Assessment and training integrated system based on DSM-V cognitive domain

Abstract

The invention discloses an evaluation and training integrated system based on a DSM-V cognitive domain, which belongs to the technical field of cognitive impairment and comprises a task module, an initial module, a training module, a physiological monitoring module and an evaluation module. The task module is used for establishing a task library according to the DSM-V cognitive domain; the initial module is used for performing cognitive impairment initial test on each user to obtain initial test data of the user; the physiological monitoring module is used for collecting physiological monitoring data of a target user; the training module is used for performing cognitive disorder training on a target user and setting each training influence item; determining evaluation data of the target user in real time; analyzing the evaluation data through a training analysis model to obtain a to-be-selected scheme; judging whether the to-be-selected scheme meets training requirements or not; when it is judged that the to-be-selected scheme meets the training requirement, the target user is trained according to the to-be-selected scheme, and the evaluation module is used for evaluating cognitive impairment training of the target user to obtain corresponding evaluation data.

Description

Technical Field

[0001] The present invention belongs to the technical field of cognitive impairment, and in particular is an integrated assessment and training system based on the DSM-V cognitive domain. Background Art

[0002] Cognitive function assessment and training are of great significance in many fields such as neuroscience, psychology and medicine. With the aging of the population and the increase in cognitive disorders, accurate assessment and effective training of cognitive function are becoming increasingly important. Traditional cognitive function assessment methods usually rely on paper-and-pencil tests or manual interviews, which are not only time-consuming and labor-intensive, but also easily affected by subjective factors. In addition, traditional training methods often lack specificity and personalization, making it difficult to meet the specific needs of different patients.

[0003] In recent years, with the development of computer technology and artificial intelligence, computer-based cognitive function assessment and training systems have gradually emerged. These systems can use computer algorithms and data analysis techniques to conduct a comprehensive and objective assessment of an individual's cognitive function and provide personalized training programs based on the assessment results. However, there are still some problems with existing computer-based cognitive function assessment and training systems. For example, some systems lack comprehensive cognitive domain coverage and cannot accurately assess the functional status of individuals in various cognitive domains; some systems cannot dynamically adjust the training program according to the patient's actual situation and training progress.

[0004] In view of the above problems, the present invention proposes an integrated assessment and training system based on the DSM-V cognitive domain. Summary of the invention

[0005] In order to solve the problems existing in the above solutions, the present invention provides an integrated assessment and training system based on the DSM-V cognitive domain.

[0006] The purpose of the present invention can be achieved through the following technical solutions: An integrated assessment and training system based on the DSM-V cognitive domain, including a task module, an initial module, a training module, a physiological monitoring module and an assessment module; The task module is used to set the compound attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain according to the DSM-V cognitive domain, and establish a task library according to the compound attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain. The task library is used to store the initial test task set and the training task set, which are respectively composed of each initial test task and training task; the compound attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain are marked as cognitive domains; and each initial test task and training task composition is classified and marked according to each cognitive domain.

[0007] The initial module is used to perform an initial cognitive impairment test on each user, obtain an initial test task set, display the initial test task set to the user, and the user takes the test according to the initial test task set to obtain the user's initial test single item value and initial test comprehensive value for each cognitive field, determine the cognitive impairment domain based on the initial test comprehensive value and the initial test single item value of each cognitive field, and integrate the initial test single item value, cognitive impairment domain and initial test comprehensive value into the user's initial test data.

[0008] Furthermore, the initial module includes a push unit, which determines each potential user in real time, and pushes preset promotion information to each potential user in real time through the push unit; the promotion information is set by the platform according to the initial test task set.

[0009] Furthermore, the initial module also includes an information import module, and the information import module is used for the user to import initial test data.

[0010] The physiological monitoring module is used to connect to the physiological monitoring device of a target user, where the target user is a user undergoing cognitive impairment training; obtain the physiological monitoring data of the target user from the physiological monitoring in real time, and send the physiological monitoring data to the training module.

[0011] Furthermore, before sending the physiological monitoring data to the training module, the physiological monitoring data is corrected, and the corrected physiological monitoring data is sent to the training module.

