15 results about "Mental analysis" patented technology

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 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.

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.

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.

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

The invention relates to the technical field of artificial intelligence and psychology crossing, in particular 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; the three types of training data sets are subjected to synonym replacement, scene generalization and verbal skill rewriting strategy data enhancement; executing four-stage model training; synchronously collecting sand tool operation, facial expression, behavior and voice response data based on a large language model, synchronously integrating a multi-modal data set according to a timestamp, and training a psychological analysis model; and based on interpretability analysis of a psychoanalysis model screening result, extracting a model attention weight and a feature importance score, performing attribution analysis on sand table image, audio and video data, and generating a text analysis report. According to the method, subjective psychological motivation is deeply mined through dynamic interaction, deep fusion analysis of multi-modal data is realized, an interpretable analysis report is provided, and the method is suitable for depression risk screening of large-scale crowds.

The invention relates to the technical field of electric digital data processing, in particular to the technical field of information auxiliary management, and particularly relates to an information auxiliary management method and system applied to human resources. Inputting the feature data set of the employee into an employee psychoanalysis model to obtain an emotional state analysis result of the employee, and giving an adjustment suggestion of the employee; acquiring a virtual scene feature data set of the employee; according to the virtual scene feature data set of the employees, determining a collaboration capability score value of each employee; and according to the emotional state analysis results of the employees, the cooperation ability score value of each employee and the adjustment suggestions of the employees, obtaining an optimized employee incentive rule and executing the optimized employee incentive rule. The physical and psychological health of the employees is guaranteed, the cohesion of the employees to a company is improved, the incentive rules of the employees are more personalized, the ability of the employees to adapt to complex scenes is improved, and meanwhile the competitive advantages of teams in different environments are improved.