion results and incorrect completion results;

[0093] Based on the patient's completion results and the personalized adjustment dimensions, multiple new cognitive test tasks are determined and output, and scores and emotional intonations regarding the completion results of each new cognitive test task are determined, until the consecutive number of new incorrect completion results reaches a preset number threshold, or the current cognitive test task is determined to be the last test task;

[0094] Generate and output the patient's cognitive function assessment report based on each completed result, the score and emotional tone of the completed result. The cognitive function data includes multiple cognitive indicators of memory, attention, and executive function;

[0095] The patient's cognitive dysfunction level is set based on preset conditions, which include the patient's total score in cognitive test tasks, reaction time, accuracy of completion results, emotional tone, and one or more of the personalized adjustment dimensions.

[0096] Among them, the patient's cognitive impairment level is set based on preset conditions, including:

[0097] When the patient's total score, reaction time, accuracy of completion results, emotional tone, and one or more of the personalized adjustment dimensions in the cognitive test task meet preset conditions, cognitive test task evaluation data are obtained;

[0098] Construct a patient's cognitive function model based on cognitive test task assessment data, personalized adjustment dimensions, and preset cognitive dysfunction level standards;

[0099] Identify multiple perspectives on the assessment of cognitive dysfunction from the cognitive function model;

[0100] To obtain the assessment priorities for each cognitive impairment assessment perspective;

[0101] Go through each cognitive dysfunction assessment perspective in order from high to low assessment priority;

[0102] Each time the traversal is performed, the traversed cognitive dysfunction assessment perspective is connected to the expert conference room; each expert in the expert conference room can view the cognitive function model through the traversed cognitive dysfunction assessment perspective;

[0103] Assist experts in the expert meeting room to conduct in-depth cognitive dysfunction assessment;

[0104] Obtain and output deep cognitive dysfunction assessment results;

[0105] Multiple perspectives on the assessment of cognitive dysfunction were identified from the cognitive function model, including:

[0106] Combine cognitive test task assessment data into multiple data sets based on total scores, reaction times, accuracy, and emotional intonation in pre-set conditions;

[0107] At least one associated co-viewing perspective is created for each data set; in the cognitive function model, the co-viewing perspective displays the digital twin corresponding to each of the cognitive test tasks in the same data set;

[0108] Based on the perspective screening condition, a target common viewing perspective associated with each data set is screened out from the common viewing perspectives associated with each data set;

[0109] Using the target co-viewing perspective as a perspective for assessing cognitive dysfunction;

[0110] The data set combination conditions include:

[0111] There is a correlation between two or more cognitive test task data in the same data set, and cognitive test task data that has no correlation with any other cognitive test task data is a separate set;

[0112] Viewpoint filters include:

[0113] The target common viewpoint comes from the common viewpoint associated with each dataset;

[0114] Furthermore, when the same cognitive test task data exists in different data sets at the same time, the overlap between the target co-viewing perspectives associated with the different data sets in which the same cognitive test task data exists at the same time is less than or equal to a preset overlap threshold;

[0115] Moreover, the sum of the perspective switching costs between target co-viewing perspectives associated with different data sets is less than or equal to the preset cost and threshold.

[0116] The working principle of the above technical solution is: before the patient enters the virtual reality cognitive function test system, the system will first collect the patient's personalized adjustment dimensions, which include the patient's cognitive development history (such as whether there is a history of learning disabilities, previous cognitive function level), cultural background (such as language, religious beliefs, etc.), living habits (such as work and rest rules, eating habits, etc.) and current health status (such as whether there are other diseases that affect cognitive function). For example: a 75-year-old elderly patient, whose cultural background is traditional Chinese culture, whose living habit is to take a nap every day, and whose current health status is mild cognitive impairment, the system will adjust the difficulty and content of the initial test task based on this information, set a simple short-term memory test task, and select scenes and objects that the patient is familiar with.

[0117] The system presents the initial cognitive function test tasks to the patient based on the personalized adjustment dimension, including object memory in virtual scenes, path navigation, or language memory tasks. For example, in a virtual home kitchen scene, the system requires the patient to remember 5 objects on the table and their locations (such as tea cups, apples, books, etc.), and then asks the patient to point out the locations of these objects after the objects are covered.

[0118] After the patient completes the task, the system records the results, including correct completion results (such as correctly remembering the location of the item) and incorrect completion results (such as the wrong location of the item). At the same time, the system collects the patient's emotional tone (such as anxiety, frustration, happiness, etc.) through the voice analysis module or facial expression recognition technology. These data are used to evaluate the patient's psychological state and cognitive stress when completing the task. For example: The patient completed the correct recall of the location of 3 items, but made an error when recalling the 4th item. The system recorded his correct rate as 60%. At the same time, the voice analysis showed that the patient had obvious anxiety in his tone when he answered incorrectly for the third time.

[0119] The system dynamically generates new test tasks based on the patient's performance in the initial task (including accuracy and emotional state). If the patient performs well in the initial task, the system will increase the difficulty of the task, such as increasing the number or complexity of the memory items; if the patient performs poorly and is emotionally nervous, the system will reduce the difficulty or give encouraging tasks to relieve the patient's stress. The system will continue to adjust and progress the tasks until the patient's consecutive number of incorrect completion results reaches a preset threshold (such as 3 consecutive errors) or the current task is the last test task. For example: In the previous task, the patient performed poorly and was emotionally anxious. The system will reduce the number of items to 3 in the next step and add encouraging prompts, such as "You did a good job. Let's try 3 items next."

[0120] The system generates a detailed cognitive function assessment report based on the patient's performance data in each task, including accuracy, reaction time, emotional tone, etc. The report covers multiple cognitive indicators such as the patient's memory, attention, and executive function. For example, the final report shows that the patient has obvious impairments in short-term memory and attention, but relatively good executive function. The report also includes his emotional response (such as the degree of anxiety when answering incorrectly).

[0121] The system sets the patient's cognitive dysfunction level (such as mild, moderate or severe) based on preset conditions, such as the patient's total score, reaction time, accuracy of completion results, emotional tone, and personalized adjustment dimensions. For example, if the patient's total score in all tasks is 65%, the average reaction time is slow, and the emotion shows a certain degree of anxiety, combined with the health status of mild cognitive impairment, the system determines that the patient has moderate cognitive dysfunction and recommends further rehabilitation training.

