231 results about "Psychological evaluation" patented technology

The invention discloses a campus green space ownership perception assessment method and system based on multi-modal learning, and the method specifically comprises the steps: inputting the output results of a visual feature coding network and an auditory feature coding network into an audio-visual modal feature fusion module for fusion processing, and obtaining an environment joint representation; inputting the physiological response data set and the psychological assessment data set into a physiological and psychological collaborative encoder for processing to obtain a physiological and psychological joint representation; inputting the environment joint characterization and the physiological and psychological joint characterization into a global fusion module for deep fusion to obtain a final fusion feature; and inputting the final fusion feature into a multi-task prediction channel for processing, and training and optimizing in combination with a loss function to obtain an environment comfort comprehensive scoring result and an explanatory decision basis. According to the invention, comprehensive assessment of campus green space perception is realized, the accuracy and scientificity of assessment are improved, and decision support is provided for optimization of campus space design.

The invention discloses an intelligent psychological intervention system based on multi-modal fusion, which is characterized in that a three-dimensional evaluation system is constructed by integrating speech sentiment analysis, keyboard dynamics monitoring and physiological signal acquisition, and time sequence alignment and feature weighted fusion of multi-source data are realized by adopting a cross-modal Transform model. The core of the system comprises an adaptive intervention engine which defines a multi-dimensional state space based on a hierarchical reinforcement learning architecture, optimizes an intervention strategy through a PPO algorithm, and realizes dynamic emotion interaction in AR and VR scenes in combination with a digital twin training module; according to the clinical decision support system, physiological behavior characteristics and psychological assessment trends are integrated by using a multi-time scale risk prediction model, and a personalized early warning threshold system is constructed, so that the psychological state recognition accuracy is improved, the intervention intensity self-adaptive adjustment response time is shortened, and the high-risk signal early warning timeliness reaches the minute level; and the problems of evaluation hysteresis and strategy stiffness of traditional psychological intervention are obviously improved.

The invention relates to the technical field of multi-modal data, provides a pilot competency dynamic evaluation method, system and device based on multi-modal data and a storage medium, and solves the problems of low accuracy of pilot competency evaluation and poor pertinence of training guidance. The method comprises the steps of collecting flight control data, physiological signal data, psychological assessment data, subjective scale data and international civil aviation organization core competency information, performing alignment fusion on multi-source data by adopting a time synchronization algorithm, and identifying an attention fixation mode based on a hidden Markov model. And constructing a workload index by fusing a subjective scale and a physiological entropy value, inputting the multi-modal features into a pre-trained competency assessment model, outputting three levels of psychological assessment indexes including a basic ability layer, a dynamic presentation layer and a risk early warning layer, and finally generating a personalized training report. According to the invention, the accuracy of pilot competency evaluation and the pertinence of training guidance are improved.

The invention provides a system platform for psychological assessment and emotion feedback. The system platform comprises a multi-source data acquisition module, an emotion data analysis module, a psychological state assessment module, an intervention scheme generation module, an emotion change feedback module, a scheme optimization module and a data security protection module. The emotion recognition accuracy is improved by synchronously acquiring physiological-behavior-environment data and combining with a dynamic feature fusion method, a personalized intervention strategy is generated based on a reinforcement learning algorithm, real-time feedback is realized, and a data security protection system is constructed by adopting federal learning and homomorphic encryption technologies, so that the data security is ensured.

The invention relates to the field of data processing, in particular to a psychological assessment method based on a large model and a related device. The method comprises the following steps: generating a psychological evaluation strategy according to a current interview task and a corresponding psychological evaluation index; generating multi-round dialogue information through an evaluation interaction model based on a psychological evaluation strategy, and interacting with the target object through the multi-round dialogue information to complete a psychological evaluation process corresponding to the current interview task; performing multi-modal interaction mode analysis on the target object based on the multi-round dialogue information and the corresponding response information to obtain a psychological assessment report of the target object; the psychological assessment report at least comprises a quantitative analysis result and a qualitative psychological analysis result aiming at the dialogue content. According to the method, by accurately guiding dialogue content generation and adjusting the evaluation strategy in real time, the psychological state of the target object is more accurately touched, individual differences are adapted, related personnel are assisted in completing psychological evaluation tasks, the accuracy of the evaluation result is improved, and the psychological evaluation efficiency is improved.

