37 results about "Mental analysis" patented technology

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 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 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 relates to the technical field of health assessment, in particular to a psychological health assessment system and method for old people, and the system comprises a psychological monitoring module, a psychological analysis module, an adjustment strategy module and an intervention execution module. According to the method, the behaviors of the old people are monitored, data are recorded, abnormal indexes of the psychological state are accurately analyzed, the behaviors are matched with the psychological state through the psychological mode atlas, the accuracy of psychological health assessment and the response speed to changes are greatly improved, and the psychological health can be effectively monitored and timely adjusted by adjusting assessment parameters in real time; after the optimized psychological state data is deeply analyzed, the tuning effect can be more accurately evaluated, personalized psychological intervention measures are provided for the elderly, the personalized degree of the intervention measures is enhanced, the individual requirements are better met, and by analyzing feedback in the intervention period and recognizing key change points, the optimization effect is improved. And the accuracy and the effect of mental health intervention are obviously improved.

The invention belongs to the technical field of multi-modal information processing, and particularly relates to a multi-modal emotion recognition method, which can give consideration to modal generality and modal difference at the same time, realizes adaptive fusion between modals, and is suitable for emotion understanding and analysis of video, voice and text multi-source data. Comprising the following steps: 1, preprocessing a CMU-MOSI data set and a CMU-MOSEI data set to generate training data; 2, processing data by adopting a pre-training encoder to obtain a high-quality initial feature sequence; 3, inputting each modal initial feature into a sharing and private coding unit through a feature decoupling module, and respectively obtaining a cross-modal public emotion sharing feature and a modal specific emotion private feature; according to the multi-modal emotion recognition method provided by the invention, the emotion recognition capability is remarkably improved, and effective data support can be provided for scenes such as psychological analysis, medical assistance and human-computer interaction.

The invention, which relates to the technical field of artificial intelligence, discloses an AI-driven student behavior analysis and early warning system comprising a behavior data acquisition module, a behavior feature extraction module, a psychological analysis module, a psychological pre-diagnosis module, a psychological health management module and a map drawing module. The behavior data acquisition module acquires physiological and spatial trajectory data of students, the behavior feature extraction module extracts physiological rhythm and behavior pattern features, the psychological analysis module analyzes psychological stress indexes and social behavior abnormality, and the psychological pre-diagnosis module generates psychological health risk indexes. The psychological health management module implements graded early warning and closed-loop feedback, and the map drawing module performs multi-dimensional visual monitoring. Through the multi-modal data fusion and deep learning technology, real-time accurate analysis of student behaviors is realized, the early warning threshold is dynamically optimized, multi-dimensional visual support is provided, the psychological health problem recognition accuracy is remarkably improved, education managers are assisted in timely intervention, and physical and psychological health development of students is promoted.

The invention provides a psychological counseling auxiliary system. The system comprises a psychological analysis module, a psychological counseling resource library, a recommendation module and an interactive interface module, the psychoanalysis module is used for receiving voice data and image data of the user in multiple rounds of dialogues and analyzing keywords in the voice data and the image data and an emotional state of the user; the psychological counseling resource library is used for storing psychological counseling resources; the recommendation module is used for providing psychological consultation suggestions and resource recommendation for the user according to historical data, keywords and emotional states of the user; and the interactive interface module is used for displaying the recommended psychological counseling suggestions and resource recommendation. Based on the natural language processing technology and the emotion recognition technology, the method can improve the insight in the psychological state of the user in the consulting process, provides accurate psychological assessment in combination with voice, text and expression analysis, solves the limitation of the existing traditional consulting tool, improves the professional property of psychological consulting, and improves the consulting efficiency. And the working efficiency is improved.

