56 results about "Mood state" patented technology

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.

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.

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 invention provides a system for monitoring the health, behavior, and safety of horses using a wearable device and an AI-enabled camera. The wearable device, affixed to the horse's pastern, measures physiological and motion data through multi-modal sensors, while the AI camera captures high-resolution facial images to assess mood states such as stress, happiness, discomfort, and pain. Data is processed locally with artificial intelligence algorithms and transmitted via WiFi, LoRa, GSM, or Bluetooth to a cloud-based platform. The platform provides real-time alerts, tracks historical trends, and enables data sharing among caregivers, veterinarians, and researchers. The system includes geofencing for safety, redundant communication protocols for reliability, and modular designs for adaptability across environments. By integrating physical, mental, and environmental monitoring, the invention delivers actionable insights to support proactive care, ensuring the health, safety, and welfare of horses.

The utility model discloses an intelligent seat and leisure cabin, this intelligent seat includes: seat body, handrail, backrest, physiological parameter sensor, air bag assembly, pressure sensor, control unit. Through seat body, handrail and backrest constitute the space for user's riding, leaning, and air bag assembly, pressure sensor set up in the backrest inside. Control unit and air bag assembly and pressure sensor electricity are connected, and after the physiological parameter sensor detects the body data of user, this is used to judge the mood state of user at this time. Adopt the intelligent seat and leisure cabin of this application, can control the size of the fluctuation degree of air bag assembly to adjust the physiological parameter of user to relieve the excited or low mood state of current user according to the excited or low mood state of user, thereby can reach the purpose of helping user to calm down.

The present invention relates to a system (1) which enables the most suitable campaigns to be offered by analyzing the emotional state of users.

The present invention provides an information display method, apparatus, device, and medium. Through this invention, audio style data of a user within each set time period can be determined based on audio playback data within that time period. Furthermore, based on this audio style data, the target emotional state information of the user within each time period can be determined, enabling the perception of the user's emotional state based on audio playback data. By displaying this target emotional state information, the information display content can be enriched, helping users understand their emotional state over past time periods and improving the user experience.

The application relates to the technical field of smart endowment, in particular to a smart endowment service automatic supervision system, which comprises classifying the activity items of the old people into timed activities and free activities, determining the mood states and activity characteristic states of the old people in different time periods based on heart rates, establishing the relevance of the mood and the activities and marking the relevant tags, and a service recommendation module combining the real-time mood, the relevant tags and the activity tags to push the optimal services; the application can push the adaptive services by combining the activity characteristics when the old people have negative emotions, timely relieve the emotions, break the vicious circle of "emotional problems leading to physical deterioration", reduce the health risks, optimize the resource allocation according to the correlation between the mood and the service effect, avoid the waste of inefficient services, provide more targeted personalized services, and comprehensively improve the endowment service quality and the life happiness of the old people.

This invention discloses a multimodal fusion-based intelligent monitoring method for cat health and emotions. The method specifically includes: cleaning and extracting features from the original multimodal data to obtain acoustic features, facial features, fur features, and body temperature features; normalizing the acoustic, facial, fur, and body temperature features, and performing dimensionality reduction using principal component analysis and t-distribution random neighborhood embedding to extract a cross-modal core fusion feature set; and using a dynamically weighted random forest classifier to make decisions based on the cross-modal core fusion feature set, identifying the cat's health and emotional state, and outputting the monitoring results. This invention integrates four types of data—cat voice, facial expression, fur condition, and body temperature—and achieves accurate and real-time monitoring of the cat's physiological health and emotional state through a two-level fusion algorithm design involving feature layer and decision layer.

This invention discloses a method for inferring pilot stress and emotional states based on video, audio, and QAR data, belonging to the field of intelligent perception technology for multimodal pilot psychological states. The method includes temporal alignment, noise reduction, and data cleaning of the acquired data; unified modeling of multimodal features; outputting results and generating interpretive visualization reports. This invention improves the usability and deployment convenience of the system in real flight or simulated training environments; enhances the accuracy and robustness of psychological state recognition; strengthens the model's cross-human generalization ability; and meets the stringent real-time and reliability requirements of aviation scenarios.