The invention belongs to the field of student psychological health management, and particularly relates to a student psychological evaluation system based on AI reinforcement learning optimization. According to the system, the psychological state of the student is dynamically evaluated through multi-modal data acquisition, deep data processing and reinforcement learning optimization, and the problems of singleness and hysteresis in a traditional psychological evaluation method are solved. The system comprises a data acquisition layer, a data processing layer, a reinforcement learning optimization layer, a gamification evaluation module, a feedback and intervention layer and a user interface layer. The data acquisition layer acquires behavior, physiological and social data in multiple channels; the data processing layer performs cleaning, feature extraction and fusion on the data; the reinforcement learning optimization layer adjusts the psychological evaluation strategy in real time; the gamification evaluation module enhances the student participation degree through a task and reward mechanism; and the feedback and intervention layer provides real-time feedback and personalized intervention suggestions. The psychological evaluation accuracy, participation and intervention effect can be improved, and the method is suitable for psychological health management scenes of schools and related educational institutions.

The invention discloses an intelligent psychological state assessment method and system based on multi-modal alignment, and relates to the technical field of psychological assessment, and the method comprises the following steps: S1, constructing a training sample set of a psychological state assessment model; s2, preprocessing video data, voice data and text data in the training data sample set; s3, performing alignment and fusion by using multi-modal cross attention, taking the text data as a main modal, and taking the video data and the voice data as assistance of the text data to obtain multi-modal fusion features for psychological state analysis; s4, training by using the aligned and fused multi-modal fusion features to obtain a psychological state analysis model; and S5, obtaining a multi-dimensional psychological analysis result of the testee through the psychological state analysis model obtained through training. According to the method, the multi-modal deep features of the teenagers are extracted by pre-training the large model, and the feature expression ability of the data is improved by using the modal alignment technology.

The invention provides a psychological analysis method and system based on multi-modal features, and relates to the technical field of psychological assessment. The method comprises the following steps: synchronously obtaining voice data, video data, text data and physiological signal data of a user; respectively denoising the data to obtain each piece of denoised modal data; performing feature extraction on each modal data to obtain each modal feature; mapping each modal feature vector to a unified semantic space through an attention weighting mechanism to generate a fusion feature matrix; a trained psychological analysis model is adopted to perform multi-task learning on the fusion feature matrix, and emotion classification, pressure indexes and psychological health risk scores are synchronously output; and updating model parameters of the psychoanalysis model through an online incremental learning mechanism based on the real-time feedback data of the user and the newly added sample. Through accurate data denoising, efficient feature extraction and flexible model optimization, comprehensive and accurate analysis of the psychological state of the user is realized.

The invention belongs to artificial intelligence, and relates to a psychological assessment method based on a large language model Agent, which comprises the following steps of: extracting user-level cue words from each round of dialogue with a user by utilizing a user psychological feature extraction module, connecting the user-level cue words with system-level cue words obtained when a large language model is loaded, performing entity recognition on the cue words spliced together through a large language model; matching the extracted entity nodes with symptom nodes in the psychological state knowledge graph by utilizing a user psychological state retrieval module, and retrieving all corresponding psychological state node sets; the Agent questioning module is used for initiating questioning according to the answer of the user; according to the psychological assessment report generation module, the large language model searches a self-scale with the highest similarity with the user state according to all features extracted by dialogue with the user, and sends a report with the highest similarity with the condition that the user completes the self-scale to the user; the use experience of the user and the effectiveness of the evaluation result are improved.

The invention relates to the technical field of psychological health education, and discloses a psychological health education-based dredging auxiliary platform, which comprises a psychological evaluation module, a data analysis module, an intervention execution module, a user archive library, a real-time monitoring module and the like. And the data analysis module is connected with the user archive library, generates a psychological state trend and intervention demand curve according to historical psychological data and behavior record data, and interacts data with other modules. And the intervention execution module receives related data, generates a real-time grooming instruction, and stores and records the instruction. The real-time monitoring module and the health rating module collect data to generate a corresponding matrix. The cognitive model optimization module optimizes parameters through a semantic association analysis network and the like. The state prediction model adopts a sliding time pane analysis method, and the health rating module adopts a fuzzy analytic hierarchy process. The platform realizes dynamic evaluation and accurate intervention, and improves the psychological health dredging effect.