[0012] Furthermore, the method for correcting the physiological monitoring data includes: Acquire user information of the target user, determine the personnel classification and physiological monitoring equipment information of the target user according to the user information; integrate the personnel classification and physiological monitoring equipment information of the target user into correction adjustment data; The correction adjustment data and the physiological monitoring data of the target user are analyzed through a preset correction model to obtain the corrected physiological monitoring data.

[0013] Furthermore, the establishment of the revised model: Determining target physiological parameters, wherein the target physiological parameters are physiological parameters that have an impact on cognitive impairment training; Identify various adapted physiological monitoring devices and mark them as reserve monitoring devices; determine various personnel factors that the reserve monitoring devices have an impact on physiological monitoring, classify them according to the various personnel factors, and form various personnel classifications; Performing simulation verification on each of the reserve monitoring devices according to each of the personnel classifications, obtaining simulation verification data of each of the reserve monitoring devices for each of the personnel classifications, wherein the simulation verification data consists of physiological monitoring data of each target physiological parameter and physiological standard data; According to each of the simulation verification data, a correction method for each of the personnel classifications under each of the reserve monitoring devices is determined, and a correction model is established according to each of the correction methods.

[0014] The training module is used to perform cognitive impairment training on the target user, set various training influence items according to the user status, training content, training intensity, and condition; and determine the evaluation data of the target user in real time; Establishing a training analysis model, analyzing the evaluation data of the target user through the training analysis model, obtaining a training plan for the target user, and marking the obtained training plan as a candidate plan; Acquire the physiological monitoring data of the target user in real time, evaluate the candidate plan according to the physiological monitoring data and each training impact item, and determine whether the candidate plan meets the training requirements; When it is determined that the candidate solution does not meet the training requirements, a new candidate solution is generated through the training analysis model, and the new candidate solution is re-evaluated until the training requirements are met; When it is judged that the candidate scheme meets the training requirements, the target user is trained according to the candidate scheme, and the candidate scheme is evaluated in real time during the training process. When it is judged that the candidate scheme meets the training requirements, normal training is performed; when it is judged that the candidate scheme does not meet the training requirements, the candidate scheme is adjusted.

[0015] Furthermore, the method for determining the evaluation data is as follows: Identify in real time the evaluation data of the target user after cognitive impairment training and mark it as training test data; When the training test data of the target user is identified, the training test data is marked as evaluation data; When the training test data of the target user is not identified, the initial test data of the target user is obtained and marked as evaluation data.

[0016] Further, the method of evaluating the candidate solutions based on the physiological monitoring data and each training impact item includes: According to each training influence item, it is divided into training restriction items and training adjustment items. The training restriction items are composed of training influence items corresponding to the user status and the condition; the training adjustment items are composed of training influence items corresponding to the training content and the training intensity; The platform sets each condition classification and the limit value corresponding to each condition classification, wherein the condition classification is composed of each training limit data; the training limit data is the physiological monitoring data corresponding to the training limit item; Processing the candidate solution through the training adjustment item to obtain training adjustment data corresponding to the candidate solution; analyzing the training adjustment data to obtain a training value of the candidate solution; Processing the physiological monitoring data through the training restriction items to obtain training restriction data; determining a condition classification according to the training restriction data, identifying a restriction value corresponding to the condition classification, and comparing the restriction value with the training value; When the training value is not greater than the limit value, it is judged that the candidate solution meets the training requirements; When the training value is greater than the limit value, it is determined that the candidate solution does not meet the training requirements.

[0017] The evaluation module is used to evaluate the cognitive impairment training of the target user and obtain corresponding evaluation data.

[0018] Compared with the prior art, the present invention has the following beneficial effects: Through the cooperation among the task module, initial module, training module, physiological monitoring module and evaluation module, comprehensive coverage and accurate evaluation of individuals in various cognitive fields (such as attention, memory, execution, language comprehension, etc.) are achieved. This not only helps to understand the individual's cognitive function status more accurately, but also provides a scientific basis for the formulation of personalized training programs, thereby significantly improving the accuracy and effectiveness of the evaluation; at the same time, the training program can be dynamically adjusted according to the user's actual situation and training situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0021] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] like Figure 1 As shown, an integrated assessment and training system based on the DSM-V cognitive domain includes a task module, an initial module, a training module, a physiological monitoring module and an assessment module.