This application relates to the field of data processing technology, and discloses an orthogonal fusion model of emotion, fatigue, and subjective will, as well as a method for assessing mental state. For the problem of emotion recognition, this application proposes a spatiotemporal entropy feature extraction method, which has good adaptability to small sample EEG data; for the problem of low recognition rate in fatigue state recognition, it proposes a power spectrum normalization feature extraction method for brain functional connectivity, which shows higher accuracy in fatigue state recognition; for the problem of feature fusion of emotion, fatigue, and work will, it proposes a mental state assessment model based on the Taguchi orthogonal method that fuses subjective and objective indicators. Experimental results show that the spatiotemporal entropy feature emotion recognition, the power spectrum recognition fatigue state recognition of brain functional connectivity, and the orthogonal fusion mental state assessment model of subjective and objective indicators proposed in this invention can complete the task of recognizing emotional state, fatigue state, and mental state.

This application provides a method, apparatus, electronic device, and storage medium for outputting perceived voice emotion tags, applied in the field of smart home device control. The method includes: acquiring user voice input information and corresponding text input information; extracting voice emotion features from the voice input information and text emotion features from the text input information; performing multimodal fusion of the voice and text emotion features to identify the user's emotional state; generating corresponding emotion tags based on the user's emotional state; and controlling at least one smart home device to perform corresponding scenario-based operations based on the emotion tags. The perceived voice emotion tag output method provided in this application enables smart home systems to proactively provide personalized service responses based on the user's current true emotions, achieving an intelligent upgrade from passive command reception to proactive emotion perception, effectively improving the naturalness of human-computer interaction and the comfort of the user experience.

In some embodiments, a method comprises receiving a first signal indicative of a current emotional state of a user, receiving a second signal corresponding to a desired emotional state of the user, and based on the first and second signals, generating a playlist of media content including a first item and an nth item. The first signal can be received from a wearable sensor. Generating the playlist can comprise selecting items of media content, and arranging the media content in a sequential order such that the playlist transitions from the first item toward the nth item. The method can further comprise playing back, via a playback device, at least the first item of the media content, and while playing back the first item, receiving a third signal indicative of an updated emotional state of the user.

This invention discloses a multimodal feature fusion method and system based on gated attention, belonging to the field of artificial intelligence and multimodal information processing technology. The method includes: S1, acquiring multimodal vectors to be fused, and performing a linear transformation on the multimodal vectors to obtain a multimodal transformation matrix; the multimodal vectors include: context vectors, personality feature vectors, and emotional state vectors; S2, calculating the gating weights of the multimodal vectors based on the multimodal vectors using an attention mechanism; S3, performing weighted fusion on the multimodal transformation matrix based on the gating weights to obtain a fused vector. The gating weights of this invention are learned from data through an attention mechanism, achieving dynamic fusion with content awareness; simultaneously, an emotion-priority dynamic adjustment mechanism ensures that the emotion weight is automatically increased during strong negative emotions.

The application discloses a kind of non-contact multimodal data acquisition and emotion monitoring method, device, system, equipment, medium and product, it is related to emotional recognition technical field.The method is first to start man-machine interaction program and target personnel are interviewed, and receive by millimeter wave biological radar module and audio and video acquisition module in the process of interview the human vital sign signal and audio and video signal collected by target personnel, then on the one hand to human vital sign signal sequentially pre-processing, signal separation processing and frequency estimation processing, obtain respiratory rate and heartbeat frequency, on the other hand to audio and video signal carries out feature extraction processing, obtains audio feature and video feature, finally according to respiratory rate, heartbeat frequency, audio feature and video feature, comprehensive analysis obtains the emotional state of target personnel, thereby can provide high-quality data support for subsequent artificial intelligence emotion early warning and evaluation model establishment, realize higher accuracy and higher reliability of emotional state analysis.

