252 results about "Mood state" patented technology

The invention discloses an emotion rehabilitation intervention method based on face recognition. The method comprises the steps that S1, a user face image sequence is collected through a front camera; s2, performing image preprocessing to generate a standardized image tensor set; s3, facial dynamic features are extracted through an improved BiFormer network, emotional states are recognized, and a multi-dimensional emotional state sequence and a facial expression coding sequence are generated; s4, jointly analyzing the emotion change trend and the expression behavior mode of the user through a multi-mode RETNet network, and outputting a psychological state grade and a future emotion fluctuation score sequence of the user; s5, matching an emotion rehabilitation intervention strategy through a preset rule engine; s6, executing the emotion rehabilitation intervention strategy, collecting user data in real time, and generating a user response scoring sequence; and S7, performing incremental updating on the multi-modal RETNet network and a preset rule engine based on the user response score sequence. According to the invention, the accuracy of emotional state recognition and the intelligent level of intervention strategy pushing are improved.

The invention relates to the technical field of artificial intelligence and emotion calculation, and discloses an emotion state evaluation method based on multi-modal data, and the method comprises the steps: obtaining and decoupling an implicit signal, an explicit signal and situation data of an evaluated object; and respectively generating implicit features, explicit features and context vectors through double-flow decoupling coding and context knowledge graph coding. And the core engine determines the internal emotional state and the extrinsic emotional representation in parallel, and dynamically regulates and controls a bridging conversion process from the internal state to the predicted extrinsic representation by utilizing the situation vector. Finally, the emotion regulation intensity is calculated by comparing actual and predicted extrinsic representations, and the emotion regulation intensity, the internal state and the extrinsic representations are jointly used as a multi-dimensional evaluation result to be output. According to the method, the dynamic relationship and the adjustment strategy between the internal feeling and the external expression can be disclosed, a deeper and more three-dimensional analysis view angle is provided for the fields of mental health, human-computer interaction and the like, and the method has remarkable application value.

The invention relates to the technical field of emotion recognition, and discloses an emotion monitoring system and method based on a brain-computer interface, and the emotion monitoring method based on the brain-computer interface comprises the steps: synchronously collecting and preprocessing physiological signals through multiple sensors; calculating credibility scores and screening available modes; adopting a credibility weighted attention mechanism to obtain a fusion feature vector and calculating feature quality; constructing a multi-branch inference network to perform emotion recognition, and outputting an emotion state and an overall credibility score; and detecting distribution drift and carrying out individualized multi-branch inference network calibration. According to the invention, through cooperative work of multi-modal physiological signals, when the quality of a single-modal signal is reduced, the stability of the overall performance can be ensured, and the emotion recognition accuracy is improved; through an online continuous learning mechanism, model calibration can be performed according to an individual emotion expression mode of a user, physiological feature differences of different users are adapted, and a complete solution is provided for practical application of an emotion monitoring technology.

The invention discloses an intelligent cabin healthy light environment adjusting system and method based on biological feedback, and belongs to the technical field of intelligent cabin and vehicle control. The method comprises the following steps: collecting a multi-modal physiological signal of a passenger; physiological signals are processed in parallel through two paths; determining a feed-forward control weight based on the dynamic change degree between the current steady-state emotional state and the future emotional state trajectory; according to the feed-forward control weight, performing weighted fusion on the current steady-state emotional state and the future emotional state track to generate a comprehensive light environment adjustment instruction; according to the comprehensive light environment adjusting instruction, a dynamic light and shadow relieving strategy is generated and executed, and the strategy at least comprises at least one of the color temperature, the brightness or the dynamic rhythm of the cabin light environment. By introducing the feedforward control mechanism, the emotional fluctuation of the passenger can be predicted and intervened in advance, the response delay of the system is reduced, the conversion from passive response to active prediction is realized, and the timeliness and accuracy of emotional relief are improved.

