94 results about "Cognitive behaviour" patented technology

The invention relates to the technical field of artificial intelligence, and discloses a multi-agent social network simulation method and system based on a cognitive inference chain, and the method comprises the steps: initializing a multi-agent system comprising a social environment engine, a user portrait engine and a cognitive inference engine, executing a multi-agent social network simulation cycle of a preset round of iteration, in each iteration round, the social environment engine pushes social information to the intelligent agent as external stimulation and activates the intelligent agent to execute an independent decision, the cognitive state of each dimension in the cognitive reasoning chain is updated through large language model reasoning, corresponding social behaviors are generated, and the social behaviors and corresponding cognitive state tracks are recorded; and periodically analyzing historical records to optimize influence coefficients among all cognitive dimensions of the cognitive inference chain, and adjusting an inference strategy of a preset large language model. The simulation of the cognitive process of the intelligent agent is a transparent and traceable evolutionary process, and the complete and understandable simulation of the'observation-cognition-behavior 'cycle is realized.

A method for developing a chatbot for mental health using generative Artificial Intelligence (genAI) and a system for recognition and recommendation are disclosed. The method comprises: designing a conversation flow, creating a flowchart that outlines the logical steps; defining guiding questions and the Depression, Anxiety, and Stress Scale (DASS) examination; fine-tuning large language models with the technical prompt engineering; collecting and labeling data for each model mental health issues detection: ill-being detection model and keyword recognition model; building pipeline and training Artificial Intelligent (AI) model for ill-being detection model and keyword recognition model with a Bidirectional Encoder Representations from Transformers (BERT) model or a pre-train model; collecting and processing mental health support resources such as Cognitive Behavioral Therapy (CBT) exercises, informative articles, inspiring movies, and effective coping strategies, and psychologists; developing mental health support resources system; and developing and integrating speech-to-text and text-to-speech models into the system.

The invention provides an artificial intelligence and cognitive behavior combined depression treatment intervention and early warning system, which comprises the steps of collecting patient interaction data, physiological perception data and third-party data through a dynamic on-demand authorization mechanism, and extracting four-dimensional feature indexes of cognition, emotion, behavior and physiology; constructing a first psychological matrix of cognition, emotion, behavior and physiological dimensions, dynamically adjusting dimension weights by adopting a Bayesian network to generate a second psychological matrix, and fusing weighted feature scores, change rates and historical mean values to output psychological health state vectors; generating a basic scheme group based on the state vector matching treatment strategy library; and calculating the unit time fluctuation intensity of the mental health state vector in real time, and triggering three-level early warning in combination with a self-adaptive Z-score safety threshold. According to the method, multi-modal data fusion analysis, dynamic personalized intervention and active risk prevention and control are realized, and the accuracy and safety of depression management are improved.

The invention discloses an online programming system based on large language model assistance and a teaching recommendation method, the system comprises a base model acquisition module, a problem decomposition module, an abstract modeling module, an algorithm design module, a code analysis and assistance module and an evaluation module, and is used for helping students to finish a programming task of teaching design online. And performing problem decomposition, abstract modeling and algorithm design on actual problems by using a large language model, and solving the problems encountered by students during programming. Based on the system, the invention further designs a teaching recommendation method, multi-modal data in the information classroom teaching process is collected, a dynamic three-level teaching interaction diagram of the space-time environment, knowledge resources and cognitive behaviors is established through man-machine, life and teacher-student interaction behaviors, and accurate teaching recommendation and intervention strategies of the human-in-the-loop are provided. According to the invention, a three-dimensional comprehensive teaching field for learning environment intellectual computing is established in a programming scene, and a guarantee is provided for high-quality modern education development.

The invention discloses a technology for targeted stimulation of a specific brain region and application of the technology in regulation and control of brain functions, and belongs to the field of animal cognitive behavior research. Techniques for targeted stimulation of specific brain regions include insulated stimulation electrodes that can generate AC voltage stimulation and a stimulation device for adjusting the AC voltage intensity and frequency. By applying the technology (ntTMS) for targeted stimulation of the specific brain region, an obvious magnetic stimulation effect can be achieved in the center of the brain region, cerebral neurons of a target region are activated, social and cognitive behaviors of animals are effectively regulated and controlled, and no obvious side effect is brought to experimental animals.