The invention discloses a multi-role collaborative management architecture based on RBAC + HIS synchronization, and the architecture comprises a role authority management module which builds a static role authority baseline based on an RBAC model, and associates the real-time organization architecture data of an HIS system through a dynamic rule engine, and generates a multi-level role authority tree; the data synchronization middleware adopts an API gateway to realize one-way data push between the HIS system and the psychological assessment platform, comprises a field-level encryption unit and an incremental data verification unit, and supports isolated transmission of patient medical records, medical advices and assessment tasks according to inpatient areas; the multi-terminal cooperation engine realizes authority mapping of the doctor workstation, the mobile nursing terminal and the patient self-service terminal through distributed session management, a conflict detection mechanism is built in, and a secondary authentication process is triggered when cross-inpatient-area operation is detected. According to the invention, dynamic authority management is realized, data secure transmission and multi-terminal cooperation are guaranteed, auditing tracing is enhanced, and business continuity when the system is abnormal is ensured.

The invention relates to a tree painting projection data collection and analysis system and method, and the system comprises a data collection module, a data preprocessing module, a feature extraction module, a quantitative analysis module, a classification and prediction module, and a result evaluation module. The modules cooperate with each other to realize standardized processing, feature extraction, quantitative analysis, intelligent classification and prediction and result evaluation of data. According to the method, the holographic theory and the Ama pothole theory are combined, the drawing features are finely analyzed through the cross-modal comparative learning and graph neural architecture search combined algorithm, a scientific and objective psychological data acquisition and analysis method is provided, the diagnosis sensitivity and specificity are improved, a powerful tool is provided for clinical psychological assessment, and the method is suitable for clinical psychological assessment. The method has important clinical and research values, and has wide application prospects in the fields of psychological problem screening, social psychological services, judicial, public security, marriage matching, talent selection and the like.

The invention relates to the technical field of psychological analysis, in particular to a student psychological interview assisting method and system based on an AI large model, and the method comprises the following steps: obtaining a student answer text, carrying out emotion vocabulary marking by using the AI large model, recognizing a grammatical role and an emotion direction of emotion vocabularies in the text, and carrying out the quantitative analysis of the intensity of each emotion word. And evaluating the emotion direction and intensity of each sentence of the student to obtain emotion state information. According to the method, the AI large model is introduced to perform emotion analysis on the answer text of the student, so that emotion evaluation is more comprehensive and detailed, the rate and amplitude of emotion fluctuation of the student are monitored in real time, the emotion fluctuation curve is drawn, the duration time is recorded, dynamic data support is provided for psychological health evaluation, the accuracy and real-time performance of psychological evaluation are improved, and the psychological evaluation efficiency is improved. The psychological health risk of the student is accurately identified by combining emotion fluctuation and psychological pressure analysis, so that the evaluation result is more personalized, and targeted and prospective support is provided for psychological experts.

The invention discloses a psychological health analysis method and apparatus, an electronic device and a storage medium, through the application, dynamic psychological assessment is generated through multi-modal data fusion analysis, and personalized scenarized dynamic interaction content is generated based on an assessment result and an interaction history, so that the psychological health analysis efficiency is improved. Meanwhile, continuous learning and correlation analysis are carried out on the psychological state of the user by utilizing a multi-dimensional memory architecture, so that the system can understand the change of the user state and adjust an interaction strategy like a human consultant, and therefore, the technical problems of insufficient emotional distraction and credibility of the user due to the adoption of a standardized reply mode in the prior art can be solved, and the user experience is improved. The technical effects of enhancing the emotion affinity of the system, establishing a continuous and credible interaction relationship and improving the durability of the psychological intervention effect are achieved.

The invention relates to the field of psychological health, and provides an employee psychological health management system and method based on cloud computing, and the system comprises a psychological archive management module which is used for collecting, classifying, storing and updating the psychological health data of employees, and calculating the comprehensive psychological health indexes of the employees; the intelligent psychological assessment module is used for acquiring psychological data of the employees and assessing psychological states of the employees by applying an advanced regression model to obtain psychological assessment results; the remote psychological counseling module is used for evaluating the psychological counseling effect of the employee to obtain a first evaluation value of the psychological counseling effect; the personalized psychological assistance plan generation module is used for generating a psychological assistance plan for the employee; and the virtual reality psychological treatment module is used for providing psychological treatment service for the employees through the virtual reality technology and evaluating the treatment effect to obtain a second evaluation value of the virtual reality psychological treatment effect. According to the invention, the psychological health state of the employee can be comprehensively and accurately improved.