The invention discloses a personalized interaction method and system based on multi-modal emotion perception, and relates to the technical field of intelligent interaction, and the method comprises the steps: collecting user historical interaction event data, and extracting interaction content features and user behavior features; obtaining interaction emotion data of the user in real time through a multi-mode sensor; fusing the interactive emotion multi-modal data to generate a dynamic emotion quantized value; generating an emotion correction factor; dynamically generating a personalized interaction strategy; and executing the interaction strategy, and collecting user response data to update a historical interaction event library. The method has the advantages that the key problem that a traditional interaction system is difficult to perceive the real-time emotional state of the user is effectively solved, a closed-loop optimization system of perception-decision-execution-feedback is constructed, and the user interaction satisfaction degree and the situation adaptive capacity of the whole system are continuously improved.

In accordance with the present disclosure, one or more computing devices and / or methods are provided. In an example, an emotional state of a user may be determined based upon one or more signals generated by one or more sensors and / or user activity of the user. A communication interface may be controlled based upon the emotional state.

An automated image processing method for assessing facially-expressed emotions of an individual, the facially-expressed emotions being caused by operation of a vehicle, machinery, or robot by the individual, including operating a vehicle, machinery, or robot by the individual and thereby expose a vision of the individual to a stimulus, detecting non-verbal communication from a physiognomical expression of the individual based on image data by a first computer algorithm, the image data of the physiognomical expression of the individual being caused in response to the stimulus, assigning features of the non-verbal communication to different types of emotions by a second computer algorithm, analyzing the different types of emotions to determine an emotional state of mind of the individual, and generating at least one of a prompt, an alert, or a change in a setting of an operational parameter of the vehicle, based on the emotional state of mind of the individual.

The invention discloses an artificial intelligence assistant method and system based on PAD emotion driving, and the method comprises the steps: collecting multi-modal data of a user, and carrying out the preprocessing of the multi-modal data; identifying the current emotion and communication intention of the user according to the preprocessed data; personality parameters and internal emotional states of the AI assistant are dynamically updated, and personification and consistency are kept in long-term interaction; long-term interactive memory of the AI is managed, and personality consistency is kept; generating a personalized recommendation and guide strategy for the user based on the personality and emotional state; generating an anthropomorphic natural language; verifying the key facts by using a knowledge graph; and performing state updating and guiding feedback. And the recommendation result not only is matched with the user behavior, but also better conforms to the evolution style and the guide target of the AI assistant, so that the acceptance and the exploration intention of the user to the recommendation are remarkably improved.

The invention discloses a customer service dialogue multi-modal dynamic emotion track detection method, system and device based on a large model and a medium, and belongs to the technical field of emotion track detection, and the method comprises the steps: collecting multi-modal original data in a customer service dialogue in real time; performing modal integrity analysis on the collected multi-modal original data, and identifying available modals and missing modals; extracting modal specific features based on the identified available modalities, and inputting the modal specific features into a pre-trained large language model; deducing the emotional state of the current dialogue fragment from the modal specific features by using a pre-trained large language model; according to the emotional states of the continuous dialogue segments, an emotional track is dynamically constructed, and the emotional track represents the change trend of emotions along with time; and outputting the emotion track to perform customer service quality control. According to the method, emotion recognition can still keep stable output under the condition of mode missing or signal degradation, and the reliability in a complex communication scene is remarkably improved.

The invention discloses an emotional state recognition method, system and device, and relates to the technical field of biomedical signal processing and artificial intelligence emotional computation.The method comprises the steps that electroencephalogram signals of a to-be-detected individual are collected; extracting power spectral density (PSD) and differential entropy (DE) features of the electroencephalogram signals on each frequency band according to a preset frequency; performing structured combination on the PSD and DE features corresponding to each frequency band, and constructing a dual-channel spectrum feature matrix; inputting the dual-channel spectrum feature matrix into a pre-trained shared encoder, extracting emotional feature representation of the individual, and obtaining an emotional state recognition result according to the emotional feature representation; according to the method, the depression emotion state of a new individual can be evaluated without participation of target domain data, the robustness and recognition precision of the model under cross-individual and low-labeling conditions are effectively improved, and the method has relatively high popularization and application potential.