[0023] The task module is used to set the composite attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain according to the DSM-V cognitive domain, and to establish a task library according to the composite attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain, and the task library is used to store the initial test task set and the training task set, and the initial test task set and the training task set are respectively composed of each initial test task and the training task; The compound attention domain, learning-memory domain, executive inhibition domain, language-speech domain, perceptual-motor domain, and social-cognitive domain are marked as cognitive domains; and the components of each initial test task and training task are classified and marked according to the cognitive domains corresponding to the compound attention domain, learning-memory domain, executive inhibition domain, language-speech domain, perceptual-motor domain, and social-cognitive domain.

[0024] The training tasks for various cognitive disorders can be statistically determined based on existing data to establish a task library, which can also be established by the platform through professionals.

[0025] For example, according to the DSM-V cognitive domain theory, cognitive functions are divided into six major domains: complex attention domain, learning and memory domain, executive inhibition domain, language and speech domain, perceptual motor domain, and social cognitive domain. For each domain, corresponding cognitive tasks will be designed and summarized to form the initial test task set and training task set.

[0026] The initial module is used to perform an initial test of cognitive impairment on each user, obtain an initial test task set, display the initial test task set to the user, and the user takes the test according to the displayed initial test task set to obtain the user's initial test single item value and initial test comprehensive value of each cognitive field, and determine the cognitive impairment domain based on the initial test comprehensive value and the initial test single item value of each cognitive field, which may have one or more, such as the first cognitive domain and the severity of other disorders, the degree of impact on daily life, or other cognitive fields with cognitive impairment whose intervention is lower than that of the first cognitive domain; each initial test single item value, cognitive impairment domain and initial test comprehensive value are integrated into initial test data.

[0027] Because there are currently detailed testing and evaluation technologies for cognitive impairment, we can analyze each initial test task based on the existing evaluation technology to determine each initial test item value and initial test comprehensive value, as well as subsequent evaluation of the training task set to determine each training item value and training comprehensive value; compare their values ​​with the corresponding thresholds to determine the cognitive impairment domain.

[0028] For example, suppose there is a patient named Mr. Zhang who suspects that he has cognitive dysfunction, so he decides to use the integrated assessment and training system based on the DSM-V cognitive domain for assessment. The following is the specific process of Mr. Zhang determining the initial cognitive level value: Show Mr. Zhang the initial test task set: Compound attention domain: Tests whether he can maintain focus on a task despite distractions, for example, quickly identifying and remembering a series of numbers in a noisy environment.

[0029] Learning and Memory Domain: Assess his memory ability, such as by memorizing a series of words or pictures and testing his recall at a later time.

[0030] Executive inhibition domain: Tests whether the child can control his behavior in the face of temptation or distraction, for example, avoiding being misled into making the wrong choice in a test.

[0031] Language and speech domain: Assess his language comprehension and expression ability, such as answering questions after reading a text, or having a simple conversation.

[0032] Perceptual-motor domain: Tests his physical coordination and motor skills, such as by completing a series of hand movements or visual tracking tasks.

[0033] Social cognition domain: Assessing his ability to understand the emotions, intentions, and behaviors of others, such as inferring their emotional state by observing their facial expressions or behaviors.

[0034] Ms. Li completed all the preliminary test questions on the system interface. The system recorded her performance in each test, including key indicators such as answering time, accuracy, and error types.

[0035] Based on Mr. Zhang's performance in each test, the system calculates a comprehensive score to reflect his initial cognitive level. This comprehensive score may be a weighted average, in which the score of each cognitive domain is given different weights according to its importance or the degree of impact on the patient's daily life.

[0036] For example, if the system believes that memory skills are critical to Zhang's daily life, then scores in the Learning and Memory domain may be given a higher weight. Similarly, if Zhang shows significant difficulty in performing a test in the Inhibition domain, scores in this area may also be given special attention.

[0037] Finally, the system generates a comprehensive score report, which lists in detail Mr. Zhang's initial test scores in various cognitive areas and initial test comprehensive scores. The report may also include some additional information, such as Mr. Zhang's performance trends in various tests, and comparative data with other patients.

[0038] For example: Mr. Zhang's initial cognitive level comprehensive score report: Composite Attention Domain: Score 85 (out of 100), good performance and able to maintain focus on the task.