[0122] Among them, patients need to participate in some cognitive test tasks, such as solving digital mazes, reaction time tests, memory challenges, etc. The results of these tasks will be recorded as data, which include: Total score: represents the patient's performance in the test. Reaction time: the time it takes the patient to complete a task. Correctness: the proportion of correct answers when the patient completes the task. Emotional tone: the emotional changes of the patient when taking the test, which may be captured by voice recognition technology. Personalized adjustment dimension: adjust the test difficulty, task type, etc. according to the personalized characteristics of different patients. In a memory challenge game in virtual reality, the patient needs to remember and rearrange a set of items. If the patient makes multiple mistakes in the game, the total score and accuracy will be lower, the reaction time may be longer, and the emotional tone may show anxiety or distress. These data are the data of cognitive test tasks. Based on the above collected data, a cognitive function model of the patient will be constructed. This model will reflect the patient's cognitive ability, including short-term memory, attention, reaction speed and other aspects. Suppose the patient does a reaction speed test in virtual reality training (such as quickly clicking on the target that appears). If the patient reacts slowly, the model will assess that the patient's reaction speed may have problems. Based on the cognitive function model, cognitive dysfunction can be evaluated from multiple perspectives. For example, the patient's cognitive impairment can be evaluated from different perspectives such as reaction speed, memory ability, and emotional response. In virtual reality cognitive training, patients may encounter different scenarios: such as a quick reaction game (testing reaction speed) and a memory challenge (testing memory). The differences in these scenarios represent multiple perspectives for evaluating cognitive dysfunction. Each perspective for evaluating cognitive dysfunction will have a priority, and the system will evaluate them in order from high to low based on these priorities. Assuming that the system identifies that the patient's memory problem is more serious, during virtual reality training, the system will give priority to experts to pay attention to and evaluate the patient's memory ability, and then evaluate other cognitive functions such as reaction speed. The expert conference room is a virtual expert collaboration platform. The system transmits the evaluation perspective to the experts. The experts can see the patient's cognitive function model on this platform and conduct in-depth evaluation of the patient based on these data. In virtual reality rehabilitation training, the patient's cognitive data (such as memory and reaction speed) will be transmitted to the expert conference room through the system. Experts can discuss in virtual meetings based on these data and make further diagnoses. Through the expert's evaluation, a deep cognitive dysfunction evaluation result will eventually be output. These results will provide a detailed analysis of the patient in certain cognitive areas, helping to provide a basis for subsequent rehabilitation training. Suppose an expert evaluates the patient's reaction time, memory ability, etc. in a virtual reality environment and concludes that the patient has a greater obstacle in "short-term memory." Therefore, the system can specially design memory training tasks in subsequent virtual reality training to help patients improve this aspect of cognitive function. During the entire evaluation process, multiple cognitive test tasks will form different data sets.If there is a correlation between these data (for example, reaction time and task completion accuracy are related), they will be classified as the same data set. Each data set will have an associated "co-viewing perspective" that allows experts to view and analyze the data from different perspectives. In VR training, a task may test both reaction speed and memory. The system links the data of these two tasks together to generate a co-viewing perspective, which experts can view at the same time to help them comprehensively evaluate the patient's cognitive ability. According to the preset filtering conditions, the system will select the most relevant "target co-viewing perspective" from the co-viewing perspectives generated by multiple data sets for further evaluation. The screening criteria include: the overlap between data sets (that is, the degree of repetition of the same data in different data sets). The cost of perspective switching (that is, the difficulty of switching between different perspectives). In VR training, if the data of the same cognitive task appears in different data sets at the same time, the system will ensure that the overlap of these data sets is low to avoid excessive repetition and minimize the difficulty of experts switching between different perspectives. Finally, based on all the evaluation results, experts adjust personalized VR cognitive training programs to help patients improve their cognitive abilities. For example, a series of VR tasks specifically designed to improve concentration may be designed for patients with attention deficit problems.

[0123] The beneficial effects of the above technical solution are as follows: by designing the initial task and subsequent tasks based on the personalized adjustment dimension, the system can better adapt to the individual differences of patients. This personalized design can not only improve the accuracy of the test, but also reduce the frustration that patients may experience when they are not adapted to the task, and enhance the patient's enthusiasm for participation; the system can dynamically adjust the difficulty of the task according to the patient's performance and emotional state in the test task. This mechanism can avoid the anxiety and pressure caused by the task being too difficult for the patient, while ensuring the authenticity and validity of the test results; the system combines multiple cognitive indicators (memory, attention, executive function, etc.) and emotional state data to generate a comprehensive cognitive function assessment report. This multi-dimensional assessment method can help doctors understand the patient's cognitive function status more comprehensively and accurately, and provide a scientific basis for the formulation of personalized rehabilitation plans. By setting the level of cognitive dysfunction of patients, the system can effectively prevent and intervene. For example, for patients with mild impairments, the system can design easy training programs to prevent further deterioration of cognitive function; for patients with moderate or severe impairments, the system can provide more rigorous and targeted rehabilitation training to improve the rehabilitation effect; by using virtual reality technology and personalized task design, the system can provide an immersive and interactive testing and training environment. This interesting and challenging experience can significantly improve patient participation and compliance, thereby improving the long-term effectiveness of rehabilitation training.

[0124] In another embodiment, generating a personalized cognitive training program includes:

[0125] Generate a personalized cognitive training program based on the cognitive function assessment report. The personalized cognitive training program sets different training tasks and difficulties according to the user's cognitive function level;

[0126] Introducing a variety of different VR scenarios, including social interactions in daily life, travel, and family activities, allowing users to interact and compete with other patients;

[0127] Conduct targeted cognitive training in a virtual reality environment, using VR headsets, handheld controllers, and motion capture equipment to provide an immersive experience for users;

[0128] During cognitive training, the patient's physiological data and training performance data are collected in real time. The physiological data include heart rate and brain waves, and the training performance data include reaction time and task completion.

[0129] Adjust the difficulty and context of cognitive training tasks based on physiological data and training performance data;

[0130] If the training effect reaches the preset standard, a prompt message is output to remind the staff that the current training plan is effective;

[0131] If the training effect does not meet the preset standard, the personalized cognitive training program will be updated and subsequent cognitive training will be carried out in a new virtual reality scenario.

[0132] The working principle of the above technical solution is as follows: First, the system evaluates the level of each cognitive ability area (such as memory, attention, executive function, etc.) by analyzing the user's cognitive function assessment report. According to the performance in different cognitive areas, the system will generate personalized training programs. For example, if a user performs poorly in short-term memory, the training tasks will focus more on improving short-term memory, while for users who have challenges in executive function, the system will provide relevant logical thinking and problem-solving training tasks. The system designs multiple immersive virtual reality scenarios for users, which imitate scenes in daily life, such as social interaction, shopping, family gatherings, etc. Virtual reality equipment includes VR helmets, handheld controllers, and motion capture devices, allowing users to interact with virtual characters or complete tasks in these scenarios. For example, users can simulate shopping in a virtual supermarket, select goods, check out, or participate in social activities to train social skills. In these scenarios, the system also allows users to interact and compete with other patients to increase interactivity and challenge. In virtual reality, users can conduct cognitive training through a series of operations. Handheld controllers can capture the user's hand movements, while motion capture devices record the user's body movements. The system uses these devices to monitor the user's performance in the virtual scene in real time. For example, in a social situation, the user may need to answer questions from a virtual character to conduct language expression training, or in a travel situation, the user needs to plan a route and navigate, which trains the user's spatial memory and executive function. During the training process, the system will collect the user's physiological data, such as heart rate and brain waves, in real time through sensors to evaluate the user's mental state and concentration. At the same time, the system will also record the user's training performance data, such as reaction time, task completion and error rate. These data are evaluated through a multi-dimensional mechanism to ensure comprehensive monitoring of the user's cognitive level. For example, when the user's heart rate is high, it means that the pressure is increasing. The system will reduce the difficulty of the task or help the user complete the task through guiding prompts. The system will dynamically adjust the difficulty of training based on physiological data and performance data. For example, if the user's reaction time in a task gradually shortens and the task completion rate improves, the system will automatically increase the complexity of the task, such as adding interference factors or shortening the completion time requirements. On the contrary, if the user's performance has not improved or the physiological data shows that the pressure is too high, the system will reduce the difficulty of the task or adjust the complexity of the scene to ensure that the user's training experience is at an appropriate level of challenge. When the user's training effect reaches the preset standard (such as the task completion rate continues to improve and the physiological data is stable within the healthy range), the system will output a prompt message to inform the staff that the current training program is effective, the user's performance is good, and the current training can continue. If the user's performance does not meet the standard, the system will automatically update the personalized cognitive training program, re-evaluate the user's cognitive function, and provide subsequent training in a new virtual reality scenario to gradually improve the user's cognitive level.