The invention discloses an employee work ability assessment method based on multi-modal health data fusion. The method comprises the steps of obtaining a plurality of health index values of physical examination data of an employee to be assessed, a plurality of self-assessment scale scores of psychological assessment data and a plurality of physiological monitoring index values of wearable device data; performing standardization processing on the acquired data, and converting the standardized data into feature vectors respectively; respectively inputting the feature vectors corresponding to the physical examination data and the psychological evaluation data into a trained multi-layer perceptron for feature extraction to obtain a physical examination feature vector and an evaluation feature vector; inputting the feature vector of the wearable device data into a trained long-short-term memory network for feature extraction to obtain a wearable feature vector; and inputting the physical examination feature vector, the evaluation feature vector and the wearing feature vector into a fusion module of a trained multi-modal learning model to perform feature fusion, and inputting the fused features into a DNN model of the multi-modal learning model to generate a work ability score.

The invention relates to the technical field of talent training, and discloses an artificial intelligence-based large-health customized talent training system, which comprises a multi-modal data acquisition module, which is used for acquiring user biological index data, behavior log data, psychological assessment data and industry demand data; and the data processing and knowledge fusion module is used for performing time sequence alignment and missing value filling on the acquired data, and constructing a skill association knowledge graph based on industry demand data. According to the invention, through the personalized ability modeling and reinforcement learning recommendation module, the personalized training path of each user is dynamically generated, it is ensured that each user can obtain training matched with health requirements, ability levels and industry requirements, and compared with a universal training scheme in the prior art, the training efficiency is greatly improved. An accurate and customized training scheme can be provided according to real-time biological indexes, psychological evaluation and behavior data of the user, and the training effect is remarkably improved.

The invention relates to the technical field of cognitive behavior therapy, in particular to a scheme intelligent pushing and task self-adaptive management method based on cognitive behavior therapy, which comprises the following steps: S1, acquiring physiological signals, behavior logs and environment interaction data of a user through a multi-modal data acquisition module; s2, constructing a dynamic psychological assessment model based on a cognitive behavior theory, and fusing multi-source data by adopting a Bayesian network to generate a user cognitive state map; s3, generating a personalized intervention scheme through a reinforcement learning algorithm according to the cognitive state map and a preset CBT intervention rule base; according to the method, through multi-modal data acquisition, dynamic psychological assessment, reinforcement learning scheme generation, task decomposition optimization, difficulty adaptive adjustment and digital twinborn simulation, full-process closed-loop management from data acquisition to intervention optimization is constructed, and efficient, safe and personalized cognitive behavior treatment scheme intelligent pushing and task adaptive management are realized.

The invention belongs to the technical field of medical treatment, and discloses a wearable intelligent method and device for monitoring the mental health of community old people, and the method comprises the steps: collecting the physiological indexes of the community old people in real time through an intelligent chest card, and achieving the dynamic collection of multi-dimensional data; data are transmitted to the cloud platform through Bluetooth or Wi-Fi, the equipment supports a data caching mechanism, and key data are temporarily stored when connection is abnormal; a dynamic evaluation model is constructed based on AI learning, and a multi-factor decision tree model and a natural language processing NLP algorithm are combined; a group psychological health trend and an environment risk thermodynamic diagram are presented in real time through a chest card APP, main factors influencing psychological health of the old are analyzed, and community managers are assisted in making an intervention plan. By making and applying the community old people mental health monitoring and early warning model, a unified mental health assessment system is provided for old people in different states, the applicability, universality and compliance of mental assessment are improved, home rehabilitation is achieved, and the overall medical cost is reduced.

The invention relates to the technical field of psychological assessment, in particular to a psychological state assessment method, system and terminal based on an interactive terminal, and the method comprises the steps: separating voice data and text data of a user into an emotion change sequence; based on the emotion tendency of the emotion change sequence, setting an emotion change quantity, and according to a matching relationship between the emotion change quantity and a dialogue situation, calculating a user response duration; obtaining the participation degree of the user at different moments by obtaining the response frequency corresponding to the response duration of the user; combining the degree of participation, the emotional variation and the emotional change probability into an emotional feature, and deducing an emotional classification and a transition label of the current emotional feature; on the basis of the emotion proportion of each emotion classification, dialogue strategy matching is carried out according to the participation amount of the emotion classification at adjacent moments, and a dialogue strategy is set; and the accuracy and effect of emotion recognition are improved.