[0039] Learning and Memory Domain: Score 70 (out of 100), memory impairment exists, requiring special attention and enhanced training.

[0040] Executive Inhibition Domain: Score 90 (out of 100), excellent performance, able to control one's behavior well.

[0041] Language and speech domain: score 80 (out of 100), language comprehension and expression ability is normal.

[0042] Perceptual-motor domain: score 85 (out of 100), good physical coordination and motor skills.

[0043] Social Cognition Domain: Score 88 (out of 100), able to understand other people's emotions and behaviors better.

[0044] Comprehensive score: 82 (full score 100). The overall cognitive level is above average, but attention should be paid to strengthening memory training.

[0045] In one embodiment, in order to facilitate the promotion of the system, a push unit is included to determine each potential user based on big data, and to establish promotional information based on the initial test task set, such as a display interface for each initial test task, which can subsequently generate initial test data based on the task completion status; the promotional information is pushed to each potential user in real time through the push unit.

[0046] In one embodiment, some users come to the system for training and recovery after being diagnosed in the hospital, or the initial test data is determined by the push unit, so further testing will affect the user experience, so it also includes an information import module, which is used for users to import initial test data. If you jump from the promotion information of the push unit, you can directly identify and import the corresponding initial test data.

[0047] The physiological monitoring module is used to perform real-time physiological monitoring of users undergoing cognitive impairment training. When it is determined that the user is undergoing cognitive impairment training, the user's physiological monitoring data is obtained in real time. In order to distinguish, the user undergoing cognitive impairment training is marked as a target user. The physiological monitoring data includes heart rate, blood pressure, gender, age and other related data. Gender, age and the like are user information of the target user. Because this system is mainly used by users at home, the corresponding physiological monitoring data can be obtained by connecting to a smart device worn by the target user, such as a common smart watch; or the platform can equip the corresponding monitoring equipment; there are multiple ways to obtain the user's physiological monitoring data. The device used by the target user to monitor its physiological monitoring data is now marked as a physiological monitoring device, that is, the physiological monitoring data collected by the physiological monitoring device is obtained in real time; the physiological monitoring data is sent to the training module.

[0048] Due to physical differences among different target users, differences in physiological monitoring equipment, and other reasons, the directly acquired physiological monitoring data may have large errors. Therefore, in order to improve the training accuracy, the acquired physiological monitoring data is corrected and then sent to the training module.

[0049] In one embodiment, the method for correcting physiological monitoring data includes: Based on a large amount of cognitive impairment training data, the physiological parameters that have an impact on the intensity and content of the training are determined and marked as target physiological parameters; such as heart rate and blood pressure; for example, when people with cognitive impairment receive high-intensity training, their bodies need more energy and oxygen to support brain activity, which will cause the heart rate to accelerate and blood pressure to rise. On the contrary, if the training intensity is low, the fluctuations of these physiological parameters will be relatively small. Secondly, the content of the training will also affect the fluctuations of physiological parameters. Some training focuses more on the recovery and training of cognitive functions, such as memory training, attention training, etc. These trainings will not directly cause large fluctuations in heart rate and blood pressure. However, if the training involves physical activities or requires high physical coordination and reaction speed, the fluctuations in heart rate and blood pressure will be more obvious. Different people have different adaptability and reactions to training. Some people may have obvious heart rate acceleration and blood pressure increase during training, while others may be relatively stable. Finally, the disease state also affects the fluctuations of physiological parameters. Cognitive impairment itself may be accompanied by some physiological changes, such as arteriosclerosis and decreased vascular elasticity, which may affect the stability of blood pressure. At the same time, some people with cognitive impairment may also have other chronic diseases, such as hypertension, heart disease, etc., which may also cause fluctuations in physiological parameters.

[0050] Obtain various physiological monitoring devices designated by the platform, that is, physiological monitoring devices of various brands and models that meet the physiological monitoring requirements, and mark them as reserve monitoring devices; Determine the personnel factors that have an impact on physiological monitoring, such as age, gender, disease, skin color and other influencing factors, conduct statistical analysis on historical physiological monitoring data based on various personnel factors, determine the degree of influence of each person on physiological monitoring, and then classify the personnel to form various personnel classifications. The personnel classification is composed of the factor ranges corresponding to each personnel factor, such as age 50-60, male gender, hypertension, yellow skin, etc. Specifically, the ranges of personnel factors with the same impact are divided into one category, and then verified and adjusted to ensure that the difference in the degree of influence corresponding to each personnel classification is within the allowable range. Users of the same personnel classification can subsequently use the same correction method for correction, such as reducing the heart rate by 2%; in actual applications, the clustering algorithm can be combined for classification to form various personnel classifications, and then verification and adjustment are performed according to each reserve monitoring device.

