75 results about "Psychological intervention" patented technology

Aiming at the problems of insufficient language understanding depth, weak personalized dialogue generation ability, lack of continuous learning and long-term user state modeling and the like in the current emotion recognition and psychological intervention technology, the invention provides a user emotion recognition and psychological intervention method combined with a large language model (LLM). According to the method, the potential emotional state is identified by analyzing free text information input by a user by utilizing the powerful capabilities of a large language model in the aspects of natural language understanding, emotional modeling and text generation; constructing a multi-round dialogue context, and reasoning a psychological change trend of the user; in combination with a psychological knowledge base, personalized and mild psychological intervention dialogue content with a dredging effect is generated. The system supports recognition and classification of various emotional states such as depression, anxiety and alonity, is suitable for various interaction scenes (such as APPs, webpages and social robots), and can greatly improve the precision of emotion recognition and the timeliness and effectiveness of psychological intervention. The emotion recognition and psychological intervention method based on the large language model provides solid technical support for constructing an intelligent, continuous and personalized psychological health management system, and has wide application prospects and profound social significance.

The invention discloses a Multi-agent-based psychological counseling platform and method. The counseling platform comprises an evaluation agent used for dynamically extracting psychological features based on dialogue behaviors of a visitor agent and updating results to a traits library module; the planning agent is used for constructing a personalized psychological counseling scheme based on the traits library module and dynamically adjusting a counseling process and a strategy according to counseling feedback; the consultant agent is used for carrying out dialogue interaction with the visitor agent according to the personalized consultation scheme and implementing emotion pacification and psychological intervention; the visitor agent is used for expressing psychological troubles, feeding back psychological state changes and promoting the consultation process; the historical dialogue long and short-term memory module is used for storing multiple rounds of psychological counseling interaction contents and comprises historical dialogue short-term memory and historical dialogue long-term memory; and the dynamic probability memory retrieval module is used for generating probability distribution based on the current consultation context and dynamically calling memory nodes from the historical dialogue long and short term memory module or the traits library module.

The invention discloses a psychotherapy and healing robot based on high human emotion fitting degree simulation analysis, and the robot comprises a multi-mode perception layer which is used for collecting the interaction data of physiology, movement and environment; the multi-modal sensing layer comprises a heterogeneous data acquisition module, a spatial-temporal feature extraction network and an attention fusion mechanism module; the dynamic decision-making layer is used for generating an intervention strategy based on the interaction data; the dynamic decision-making layer comprises a reinforcement learning strategy engine and a hierarchical intervention selection tree; the generative interaction layer is used for generating a co-estrus response conforming to ethical specifications based on the intervention strategy; the generative interaction layer comprises an ethical constraint system and an emotional response generator; the brain science verification layer is used for monitoring neural feedback in real time through EEG and adjusting an intervention strategy; and the brain science verification layer comprises a neural feedback regulation module and a multi-mode feedback design module. Therefore, a precise and personalized psychological intervention decision closed loop is provided, and the defects of an existing AI psychological product in the aspects of emotion recognition, intervention strategies and effect quantification are overcome.

The invention relates to a clinical psychological treatment effect evaluation method and system based on machine learning, and the method comprises the steps: obtaining biological signals, behavior patterns and psychological state data of a patient during treatment, constructing a three-dimensional tensor structure with aligned timestamps, and carrying out the standardization of the three-dimensional tensor structure to generate a multi-dimensional data matrix; dimensionality reduction, reconstruction and verification are carried out on the matrix through a deep auto-encoder network, and unified feature vector representation is output; utilizing an improved support vector regression algorithm to establish a nonlinear mapping model of the feature vector and the curative effect score; according to the method, the curative effect score is predicted in real time, when the score is abnormal or fluctuation exceeds a threshold value, a personalized treatment scheme optimization mechanism based on the knowledge graph is triggered, deep fusion of multi-source heterogeneous data is achieved, evaluation precision and treatment adaptability are improved through a dynamic optimization mechanism, and intelligent decision support is provided for clinical psychological intervention.