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 provides an intelligent psychological counseling system based on a multi-mode large model and a cognitive behavior therapy, and the system comprises the steps: recognizing voice from a user side through the multi-mode large model, and obtaining text information and emotional state information; analyzing the text information by using a large language model, carrying out conversation with the user side, and extracting psychological state information of the user side from the conversation; a cognitive behavior treatment strategy matched with the user side is determined according to the emotional state information, so that a voice response to the user side is generated according to the matched cognitive behavior treatment strategy by using a multi-mode large model; by combining a multi-modal large model and a large language model, accurate and efficient natural language understanding of a user side is realized, highly anthropomorphic voice response is provided, dependence on professional psychological consultants is reduced, limitation of psychological consultation services on time and regions can be broken through, large-scale consultation service requirements can be met in an all-weather and low-cost manner, and the psychological consultation service experience is improved. The man-machine interaction experience in the consultation process is improved, and high-quality and high-practicability psychological consultation and treatment services are provided.

The invention relates to the technical field of medical treatment, and discloses a patient cognitive impairment recognition method and system and electronic device.The method comprises the steps that patient original data are obtained, and the patient original data comprise clinical biochemical data, image data and cognitive behavior data; preprocessing the original data of the patient to obtain preprocessed data; feature extraction is conducted on the preprocessed data, key features are obtained, and the key features comprise clinical biochemical features, image features and cognitive behavior features; fusing the clinical biochemical features, the image features and the cognitive behavior features to obtain fused features; and determining a cognitive impairment recognition result based on the fusion features and the cognitive impairment recognition function. According to the embodiment of the invention, the early detection rate of cognitive impairment of the pituitary adenoma patient is improved, missed diagnosis and misdiagnosis are reduced, and the early warning cognitive risk when obvious clinical symptoms do not appear in cognitive impairment recognition of the pituitary adenoma patient is reduced.

The invention relates to a construction method for an education prediction large model based on AI students, and the method comprises the following steps: 1, constructing a standard model for learners of 0-100 years old, collecting the cognitive behavior data of real learners, and forming a dynamic data set according to the number of days of age as a unit; 2, extracting a 6-18-year-old K12 stage data subset from the dynamic data set, and forming a standard student model by analyzing learning features; step 3, utilizing a large language model to perform inverse derivation on the dynamic data set and the standard student model, and generating a personalized learning path conforming to individual learning rules and cognitive development; and 4, dynamically adjusting a learning path by adopting reinforcement learning and a Monte Carlo tree search algorithm, and performing path prediction in combination with the starting point of the initial state of the student and the terminal point of the model model knowledge base.

The invention discloses a cognitive behavior training system, method and device and a program product, relates to the field of medical rehabilitation, and is used for solving at least one problem of single training target, single task difficulty and single task element. According to the method, main training tasks of five dimensions are carried out in stages, cognitive competence corresponding to task training of each dimension is progressively carried out step by step, and centralized, continuous, selective, alternate and dispersive attention cognitive competence intervention is respectively carried out. The main training task of each dimension sequentially comprises multiple levels of sub-training tasks with gradually increased difficulty, and each level of sub-training task comprises multiple groups of segmented tasks. And respectively evaluating the training effect under each dimension. According to the method, the difference and compliance of cognitive behavior training are improved, the intervention efficiency is improved, and the long-term intervention effect is ensured.

The invention relates to the technical field of data processing and intelligent environment control, in particular to a sleep environment feedback control data processing method based on cognitive behavior therapy logic, which comprises the following steps: a reference model construction step: acquiring a non-contact multi-mode time sequence signal, and reconstructing a reference signal balance curve to construct a target signal manifold model; a simulation flow generation step of converting the preset interference characteristics into signal modulation operators and injecting the signal modulation operators into the model to generate a simulation signal flow; a double-track difference calculation step: executing double-track difference operation to respectively extract residual features representing system deviation and theoretical interference; a similarity judgment and control step: calculating the topological similarity of the residual features in a time-frequency domain, judging a deviation dominant type, generating a corresponding control instruction, and driving an execution mechanism to act; according to the method, psychological anxiety and environmental discomfort are effectively distinguished by using a double-track differential mechanism, and accurate attribution analysis of sleep interference sources is realized.

The invention discloses a computer-aided old-age language erosion assessment method and assessment system, and relates to the technical field of old-age health assessment, and the method comprises the following steps: S1, collecting the voice data, text input data and interactive behavior data of an old-age user; s2, preprocessing the data, and extracting voice acoustic features, language structure features and cognitive behavior features; s3, inputting the extracted features into a pre-trained language erosion evaluation model, and outputting a language ability score and an erosion type classification result; and S4, generating a visual evaluation report, wherein the visual evaluation report comprises the language ability degradation degree, key obstacle points and intervention suggestions. According to the method, the score and classification result is automatically output through the multi-modal data acquisition and pre-trained deep learning model, so that the evaluation time is greatly shortened, the subjective deviation is eliminated, the result objectivity is ensured, the problems of low manual evaluation efficiency and high subjectivity are solved, and the effect of automatic evaluation is realized.