[0051] Perform simulation verification on each reserve monitoring device to obtain simulation verification data of each personnel classification under each reserve monitoring device, the simulation verification data consists of physiological monitoring data of each target physiological parameter and physiological standard data, the physiological standard data is the real physiological data of the corresponding personnel; determine the monitoring error of different personnel classifications on each reserve monitoring device according to each simulation verification data, and then set the correction method of each target physiological parameter, and establish a correction model according to each correction method combined with existing intelligent technology; the correction model is used to correct the physiological monitoring data according to the personnel classification of the user and the information of the physiological monitoring device, and obtain the corrected physiological monitoring data; specifically, it can be established based on neural networks, etc., or it can be established based on other intelligent technologies; Obtain the target user's user information, including gender, age, historical diseases, information on the physiological monitoring equipment used, and other relevant data; determine the target user's personnel classification and physiological monitoring equipment information based on the user information, and integrate them into corrected and adjusted data; analyze the corrected and adjusted data and the target user's physiological monitoring data through a correction model to obtain corrected physiological monitoring data.

[0052] The training module is used to perform cognitive impairment training on the target user, set various training influence items according to the user status, training content, training intensity, and condition; and determine the evaluation data of the target user in real time; A training analysis model is established based on existing technologies. The training analysis model is used to analyze the evaluation data, determine the various training tasks suitable for the target user training, and form a training plan. The existing mature training technology is used for determination. Since there are currently many technologies for determining training plans based on evaluation data, the existing technology can be directly applied to establish the training analysis model. However, when it is determined that the training plan does not meet the requirements, a new training plan will be generated based on the evaluation data. Analyze the target user's evaluation data through the training analysis model, determine the training plan, and mark it as a candidate plan; Obtain the target user's physiological monitoring data, evaluate the candidate plan based on the physiological monitoring data and various training impact items, and determine whether the candidate plan meets the training requirements; When it is determined that the candidate solution does not meet the training requirements, a new candidate solution is generated through the training analysis model, and the new candidate solution is re-evaluated until it meets the training requirements; When it is judged that the candidate scheme meets the training requirements, the target users are trained according to the candidate scheme, and the candidate scheme is evaluated in real time during the training process. When it is judged that the candidate scheme meets the training requirements, normal training is carried out, that is, the training remains unchanged; when it is judged that the candidate scheme does not meet the training requirements, the candidate scheme is adjusted, that is, the training is stopped until a candidate scheme that meets the requirements is determined.

[0053] Therefore, real-time evaluation can be performed during the training process, and training adjustments can be made when the requirements are not met.

[0054] The method for determining the evaluation data is as follows: Identify the evaluation data of the target user after cognitive impairment training in real time, mark it as training test data, and refer to the evaluation data after the latest training; When the training test data of the target user is identified, it indicates that the user is undergoing post-cognitive impairment training, and the training test data is marked as evaluation data; When the training test data of the target user is not identified, the initial test data of the target user is identified and marked as evaluation data.

[0055] In one embodiment, the method for evaluating the candidate solutions based on the physiological monitoring data and each training impact item is: evaluating based on the existing technology to determine whether the candidate solutions meet the training requirements.