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 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 provides a remote rehabilitation system for a stroke patient, relates to the technical field of stroke rehabilitation, and aims to remotely diagnose the patient, periodically generate a personalized rehabilitation scheme for the patient, and timely adjust and update a training scheme according to the exercise effect of the patient. The system comprises a data acquisition terminal, a data transmission terminal, a control terminal, a doctor monitoring terminal and a patient terminal, a personalized rehabilitation training scheme generation algorithm is applied, multi-dimensional data is fused to form a comprehensive feature vector, and rehabilitation potential and requirements are evaluated. Personalized schemes covering exercise, cognition and psychological intervention are customized for the patient, dynamic adjustment is conducted according to feedback, and precise rehabilitation is achieved. The system has the functions of real-time monitoring, intelligent reminding and abnormity early warning, the rehabilitation effect is optimized, the medical burden is relieved, the life quality of patients is improved, and the system is suitable for medical institutions at all levels.

The invention discloses a mental health monitoring and nursing robot with body-multi-dimensional intelligent cooperation. The robot comprises a mobile robot platform equipped with a differential driving chassis, a laser SLAM navigation module and the like; a multi-mode sensing network integrating an RGB-D depth camera, a thermal imager and the like processes data in real time through an edge computing unit; an intelligent decision-making engine based on a micro-service architecture covers a patrol recognition module, a vital sign monitoring module, a psychological support Transform dialogue model, a multi-modal emotion recognition module and the like; and the man-machine interaction interface is connected through an end-to-end encrypted 5G network. A medicine compliance management module, an RFID medicine box and a privacy protection scheme of medicine taking action recognition and federal learning and differential privacy are further arranged. The method has the advantages that nursing efficiency is improved by more than 40%, adverse event occurrence rate is reduced by 35%, psychological intervention coverage rate is improved, medicine taking compliance is improved, sublingual Tibetan medicine detection rate is improved to more than 95%, data privacy is safe and controllable, and intelligent upgrading of mental health nursing is promoted.

The invention relates to the technical field of psychological intervention adjustment, in particular to a dynamic structured self-adaptive training method which is applied to a training framework comprising an acquisition terminal, a processing terminal and an execution terminal. The acquisition terminal is used for acquiring a physiological signal, a behavior signal and an environment context of an individual, the processing terminal fuses the information and calculates an anxiety index and an uncertainty probability value, and when the uncertainty probability value is lower than a preset threshold value, an initial task graph is constructed according to a target task and the environment context. The initial task graph is subjected to structure and parameter updating through a preset rule generator in combination with a reward function and an anxiety index, an individualized task graph is generated, cross-age migration is further carried out based on physiological and behavior signals, an execution graph bound with an execution terminal is obtained, and the execution terminal carries out intervention according to the execution graph. The problem that an existing training method is difficult to give consideration to behavior complexity and psychological bearing capacity is solved, and training individuation and stability are improved.

The invention belongs to the technical field of genes, and discloses intelligent wearable equipment for real-time monitoring and intervention of chronic fatigue syndromes. The equipment comprises a user input module, an intelligent screening module, a control center, a dynamic risk assessment module, a health monitoring module, a cloud server, an intelligent scheme generation module, a display module, a sound production module, an intelligent supervision module and an intelligent optimization module. According to the method, through a multi-modal data fusion technology, the accuracy of CFS early recognition is remarkably improved, and clinical verification shows that the screening accuracy reaches 92.3%; due to the innovative dual-mode design (treatment mode / conventional monitoring mode), the system can flexibly adjust the monitoring intensity according to user requirements, and the energy consumption is optimized while the effect is ensured; a cognitive behavior therapy is digitalized, psychological intervention is implemented in an intelligent interaction mode, and user compliance is improved by 56%.