The invention relates to the technical field of block chain data sharing, and discloses a student psychological assessment data sharing method and system based on a block chain. The method comprises the following steps: when a user logs in through a browser client, a system triggers a zero-knowledge proof generation process; and the client signs the timestamp and the random number by using a local false identity private key to form a zero-knowledge proof request packet, and submits the zero-knowledge proof request packet to the alliance chain node through a secure channel. And the node calls an identity verification contract to verify the signature, generates a session token containing a role type and a validity period after the signature passes, writes the token in an alliance chain account book in a hash manner and returns the token to the client. The client encrypts and stores the token, and a subsequent data request is carried through an HTTP header; and when it is detected that the token is expired or abnormal, the client automatically re-triggers the zero-knowledge proof process. The method depends on the block chain and zero knowledge proof technology, optimizes identity verification and session management, guarantees data sharing safety, compliance and stability, and is suitable for student psychological assessment data sharing among multiple subjects.

The invention relates to the technical field of psychology and artificial intelligence, in particular to a personalized psychological portrait generation evaluation method, which comprises the steps of constructing a multi-source heterogeneous data acquisition system, updating a time sequence behavior pattern, performing multi-dimensional association analysis, dynamically adjusting an adaptive optimization algorithm and the like. According to the method, real-time capturing and modeling of the psychological state of the user can be achieved by fusing multi-source data, the accuracy and adaptability of the psychological portrait are improved by combining the graph neural network and the genetic algorithm, and the defects in the aspects of dynamic psychological state capturing, individual difference modeling and multi-modal data processing in the prior art are overcome; and technical support is provided for psychological health intervention, behavior prediction and psychological assessment in a complex environment.

The invention relates to the technical field of artificial intelligence, and discloses an artificial intelligence assisted psychological assessment system. The artificial intelligence assisted psychological assessment system comprises a data collection module, a data analysis module, a scale generation module, a result presentation module, a user interaction module, an online AI consultation module and a modal selection and decision optimization module, according to the artificial intelligence assisted psychological assessment method, personalized and accurate psychological health assessment and intervention are realized through the steps of multi-modal data collection, psychological state modeling, data analysis, scale generation, result presentation, modal optimization, online consultation and the like, and the assessment efficiency and accuracy are improved; according to the method, accurate and personalized psychological assessment and intervention are provided through multi-modal data collection and analysis, information entropy optimization, variational reasoning data analysis and personalized scale generation; compared with the prior art, the accuracy and efficiency of evaluation and the user experience are improved.

The invention discloses a patient psychological assessment method and device based on information interaction and a storage medium, and relates to the technical field of medical information processing.The method comprises the steps that a scene interaction module is constructed, and a multi-modal data set of a patient is collected under multiple scene samples; the method comprises the following steps: performing space-time alignment on a multi-modal data set, inputting a multi-modal fusion psychological assessment model, learning correlation among different modals, outputting a plurality of psychological assessment indexes corresponding to a plurality of scene samples, performing fusion analysis, obtaining fusion psychological assessment indexes, and sending the fusion psychological assessment indexes to an interaction upper computer for medical record storage. The technical problems that in the prior art, a traditional psychological assessment method depends on manual observation, the assessment dimension is single, emotion changes cannot be comprehensively captured, and the assessment accuracy, real-time performance and comprehensiveness are poor are solved, and the purposes of automatically assessing the psychological state of the patient by fusing multi-dimensional data, improving the accuracy and accuracy of assessment and the like are achieved. And the accuracy, the real-time performance and the comprehensiveness of psychological assessment are improved.

The invention relates to the technical field of psychological state assessment, and particularly discloses a psychological state assessment method and system based on environmental perception, and a readable storage medium, and the method comprises the following steps: collecting an environment scene and an assessed object behavior image through an RGB camera, and extracting an object category, a spatial layout and a dynamic event through a semantic segmentation model; acquiring an environment voiceprint through a microphone, and recognizing a voice category by using a voice recognition model; synchronously acquiring facial micro-expression feature points, voice rhythm features and head, neck and shoulder vibration frequencies of the evaluated object; and generating a semantic vector from the object / scene label through a semantic embedding model. According to the psychological state assessment method based on environmental perception, through three core innovations of quantitative modeling of environmental semantics, causal reasoning and a dynamic attention mechanism and personalized adaptive calibration, the neglect limitation of traditional psychological assessment on environmental factors is broken through, and the accuracy, robustness and practicability of psychological state assessment are remarkably improved.