The invention discloses a behavior data analysis method and system based on intelligent perception. The method and system are used for improving the reliability of child behavior analysis. The method comprises the following steps: acquiring multi-dimensional monitoring data of a plurality of children in a monitoring environment, wherein the multi-dimensional monitoring data comprises visual information, auditory information and physiological information of each child; performing multi-source fusion on the visual information, the auditory information and the physiological information of each child to generate a behavior feature set; inputting the behavior feature set into a preset behavior and emotion classification model for classification to obtain a behavior mode and an emotion state of each child; on the basis of individual information of different children, the behavior modes and the emotional states in combination with scene information of the monitoring environment, knowledge graph construction on a time sequence is carried out, a children behavior graph is obtained, and the children behavior graph is used for displaying behavior events of the children in a preset time period.

The invention relates to the technical field of artificial intelligence, in particular to a personalized mental health assessment system based on artificial intelligence. According to the method, the multi-modal psychological characterization data is acquired to comprehensively describe the emotion and psychological characteristics of the user, the culture attribute characterization is acquired according to the word segmentation sequence and the voice expression data, and then the basic emotion expression vector is calibrated, so that the condition that the specific expression under a certain culture is misjudged as the general emotion characteristic is avoided, and the accuracy of the emotion expression is improved. According to the method, the problem of low emotion recognition accuracy caused by expression habit difference in a cross-culture scene is solved, then micro-expression features are analyzed through an optical flow algorithm, matching verification is carried out on the micro-expression features and emotion calibration vectors, association analysis is carried out on voice features and physiological signals, the problem of misjudgment of a traditional method on the emotional state with different words is solved, and the emotion recognition accuracy is improved. And finally, by analyzing the consistency of the emotion feedback vector and the physiological dominant representation vector, outputting comprehensive assessment data, thereby significantly improving the accuracy of mental health assessment.

In accordance with the present disclosure, one or more computing devices and / or methods are provided. In an example, an emotional state of a user may be determined based upon one or more signals generated by one or more sensors and / or user activity of the user. A communication interface may be controlled based upon the emotional state.

The invention discloses an interactive system based on a YOLO-CNN face emotional state model and multi-modal behavior response, and the system comprises six modules which are connected in sequence. The system obtains facial emotion features through a face emotion feature extraction module, a multi-modal fusion module fuses the features with voice and limb movement features to generate a fusion feature matrix, an emotion reasoning engine outputs an emotion reasoning result based on the matrix, and a closed-loop reinforcement learning optimization module optimizes a co-emotional response strategy in combination with historical and real-time interaction data. The virtual body interaction control module generates a control instruction, and the virtual body interaction execution module drives the virtual body to complete interaction and feed back data. The system improves the multi-modal information fusion depth and common situation strategy dynamic optimization capability, solves the problems of fusion limitation and strategy optimization lack closed loop in the prior art, adapts to the fields of education, medical treatment and the like, and enhances the human-computer interaction emotion suitability and stability.

The invention relates to a device (1) for operating an entertainment and / or comfort system of a vehicle, by means of which, starting from a deactivated state of the entertainment and / or comfort system, at least one function generated by the entertainment and / or comfort system and acting on at least one occupant (IN) is automatically activated depending on a determined mood state (GZ1 to GZn) of the at least one occupant (IN) and parameters of the at least one function (IN) are set depending on the mood state (GZ1 to GZn) of the at least one occupant (IN).

The current document is directed to methods and systems that provide an emotional compass that reflects the emotional states of human beings, dynamics of the emotional states over time periods, emotional synchronization between humans and between humans and automated interactive systems, and the degree to which the emotional state of one human is influenced or affected by the emotional state of another human or by an automated interactive system. The emotional compass can be used for continuous or intermittent emotional orientation by both automated systems and human analysts. The emotional awareness provided by the emotional compass facilitates continuous or intermittent strategy selection for achieving various different types of emotion-related results.

We provide the system. [Solution] Equipment for collecting visitor biometric information, An inference device for estimating an emotional state using the aforementioned biological information, A generating device that generates visual and auditory content based on the estimated emotional state, A system including a terminal for displaying the generated content.