The invention belongs to the technical field of artificial intelligence, and relates to an AI psychological tutoring system with emotion intelligence and privacy calculation double engines, comprising: a data acquisition and fusion module for generating a fusion input stream with time-space alignment; the emotional state analysis module is used for generating a dynamic emotional state matrix; the privacy strategy generation module is used for triggering a privacy calculation engine to construct a differential privacy domain according to the dynamic emotional state matrix and generating hierarchical data grids; the privacy recoding module is used for executing privacy recoding on the fused input stream according to the hierarchical data grids to generate an anti-reverse engineering ciphertext packet; the self-adaptive strategy generation module is used for generating a self-adaptive tutoring strategy tree; and the closed-loop intervention execution module is used for driving the terminal equipment to execute feedback of the self-adaptive tutoring strategy tree and generating a closed-loop psychological intervention flow. According to the invention, the problem that a real-time capture and response mechanism for user feedback is lacked due to the fact that most interaction modes are one-way output is solved.

The invention discloses a psychological assessment and psychological measurement platform, which relates to the technical field of artificial intelligence and comprises a multi-dimensional data acquisition module, a precise measurement and assessment analysis module, a personalized report generation module, a customized psychological intervention suggestion module and a visual presentation module. By integrating various psychological assessment tools and an advanced data analysis technology, comprehensive and accurate psychological health assessment and psychological feature analysis are provided for individuals, measurement and assessment are performed by adopting an advanced multi-dimensional data acquisition mode and combining artificial intelligence and a big data analysis technology, and data processing and analysis functions provided by the platform are more accurate and accurate. A detailed personalized report can be generated in real time, an intelligent evaluation system of the platform can provide customized psychological intervention suggestions according to basic information, behavior data and physiological data input by a user, and the user is helped to understand psychological characteristics and behavior modes of the user more visually in a data visualization mode.

The application belongs to the technical field of virtual reality, and particularly relates to a sound-driven VR serious game interaction control method for semi-blind people. The method comprises the following steps: constructing a 3D sound scene space and a motion guide field, and converting a motion path into a sound change rule; collecting and fusing user pose and physiological feedback signals in real time; dynamically adjusting sound source parameters and tactile feedback according to pose deviation to realize non-visual orientation guidance; performing boundary verification and area determination through ray projection to ensure interaction safety; synchronously processing collision by using a bounding box model and quaternion interpolation; and establishing a mapping model of emotional parameters and sound characteristics to synthesize exciting sound effects. Through multi-modal collaborative interaction, the application significantly improves the perception accuracy and safety of semi-blind users in a virtual space, realizes the cooperation of psychological intervention and motion rehabilitation, and has excellent real-time response capability.

The invention is applied to the technical field of dialogue interaction systems, and particularly discloses an induced dialogue interaction system based on a psychological intervention artificial intelligence model, which comprises a voice recognition module, a deep language module, a voice output module, a closed feedback module and an abnormal condition processing module, the voice recognition module is connected with the deep language module through wireless signals, and the deep language module is connected with the voice output module through wireless signals. According to the induced dialogue interaction system based on the psychological intervention artificial intelligence model, psychological theories such as a social emotion selection theory, a communication adaptation theory and the like are introduced in the system, and an old people age layering optimization deep language model is combined, so that the recognition and fitness reply ability of the model to common emotion expression of old people is enhanced; meanwhile, by means of intervention boundary setting, psychological intervention scenes of the old people are accurately adapted, and intervention safety and effectiveness are guaranteed.

The invention discloses a wake-up method based on expression recognition, a robot and an interaction device capable of performing wake-up control through facial expressions of a user. The wake-up method and the robot are suitable for scenes such as psychological care, accompanying robots, child / old-age auxiliary equipment and the like. The device has multi-modal fusion perception and facial emotion active recognition awakening capability, and can remarkably improve the awakening accuracy, the humanization degree and the technical depth. By integrating an expression recognition awakening mechanism, the naturalness and initiative of man-machine interaction are improved, and the limitation of awakening depending on a single mode such as voice and touch control in the prior art is improved. The robot supports voice wake-up, touch wake-up and button wake-up modes at the same time, and a multi-mode fusion wake-up mechanism is achieved. The naturalness and usability of the psychological support robot in the man-machine interaction process are improved, and the psychological support robot is particularly suitable for non-contact emotion accompanying and psychological intervention of children, old people and language barrier users.

