52 results about "Emotion assessment" patented technology

The invention relates to a method and device for emotion evaluation, a medium and a program product. The method comprises the steps of obtaining multi-modal emotion evaluation data of a to-be-evaluated object in a process of performing a plurality of predetermined emotion evaluation tasks on the to-be-evaluated object; performing feature extraction processing on each item of data included in the emotion evaluation data to obtain corresponding feature information; fusing the feature information corresponding to each data to obtain corresponding fused feature information; and outputting a corresponding emotion evaluation result based on the fused feature information by using a trained emotion prediction model. According to the method, the trained emotion prediction model is used, the corresponding emotion evaluation result is output based on the feature information of the multi-modal emotion evaluation data, model pre-training and automatic iteration updating are carried out by adopting the meta-learning algorithm, individual differences are rapidly adapted, and the performance, efficiency and robustness of model prediction are improved.

The invention belongs to the field of financial science and technology and data analysis, and particularly relates to a financial transaction emotion analysis and price trend prediction method based on data fusion, which is mainly used for solving the problems of complexity and real-time demand of stock price prediction in a financial market. According to the method, a fundamental analysis module, an emotion evaluation module and a price prediction module are integrated, multiple data sources are integrated, an advanced machine learning algorithm is adopted, and the real dynamic state of the market is more comprehensively and accurately captured. The fundamental analysis module is used for systematically analyzing financial data, announcement information and other related indexes of the stock and providing deep understanding of a target stock; the emotion evaluation module analyzes text data in social media and financial forums and combines various emotion analysis methods to generate dynamic indexes reflecting market emotions; the price prediction module carries out modeling based on data of different time scales such as minute, hour and day lines, and the prediction precision is improved through a layer-by-layer feedback mode.

The emotion assessment apparatus has a detecting unit detecting heartbeat information including the heart rate of a subject, an emotion assessment unit assessing whether the emotion of the subject is a negative emotion or a positive emotion based on the heartbeat information, a counting unit counting the number of heart rate variations within a predetermined time period, an emotional expression assessment unit assessing the mental state of the subject based on the number of heart rate variations, and using the assessment results from the emotion assessment unit to assess the mental state, and an output unit outputting the assessment results from the emotional expression assessment unit.

To provide an emotion estimation device capable of starting emotion estimation processing early, an emotion estimation method, an emotion estimation program, and an emotion estimation system.SOLUTION: An emotion estimation device performs emotion estimation according to an emotion index value about a biological state in a person whose emotion is estimated on the basis of an estimation condition adjusted by calibration, and has a controller. The controller extracts and stores singular point information to be a characteristic of detected time series data of emotion index value during calibration, extracts correspondence information corresponding to the singular point information in the detected time series data of emotion index value during emotion estimation, and performs emotion estimation in accordance with difference between the singular point information and the correspondence information.SELECTED DRAWING: Figure 1

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 discloses an emotional pressure monitoring method and system based on an intelligent ring and multi-modal data. The method comprises the following steps: continuously acquiring sensing data of multiple modals of a target user in a preset time period through the intelligent ring; based on a preset feature extraction algorithm, extracting a health feature parameter corresponding to each piece of sensing data; forming multi-modal feature data by using all the health feature parameters, and respectively inputting the multi-modal feature data into prediction models corresponding to a plurality of evaluation dimensions to obtain a plurality of output emotional pressure vectors; and according to the plurality of output emotional pressure vectors and an emotional recognition event corresponding to the preset time period, determining an emotional pressure condition of the target user in the preset time period. It can be seen that accurate emotional pressure analysis based on multi-modal data and dimension evaluation can be achieved, the comprehensiveness and real-time performance of user emotional health monitoring are improved, and the risk of emotional evaluation deviation caused by single dimension or event neglect is reduced.

The present invention provides an employee status monitoring method and system based on deep learning of facial multimodal information, relating to the technical field of employee status monitoring. The system includes a facial acquisition module, a facial processing module, a deep learning module and an emotion assessment module; the facial acquisition module is used to collect basic facial information and work facial information of employees; the facial processing module is used to analyze the collected data; the deep learning module is used to construct a convolutional neural network; the emotion assessment module evaluates the work facial information of employees based on the convolutional neural network to obtain the real-time status of employees; the present invention obtains facial data of employees in basic status and work status, compares and analyzes the facial data of employees in different states, and obtains the real-time status of employees, so as to solve the problem that the existing employee monitoring system does not obtain and analyze the facial status of employees, resulting in the inability to judge the fatigue status of employees.

The present disclosure relates to an apparatus and a method for managing depression in a perinatal period. The apparatus comprises: a memory that stores at least one instruction for managing depression in a perinatal period; and a processor that performs an operation according to the instruction, wherein the processor analyzes, through a cognitive therapy model, questionnaire information and speech information collected from a terminal of a mother, so as to identify negative thought patterns and emotions of the mother, and evaluates the mental health level of the mother according to the identified negative thought patterns and emotions, the cognitive therapy model learns a trigger keyword related to depression of the mother, and, when a word showing similarity greater than or equal to a preset level with the learned trigger keyword is detected from the questionnaire information or the speech information, the mental health level of the mother can be evaluated according to the analysis result of the detected keyword.