[0133] The beneficial effects of the above technical solution are as follows: through the personalized training program generated based on the user's cognitive assessment report, the specific cognitive function defects of each user can be accurately located, and the training difficulty can be dynamically adjusted to ensure that the training content is always suitable for the user's ability level. Compared with the traditional one-size-fits-all training method, this method is more targeted and effective; the virtual reality scenario provides a highly immersive experience environment, simulating typical scenarios in the user's daily life, such as socializing, shopping, etc., which makes the user's training process closer to reality, improves the practicality of the training and the user's participation. In addition, the diversity of virtual scenarios can prevent the training process from becoming monotonous and boring, and increase the user's enthusiasm; through the real-time collection and analysis of physiological data and performance data, The system can respond quickly and dynamically adjust the difficulty of training. This real-time feedback mechanism ensures the efficiency of the training process while preventing users from feeling frustrated or bored due to tasks that are too simple or too difficult. Users can interact or compete with other patients in virtual reality scenarios, and improve their social skills and emotional communication abilities through dialogue and cooperation with others. The competitive element can motivate users and prompt them to put more effort into training, thereby accelerating the improvement of cognitive function. When the training effect does not meet expectations, the system can automatically update the training plan and select a new virtual scenario to carry out training. This continuous improvement mechanism ensures that users are always in a challenging state during training and maintain the trajectory of improving cognitive function for a long time without stagnation.

[0134] In another embodiment, generating a periodic feedback report includes:

[0135] Based on the physiological data of the subjects, a physiological state change curve is established to analyze the fluctuation of physiological state before, during and after training;

[0136] Based on the training performance data of the subjects, generate training performance trend charts to evaluate the dynamic performance of reaction time, task completion and error rate as the training tasks change;

[0137] Combine the physiological state change curve and training performance trend chart to generate a phased feedback report.

[0138] The working principle of the above technical solution is: the physiological state change curve is dynamically modeled by collecting key physiological data (such as heart rate, skin conductance, brain waves, etc.) of the subject before, during and after training to depict the fluctuation trend of the physiological state.

[0139] Heart rate: reflects the degree of tension or physical exertion of the subject. For example, in virtual reality (VR) cognitive rehabilitation training, users complete memory training through a virtual supermarket shopping task. At the beginning of the task, the heart rate may be high, indicating tension or excitement; as proficiency increases, the heart rate gradually decreases. Skin conductance: related to the intensity of emotional response. If unexpected stimuli occur in the virtual task (such as increasing the difficulty of the task), the skin conductance value will rise for a short time. Electroencephalogram (EEG): Analyze the alpha waves (related to relaxation) and beta waves (related to concentration) in the brain waves. After becoming familiar with the task rules, the alpha waves increase, indicating that the user is more relaxed; when the difficulty increases, the proportion of beta waves increases, indicating concentration.

[0140] For example, in a virtual supermarket, the system monitored that the user's heart rate rose from 80 beats / minute to 100 beats / minute, accompanied by a rapid increase in skin conductance, indicating that the user entered a state of high stress. When the task was completed, the heart rate and skin conductance gradually returned to the baseline level (for example, the heart rate returned to 85 beats / minute), indicating that the user was relieved from the task pressure.

[0141] The training performance trend chart is drawn based on the user's specific performance at different task stages (such as reaction time, task completion, error rate, etc.) and is used to quantify the training effect. Reaction time: refers to the time from when the user receives the task instruction to when the action is executed. For example, in virtual training, the user needs to quickly click on the product image that appears on the screen, and the click delay time is the reaction time. Task completion: refers to the proportion of users completing the specified task. For example, the virtual supermarket shopping task requires the purchase of 10 specified products, and the user only selects 8, then the completion rate is 80%. Error rate: The proportion of errors made by users when performing tasks. For example, in the sorting task, the products are required to be arranged from low price to high price. The more errors, the higher the error rate.

[0142] For example, in the first stage of the virtual shopping task, the average user reaction time was 2 seconds, the task completion rate was 70%, and the error rate was 30%. After training, the user's reaction time was shortened to 1.2 seconds, the task completion rate was increased to 90%, and the error rate was reduced to 10%. The trend chart shows the dynamic progress of the user. For example, the reaction time in the first stage fluctuated greatly, indicating that the user was still adapting to the task rules; the reaction time in the subsequent stage tended to be stable, indicating that the training was effective.

[0143] Combine the physiological state change curve with the training performance trend chart to generate a comprehensive phased feedback report to help users understand their own training status and results. For example, when the physiological state curve shows that the user's heart rate and skin conductance remain high, and the error rate remains high, it means that the user may have affected the task performance due to high stress. If the physiological state data gradually stabilizes and the training performance data gradually improves (such as increased task completion and decreased error rate), it means that the user has gradually adapted to the training content and made progress.

[0144] For example, the user's phased feedback report shows: In the first phase, the user's heart rate is high, the error rate is 50%, and the task completion rate is 50%, indicating that the task is stressful for the user. In the second phase, the heart rate returns to normal, the task completion rate increases to 80%, and the reaction time is shortened to 1.5 seconds, indicating that the user gradually adapts to the task. In the final phase, the physiological state is stable, the task completion rate reaches 95%, and the error rate drops to 5%, indicating that the training goal has been basically achieved.

[0145] The beneficial effects of the above technical solution are: through the physiological state curve, the system can dynamically capture the user's physiological response process, identify whether the user is in a state of anxiety, fatigue, etc., and adjust the rhythm of the training task in a timely manner. The training performance trend chart provides users and managers with visual dynamic feedback to help discover the user's progress and weak links in training. The feedback report can clearly present the user's training status and effect, allowing users and training designers to adjust the training content more targetedly.