[Problem] To make it possible to determine whether cognitive behavioral therapy is appropriate. [Solution] An information processing system (2) for assisting cognitive behavioral therapy is characterized by comprising: a start permission inquiry unit (211) that transmits, to a patient, an inquiry as to whether or not the patient can engage in the cognitive behavioral therapy before the start of the cognitive behavioral therapy; and a determination unit (212) that determines whether or not the patient can start the cognitive behavioral therapy on the basis of an input given by the patient in response to the inquiry.

The application belongs to the field of neuropharmacology and medicine, and particularly relates to application of taurine cholic acid in preparation of a drug for preventing or treating Alzheimer's disease. Through animal model experiment verification, the A beta lateral ventricle injection is used to prepare an AD mouse model, and after oral administration of TCA for 2 weeks, cognitive behavior and pathological indexes are significantly improved.

The invention provides a cognitive behavior intervention system assisted by multi-modal artificial intelligence recognition, which can acquire multi-modal information, realize deep feature fusion and analyze a cognitive behavior association mechanism, and comprises the following modules: a multi-modal data acquisition module for acquiring and preprocessing multi-modal data of a depression patient; the feature fusion module is used for extracting features of the preprocessed multi-modal data for feature fusion to obtain a cognitive state feature vector and a behavior mode feature vector; the cognitive behavior association module is used for constructing a cognitive and behavior association model to generate a cognitive behavior analysis report according to the cognitive state feature vector and the behavior mode feature vector in combination with a preset cognitive deviation type library and a behavior trigger factor library; and the personalized intervention module is used for generating a personalized cognitive behavior intervention strategy through a decision optimization algorithm based on multi-feature weighting according to the cognitive behavior analysis report in combination with a preset user basic information library and a cognitive behavior intervention scheme library.

The present invention discloses a knowledge tracing method and system based on a dynamic memory key-value pair network. The method includes: obtaining exercise tags and corresponding exercise difficulties; constructing a knowledge tracing network model including an embedding layer, a key-value pair memory layer, a cognitive behavior layer, and an output layer; training the network model using the exercise difficulty and the exercise tags, and implementing knowledge tracing using the trained network model. The knowledge tracing method based on the dynamic memory key-value pair network proposed by the present invention constructs a knowledge tracing model by integrating cognitive behaviors. This model can trace the impacts brought by cognitive behaviors such as changes in users' knowledge point mastery levels, guesses, and mistakes, thereby predicting users' performances in answering exercises, clustering the exercises based on users' answering records, having good interpretability, being applicable to different types of users, and having a high accuracy rate.

This invention relates to the field of artificial intelligence technology and discloses a multi-agent social network simulation method and system based on a cognitive reasoning chain. The method includes: initializing a multi-agent system comprising a social environment engine, a user profile engine, and a cognitive reasoning engine; executing a multi-agent social network simulation loop with a preset number of iterations; in each iteration, the social environment engine pushes social information to the agents as external stimuli and activates the agents to make independent decisions; updating the cognitive states of each dimension in the cognitive reasoning chain and generating corresponding social behaviors through reasoning using a large-scale language model; recording the social behaviors and their corresponding cognitive state trajectories; periodically analyzing historical records to optimize the influence coefficients between the cognitive dimensions of the cognitive reasoning chain; and adjusting the reasoning strategy of the preset large-scale language model. This makes the simulation of the agent's cognitive process a transparent and traceable evolutionary process, achieving a complete and understandable simulation of the "observation-cognition-behavior" cycle.

The invention discloses an analysis method for observing cognitive behaviors of fishes, and particularly relates to the field of cognitive behavior analysis. The method comprises the following steps: acquiring behavior trajectory data generated by a plurality of fish individuals, and dividing the behavior trajectory data into a fish single behavior reference data set and a mixed behavior original data set; independent analysis of characteristic modes is carried out on the single-behavior reference data set, a single-behavior characteristic threshold database is constructed, multi-dimensional time sequence decoupling is carried out on the mixed-behavior original data set, and mixed-behavior cross interference characteristic data is extracted; performing nonlinear difference analysis on the cross interference characteristic data, and constructing a fish heterogeneous behavior characteristic separation model; performing feature correction on the mixed behavior data set according to a heterogeneous behavior feature separation model, outputting a corrected feature data set of the fish cognitive behavior, and establishing a fish cognitive behavior analysis model to realize behavior pattern recognition and evaluation of the fish under a specific environment or stimulation condition; and the capability of distinguishing multiple behavior modes of the fish under the interference of a complex environment is improved.