The invention discloses a simulated flight emotional stability objective quantitative evaluation method and system, and the method comprises the steps: carrying out the physiological representation mapping of a data unit in a monitoring period of each stage of simulated flight based on a pre-trained simulated flight emotional evaluation model, and obtaining the global physiological features and stage-specific physiological features of an individual, performing dimension reduction based on the physiological relevancy to obtain a time sequence structure of a preset time window; collaboratively embedding a preset global physiological mapping feature and a stage-specific physiological mapping feature, and generating a self-correlation feature representation integrated with the core physiological feature through a self-correlation coding layer; extracting cross-layer correlation features between the self-correlation feature representation and the two types of time sequence structure features; and identifying an emotion quantitative evaluation result based on the cross-layer related features. According to the method, emotion-related physiological changes of each stage of simulated flight can be accurately captured, and the objectivity and accuracy of evaluation are improved.

The invention discloses a personalized emotion evaluation questionnaire generation method and system based on real-time physiological data and neural network modeling, relates to the technical field of emotion evaluation, and solves the problems of lack of personalization, data isolation and poor dynamic adaptability of an emotion evaluation questionnaire in the prior art. The method comprises the steps of obtaining multi-modal physiological data and performing dynamic feature extraction, predicting emotional state classification and emotional degree indexes of a user by utilizing an emotional state evaluation model, and automatically generating a personalized emotional evaluation questionnaire by utilizing a questionnaire generation model according to a model prediction result. And a feedback mechanism is constructed to continuously optimize the emotional state evaluation model and the questionnaire generation model, so that the problems of insufficient personalization, data isolation and poor dynamic adaptability in the prior art can be effectively overcome, automatic generation of the personalized emotional evaluation questionnaire is realized, the emotional evaluation efficiency is improved, and the user experience is improved. And the questionnaire content can be differentiated according to individual differences.

An object of a system according to an embodiment is to effectively stimulate power of idea of a user.SOLUTION: A system according to an embodiment includes AR goggles, an eye tracking sensor, a voice recognition function, and an emotion estimation function. AR goggles are worn by a user. The eye tracking sensor is built into the AR goggles and tracks the user's eye gaze. The voice recognition function is built into the AR goggles and recognizes the voice of the user. The emotion estimation function is built into the AR goggles, and estimates the user's emotion.SELECTED DRAWING: Figure 1

The task-based thermal imaging and near-infrared mania assessment method, system, and device of this application captures the user's facial features, pupil features, and behavioral characteristics during an irritability psychology experimental paradigm assessment; constructs a multimodal fusion neural network; and inputs the facial features, pupil features, and behavioral features into the multimodal fusion neural network to obtain the user's mania assessment results. This application integrates thermal imaging and eye tracking technology to achieve real-time and accurate detection of emotional states such as manic mood disorder. This multimodal fusion technology breaks through the limitations of traditional methods and provides a new solution for the screening and assessment of emotional disorders. It has broad application prospects, especially in emotional management and mental health monitoring involving high-risk populations.

The invention discloses a physiological data acquisition method for an air traffic controller, and relates to the technical field of data acquisition, and the method comprises the steps: obtaining the multi-modal physiological data of the air traffic controller at the current moment; inputting the multi-modal physiological data into the trained fatigue-emotion evaluation model to obtain a predicted fatigue score and predicted emotion state probability distribution at the current moment; based on the predicted fatigue score, the predicted emotional state probability distribution and the multi-modal physiological data, processing tasks of different priorities are generated; processing tasks are executed according to priorities through a hierarchical scheduling algorithm, and physiological data collection is completed. Through multi-modal data fusion and model evaluation, the physiological state of the controller is accurately obtained, tasks are processed according to priorities, timely response of key data is guaranteed, reliable physiological information support is provided for air traffic control, and the flight safety guarantee level is improved.

The application discloses a kind of based on action unit AU and micro-expression question and answer mood evaluation method and device, obtain the question and answer video of user to be detected, the first image about non-basic question and answer in question and answer video is input into face detection model and obtains first face image, first face image is input into the multi-task identification model based on AU and micro-expression, output multiple first AU scores and multiple first micro-expression scores of first face image. By the corresponding relationship between multiple AU, multiple micro-expression and multiple emotional parameters, multiple first AU scores and multiple first micro-expression scores are weighted to obtain multiple target emotional values corresponding to multiple emotional parameters. Compare multiple target emotional values with multiple basic emotional values corresponding to multiple emotional parameters to obtain comparison result. The question and answer mood of user to be detected is evaluated by comparison result. In this way, the analysis standard of question and answer mood is set, and the fairness and credibility of evaluating question and answer mood are improved.