1. The name of the design product: intelligent robot. 2. The use of the design product: intelligent robot for data collection, processing, result display of psychological test, and content display, user interaction and process implementation of psychological intervention training. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses a psychological intervention adaptability training method and system driven by a virtual reality scene, and relates to the field of virtual reality intervention training, and the technical scheme is characterized in that a virtual training scene with configurable parameters is generated according to psychological assessment data; obtaining a second training target vector which is logically complementary with the first training target vector; receiving second behavior data of a second user, and mapping the second behavior data into a virtual role behavior in the virtual training scene corresponding to the first user; and collecting first behavior data of the first user in the virtual training scene, and transmitting the first behavior data to the second user so as to map the first behavior data into a virtual character behavior in the virtual training scene corresponding to the second user. The invention also discloses a method. According to the method, the virtual character can be quickly constructed, the authenticity and the reaction efficiency of the virtual character can be enhanced, the computing resources required for driving the virtual reality scene are reduced, and the skill migration rate can be improved.

The invention discloses an intelligent monitoring method and system for the mental health state of teenagers, and particularly relates to the technical field of mental health monitoring. The method comprises the following steps: collecting emotional response data and intervention feedback data generated by teenager individuals in a psychological intervention process, and constructing an initial psychological state feature sequence; performing quantitative evaluation on a matching effect between the intervention measure and the teenager psychological state based on the initial psychological state feature sequence to obtain intervention measure dynamic effectiveness evaluation index data; obtaining intervention measure utility attenuation trend prediction data and intervention measure instant utility response feature data by analyzing and identifying a long-term interaction change trend and a short-term action effect between the intervention measure and a psychological state; the psychological state matching adaptation degree data is generated through feature combination and optimization, the intervention measures are dynamically optimized, the real-time optimization intervention strategy is output, and the stability and the individualized adaptation degree of the psychological intervention process are improved.

The present application relates to a smart classroom system, comprising: a classroom comprising a public area for a plurality of testees [1] to simultaneously perform psychological assessment and a private area for a single testee to perform psychological intervention; a plurality of pairs of tables and chairs, wherein each table is provided with a first user terminal; the shared information presentation mechanism comprises a main body and an information presentation device arranged on the main body; the wearable virtual reality equipment is used by a testee during psychological intervention; the second user terminal is used by a psychological intervener during psychological intervention; the server generates psychological drama sand table placement information and a first evaluation result in a scene that multiple persons perform psychological evaluation at the same time; in a scene of performing psychological intervention on the testee, the wobble information is respectively sent to the paired second user terminal and the wearable virtual reality device by the server, and the server generates a second evaluation result in response to a second operation of the testee on the psychological drama sand table presented on the wearable virtual reality device.

The invention discloses a psychological stress state assessment method based on multi-knowledge domain information, and relates to the technical field of signal analysis. According to the psychological stress state assessment method based on the multi-knowledge-domain information, key factors are drafted through multiple knowledge domains, multi-modal data are generated in combination with physiological information, psychological information and the key factors, the data analysis confidence is improved, and meanwhile, the psychological stress state assessment method based on the multi-knowledge-domain information is established through a key factor association network and topology analysis mode. According to the psychological stress state evaluation method, the relationship between factors is disclosed, feature selection is optimized, model performance is improved, feature fusion and classification are carried out in cooperation with a deep learning model, the psychological stress state is accurately evaluated, the accuracy and reliability of psychological stress state evaluation are improved, and powerful support is provided for subsequent psychological intervention and treatment.