The invention discloses a premature infant mother psychological intervention effect assessment method and system, and relates to the technical field of psychological assessment. A premature infant mother psychological intervention effect evaluation system comprises a data arrangement module and an effect evaluation module. By analyzing the behavior analysis data set and the face analysis data set of the evaluated mother at the same time, the psychological state of the mother can be comprehensively evaluated from multiple angles; the behavior analysis model and the face analysis model respectively provide independent evaluation of behavior performance and emotional response, so that the evaluation result is more comprehensive and accurate, and the emotional fluctuation and psychological change of the mother and the response to the premature infant can be effectively identified; through multi-level and multi-dimensional behavior analysis, the mood, psychological stress and behavior mode of the mother are deeply recognized, the behavior mode of the mother is considered, the internal mechanism of the mood can be deeply discussed, and therefore powerful data support is provided for psychological intervention.

The invention relates to the field of psychological health assessment, and discloses an interactive psychological assessment method, device and equipment and a storage medium. The method comprises the following steps: converting a question text in a DSM-5 psychological assessment question bank into a corresponding question audio through a text-to-speech model; driving the virtual character image according to the question audio and the question text, and transmitting the question audio to the user; obtaining an answer audio fed back by the user according to the question audio, and converting the answer audio into a corresponding answer text through a voice recognition model; obtaining a face image when the user answers, and obtaining an emotional state of the user through a multi-modal model according to the face image and the answer audio; according to the emotional state and the answer text, a model is generated through voice, and the virtual character image is driven to conduct co-situation reply. In the embodiment of the invention, the interactivity of evaluation can be increased, and the user can be effectively guided to express real emotions, so that the effectiveness and the accuracy of an evaluation result are improved.

The invention relates to the technical field of psychological assessment, in particular to a psychological health assessment method based on VR (virtual reality), which comprises the following steps: based on virtual scene event nodes, analyzing event types, interaction states and priorities, screening adaptive nodes, adjusting an acquisition window, judging amplitude variation of brain waves, identifying segmentation moments, and combining extreme values and response intervals. And matching a high-risk reference, and classifying psychological risk indexes. According to the method, through dynamic mapping of user interaction behaviors and virtual situation events, whole-course closed-loop management of data streams is achieved, an acquisition window is adjusted in a linkage mode according to multi-source parameters, signal segmentation is defined in real time according to actual brain wave motion and a scene cognitive state, brain wave extreme values and behavior response time sequences are synchronously extracted, and coupling analysis is conducted on multi-dimensional features; dynamic grouping of psychological risks is jointly set based on multiple index intervals, timeliness guarantee is obtained for data in a high-frequency interaction scene, and an evaluation result can reflect continuous evolution of psychological states of a user in a complex environment.

The invention relates to a high-precision multi-modal psychological normal form assessment method and system. The method comprises the following steps: constructing and training a multi-modal psychological normal form assessment model; preprocessing the to-be-detected data; performing long-range dependency relationship modeling on the coding result to obtain an enhanced single-mode coding result; performing feature fusion on the enhanced single-modal coding result to obtain a fused modal feature, and optimizing the fused modal feature; carrying out classification evaluation of a psychological normal form of multi-modal input on the optimized modal features to obtain a multi-modal evaluation result; and performing classification evaluation of the psychological normal form of single-mode input on the enhanced single-mode coding result to obtain a single-mode evaluation result. According to the method, high robustness is shown in multi-modal sentiment analysis, the calculation cost is controllable, and a reliable solution is provided for actual deployment of the multi-modal psychological assessment technology.

The invention discloses an intelligent psychological sand table assessment and healing system based on VR, and relates to the technical field of psychological assessment and healing. A VR-based intelligent psychological sand table assessment and healing system is characterized in that a user side comprises a VR head-mounted display device, a spatial positioning and gesture interaction module and a virtual sand table scene generation engine, and a system terminal comprises a user behavior data acquisition and analysis module, an intelligent analysis and assessment engine and an immersive healing guide module. According to the invention, the regional limitation is broken through the virtual reality technology, the efficient and personalized psychological healing service is provided, the deficiency of professional resources in low-resource regions is made up, the psychological health intervention effect is improved, and the improvement of the overall social psychological health level is facilitated. The system adopts a modular design, is easy to expand and maintain, supports simultaneous online of multiple users, ensures data security and privacy protection, is suitable for multiple scenes such as schools, communities and medical institutions, effectively reduces psychological assessment and healing thresholds, and promotes popularization of psychological health.