This invention discloses a method and system for generating dynamic, emotionalized doctor-patient communication dialogues based on a large language model, belonging to the fields of artificial intelligence and medical education technology. The method includes: defining typical doctor-patient communication scenarios and basic emotion tags; establishing quantifiable intensity models for emotions; automatically mapping from keywords to emotion tags based on dialogue content; defining emotion conversion rules; real-time parsing of doctor-patient dialogue content; identifying the emotion types and specific doctor-patient communication scenarios involved in the current dialogue; outputting structured context objects; based on the context analysis results, applying preset emotion conversion rules, dynamically deciding the emotional state that the system should present, and outputting quantified objects of each emotion; encoding the state and the output quantified emotion objects into prompt words for the large language model, guiding the model to generate emotionally charged responses. This invention can provide doctors with a high-fidelity, repeatable, and low-cost communication training environment.

The application discloses an interactive psychological intervention robot dog with real-time emotion sensing capability, comprising a bionic robot dog body, a signal acquisition module, an emotion evaluation module, an execution control module, a collaborative intervention module, a remote monitoring module and a man-machine interaction module, which can monitor the physiological state of a user in real time, automatically identify the emotional state, and actively guide slow breathing training, mindfulness meditation, muscle relaxation and biofeedback training, cooperate with intervention measures such as vibration stimulation and sound and light stimulation, continuously monitor the emotional changes, adjust the intervention measures, realize closed-loop control, and meanwhile, the physiological regulation effect of the user can trigger positive behavior feedback of the robot, and improve the treatment participation degree. The application is suitable for the old, patients with anxiety and depression, and people with low motivation and low digital literacy, and can realize personalized and high-compliance psychological health support in family, nursing homes and other scenes, and has the advantages of mobility, intelligence, closed-loop regulation and control and strong interaction.

The application discloses a kind of based on the standardization adaptation method of mood interaction of companion device, comprising the following steps: obtaining the multimodal data of companion device, and standardization processing is generated adaptation state parameter;Identify current mood state, determine corresponding role quota constraint;Identify current device response capability, determine the coupling constraint relationship between each device capability unit;Determine the proposal rule, acceptance rule and update rule of current round stable matching, form the basis of current round stable matching;Using Gale-Shapley stable matching algorithm executes multiple-to-one stable matching, obtains current round stable matching result;Around current round stable matching result, determine local broken stable area;For local broken stable area, again using Gale-Shapley stable matching algorithm executes local reconfiguration, generates target mood interaction adaptation result.The application improves the accuracy, continuity and coordination of mood interaction response.

An electronic device delays communication connection and / or presents soothing output during communication initiation in response to detecting user's first emotional state. The electronic device has a memory including a communication management module, a communications subsystem that links the electronic device to a communication network, and a processor. The processor is configured to cause the electronic device to: monitor an emotional state of a user of the electronic device; and in response to detecting that the user is in a first emotional state while communication event with a second electronic device is being connected present a soothing output via at least one output device prior to completing a connection of the communication event. The processor is further configured to cause the electronic device to delay the connection of the communication event to enable the soothing output to be presented to the user for at least a pre-established cooling off period.

Systems and methods for analyzing an emotional state of a user over time include receiving audible communications of the user across one or more contexts. The audible communications may be associated with contextual factors such as time of day, location, user activity, or digital interaction. The audible communications may be transcribed, and an emotional-state machine learning model may interpret verbal and nonverbal cues to determine emotional indicators. The emotional indicators may be correlated with the contextual factors to generate correlated emotional indicators. Portions of the audible communications associated with the correlated emotional indicators may be determined as citations. A summary of emotional trends of the user may be generated over the period of time based on the correlated emotional indicators. The summary may include the citations.

According to an embodiment, a computing device includes one or more processors and one or more computer-readable media that collectively store instructions that, when executed by the processor(s), cause the computing device to perform operations. The operations can include: detecting a trigger event associated with physiological data of a user; presenting one or more mood states to the user for selection based on detecting the trigger event, the mood state(s) corresponding to at least one mood experienced by the user at a defined time associated with the trigger event; annotating the physiological data with one or more annotations indicative of the at least one mood based on selection of the mood state(s) by the user; and training a model based on the annotation(s) such that the model identifies a correlation or an absence of correlation between the trigger event and the at least one mood.