An artificial intelligence device according to one embodiment of the present disclosure may comprise: a memory for storing a brain-mimicking artificial intelligence model trained through reinforcement learning; a mental health meter for collecting subject data including a numerical value of memory recall confidence, memory recall accuracy, a numerical value of inference confidence, inference accuracy, learning accuracy, and strategic decision-making bias according to the execution of a meta-memory game of a user; and a processor which acquires a plurality of cognitive behavior numerical values from the subject data by using the brain-mimicking artificial intelligence model, acquires a plurality of brain function estimation signals corresponding to the plurality of cognitive behavior numerical values, respectively, and maps each brain function estimation signal to a brain signal corresponding to a specific brain function.

The invention provides a live broadcast goods carrying scene optimization method and system combined with digital multimedia, and relates to the technical field of digital multimedia, and the method comprises the steps: firstly obtaining the cognitive association data of a live broadcast goods carrying scene, including the commodity cognitive multimedia content, the user cognitive behavior record and the commodity information set; then, based on the cognitive association data, establishing a corresponding relationship between the user cognitive behavior record and the commodity cognitive multimedia content, and generating a cognitive rhythm adaptation sequence; user cognitive behavior records and cognitive stage entries are matched in real time in live broadcast, and the commodity cognitive multimedia content is adjusted according to the adjustment rule parameter set; and collecting user subsequent behavior data during the adaptation period, adjusting the cognitive rhythm adaptation sequence after correlation analysis, generating a digital multimedia cognitive adaptation strategy, and applying the digital multimedia cognitive adaptation strategy to subsequent live broadcast. The live broadcast goods carrying effect and the user experience can be improved.

The invention discloses a traffic law enforcement virtual simulation training method based on a dynamic scene and cognitive evaluation, and the method comprises the steps: generating an initialization parameter according to a trainee portrait and a training target, and driving an emergence type scene generation engine to synthesize a dynamic three-dimensional virtual training scene containing composite illegal elements; in scene operation, multi-modal interaction behaviors and physiological response data of the trainees are synchronously collected to form a data stream; through real-time analysis of the data flow, a cognitive behavior analysis report for evaluating attention, cognitive load and decision intention is generated; constructing a space-time knowledge graph based on the student operation sequence, performing automatic reasoning and contradiction detection in combination with formalized legal rules, and outputting an evidence chain logic verification result; and fusing the report and the result to carry out multi-dimensional weighted evaluation, and generating a comprehensive score and personalized feedback. According to the method, normal form transformation from preset process training to open cognitive evaluation is realized, and the authenticity, pertinence and evaluation depth of training are improved.

A method for providing a cognitive behavioral therapy program based on a large language model according to the present invention may comprise the steps of: providing, to a user terminal, at least one questionnaire related to a cognitive behavioral therapy; and by using response data to the questionnaire received from the user terminal, generating a prompt to be input to a large language model.

The invention belongs to the technical field of exercise psychology and cognitive behavior intervention, and particularly discloses a shadowboxing cognitive intervention method and system based on exercise psychology. The method comprises the steps that historical cognition and emotion data of an intervention object are collected, multi-dimensional state evaluation and grouping are carried out in combination with action execution performance, and then a personalized shadowboxing training scheme and a psychological intervention strategy are formulated. The system dynamically adjusts an intervention path through multi-source data acquisition, action recognition, emotion perception and an intervention effect feedback mechanism, and realizes continuous optimization of a cognitive state. The method and the system can be widely applied to psychological rehabilitation, educational intervention and emotion regulation scenes, and have the characteristics of high intelligent degree, high intervention precision and good adaptability.

The invention discloses a multi-mode mental health intelligent assessment and intervention system for old people. The system comprises a cognitive behavior intervention module, a respiratory training intervention module, a memory intervention module and a group art intervention module. The multi-modal signal acquisition module is used for acquiring multi-modal data of voice, video, physiology and semantics when a user selects the corresponding intervention module to perform intervention; and the unified fusion and evaluation module is used for performing time sequence alignment, feature extraction, feature normalization and feature fusion processing on the collected voice, video, physiological and semantic data, inputting a pre-trained classification model and outputting a mental health comprehensive report and personalized intervention suggestions of the day. According to the multi-mode mental health intelligent assessment and intervention system for the old people, psychological assessment, intervention adjustment and closed loop of feedback reports after adjustment can be achieved, and the authenticity and accuracy of assessment and intervention are improved.