[0056] In one embodiment, the method for evaluating the candidate solutions based on the physiological monitoring data and each training impact item includes: According to each training influence item, the historical cognitive impairment training data is analyzed to determine the influence of each training influence item on cognitive impairment training, wherein the training influence items corresponding to the disease state and user status are marked as training restriction items, and the training influence items corresponding to the training content and training intensity are marked as training adjustment items; the control variable method can be adopted for analysis, and the training adjustment items are used for variable analysis to determine the training values ​​corresponding to different training contents and training intensities. The training value range is [0, 100]. The training value corresponding to the combination of the maximum intensity and the most difficult content is 100. The greater the adverse effect on the patient, the less likely the patient is to receive training if the patient does not receive training. The adverse effect caused by not receiving training is zero, and the other factors are The setting can be based on the degree of adverse effects of the training on the patient, and can be compared with the actual historical effects. The training values ​​can be calculated proportionally according to the differences in the degrees of effects to form training values ​​for various situations. The training values ​​can be subsequently determined based on the actual conditions corresponding to the training adjustment items. A training value analysis model can also be established based on neural networks, etc., and a corresponding training set can be established manually for training. The training set includes input data and output data. The input data is the training content data and training intensity data corresponding to the training adjustment items, which are integrated into training adjustment data. The output data is the training value. The corresponding training value can be obtained by analyzing the training value analysis model after successful training.

[0057] Variable analysis is performed on training restrictions to understand the maximum allowable tolerance of users in different situations, that is, the maximum training value that users with the corresponding medical conditions and user status can accept under permitted conditions. The user status is represented by corresponding physiological data, gender, age, etc.; specifically, various possible user condition data can be determined according to the training restrictions, and the existing methods such as clustering algorithms are used to classify the user condition data to form various user classifications, which are marked as condition classifications. The maximum training values ​​of users belonging to the same condition classification are the same; each formed condition classification can be verified, and then dynamic adjustment of the condition classification can be achieved; the maximum tolerable training value is marked as a limit value; each condition classification and limit value is analyzed and set by the platform, that is, it can also be directly set manually by professionals of the platform; the user condition data corresponding to the training restriction item is marked as training limit data.

[0058] The candidate scheme is processed through the training adjustment item to obtain the training adjustment data corresponding to the candidate scheme. If the candidate scheme is being trained, the processed part is the part that has not been trained, and the training adjustment data is analyzed to obtain the training value corresponding to the candidate scheme; Processing the physiological monitoring data through the training restriction items to obtain the training restriction data corresponding to the user; the training restriction data is the physiological monitoring data corresponding to the training restriction items; determining the condition classification corresponding to the user according to the training restriction data, identifying the restriction value corresponding to the condition classification, and comparing the restriction value with the training value; When the training value is not greater than the limit value, it is judged that the candidate solution meets the training requirements; When the training value is greater than the limit value, it is determined that the candidate solution does not meet the training requirements.

[0059] In other embodiments, the limit value and the training value may also be determined based on the existing technology according to the physiological monitoring data and the candidate schemes.

[0060] The evaluation module is used to evaluate the cognitive impairment training of the target user and obtain corresponding evaluation data. The evaluation is performed based on existing mature evaluation methods and can be combined with the initial cognitive impairment test method.

[0061] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0062] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An integrated assessment and training system based on the DSM-V cognitive domain, characterized in that: It includes task module, initial module, training module, physiological monitoring module and evaluation module; The task module is used to set the compound attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain according to the DSM-V cognitive domain, and to establish a task library according to the compound attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain, and the task library is used to store the initial test task set and the training task set, and the initial test task set and the training task set are respectively composed of each initial test task and training task; the compound attention domain, learning memory domain, executive inhibition domain, language and speech domain, perceptual motor domain and social cognitive domain are marked as cognitive domains; each initial test task and training task is classified and marked according to each cognitive domain; The initial module is used to perform an initial test of cognitive impairment on each user, obtain an initial test task set, display the initial test task set to the user, and the user takes the test according to the initial test task set to obtain the user's initial test single item value and initial test comprehensive value of each cognitive field, determine the cognitive impairment domain according to the initial test comprehensive value and the initial test single item value of each cognitive field, and integrate each initial test single item value, cognitive impairment domain and initial test comprehensive value into the initial test data of the user; The physiological monitoring module is used to connect to the physiological monitoring device of the target user, and the target user is a user who is undergoing cognitive impairment training; Acquire physiological monitoring data of the target user by the physiological monitoring in real time, and send the physiological monitoring data to a training module; The training module is used to perform cognitive impairment training on the target user, set various training influence items according to the user status, training content, training intensity, and condition; and determine the evaluation data of the target user in real time; Establishing a training analysis model, analyzing the evaluation data of the target user through the training analysis model, obtaining a training plan for the target user, and marking the obtained training plan as a candidate plan; Acquire the physiological monitoring data of the target user in real time, evaluate the candidate plan according to the physiological monitoring data and each training impact item, and determine whether the candidate plan meets the training requirements; When it is determined that the candidate solution does not meet the training requirements, a new candidate solution is generated through the training analysis model, and the new candidate solution is re-evaluated until the training requirements are met; When it is determined that the candidate solution meets the training requirements, the target user is trained according to the candidate solution, and the candidate solution is evaluated in real time during the training process. When it is determined that the candidate solution meets the training requirements, normal training is performed; When it is determined that the candidate solution does not meet the training requirements, adjusting the candidate solution; The evaluation module is used to evaluate the cognitive impairment training of the target user and obtain corresponding evaluation data.