The application discloses a kind of emotion evaluation and intervention method and system based on multi-modal data.Through terminal synchronous acquisition voice, face, screen tremor and so on multi-modal data;Reaction mode vector is generated based on context information and data verification fusion;The composite emotional state of user is determined using emotional emergence model.At the same time, personalized emotional causal diagram is constructed and updated, and the enhanced state vector is generated by extracting key causal path features.The vector is input into the intervention agent to output intervention actions;After execution, the emotional state is evaluated again and the reward is calculated, and the system model is updated online.The application realizes accurate emotion evaluation and closed-loop adaptive intervention that strikes the root.

The application discloses a mindfulness prediction-intervention-feedback system and a control method, relates to the technical field of mindfulness training systems, and comprises a wearable user interaction device and sequentially connected user management module, mindfulness intervention training module, dynamic prediction module, intervention effect evaluation module and feedback interaction module; the initial mindfulness level, depression level and anxiety level of a user are determined; based on the depression level and anxiety level of the user, a target training scheme of the user is determined, and the user is prompted to perform mindfulness training according to the target training scheme; the target training scheme is adjusted based on an emotional state factor; the real-time mindfulness level of the user and the completion progress of the target training scheme by the user are determined according to a preset time interval, a mindfulness training report is generated in combination with the initial mindfulness level, and visual processing is performed; the mindfulness training method is selected by evaluating the mindfulness level of the user, and the rationality of the mindfulness training scheme can be improved.

The invention provides a man-machine collaborative creation method and device, terminal equipment and a storage medium, and is suitable for the technical field of man-machine interaction. The method comprises the following steps: acquiring physiological feature information of a target object, and determining emotional state information of the target object based on the physiological feature information; the resonance direction of the target object is determined based on the emotional state information, the resonance direction comprises forward resonance and reverse resonance, the forward resonance is used for representing that the emotional state of the target object is positive emotional, and the reverse resonance is used for representing that the emotional state of the target object is negative emotional; based on the resonance direction, acquiring an emotion style template corresponding to the resonance direction from a preset suggestion generation strategy library; and determining creation suggestion content based on the emotion style template. According to the embodiment of the invention, the corresponding creation suggestion content can be given based on the emotion of the user, and the man-machine cooperation efficiency is improved.

In a system that provides psychological support based on dialogue with children, this technology offers support that enables information sharing (advocacy) that respects the child's wishes while appropriately understanding changes in the child's emotional state and the urgency of the situation. [Solution] The child support AI system according to the present invention comprises: dialogue history holding means for holding a history of conversations with a user; emotion analysis means for analyzing the user's emotional state based on input information included in the dialogue history; and state mark generation means for determining psychological urgency and generating a state mark based on two evaluation indicators: (i) the frequency (temporal density) of negative emotions appearing within a predetermined time period, and (ii) the emotional intensity in a single conversation. Furthermore, this system presents supporters with status markers corresponding to the determined psychological urgency, and also includes visualization means that, based on user permission to share, presents supporters with summarized information of the conversation content that has been permitted to be shared.

The system according to this embodiment aims to analyze the emotional state of conversation participants in real time and promote constructive dialogue. [Solution] The system according to the embodiment comprises an emotion analysis unit, a dialogue mediation unit, an advice provision unit, and a follow-up unit. The emotion analysis unit analyzes the emotional state of the conversation participants in real time. The dialogue mediation unit analyzes and understands the conversation between the parties based on the emotional state analyzed by the emotion analysis unit and makes constructive suggestions and questions at appropriate times. The advice provision unit provides advice on improving communication optimized for each participant based on the suggestions and questions made by the dialogue mediation unit. The follow-up unit periodically monitors the relationship after the dialogue based on the advice provided by the advice provision unit and provides additional support as needed.

This application discloses an emotion assessment method and apparatus based on deep temporal modeling. The method includes: real-time acquisition of speech data and EEG signals of a target object; conversion of the acquired speech data into an audio sequence and the EEG signals into an EEG sequence according to a preset time interval; inputting the audio sequence into a first sub-network of an emotion extractor to obtain speech emotion results; inputting the EEG sequence into a second sub-network of the emotion extractor to obtain brain activity emotion results; evaluating the emotional state of the target object based on the speech emotion results and brain activity emotion results at different times to obtain multiple emotion scores; fusing the multiple emotion scores of the target object within a target time period to obtain a comprehensive emotion score evaluation; and determining the emotional state type of the target object according to a preset emotion score scale.