[0146] In another embodiment, optimizing a subsequent cognitive training program based on the analysis results includes:

[0147] Based on the periodic feedback report, generate the rehabilitation effect evaluation of the tested subjects in different training cycles;

[0148] Provide improvement suggestions for different stages of physiological status and training performance in the periodic feedback report, including recommended training content, optimized training situation and suggested physiological status regulation methods;

[0149] Generate optimization strategies for subsequent training tasks based on periodic feedback reports, including task goal adjustment and situation optimization;

[0150] Generate optimization strategies for subsequent training tasks, including generating more difficult training tasks based on current feedback when comprehensive evaluation indicators show excellent status, and adjusting key parameters of training tasks, including increasing task operation complexity, shortening reaction time limits, and raising task completion requirements;

[0151] When the comprehensive evaluation indicators show an abnormal state, new adaptive training tasks are generated based on the current feedback, the difficulty of the training tasks is reduced, and the task situations are adjusted, including increasing the task rest interval, extending the operation time, or reducing task interference.

[0152] The working principle of the above technical solution is: the system will generate periodic feedback reports based on the training performance and physiological data of the subject to evaluate the rehabilitation effect. Feedback data usually includes reaction time, task completion rate, error rate, and physiological indicators (such as heart rate variability, brain waves, etc.). For example: In a virtual supermarket shopping task, a subject needs to remember and buy specific goods. The report shows that his task completion rate has increased from 60% in the first cycle to 85% in the second cycle, and the reaction time has been shortened by 20%, indicating that his attention and memory abilities have improved.

[0153] The system combines feedback data to identify the shortcomings and strengths of the subjects at different stages, and puts forward targeted improvement suggestions, including training content, situation optimization and physiological state regulation methods. Training content: If the report shows that the subject performs poorly in the concentration task (for example, frequently missing designated items in the virtual supermarket), the system will recommend adding concentration training tasks, such as attention allocation training in a virtual traffic environment. Training situation: When the system finds that the subject is sensitive to the noise environment, which may lead to a decrease in task completion rate, it is recommended to optimize the situation, reduce the background noise in the training environment, or introduce noise interference in stages. Physiological state regulation: If the system detects a high fatigue state (such as reduced heart rate variability or reduced alpha waves in the brain wave), it will recommend that the subject perform deep breathing training or relaxation exercises, and increase rest time between training.

[0154] By analyzing the feedback report, the system can automatically adjust the task goals and situations and generate personalized optimization strategies. Task goal adjustment: If a subject performs well in the memory task (such as an error rate of less than 5%, and a significantly shortened reaction time), the system will increase the difficulty of the task goal, such as increasing the amount or complexity of the memory information. Situation optimization: For individuals at a relatively low performance stage, the system will adjust the situation to reduce the difficulty. For example, if the subject is not used to multi-tasking in virtual traffic training, distractions can be reduced (such as reducing the number of virtual pedestrians or cars) to help the subject adapt to the training.

[0155] When the comprehensive evaluation indicators show an excellent state, the system automatically generates a high-difficulty training task and adjusts key parameters to increase the challenge. Task operation complexity: If the subject can quickly complete the virtual factory assembly task, the system will increase the complexity of the task, such as requiring it to memorize multiple assembly sequences or introduce random changes. Shorten the reaction time limit: In the virtual traffic scenario, if the subject can quickly avoid the vehicle, the system will shorten the time interval between vehicles approaching and increase the challenge of the task. Increase the completion requirements: In the virtual supermarket shopping task, increase the variety of goods or require to remember the specific price and location of the goods.

[0156] When the comprehensive evaluation indicators show an abnormal state (such as severe distraction or low task completion rate), the system will generate adaptive training tasks to reduce the difficulty of training and optimize the task situation. Reduce the difficulty of training: If the subject performs poorly in the memory task (the error rate of memory information is higher than 50%), the system will reduce the amount of information memorized at one time. Adjust the task situation: Extend the operation time limit (such as extending the countdown time in the virtual task) or reduce interference elements (such as reducing dynamic changes in the virtual environment). Increase the task rest interval: For example, in virtual driving training, increase the pause time when simulating a red light to help the subject regain attention.

[0157] The beneficial effect of the above technical solution is that through real-time feedback and personalized optimization strategies, the system can help the subject to complete cognitive training more efficiently. For example, by analyzing the performance and adjusting the difficulty of the task, the training can be avoided from being too simple or too complex, so as to achieve the best training effect. The optimized training task helps to carry out rehabilitation intervention for the specific problems of the subject, such as training the cognitive flexibility of high-level subjects by increasing the complexity of the task, or helping low-level subjects gradually adapt to the task by reducing the difficulty. When the system recognizes an abnormal state, dynamically adjusting the task difficulty and context can reduce the pressure brought by training and avoid the frustration caused by task failure. For example, by extending the operation time or reducing interference, it helps to enhance self-confidence in training. The feedback report combined with physiological data can not only optimize the training content, but also help the subject to adjust its own state. For example, through methods such as relaxation training and breathing regulation, the individual's training experience and concentration can be improved. The cognitive ability, fatigue level and training needs of different subjects are different. The system realizes truly personalized rehabilitation training by dynamically adjusting the task goals, contexts and difficulties. For example, for patients with attention deficit, the concentration tasks designed by the system are more in line with their rehabilitation goals.

[0158] In another embodiment, based on the patient's personalized adjustment dimensions, the virtual reality module presents the patient with an initial cognitive function test task, including:

[0159] Obtain the patient's personalized adjustment dimension data, which includes the patient's cognitive development history, cultural background, living habits and current health status;

[0160] According to the personalized adjustment dimension data, the virtual reality module generates cognitive function test tasks and presents the initial cognitive function test tasks to the patient through the virtual reality display device;

[0161] Obtain patient test feedback data from initial cognitive function test tasks;

[0162] Update the patient's personalized adjustment dimensions based on test feedback data, including: adjusting the difficulty of test tasks based on cognitive development history, optimizing task content based on cultural background, adjusting task rhythm based on living habits, and adjusting task duration based on current health status;

[0163] The updated personalized adjustment dimensions are input into the virtual reality module to generate subsequent cognitive function test tasks, which are presented to the patient for the next round of cognitive training;

[0164] Based on the patient's feedback, continue to optimize the personalized adjustment dimensions until the patient's cognitive function test tasks reach the preset rehabilitation standards;

[0165] Build a data analysis model to perform cluster analysis on the cognitive function test results of patients in different time periods, generate cognitive function change trends, and adjust subsequent cognitive training programs based on the change trends;

[0166] Ultimately, a personalized cognitive function rehabilitation report is generated for the patient, and the report is integrated with the patient's virtual reality training data to optimize the rehabilitation effect and improve cognitive function.

[0167] The working principle of the above technical solution is: the system first collects the patient's personalized adjustment dimension data through questionnaires, patient historical data records, etc. These data include the patient's cognitive development history (such as memory deterioration time, past cognitive training records, etc.), cultural background (such as language preference, cultural habits), living habits (such as daily routine, eating habits) and current health status (such as chronic diseases, mental state); assuming that the cognitive development history of an elderly patient shows that he has a tendency of language ability deterioration, and his cultural background is traditional Chinese culture, his living habits are to get up early and go to bed early, and he has high blood pressure problems. The system will generate personalized initial test tasks based on this information, such as using familiar poetry sentences for memory tests. The tasks are scheduled in the morning and the test time is short to avoid patient fatigue.