According to the multi-modal mental health detection method based on thinking chain prompt and feature enhancement, deep semantic information including emotional tendency, symptom expression, hidden metaphor and the like contained in images and texts is deeply mined through thinking chain prompt by using a large model prompt module, so that the detection accuracy is improved; therefore, the analysis capability of the model on the implicit content in the user expression is improved. Besides, information obtained through a large model prompt module is fused by dominant text and image features, so that single-mode key information can be ensured not to be diluted, implicit association between the text and the image can be captured, and information of different modes can be effectively integrated. The method is superior to a current multi-modal large model in identification precision and the like, has high accuracy and robustness, is suitable for various scenes such as early psychological intervention and clinical medical assistance, can effectively monitor the psychological health state of the user, provides technical support for public psychological health detection, and has a good application prospect.

The invention discloses a VR psychological intervention method fusing emotion release and wake-up, and relates to the technical field of VR psychological intervention, comprising the following steps: after a user enters a virtual reality psychological intervention environment, a system synchronously collects physiological signals, voice intonation and facial micro-expression information of the user to obtain multi-modal data; the physiological signals comprise galvanic skin response, heart rate and heart rate variability; based on the multi-modal data, the emotional states of the user are classified, emotional state labels are generated, and the emotional state labels comprise three types of high-negative emotions, low-negative emotions and positive emotions; when the emotional state label indicates that the user is in a high-negative emotional state, an emotional release stage is triggered, the user captures a dark energy ball appearing in a virtual space through gesture interaction and executes a throwing-out action, and the energy ball moves along with a gesture track of the user and explodes and dissipates after the release action of the user is completed.

The invention discloses a carbon behavior quantification method and system based on psychological intervention, and belongs to the technical field of carbon behavior quantification of psychological intervention, and the method comprises the steps: collecting user genes, living habits, psychological states and daily carbon behavior data in real time through household detection equipment and an AI system, and building a dynamic personal database; an AI algorithm is utilized to analyze user data, a personalized psychological health scheme is generated, disease risks and carbon behavior relevance are predicted, potential disease problems are warned in advance, a user psychological health feature portrait is constructed by utilizing deep learning and a knowledge graph technology, and the disease risks are predicted; identifying potential health risks by associating gene defects, living habits and carbon behavior tracks; a time sequence prediction model is combined to realize early warning of disease tendency; clinical psychology standards and low-carbon behavior guide are integrated, a personalized scheme of psychotherapy healing and carbon emission reduction is generated, the scientificity and adaptability of an intervention strategy are improved, the health risk of a user is reduced, and sustainable behaviors are guided.

The invention relates to the technical field of psychological intervention and tactile interaction, in particular to a group psychological sand table somatosensory interaction device based on tactile interaction, which comprises a pressure dynamic fingerprint acquisition unit and a dynamic adjustment feedback unit. A pressure dynamic fingerprint containing a pressure topological structure variation index and a pressure gravity center migration acceleration is obtained, a dynamic adjustment feedback unit inputs the pressure dynamic fingerprint into a lightweight space-time diagram convolutional network optimized by adversarial training, synchronously outputs an operator identity label and an operation intensity level, activates a corresponding wrist strap tactile feedback device, dynamically adjusts parameters, and outputs a corresponding wrist strap tactile feedback result. When the intensity is low, high-frequency micro-vibration is triggered, when the intensity is high, progressive pressure waves are triggered, when the similarity of two sand tool pressure fingerprints exceeds a threshold value, freezing is carried out, then a sand tool feedback channel is operated, and the equipment improves feedback accuracy and interaction orderliness and is suitable for group psychological sand table treatment.

The application discloses a psychological intervention method and system based on dynamic intention routing and thought chain reasoning, and belongs to the technical field of artificial intelligence and mental health. The method comprises the following steps: performing feature scanning on user input through a double-track detection mechanism composed of a semantic similarity model and a sensitive word matching algorithm, and generating an emotional tendency score and a crisis risk weight; comparing the scanning result with a preset threshold, and shunting to a red early warning, yellow intervention or green general path; triggering a three-level early warning action for the red path; starting a thought chain reasoning engine for the yellow path, sequentially calling multiple logic operators, and generating a step-by-step traceable intervention strategy; calling a general dialogue engine for the green path; and dynamically adjusting the guidance intensity and the level of empathy based on user feedback. The application realizes millisecond-level recognition and forced interruption of high-risk intentions, ensures the professionalism and interpretability of the intervention process through structured reasoning, and significantly improves the safety, professionalism and response efficiency of the psychological intervention system.