The application belongs to the field of advertisement delivery, and provides an advertisement delivery method and system based on multi-source data analysis, which comprises collecting multi-source original data related to users; identifying multiple cognitive state nodes based on click behavior data and transaction path data; constructing a cognitive behavior causal graph based on the multiple cognitive state nodes, wherein the nodes of the causal graph represent user cognitive states; combining historical behavior samples and path structures in the causal graph, using a Bayesian inference model to predict advertisement response probability and conversion probability of target users, and estimating state transition probability of users from a current state node to a target state node based on different advertisement intervention contents; determining an optimal advertisement intervention path of users from a current cognitive state to an expected conversion state based on the state transition probability and the causal graph structure, and constructing a corresponding advertisement delivery sequence based on the path.

The present disclosure relates generally to the supplementation of butyrate in the diet of mammals. Specifically, the present disclosure relates to a method for supplementing butyrate in the diet of a mammal resulting in improved physiological outcomes through the gut-brain axis, including improvements in anxiety and depression, and other cognitive behaviors, such as brain function, cognitive performance, executive function, stress, sleep, and focus. The present disclosure and methodology demonstrates advantages of administering a direct butyrate generating supplement, to influence the gut-brain axis through two pathways: a first pathway of butyrate generation leading to improvements in gut health which lead to improvements in brain health, and a second pathway of direct butyrate generation in the gut directly leading to improvements in brain health, independent of gut health.

This invention relates to the field of cognitive modeling technology, and particularly to a humanoid intelligent agent framework and method based on a cognitive triangle psychological mechanism. It includes: designing a psychological mechanism intelligent agent, specifically a framework based on a cognitive triangle, in which emotion, thought, and behavior interact to form the agent's cognitive-behavioral structure. For the emotion module, this invention introduces a hierarchical emotion model; for the thought module, this invention introduces a triple network model and reconstructs the existing intelligent agent framework. Compared to previous research, this invention simulates more realistic intelligent agent emotions and thoughts, contributing to the simulation of human-like behavior.

This application provides an emotion regulation system and device with an adaptive withdrawal mechanism. The system includes: a sensor module for collecting physiological and motor data; a state confirmation module for determining emotional dysregulation based on a stress characteristic model; and an interaction module for initiating a hierarchical cognitive-behavioral guidance process upon determining emotional dysregulation, including at least: a basic intervention stage, which sequentially generates sensory anchoring, value clarification, and behavioral activation guidance instructions, with each subsequent instruction conditionally dependent on the execution feedback of the preceding instruction; and a deep review stage, activated after the basic intervention stage, which outputs structured review guidance for the emotional dysregulation event and generates cognitive reconstruction instructions based on user responses to update cognitive representations. The adaptive withdrawal module generates a self-regulation success rate based on continuous interaction results, dynamically reducing the sensitivity of the state confirmation module accordingly to guide the user to gradually develop independent emotional self-regulation capabilities, ultimately freeing them from dependence on the device.

The application discloses a kind of multilevel geometric entity cognitive behavior modeling method, device and medium, belong to computer-aided path field.The method includes: in the part modeling stage, interactive feature pair (IFP) is associated, and the belief-desire-intention cognitive behavior model of multilevel geometric entity is established based on interactive feature pair;Wherein, multilevel geometric entity includes basic interactive feature pair (B-IFP), composite interactive feature pair (C-IFP) and part;According to the belief-desire-intention cognitive behavior model constructed, the part with cognitive ability realizes assembly path planning process autonomously.The application establishes the method of multilevel geometric entity cognitive behavior model, enhances the cognitive ability of part, reduces the heavy man-machine interactive operation in assembly process, effectively improves the intelligent degree of assembly path planning process.

The application belongs to the technical field of artificial intelligence and natural language processing, and discloses a cognitive behavior modeling method and system based on large language model semantic enhancement, which comprises the following steps: generating a structured semantic diagnosis description for each question; encoding the structured semantic diagnosis description and the student's historical answering behavior into vector representations respectively; mapping the vector representations of the semantic diagnosis description and the answering behavior into the same similarity space through a kernel function alignment mechanism and performing weighted fusion; receiving the fused representations and modeling the interaction between the student and the question, and outputting knowledge state inference and explainability feedback. The application fuses the question semantic information generated by the LLM and the student's answering behavior data to construct a cognitive behavior modeling method with high prediction performance and strong explainability.