[0168] After collecting the personalized adjustment dimension data, the system generates the initial cognitive function test tasks through the virtual reality (VR) module. The virtual reality equipment can provide patients with an immersive training experience and present the initial test tasks intuitively to the patients. In virtual reality, patients can see a scene, such as a home environment with multiple objects and characters appearing. The system will guide patients to complete the task of remembering the location of objects or talking with virtual characters. For patients with cultural background needs, traditional festival scenes can be designed, such as the background of the Mid-Autumn Festival, so that patients can remember the names and placement order of different foods.

[0169] The system will record the patient's performance in the initial cognitive function test tasks, such as task completion, reaction time, concentration, etc., and generate test feedback data. Based on these feedback data, the system will update the patient's personalized adjustment dimensions in real time; if the system detects that the patient has inattention during the task and the completion rate is low, it is because the current task is too difficult or the task content does not match the patient's cultural background. The system will reduce the difficulty of the task, such as changing the task of memorizing multiple items to memorizing a single item, or changing the background scene from a complex home environment to a simple park walk scene.

[0170] The system inputs the updated personalized adjustment dimensions into the virtual reality module to generate new cognitive function test tasks. These tasks will be more in line with the patient's cognitive level and cultural preferences, and gradually increase the complexity and challenge of the tasks; after the update, the system arranges a new task for patients - shopping in the virtual market. Patients need to remember and buy different items according to the shopping list. This not only tests memory, but also enhances patients' life skills. After the patient completes the task, the system will record the patient's performance data in a timely manner, such as whether the product name and location can be accurately remembered, and further optimize the difficulty of the task.

[0171] The system clusters and analyzes the patient's cognitive function test results in different time periods to generate a cognitive function change trend chart. Based on these trends, the system can determine whether the patient's rehabilitation effect has reached the preset standard and adjust the subsequent cognitive training plan accordingly; if the trend chart shows that the patient's memory and attention have improved significantly in the past six months, but the language ability has improved more slowly, the system will give priority to arranging more training tasks involving language skills, such as reading aloud, talking with virtual characters, etc., and appropriately reduce the proportion of memory tasks.

[0172] After the rehabilitation cycle, the system will generate a personalized cognitive function rehabilitation report for the patient, detailing the patient's changes in various cognitive function dimensions. The report will be integrated with the patient's virtual reality training data to form a complete record of the rehabilitation process. In the report, the system will list the patient's specific changes within six months, such as a 30% improvement in memory, a 20% improvement in attention, and a 10% improvement in language ability. At the same time, the system will provide further training suggestions based on these data, such as increasing social interaction training or trying new types of cognitive challenges.

[0173] The beneficial effects of the above technical solution are as follows: the system can customize personalized cognitive training tasks based on multi-dimensional data such as the patient's cognitive development history, cultural background, living habits and health status, so that the training content is closer to the patient's actual situation and improves the rehabilitation effect; by continuously obtaining patient feedback data, the system can adjust the difficulty and content of the task after each training to ensure that each task can effectively challenge the patient's cognitive ability without excessively increasing stress; virtual reality technology can provide patients with a highly realistic and interactive cognitive training environment, improve patients' sense of participation and interest, and thus promote the recovery of cognitive function; through cluster analysis and trend judgment of patients' cognitive function test results, the system can help medical staff fully understand the patient's rehabilitation progress, and adjust the rehabilitation plan in time to improve the efficiency and effectiveness of rehabilitation; the final rehabilitation report can provide patients and their families with detailed changes in cognitive function, and provide data support and reference for subsequent rehabilitation plans to ensure continuous optimization and improvement of the rehabilitation process.

[0174] In another embodiment, determining the patient's completion results regarding the current cognitive test task and the score and emotional tone of the completion results includes:

[0175] Obtain the patient's response behavior data and reaction time in the current cognitive test task. The reaction time is the time from the output of the current cognitive test task to the acquisition of the response behavior.

[0176] Determine the completion result and emotional tone of the current cognitive test task based on the response behavior data, the completion result includes a correct completion result and an incorrect completion result;

[0177] If the completion result is a correct completion result, determining a first score of the correct completion result based on the reaction time and the response behavior data;

[0178] If the completion result is an erroneous completion result, the second score of the erroneous completion result is determined to be 0.

[0179] The working principle of the above technical solution is as follows: suppose a patient is taking a simple cognitive test task, which requires the patient to see a math problem on the screen (such as "5+3=?") and then select the correct answer on the interface. The response behavior data is the patient's response behavior to the test question. In this example, the response behavior data includes the specific answer selected by the patient (such as "8" or "7") and the time point of the selection. The reaction time is the length of time from the presentation of the question to the patient's response behavior. For example, after the question is presented, the patient selects "8" after 3 seconds, and the reaction time is 3 seconds. Judgment of completion results and emotional tone: The system will judge the completion results of the task and the patient's emotional tone based on the response behavior data.

[0180] If the patient's answer is correct, the system will determine it as a correct completion result. For example, if the patient selected "8", it will be a correct completion result. If the patient selects an incorrect answer, the system will determine it as an incorrect completion result. For example, if the patient selected "7", the system will determine it as an incorrect completion result.

[0181] In addition, the system can recognize the patient's emotional tone by analyzing voice or facial expressions. For example, when answering questions, the patient may speak the answer through a voice assistant, and the system can analyze the tone, rhythm, etc. of the voice to infer the patient's emotions (such as anxiety, calmness, happiness, etc.). Score calculation for correct completion results: If the task completion result is correct, the system will calculate the score based on the patient's reaction time and answering behavior data. For example, the system may set a scoring standard based on the reaction time: the shorter the reaction time, the higher the score. If the reaction time is 3 seconds, the first score may be 90 points, and when the reaction time is 5 seconds, the score is 80 points. Score calculation for incorrect completion results: If the task completion result is incorrect, the system will set the patient's score to 0. For example, after the patient answered "7" incorrectly, the system directly gave the second score as 0 points.

[0182] The beneficial effects of the above technical solution are: the system can automatically record the patient's response behavior and reaction time, avoiding the error of manual recording. The accurate calculation of reaction time can reflect the patient's concentration and cognitive processing speed in cognitive test tasks, providing support for further diagnosis; through response behavior data and voice emotion recognition, the system can determine in real time whether the patient completes the task correctly and analyze his emotional state. This is very helpful for understanding the patient's emotional response in the test (such as anxiety, depression or self-confidence), which helps doctors to more comprehensively evaluate the patient's cognitive state and psychological state; the system calculates scores based on reaction time and correctness, and this scoring mechanism can help doctors better quantify the patient's cognitive level. By tracking the scores, doctors can understand the patient's progress and develop more personalized training and intervention plans; the working principle of the system allows doctors to make objective evaluations based on data. The quantification of response behavior and reaction time provides a standardized way to measure the patient's cognitive ability, thereby helping doctors make more accurate diagnoses, especially in assessing attention, reaction speed and emotional regulation.