The invention relates to the technical field of psychological analysis, in particular to a user psychological state analysis method and system based on an intelligent robot. The method comprises the following steps: carrying out dynamic interaction with a user based on an intelligent robot, collecting a real-time interaction video of the user, and obtaining physiological state parameters of the user through a sensor; performing image optimization on the user real-time interaction video, and constructing a filtering optimization interaction video; performing user dynamic micro-expression analysis on the filtering optimization interaction video to obtain user deep micro-expression state features; performing dynamic limb behavior feature mining on the filtering optimization interaction video to generate personalized limb behavior features of the user; performing time sequence fluctuation trend fitting on the physiological state parameters of the user so as to construct a physiological state fluctuation trend curve; and performing user emotional state analysis on the personalized limb behavior characteristics of the user based on the deep micro-expression state characteristics of the user to generate a user emotional evolution rule. According to the invention, efficient and accurate psychological state analysis is realized.

The invention discloses an employment psychological analysis model construction method and an employment psychological analysis method, and belongs to the field of artificial intelligence, and the method comprises the steps: distributing a corresponding dynamic distribution weight for each psychological traits dimension according to a center vector of each psychological traits dimension and an original embedded vector of each word, combining the projection matrix and the original embedded vector of each word to generate a characteristic projection embedded vector of each word; calculating an intensity score vector of each psychological traits dimension according to the traits projection embedding vector of each word in combination with high and low expression intensity reference vectors, and adjusting a universal language model in combination with a position coding vector, the traits projection embedding vector and an attention head output vector; and training the adjusted model by using the employment psychological assessment question and answer data set to obtain an employment psychological analysis model. By implementing the application, the problem that a general language model in the prior art cannot decouple the employment psychological dimensions of the college students and cannot capture the employment psychological traits of the college students can be solved.

The invention discloses a cognition improving system and method based on a drawing therapy. The cognition improving system comprises an evaluation module which is internally provided with a pre-training model and a comparison unit so as to interpret painting works and compare and analyze data; the cognitive learning module comprises a voice unit and a learning unit and is used for forming a personalized cognitive learning scheme according to user selection on the basis of preset cognitive painting works; the practical operation training module comprises a theme practical operation unit and is used for forming a personalized practical operation training scheme according to a preset practical operation painting work and user selection; and the feedback module is used for pushing the personalized cognitive learning scheme and the personalized practical operation training scheme to the user for cognitive learning and practical operation training, so that the cognitive ability of the user for psychological analysis of the cognitive painting works is improved.

A multimodal human behavior and psychological analysis platform based on generative artificial intelligence includes: a multimodal behavior data input module that receives data from multiple sources from users to establish a correlation between behavior and psychological state; a behavior and psychological analysis module that generates a psychological state scale based on the user's data from multiple sources and the correlation between behavior and psychological state; a game adaptation module that adjusts the game difficulty in real time to adapt to the correlation between the user's behavior and psychological state; an image story generation module that generates a story progression plot in real time to adapt to the correlation between the user's behavior and psychological state; an analysis and suggestion module that generates a psychological state change trend chart and psychological analysis assessment suggestions based on the user's data from multiple sources and the psychological state scale; and a report generation and progress tracking module that generates a psychological analysis assessment report for the user based on data from multiple sources, the psychological state scale, and the psychological analysis assessment suggestions, and adjusts personal goals in real time to adapt to the user's progress feedback.

The invention relates to the technical field of psychological analysis, and discloses a psychological real-time analysis method through facial micro-expressions and limb behaviors. A user real-time dynamic acquisition module, a user real-time dynamic preprocessing module, a user psychological real-time analysis module, a user psychological real-time evaluation module and a user mentality improvement module are arranged in the model, the user real-time dynamic acquisition module acquires original data, and the user real-time dynamic preprocessing module preprocesses the acquired original data. The user psychological real-time analysis module calculates a facial micro-expression comprehensive characteristic value, a limb behavior comprehensive characteristic value and a comprehensive mood index by using original data obtained in real time and combining user historical data, and the user psychological real-time evaluation module evaluates the current mood of the user according to the calculation result. And the user psychological state improvement module provides personalized psychological state improvement measures according to the current psychological assessment result of the user in combination with the current environmental conditions and the personal information of the user.