The application discloses a virtual reality scene driven psychological intervention adaptive training method and system, relates to the virtual reality intervention training field, and has the technical scheme as follows: a virtual training scene with configurable parameters is generated according to psychological evaluation data; a second training target vector with logical complementarity with the first training target vector is acquired; second behavior data of a second user is received, and the second behavior data is mapped into virtual role behavior in a virtual training scene corresponding to the first user; first behavior data of the first user in the virtual training scene is collected, and the first behavior data is transmitted to the second user, so that the first behavior data is mapped into virtual role behavior in a virtual training scene corresponding to the second user. The application can not only quickly construct a virtual role, but also enhance the authenticity and reaction efficiency of the virtual role, reduce the required computing resources of the virtual reality scene driving, and improve the skill transfer rate.

The application provides an artificial intelligence-based postoperative rehabilitation nursing system for the elderly, and relates to the field of intelligent nursing, which first encrypts and normalizes the collected emotional log data set of the target elderly object to obtain the time sequence distribution of the encrypted emotional log, then uses an artificial intelligence-based data analysis method to summarize the content and embed the semantics of the time sequence distribution of the encrypted emotional log to obtain the time sequence distribution of the emotional log summary semantic features, and obtains the emotion recognition result based on the context causal correlation coding features of the time sequence distribution of the emotional log summary semantic features, and finally judges whether to generate a psychological intervention prompt signal based on the emotion recognition result. In this way, by continuously monitoring and analyzing the emotional fluctuations and laws of the elderly, it is helpful to more accurately capture the emotional state, and thus improve the timeliness, effectiveness and intelligent degree of psychological intervention.

The invention provides a large model interaction system based on a cognitive behavior therapy, relates to the technical field of large model interaction, and realizes specialized intelligent intervention based on the cognitive behavior therapy by integrating a cognitive challenge technology library, a process modeling module, a double-track agent collaboration module and a quantitative evaluation module. Wherein the process modeling module is used for calling a structured cognitive reconstruction technology, dividing the whole process of the cognitive behavior therapy into stages with definite quantitative switching standards, and ensuring the continuity and target orientation of the therapy; the double-track intelligent agent works cooperatively, the dialogue interaction intelligent agent guides a user to complete a task in a natural language, and meanwhile, the process evaluation intelligent agent evaluates information quality and a target achievement condition in real time to realize dynamic process regulation and control; the quantitative evaluation module generates a quantifiable improvement signal through multi-dimensional scoring, and provides an objective basis for completion degree judgment and process promotion of each stage of the whole process of the cognitive behavior therapy, so that the normalization and effectiveness of psychological intervention are improved.

The invention provides a self-adaptive psychological intervention system and method based on emotional state recognition, and belongs to the technical field of information and communication specially used for treating or processing medical or health data. The system comprises a multi-modal emotion recognition module, a hybrid retrieval sequencer, a multi-modal generation controller and an emotion migration control module, the multi-modal emotion recognition module is used for capturing the real-time emotion state of the user according to the multi-modal data; the mixed retrieval sequencer is used for dynamically generating a metadata filtering condition according to the emotional state of the current dialogue round of the user; on the basis of the metadata filtering condition, a pre-constructed psychological intervention knowledge base is combined to obtain a retrieval result; the multi-modal generation controller is used for converting a retrieval result into an intervention response of emotion coordination; and the emotion migration control module is used for dynamically adjusting an intervention strategy through a deep reinforcement learning strategy. According to the scheme, the emotion mismatching problem existing in an existing psychological intervention system can be relieved, and accurate psychological intervention is achieved.