[0183] In another embodiment, different training tasks and difficulties are set, including:

[0184] Based on the cognitive function assessment report, obtain the user's cognitive function level data, which includes the user's cognitive function indicators of memory, attention, executive function and language ability;

[0185] According to the cognitive function level data, a personalized cognitive training program is generated. The personalized cognitive training program sets different training tasks and difficulties according to different cognitive function indicators, including:

[0186] When the memory index is low, set tasks that require patients to recall daily life events, and adjust the complexity of the tasks by increasing difficulty, from simple object memory to complex event recall;

[0187] When the attention index is low, the patient is required to concentrate on completing tasks in a distracting situation, and the difficulty of the task gradually switches from single attention to multi-tasking;

[0188] When executive function is low, set training tasks that require patients to plan and perform multi-step operations, and dynamically adjust the difficulty of the task based on the accuracy and time of execution;

[0189] When language ability is low, training tasks based on language comprehension and expression are set, and the tasks gradually upgrade from simple word selection to complex dialogue construction.

[0190] The working principle of the above technical solution is: suppose a patient undergoes a cognitive function assessment, and the system gives the following cognitive function level data based on the test results:

[0191] Memory: Low, reflecting the patient's difficulty in recalling recent events;

[0192] Concentration: Moderate, patients can concentrate to some extent but are easily distracted;

[0193] Executive function: Low, with patients having problems planning and carrying out tasks;

[0194] Language ability: Good, able to understand and express basic language information.

[0195] Generate personalized cognitive training programs:

[0196] Based on these cognitive function indicators, the system generates targeted training tasks:

[0197] Memory training: Since the patient's memory index is low, the system has designed a series of memory improvement tasks for the patient, starting with simple object memory, such as asking the patient to remember 5 common objects (such as keys, wallets, mobile phones, etc.), and then gradually increasing the difficulty, requiring the patient to recall more life details or complex events, such as 3 different things that happen every day.

[0198] Attention training: Because the attention index is medium, the system will set a concentration training task for the patient. The task starts with completing a simple concentration task in a quiet environment, such as asking the patient to find a specific object in the picture. As the training progresses, the difficulty will gradually increase, such as asking the patient to concentrate and complete tasks that require frequent switching of attention in the presence of background noise or multi-tasking interference.

[0199] Executive function training: Since the patient's executive function is low, the system will set up multi-step task planning training for them. The initial task may be to ask the patient to complete three simple operations in sequence, such as "turn on the TV, take out the remote control, and change the channel." As the patient's performance improves, the system will dynamically adjust the difficulty based on the accuracy and time of execution, such as adding steps or complexity, allowing the patient to plan the steps to perform a complex task (such as cooking a dish) and complete it within the specified time.

[0200] Language ability training: Although the patient's language ability is relatively good, the system still designs language comprehension and expression tasks to further improve it. The training starts with simple word selection tasks, such as asking the patient to choose the correct word meaning match, and gradually increases the difficulty, eventually requiring the patient to participate in dialogue construction tasks and conduct more complex language communication.

[0201] Task difficulty adjustment: As the patient progresses in each cognitive training area, the system will dynamically adjust the difficulty of the training task based on the task completion (such as accuracy, completion time, performance stability, etc.). For memory training, if the patient performs well, the system may transition from simple object memory to requiring the patient to recall the details of events that occurred within a day, further challenging the patient's short-term and long-term memory.

[0202] The beneficial effects of the above technical solution are: the training program generated by the system is dynamically adjusted based on the patient's cognitive function assessment results, so each training task targets the patient's specific weaknesses to ensure that the patient is effectively trained in these areas. This personalized training method can improve the patient's cognitive function more quickly. The design of the training task takes into account the patient's actual ability and helps the patient gradually adapt to a higher cognitive load by increasing the difficulty. For example, the task gradually transitions from a simple object memory task to a complex event recall task to ensure that the task is challenging without overly tiring or frustrating the patient. By monitoring the patient's performance in real time, the system can dynamically adjust the difficulty of the task according to the patient's performance level, so that the training task is always in the "development zone" of the patient's ability, that is, neither too easy nor too difficult, thereby ensuring the maximization of the training effect. The training program covers multiple cognitive areas, including memory, attention, executive function and language ability, providing a full range of cognitive function recovery training. This can not only improve a specific cognitive function of the patient, but also help him better handle comprehensive tasks in daily life. By analyzing the patient's cognitive function level data, the system can provide a personalized treatment plan based on data. This data-driven approach can help doctors make more accurate treatment decisions and provide patients with personalized rehabilitation plans to help them restore their cognitive abilities faster.

[0203] In another embodiment, a variety of different virtual reality scenarios are introduced, including:

[0204] In social interaction situations in daily life, users communicate with virtual characters or other patients, improving their language and social interaction skills through dialogue tasks;

[0205] In a virtual travel scenario, users need to complete relevant tasks during the trip, including sense of direction tests and object identification tasks, to improve memory and executive function;

[0206] Virtual family activity scenarios simulate daily affairs management in the family, including cooking, housework planning and time management, to enhance users' executive functions and planning abilities.

[0207] Among them, the virtual family activity scenario simulates the daily affairs management in the family, including:

[0208] Through the virtual platform, simulate the layout of the home environment, including the physical location, function and task allocation scenarios of the kitchen, living room, bedroom and bathroom areas;

[0209] Based on the family task model, determine the roles and responsibilities of each family member, including the allocation and execution priorities of tasks such as cooking, housework planning, and time management;

[0210] According to the roles of virtual family members, obtain the task execution data of each family member, including key indicators of task completion time, efficiency, and progress;

[0211] Based on task execution data, adjust the task allocation of family members in real time to ensure that daily affairs can be completed efficiently and in a coordinated manner;

[0212] Based on the family task model and the execution data of the current tasks, the task load and available time of each family member are calculated, and the urgency and importance of the tasks are evaluated;

[0213] Compare the task execution time with the preset time to determine whether the current task is completed as planned. If there is a delay, automatically adjust the time allocation and priority of subsequent tasks;

[0214] Optimize the time allocation and priority of tasks in real time, generate personalized family activity management strategies, and help family members complete various household chores efficiently;

[0215] Based on the personal characteristics, abilities and preferences of family members, the task allocation strategy is dynamically adjusted to ensure that each member performs tasks in the most suitable time period, thereby improving execution efficiency.

[0216] The working principle of the above technical solution is: the user enters a virtual social scene and can choose to have a conversation with a virtual character or other patients. The system will provide different conversation tasks based on the scene and character selected by the user. For example:

[0217] Scenario: Ordering food in a restaurant;

[0218] Role: Virtual waiter;

[0219] Task: The user needs to order food from the virtual waiter and choose the appropriate dishes according to the menu. The system will evaluate the user's language expression ability and grammatical structure and provide corresponding feedback.