The present application relates to the technical field of artificial intelligence and psychology, and particularly relates to a digital sand table multi-modal data analysis method based on an intelligent chat robot, which comprises the following steps: constructing a knowledge-enhanced large language model architecture; using synonym replacement, scene generalization and dialogue rewriting strategy data enhancement on three types of training data sets; executing four-stage model training; synchronously collecting sand tool operation, facial expression, behavior and voice response data based on the large language model, synchronously integrating the multi-modal data sets according to timestamps, training a psychological analysis model; based on the explainability analysis of the screening results of the psychological analysis model, extracting the model attention weight and feature importance score, and performing attribution analysis on the sand table image, audio and video data to generate a text analysis report. The method can deeply mine subjective psychological motivation through dynamic interaction, realize deep fusion analysis of multi-modal data, and provide an explainability analysis report, and is suitable for depression risk screening of a large number of people.

The invention discloses a psychological health state projection assessment method and system based on AI recognition, and relates to the technical field of psychological health assesses.The method comprises the steps of analysis model construction, user psychological analysis and group psychological analys.The method comprises the steps that firstly, house tree person data of historical users without external intervention are collected through analysis model construction; building a fusion data AI analysis model through distributed GPU cluster training, then collecting house tree person drawing and dynamic behavior data of a target user and model output system state data through user psychological analysis, analyzing dynamic behaviors to obtain a psychological positive feedback coefficient, and outputting a psychological level after verification; and finally, through group psychological analysis, analyzing the state change of a target user system to identify an abnormal psychological state, summarizing user group data, and performing early warning according to the focused attention state when the user group is abnormal, objective and efficient evaluation is realized through AI, the precision is improved through two-dimensional verification, and the method is used for supporting individual and group psychological health management and control.

The application provides a psychological evaluation method and device, electronic equipment and product. The method is based on historical interaction data and user feedback corresponding to scale questions of a current question and answer round, modifies scale corpus to obtain updated scale corpus, and determines scale questions of the next question and answer round from the updated scale corpus. After the question and answer ends, psychological analysis is performed based on scale questions of each question and answer round, scale original questions corresponding to each scale question, and user feedback corresponding to scale questions of each question and answer round, to obtain a psychological evaluation result of the user. The scheme can automatically determine scale questions for asking and automatically perform psychological analysis, realize automatic psychological evaluation, and improve the psychological evaluation efficiency. Furthermore, the scale questions are modified based on historical interaction data and current user feedback, so that the scale questions are more suitable for the user, thereby improving the user experience of psychological evaluation.

According to the child painting psychological analysis and guidance method based on artificial intelligence, image processing and artificial intelligence analysis are carried out on the child painting work, the psychological state of a child is objectively evaluated, and a corresponding guidance scheme is provided. The method improves objectivity and efficiency of psychological analysis, and can be widely applied to the field of child psychological health.

This invention discloses an information processing method and apparatus for psychological crisis screening, comprising the following steps: acquiring group behavioral characteristic information of students through information collection devices installed on campus; determining the preliminary psychological risk level of an individual based on the acquired group behavioral characteristic information; when the preliminary psychological risk level of an individual exceeds a set threshold, performing precise analysis on the individual characteristic information, extracting multimodal specific features and performing time-series modeling to determine the precise psychological risk level of the individual; when the precise psychological risk level exceeds a set threshold, focusing on the abnormal behavior areas of the individual through a heatmap visualization model, generating an abnormal behavior report containing the abnormal behavior areas, psychological risk level, and determination criteria, and sending the behavior report to the administrator for reminder. This invention achieves low-cost, low-intrusive acquisition of behavioral information for psychological analysis.

The invention discloses an interactive multi-modal artificial intelligence psychological behavior assessment method and system based on drawing analysis. The method comprises the steps that multi-modal data are synchronously collected, static drawing data, dynamic behavior data and physiological signal data of a user in the drawing process are obtained, and time alignment is conducted on the multi-modal data; analyzing the collected multi-modal data, feeding back an analysis result to the user in a suggestion or question form, then executing the data collection stage again to grasp a reaction result of the user to the suggestion or question, analyzing the collected multi-modal data, and then executing a fusion analysis stage; performing fusion analysis on data of three dimensions of static drawing, dynamic behaviors and physiological signals to generate a multi-modal feature representing a comprehensive psychological state of the user; and according to the multi-modal features representing the comprehensive psychological state of the user, in combination with psychological knowledge and a database, generating and outputting relative reports among individuals and psychological portraits in the individuals after multiple times of evaluation of the user by utilizing a natural language generation model. Starting from multiple dimensions, the defects of the current drawing psychological analysis technology can be effectively overcome, and the accuracy of psychological assessment is improved.