2. The integrated assessment and training system based on the DSM-V cognitive domain according to claim 1, characterized in that: The initial module includes a push unit, which determines each potential user in real time and pushes preset promotion information to each potential user in real time through the push unit; the promotion information is set by the platform according to the initial test task set.

3. The integrated assessment and training system based on the DSM-V cognitive domain according to claim 2, characterized in that: The initial module also includes an information import module, and the information import module is used for users to import initial test data.

4. The integrated assessment and training system based on the DSM-V cognitive domain according to claim 1, characterized in that: Before sending the physiological monitoring data to the training module, the physiological monitoring data is corrected, and the corrected physiological monitoring data is sent to the training module.

5. The integrated assessment and training system based on the DSM-V cognitive domain according to claim 4, characterized in that: Methods for correcting physiological monitoring data include: Acquire user information of the target user, determine the personnel classification and physiological monitoring equipment information of the target user according to the user information; integrate the personnel classification and physiological monitoring equipment information of the target user into correction adjustment data; The correction adjustment data and the physiological monitoring data of the target user are analyzed through a preset correction model to obtain the corrected physiological monitoring data.

6. The integrated assessment and training system based on the DSM-V cognitive domain according to claim 5, characterized in that: Correction model establishment: Determining target physiological parameters, wherein the target physiological parameters are physiological parameters that have an impact on cognitive impairment training; Identify various adapted physiological monitoring devices and mark them as reserve monitoring devices; Determine various personnel factors that have an impact on physiological monitoring of the reserve monitoring equipment, classify according to each of the personnel factors, and form various personnel classifications; Performing simulation verification on each of the reserve monitoring devices according to each of the personnel classifications, obtaining simulation verification data of each of the reserve monitoring devices for each of the personnel classifications, wherein the simulation verification data consists of physiological monitoring data of each target physiological parameter and physiological standard data; According to each of the simulation verification data, a correction method for each of the personnel classifications under each of the reserve monitoring devices is determined, and a correction model is established according to each of the correction methods.

7. The integrated assessment and training system based on the DSM-V cognitive domain according to claim 1, characterized in that: The method for determining the evaluation data is as follows: Identify in real time the evaluation data of the target user after cognitive impairment training and mark it as training test data; When the training test data of the target user is identified, the training test data is marked as evaluation data; When the training test data of the target user is not identified, the initial test data of the target user is obtained and marked as evaluation data.

8. The integrated assessment and training system based on the DSM-V cognitive domain according to claim 1, characterized in that: Methods for evaluating candidate options based on physiological monitoring data and various training impact items include: According to each training influence item, it is divided into training restriction items and training adjustment items. The training restriction items are composed of training influence items corresponding to the user status and the condition; the training adjustment items are composed of training influence items corresponding to the training content and the training intensity; The platform sets each condition classification and the limit value corresponding to each condition classification, wherein the condition classification is composed of each training limit data; the training limit data is the physiological monitoring data corresponding to the training limit item; Processing the candidate solution through the training adjustment item to obtain training adjustment data corresponding to the candidate solution; analyzing the training adjustment data to obtain a training value of the candidate solution; Processing the physiological monitoring data through the training restriction items to obtain training restriction data; determining a condition classification according to the training restriction data, identifying a restriction value corresponding to the condition classification, and comparing the restriction value with the training value; When the training value is not greater than the limit value, it is judged that the candidate solution meets the training requirements; When the training value is greater than the limit value, it is determined that the candidate solution does not meet the training requirements.

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