[0220] Steps:

[0221] The user chooses to enter the "restaurant ordering" scene.

[0222] The system displays a virtual waiter and provides a menu.

[0223] Users need to choose dishes according to the menu and express their needs in words.

[0224] The system evaluates the user's language expression and provides feedback. For example, if the user makes a grammatical error, the system will prompt the user to correct it.

[0225] Users can make adjustments based on system feedback and continue the conversation with the virtual attendant.

[0226] When users enter the virtual travel scene, they need to complete tasks provided by the system, such as:

[0227] Scenario: Virtual museum;

[0228] Task: Users need to find the designated exhibits according to the map and describe the characteristics of the exhibits. The system will evaluate the user's sense of direction, memory and language expression ability.

[0229] Steps:

[0230] The user chooses to enter the "virtual museum" scene.

[0231] The system provides maps and mission objectives, such as "find the museum's most valuable treasure."

[0232] Users need to find the target exhibits based on the map and describe the characteristics of the exhibits in words.

[0233] The system evaluates the user's description and actions and provides feedback. For example, if the user's description is wrong, the system will prompt the user to observe again.

[0234] Users can make adjustments based on system feedback and continue to complete the task.

[0235] When users enter a virtual home scene, they need to complete daily affairs management in the simulated home, such as:

[0236] Scene: Virtual kitchen;

[0237] Task: Users need to cook according to the recipe and arrange their time properly. The system will evaluate the users based on their planning ability, execution ability and time management ability.

[0238] Steps:

[0239] The user chooses to enter the "virtual kitchen" scene.

[0240] The system provides recipes and the ingredients needed, and sets a time limit.

[0241] Users need to cook according to the recipe and arrange their time reasonably to complete all steps.

[0242] The system evaluates the user's operations and schedule and provides feedback. For example, if the user's schedule is unreasonable, the system will prompt the user to adjust it.

[0243] Users can make adjustments based on system feedback and continue to complete the task.

[0244] The beneficial effects of the above technical solution are: by having conversations with virtual characters or other patients, users can practice oral expression, grammatical structure and vocabulary usage; they can learn how to communicate effectively with others and master social etiquette; practicing social interaction in a virtual environment can help users overcome social phobia and enhance self-confidence.

[0245] In another embodiment, a method for cognitive function rehabilitation training based on virtual reality comprises:

[0246] S101: Based on the virtual reality module, the patient's cognitive dysfunction test is evaluated and a cognitive function assessment report is generated;

[0247] S102: Generate a personalized cognitive training program based on the cognitive function assessment report, and carry out targeted cognitive training in a virtual reality environment. During the cognitive training, collect the patient's physiological data and training performance data;

[0248] S103: Comprehensively analyze physiological data and training performance data and generate a phased feedback report;

[0249] S104: Based on the periodic feedback report, analyze the patient's rehabilitation effects in different time periods, and optimize the subsequent cognitive training program based on the analysis results.

[0250] The working principle of the above technical solution is as follows: During the cognitive function testing and evaluation stage, the patient puts on a VR device (such as a VR helmet) and enters a customized virtual scene. The patient is placed in a virtual "supermarket shopping" scene, and the system requires the patient to remember the items on the shopping list and then find these items in the virtual supermarket in order. This scene mainly tests the patient's memory, attention and executive function. The system will generate a detailed cognitive function assessment report based on data such as the patient's accuracy, reaction time, and error type in the task. For example, the report may indicate that the patient has a slight impairment in memory but has a good ability to maintain attention.

[0251] Based on the cognitive assessment report, the system automatically generates a personalized cognitive training program and conducts training in a VR environment. For patients with memory disorders, the system designs multiple rounds of memory training tasks. For example, in a virtual "find lost items" scenario, the patient needs to remember the location of an item in a room and then retrieve it. During the training process, the VR device will also collect the patient's physiological data (such as heart rate, brain waves, etc.) and training performance data (such as the time required to complete the task, error rate, etc.) in real time. These data are recorded and transmitted to the system through sensors (such as brain wave acquisition devices or bracelets).

[0252] The collected data will be comprehensively analyzed through algorithms to generate periodic feedback reports. If the patient shows gradually improved accuracy in multiple rounds of memory training, but the reaction speed is still slow, the report may point out that "the patient's memory ability has recovered, but the reaction speed still needs to be further strengthened." The report includes chart analysis (such as the change in the patient's task completion time before and after training) and a text description of the rehabilitation progress.

[0253] The system analyzes the patient's rehabilitation effects at different stages based on periodic feedback reports and optimizes subsequent training plans. If the report shows that the patient's memory has improved significantly, but the executive function is still insufficient, subsequent training may introduce "planning and execution" tasks. For example, in a virtual scene, the patient is asked to design an efficient route and complete a series of tasks (such as delivering express in order or planning a schedule).

[0254] Through this dynamic adjustment mechanism, the patient's rehabilitation training plan will be continuously optimized to maximize the rehabilitation effect.

[0255] The beneficial effects of the above technical solutions are: traditional cognitive training is often boring, while VR technology provides a more realistic and interesting environment through immersive experience. The system adjusts the training content according to the patient's real-time performance and physiological data to ensure the personalization and scientific nature of the program. The phased feedback report allows the patient's rehabilitation progress and training effect to be clearly quantified, helping doctors and patients to intuitively understand the rehabilitation situation. The optimization mechanism of the subsequent training program can adjust the focus and difficulty according to the individual needs of the patient, thereby more effectively improving the rehabilitation effect.

[0256] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention belong to the scope of the same technology, the present invention is also intended to include these changes and variations.

Claims

1. A cognitive function rehabilitation training system based on virtual reality, characterized in that: include: A cognitive function testing unit, which is used to test and evaluate the patient's cognitive dysfunction based on a virtual reality module and generate a cognitive function evaluation report for the patient; The cognitive training unit is used to generate personalized cognitive training programs based on cognitive function assessment reports and carry out targeted cognitive training in a virtual reality environment. During the cognitive training process, the patient's physiological data and training performance data are collected; Feedback unit, used to comprehensively analyze physiological data and training performance data and generate periodic feedback reports; The rehabilitation effect tracking unit is used to analyze the patient's rehabilitation effects in different time periods based on periodic feedback reports, and optimize subsequent cognitive training programs based on the analysis results.

2. The virtual reality-based cognitive function rehabilitation training system according to claim 1, characterized in that: Generate a patient's cognitive function assessment report, including: The VR module presents the patient with initial cognitive function test tasks based on the patient's personalized adjustment dimensions, which include cognitive development history, cultural background, lifestyle habits, and current health status; Determine the patient's completion results of the current cognitive test task and the scores and emotional tone of the completion results, including correct completion results and incorrect completion results; Based on the patient's completion results and the personalized adjustment dimensions, multiple new cognitive test tasks are determined and output, and scores and emotional tones regarding the completion results of each new cognitive test task are determined, until the consecutive number of new incorrect completion results reaches a preset number threshold, or the current cognitive test task is determined to be the last test task; Generate and output the patient's cognitive function assessment report based on each completed result, the score and emotional tone of the completed result. The cognitive function data includes multiple cognitive indicators of memory, attention, and executive function; The patient's cognitive dysfunction level is set based on preset conditions, which include the patient's total score in cognitive test tasks, reaction time, accuracy of completion results, emotional tone, and one or more of the personalized adjustment dimensions.