The invention relates to the field of psychological analysis, in particular to a multi-source data acquisition method for sand table psychological assessment, which comprises the following steps: firstly, acquiring multi-source data and marking a timestamp, then extracting a person and a moving track thereof by using a multi-target tracking algorithm, positioning a face area and matching person information; the method comprises the following steps: constructing an expression extraction model and an expression recognition model, recognizing an expression sequence based on the expression extraction model and the expression recognition model, ensuring the synchronism of multi-source data in time and space through data alignment, finally constructing a multi-modal fusion model by using deep learning, integrating the multi-source data, and judging whether data acquisition fusion is qualified based on the sum of key principal component interpretation ranges. And relevant parameters are corrected according to abnormal reasons when the product is unqualified. The acquisition method provided by the invention effectively solves the problem that the existing method is insufficient in data acquisition precision in a multi-person entity sand table scene, provides more accurate data support for sand table psychological assessment, and remarkably improves the accuracy of data acquisition.

The application relates to the technical field of data processing, and provides a psychological disease analysis method and system based on a micro-expression large model. Based on an acquired sympathetic nerve activation rate, a data sampling frequency is determined to acquire micro-expression data of a user's face; a first tensor is generated based on the micro-expression data and homodyne analysis is performed to generate a multi-dimensional topological structure, and attribute parameters and a topological parameter set of the topological structure are analyzed; a psychological state model representing a mapping relationship between micro-expression and psychological state is constructed based on the topological parameter set, nonlinear processing is performed on features of adjacent nodes in the psychological state model to generate feature representation and symptom contribution degree, so as to construct a psychological state atlas; and based on the psychological state atlas, a psychological analysis result and intervention suggestions are generated. The discrete psychological state nodes are converted into a weighted correlation network, the accuracy of the correlation representation between the expression and the psychology is enhanced, and the objectivity and accuracy of the psychological analysis are improved.

The application relates to a psychological state detection method, system, device and storage medium, and belongs to the technical field of psychological measurement. The method comprises the following steps: acquiring image features and sound features, wherein the image features represent behaviors and / or expressions of a to-be-tested person in a detection process, and the sound features represent sounds and / or languages spoken by the to-be-tested person in the detection process; inputting the image features and the sound features into a preset psychological detection model to obtain psychological detection data; and determining a psychological detection result of the to-be-tested person according to a preset result comparison table and the psychological detection data. The application has the effect of improving the accuracy of psychological analysis conclusions.

To provide a technology for accurately performing feedback necessary for securing safety of a worker in delivery work.SOLUTION: The behavior extracting unit 13 monitors a worker who performs delivery work using a vehicle, and determines whether or not a safety behavior, which is a behavior for ensuring the safety of the work, is appropriately performed, thereby extracting an inappropriate safety behavior as an unsafe behavior. The psychological analysis unit 14 estimates the psychological state of the worker. The information generating unit 15 generates feedback information including the content of the extracted unsafe behavior, the timing at which the unsafe behavior occurred, and the psychological state of the worker estimated by the psychological analysis unit 14. The notification unit 17 notifies at least one of the worker and a manager who manages the worker of the generated feedback information.SELECTED DRAWING: Figure 1

This invention discloses an intelligent psychological state assessment method and system based on multimodal alignment, belonging to the field of psychological assessment technology. The method includes the following steps: S1: Constructing a training sample set for a psychological state assessment model; S2: Preprocessing video data, audio data, and text data in the training data sample set; S3: Utilizing multimodal cross-attention, aligning and fusing text data as the primary modality and video and audio data as auxiliary data for text data to obtain multimodal fusion features for psychological state analysis; S4: Training a psychological state analysis model using the aligned and fused multimodal fusion features; S5: Obtaining multidimensional psychological analysis results of the test subjects through the trained psychological state analysis model. The method of this invention extracts deep multimodal features of adolescents through pre-training a large model and improves the feature representation ability of the data using modal alignment technology.