The application provides an emotion recognition method and device based on images, equipment and a storage medium, relates to the technical field of deep learning, and comprises the following steps: obtaining a target image and a description text of the target image by a target user, the target image being an image that can cause the user to produce an emotion; inputting the target image into an image caption generation model to generate an image caption, so as to obtain an image caption of multiple emotional styles corresponding to the target image; determining a first PAD value corresponding to the image caption of each emotional style in the image captions of multiple emotional styles; determining a second PAD value corresponding to the description text; determining a target PAD value according to the multiple first PAD values and the second PAD value, and then determining an emotional state of the target user according to the target PAD value, so as to improve the accuracy of the recognition result. In addition, the obtained image captions of multiple emotional styles can further improve the accuracy of the recognition result of the emotional state of the user.

To provide a method and system for recommending and composing emotional music.SOLUTION: A method includes identifying a listener's current emotional state and a target emotional state, and generating an audio stream that is a music playlist to be presented to a user as auditory stimulation with an intention of producing a controlled trajectory of the listener's emotional state from the current state to the target state. The audio stream is generated by a machine learning system trained using data from the listener and / or other users indicating effectiveness of specific audio segments having specific features in producing a desired emotional trajectory, and is updated based on changes in an emotional state induced in the listener after exposure to the auditory stimulation. The machine learning system acquires, over time, a robust interpretation of a relationship between music and human emotion, and composes, masters, and / or adapts music configured to induce specific emotional responses in listeners.SELECTED DRAWING: Figure 17A

We provide the system. [Solution] A means of receiving natural language input from users, An analysis means for analyzing the aforementioned input and identifying the user's emotional state, A generation means for generating stress management suggestions based on identified emotional states, A means for presenting the aforementioned proposal to the user, An analytical means that acquires user meal data and estimates nutrient amounts through image analysis, A predictive method that uses past health data to predict future health risks, A system that includes this.

The invention discloses an AI accompanying toy and method based on an emotional acoustic wave algorithm, and relates to the technical field of man-machine interaction, a core processing layer establishes an independent virtual heart rate system for each AI role, and generates a personalized basic heart rate and an emotional intimacy initial value according to role attributes; dialogue content and AI emotional state are analyzed in real time based on data acquired by the input layer, and emotion type and intensity are identified; calculating a target heart rate and a spectrum modulation parameter according to the emotional state; dynamically adjusting parameters according to the interaction time, the dialogue depth and the emotion intimacy; the heart rate rhythm and spectrum modulation are applied to AI voice in real time; and the output layer presents the fused information of the emotional sound wave and the emotional state in a graph or color mode. Therefore, personification and life feeling of the AI role are greatly enhanced, man-machine interaction is upgraded from simple information exchange to accompanying experience with emotional depth and physiological resonance, and interaction naturalness and emotional attachment of the user are remarkably improved.

The invention discloses an emotion regulation and sleep improvement method based on audio and video combination and essential oil sniffing, comprising the steps of S1, brain wave detection and state evaluation, S2, audio and video prescription generation, S3, essential oil sniffing, S4, multi-mode coordinated regulation, S5, effect evaluation and strategy optimization, S6, sleep triggering and wakeup intervention, and S7, sleep improvement. And a user interaction and preference setting step. The emotional state is evaluated by collecting the physiological signals of the user, the audio and video prescription and the essential oil formula are dynamically matched based on the evaluation result, time sequence cooperation of audio and video content and essential oil release is achieved, and therefore accurate intervention on emotion and sleep is achieved on the multi-sensory level; self-adaptive adjustment can be carried out according to individual differences of users and real-time feedback, the effects of emotion adjustment and sleep improvement are remarkably improved, meanwhile, side effects of drugs are avoided, and the method has the advantages of being safe, convenient to use and high in individuation.