3. The virtual reality-based cognitive function rehabilitation training system according to claim 1, characterized in that: Generate a personalized cognitive training program, including: Generate a personalized cognitive training program based on the cognitive function assessment report. The personalized cognitive training program sets different training tasks and difficulties according to the user's cognitive function level; Introducing a variety of different VR scenarios, including social interactions in daily life, travel, and family activities, allowing users to interact and compete with other patients; Conduct targeted cognitive training in a virtual reality environment, using VR headsets, handheld controllers, and motion capture equipment to provide an immersive experience for users; During cognitive training, the patient's physiological data and training performance data are collected in real time. The physiological data include heart rate and brain waves, and the training performance data include reaction time and task completion. Adjust the difficulty and context of cognitive training tasks based on physiological data and training performance data; If the training effect reaches the preset standard, a prompt message is output to remind the staff that the current training plan is effective; If the training effect does not meet the preset standard, the personalized cognitive training program will be updated and subsequent cognitive training will be carried out in a new virtual reality scenario.

4. The virtual reality-based cognitive function rehabilitation training system according to claim 1, characterized in that: Generate periodic feedback reports, including: Based on the physiological data of the subjects, a physiological state change curve is established to analyze the fluctuation of physiological state before, during and after training; Based on the training performance data of the subjects, generate training performance trend charts to evaluate the dynamic performance of reaction time, task completion and error rate as the training tasks change; Combine the physiological state change curve and training performance trend chart to generate a phased feedback report.

5. The virtual reality-based cognitive function rehabilitation training system according to claim 1, characterized in that: Optimize subsequent cognitive training programs based on the analysis results, including: Based on the periodic feedback report, generate the rehabilitation effect evaluation of the tested subjects in different training cycles; Provide improvement suggestions for different stages of physiological status and training performance in the periodic feedback report, including recommended training content, optimized training situation and suggested physiological status regulation methods; Generate optimization strategies for subsequent training tasks based on periodic feedback reports, including task goal adjustment and situation optimization; Generate optimization strategies for subsequent training tasks, including generating more difficult training tasks based on current feedback when comprehensive evaluation indicators show excellent status, and adjusting key parameters of training tasks, including increasing task operation complexity, shortening reaction time limits, and raising task completion requirements; When the comprehensive evaluation indicators show an abnormal state, new adaptive training tasks are generated based on the current feedback, the difficulty of the training tasks is reduced, and the task situations are adjusted, including increasing the task rest interval, extending the operation time, or reducing task interference.

6. The virtual reality-based cognitive function rehabilitation training system according to claim 2, characterized in that: Based on the patient's personalized adjustment dimensions, the VR module presents the patient with initial cognitive function test tasks, including: Obtain the patient's personalized adjustment dimension data, which includes the patient's cognitive development history, cultural background, living habits and current health status; According to the personalized adjustment dimension data, the virtual reality module generates cognitive function test tasks and presents the initial cognitive function test tasks to the patient through the virtual reality display device; Obtain patient test feedback data from initial cognitive function test tasks; Update the patient's personalized adjustment dimensions based on test feedback data, including: adjusting the difficulty of test tasks based on cognitive development history, optimizing task content based on cultural background, adjusting task rhythm based on living habits, and adjusting task duration based on current health status; The updated personalized adjustment dimensions are input into the virtual reality module to generate subsequent cognitive function test tasks, which are presented to the patient for the next round of cognitive training; Based on the patient's feedback, continue to optimize the personalized adjustment dimensions until the patient's cognitive function test tasks reach the preset rehabilitation standards; Build a data analysis model to perform cluster analysis on the cognitive function test results of patients in different time periods, generate cognitive function change trends, and adjust subsequent cognitive training programs based on the change trends; Ultimately, a personalized cognitive function rehabilitation report is generated for the patient, and the report is integrated with the patient's virtual reality training data to optimize the rehabilitation effect and improve cognitive function.

7. The virtual reality-based cognitive function rehabilitation training system and method according to claim 2, characterized in that: Determine the patient's performance and emotional tone regarding the current cognitive testing task, including: Obtain the patient's response behavior data and reaction time in the current cognitive test task. The reaction time is the time from the output of the current cognitive test task to the acquisition of the response behavior. Determine the completion result and emotional tone of the current cognitive test task based on the response behavior data, the completion result includes a correct completion result and an incorrect completion result; If the completion result is a correct completion result, determining a first score of the correct completion result based on the reaction time and the response behavior data; If the completion result is an erroneous completion result, the second score of the erroneous completion result is determined to be 0.

8. The virtual reality-based cognitive function rehabilitation training system according to claim 3, characterized in that: Set different training tasks and difficulties, including: Based on the cognitive function assessment report, obtain the user's cognitive function level data, which includes the user's cognitive function indicators of memory, attention, executive function and language ability; According to the cognitive function level data, a personalized cognitive training program is generated. The personalized cognitive training program sets different training tasks and difficulties according to different cognitive function indicators, including: When the memory index is low, set tasks that require patients to recall daily life events, and adjust the complexity of the tasks by increasing difficulty, from simple object memory to complex event recall; When the attention index is low, the patient is required to concentrate on completing tasks in a distracting situation, and the difficulty of the task is gradually switched from single attention to multi-tasking. When executive function is low, set training tasks that require patients to plan and perform multi-step operations, and dynamically adjust the difficulty of the task based on the accuracy and time of execution; When language ability is low, training tasks based on language comprehension and expression are set, and the tasks gradually upgrade from simple word selection to complex dialogue construction.

9. The virtual reality-based cognitive function rehabilitation training system according to claim 3, characterized in that: Introducing a variety of different VR scenarios, including: Social interaction situations in daily life, allowing users to communicate with virtual characters or other patients, improving language skills and social interaction skills through conversation tasks; In a virtual travel scenario, users need to complete relevant tasks during the trip, including sense of direction tests and object identification tasks, to improve memory and executive function; Virtual family activity scenarios simulate daily affairs management in the family, including cooking, housework planning and time management, to enhance users' executive functions and planning abilities.

10. A cognitive function rehabilitation training method based on virtual reality, characterized in that: include: S101: Based on the virtual reality module, the patient's cognitive dysfunction test is evaluated and a cognitive function assessment report is generated; S102: Generate a personalized cognitive training program based on the cognitive function assessment report, and carry out targeted cognitive training in a virtual reality environment. During the cognitive training, collect the patient's physiological data and training performance data; S103: Comprehensively analyze physiological data and training performance data and generate a phased feedback report; S104: Based on the periodic feedback report, analyze the patient's rehabilitation effects in different time periods, and optimize the subsequent cognitive training program based on the analysis results.

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