The present invention discloses an immersive art therapy auxiliary system and an application method thereof, which relates to the field of psychotherapy technology and includes an information collection module, an environment construction module, a psychological analysis module, a program generation module, a model training module and a blockchain recording module. The advantages of the present invention are: generating a quantitative psychological assessment report through multimodal data analysis and a machine learning algorithm, making up for the deficiency of relying on subjective judgment in traditional art therapy; patients can create art in an immersive virtual environment, gain an immersive experience, enhance the sense of participation and effect of treatment, and can dynamically generate personalized treatment plans according to the patient's psychological state and creative behavior, thereby improving the accuracy and effect of treatment. The model training module helps to continuously optimize the psychological analysis model, improve the accuracy and reliability of the model, and enable it to more accurately analyze the patient's psychology in practical applications.

The present disclosure relates to a user psychological analysis system, method, device and storage medium. In the embodiment of the present disclosure, multiple psychological research devices are set up, such as a first psychological research device and a second psychological research device to perform preliminary acquisition of image data, behavior data, emotion data and relationship data, and then upload these data to a data analysis device for analysis to obtain further psychological characteristic data. In this way, further psychological characteristic data can be centrally processed by a data analysis device with more advanced software and hardware configurations. The software and hardware configurations of multiple psychological research devices do not need to be too advanced to achieve the research purpose, and the economic cost of the psychological data research device is also controlled to a certain extent. In addition, data distribution through a unified data analysis device can save communication resources on the premise of achieving interaction between different psychological research devices.

The invention relates to the technical field of deep learning, in particular to a dialogue understanding and psychological analysis method and system based on a psychological health model, and the method comprises the steps: obtaining first dialogue data and first face data; performing feature extraction and fusion on the first dialogue data and the first face data, and updating the fused features into historical context features; generating second dialogue data according to the historical context features; performing feature extraction and fusion on the second face data and the second dialogue data, and updating historical context features; and generating a psychological assessment result according to the updated historical context features. And predicting second dialogue data through the first dialogue data and the historical context features during dialogue. And when the dialogue is completed, predicting a psychological assessment result through the updated historical context features. According to the method, the historical context features fusing the face data and the dialogue data are directly used as input for training, so that the parameter quantity can be greatly reduced.

The invention belongs to the technical field of machine vision, and particularly relates to an efficient micro-expression emotion recognition method, which comprises the following steps of: 1, performing preprocessing operation on SAMM, CASME II and CAS (ME) 3 data sets to generate data for training; 2, dividing the preprocessed data into a training set, a verification set and a test set; the multi-stage multi-scale terrace feature extraction module and the space-time genetic attention module act on an intra-frame feature extraction stage and inter-frame tiny motion perception, so that a network can effectively perceive an area where main features occur and an area where secondary features occur, and loss of micro-expression features is reduced. According to the provided micro-expression emotion recognition model, the micro-expression emotion recognition capability is remarkably improved, and effective data support can be provided for scenes such as psychological analysis, medical assistance and human-computer interaction.

The present invention belongs to the field of psychological monitoring, and discloses a psychological state monitoring method based on virtual reality, including: S1, obtaining the heart rate of the treated person through a physiological monitoring device worn on the treated person; S2, based on the heart rate, using an adaptive update interval to update the number of images taken per second; S3, based on the number of images taken per second, obtaining images containing the treatment person's movements; S4, transmitting the obtained images to a target device. The present invention controls the change in the number of images taken per second through the change in the heart rate of the treated person, and updates the number of images taken per second once after each adaptive update interval, effectively reducing the number of images obtained when the movement changes slightly, and can timely obtain a sufficient number of images when the movement changes significantly, thereby facilitating the improvement of the efficiency of subsequent psychological analysis based on images.