The application discloses a kind of children multimodal emotion recognition and UE5 scene self-adaptive adjustment method, it is related to the technical field of children mental health, including the following steps: S1, children multimodal emotion dataset construction;S2, multimodal emotion recognition model training and end side deployment;S3, children emotion real-time end side identification;S4, emotion-scene linkage rule base configuration;S5, UE5 scene real-time linkage adjustment.The application effectively solves the many problems of low accuracy of children emotion recognition in the prior art, poor linkage with 3D scene, end side landing difficulty and insufficient adaptation of special children, can realize high-precision, low-delay real-time identification of children's emotions on edge devices, and complete dynamic self-adaptive adjustment of virtual scene according to emotional state, can be widely adapted to the emotional intervention needs of ordinary children and ASD children, with strong practicality and landing promotion value.

The application discloses a car machine voice assistant interaction method and device, equipment and storage medium, relates to the technical field of vehicle voice processing, and the car machine voice assistant interaction method comprises the following steps: acquiring multi-modal data affecting the mood of a user, comprehensively judging the mood state of the user; and adjusting the image and voice information of the car machine voice assistant according to the mood state judgment result of the user. The application can solve the problems of single dialogue mode and insufficient emotional expression of the existing car machine voice assistant.

This invention provides a music recommendation method based on multidimensional data. The method includes the following steps: acquiring multidimensional data of the target user, including physiological data, environmental data, user behavior data, and voice data; determining the target user's comprehensive emotional state and current activity type based on the user's multidimensional data; combining the target user's historical music listening behavior and current comprehensive emotional state, and generating a music preference model based on the user's historical music preference data in different scenarios; and generating a personalized recommended music list by fusing and analyzing the comprehensive emotional state, scenario activity type, and music preference model. This invention, by acquiring and comprehensively processing the target user's multidimensional data, can accurately identify the user's current emotional state and activity scenario, achieving a comprehensive perception of the user's emotions and environment.

The application provides a kind of antenatal education interaction method based on vocal singing feedback training interface, the method is based on the user brain wave data set, the activity of different frequency bands is analyzed, the intensity of each wave band is identified and quantified, and the current emotional state of the user is judged by comparing with the preset threshold, and the time point of emotional change is recorded, the emotional analysis result is obtained, the rhythm, volume and spatial sound effect setting of music are adjusted, the dynamic adjustment of music output parameter is realized, the emotional intervention demand is optimized, and according to the change of user brain wave, the emotional improvement and user satisfaction are evaluated, the improvement effect of music intervention on user psychological state can be measured, the effectiveness of feedback closed loop is ensured, and more efficient, accurate and psychological demand meeting music feedback training effect is provided for user.

This application discloses a control method, device, and storage medium for an advertising evaluation system, belonging to the field of advertising evaluation technology. The method includes: acquiring the neurophysiological signals of a user when receiving media content, extracting a target rhythm signal from the neurophysiological signals, calculating the difference parameters of the target rhythm signal between preset brain regions, identifying the user's emotional state type based on the difference parameters using an emotion analysis model, aligning the emotional state type with the timestamp of the media content to generate an emotion state curve, and determining the playback effect of the media content based on the emotion state curve. This application analyzes the time and degree of a user's specific emotions based on the neurophysiological signals when watching media content, thereby determining the playback effect of the media content.

This application belongs to the field of emotion monitoring technology, and provides a method and system for emotion monitoring and intervention based on multimodal neurochemical sensing. It acquires electroacoustic and optical fluorescence spectral signals from a user's target tissue region through a wearable device, and identifies neurotransmitter system activity information through signal fusion and decoding. This information is then input into an individualized dynamic emotion monitoring model to obtain the user's current emotional state type and intensity. Combining these two indicators, an emotion instability index is calculated in real time. When the index exceeds an individualized critical threshold, a personalized intervention plan matching the instability characteristics is generated and executed. The critical threshold can also be dynamically adjusted based on the intervention effect and real-time physiological state. This invention achieves non-invasive neurotransmitter monitoring and emotion monitoring, assessment, and intervention, improving monitoring accuracy and the timeliness and personalization of intervention, and is applicable to fields such as medicine and education.