An emotion inference device according to one aspect of the present invention includes: a subjectivity information acquisition unit for acquiring subjectivity information related to subjectivity of a target person; a psychological characteristic database for containing information on a plurality of psychological characteristics related to a sense of unity; a psychological characteristic calculation unit for calculating, on the basis of the subjectivity information and the information in the psychological characteristic database, a plurality of psychological characteristic scores respectively corresponding to the plurality of psychological characteristics; a behavior information acquisition unit for acquiring behavior information related to behavior of the target person; a behavior information processing unit for calculating, on the basis of the behavior information, target person behavior data by analyzing the behavior of the target person; an event information acquisition unit for acquiring event information related to the content of an event; an audience information acquisition unit for acquiring audience information related to an audience around the target person; an audience information processing unit for calculating color phase information on the entire audience at an event site on the basis of the audience information; and a sense-of-unity calculation unit for calculating sense-of-unity inference data in which the psychological characteristics related to the sense of unity are quantified by using the plurality of psychological characteristic scores, the target person behavior data, and the color phase information.

The invention discloses a head physiotherapy instrument control method and system based on a multi-element stimulation mode, and relates to the technical field of head physiotherapy, and the method comprises the steps: calculating a comprehensive emotional state value through a fusion algorithm according to the geometric features, deep expression features, voice emotion scores and skin electric emotion scores of a face region, and obtaining a comprehensive emotional state value; judging an emotion category according to the emotion state value, and selecting a physiotherapy instrument mode according to the emotion category; when the physiotherapy instrument is used, a skin conductance value is collected in real time, heart rate variability data is collected through the photoelectric volume pulse wave sensor, and the physiotherapy instrument mode is dynamically adjusted through the skin conductance value and the heart rate variability data. According to the method, the facial image, the voice signal and the skin conductance data are comprehensively collected, deep learning and machine learning algorithms are combined, the emotional state of the user is accurately evaluated, and the problems of low emotional evaluation precision, fixed treatment mode and the like in the prior art are solved.

An object of a system according to an embodiment is to realize efficient delivery through selection of a deliverer and optimization of a delivery route.SOLUTION: A system according to an embodiment includes a deliverer selector, a delivery route generator, a health monitor, and an emotion estimator. The deliverer selection section analyzes the past delivery history of the deliverer to select the most efficient deliverer. The delivery route generation section generates an optimal delivery route for the deliverer selected by the deliverer selection section. The health monitoring unit monitors the health condition of the courier. The emotion estimator analyzes the emotional state of the delivery person.SELECTED DRAWING: Figure 1

The invention discloses an emotion evaluation and sound-light therapy healing method based on multi-modal signal fusion. The method comprises the following steps: S1, collecting an electroencephalogram signal and a photoelectric volume pulse wave signal of a user; s2, extracting a first feature value representing the relaxation degree of the user, and extracting a second feature value representing the heart rate variability of the user; s3, calculating a real-time emotional state index of the user; s4, matching a corresponding acoustic-optical therapy healing scheme from a preset therapy healing strategy library; and S5, controlling an acoustic unit and an optical unit to execute the acoustic-optical therapy healing scheme. The invention belongs to the technical field of emotion evaluation and healing, and particularly provides a method for realizing more accurate evaluation of the emotional state of a user by fusing electroencephalogram and pulse wave signals, dynamically matching and executing an optimal sound-light healing scheme based on an evaluation result, realizing personalized and adaptive closed-loop healing, and improving the healing efficiency. The emotion evaluation and acoustic-optical therapy healing method and system based on multi-modal signal fusion can effectively improve the emotion healing effect.

To improve estimation accuracy of a condition of a user without imposing troublesome work, etc., on the user.SOLUTION: An exemplary information processing device estimates a condition of a user by performing weighting processing on outputs of a plurality of AI models estimating the condition of the user. The information processing device detects a target event of calibration processing with respect to the weighting processing based on a peripheral environment of the user and adjusts a weight in the weighting processing in accordance with an output situation of each of the plurality of AI models when the target event is detected.SELECTED DRAWING: Figure 2

To provide an emotion estimation device that can improve the accuracy of emotion estimation. [Solution] The emotion estimation device 100 includes an electroencephalogram (EEG) signal input unit 111 into which time-series data of the subject's EEG signal is input, an estimation unit 112 that estimates the subject's emotion in the target time interval by inputting at least the EEG signal data in a target time interval which is a predetermined time interval, and the EEG signal data in the preceding time interval which is a predetermined time interval immediately preceding the target time interval, into a regression model, and an emotion output unit 113 that outputs the estimated emotion.

The invention relates to the technical field of user emotion recognition in digital customer service, in particular to a user emotion recognition method based on text information, a medium and equipment. The method comprises the following steps: determining an influence time period and range of emotional infection based on current time and position; and calculating a comprehensive negative emotion value in combination with the basic emotion score and the emotion scores of other users meeting the conditions. Emotion scores, spatial distance weights and intention weights of other users are considered in a calculation formula, wherein the weight of a high anxiety common intention is higher. The emotion infection effect is accurately modeled through the spatial distance weight function, infection weights of common anxiety and non-common anxiety are distinguished, the accuracy of emotion evaluation under a single text mode is improved, higher weights are distributed to common anxiety events, and the emotion infection effect is enhanced. Therefore, the emotion underestimation of the target user caused by the single text input can be compensated.

The invention relates to a media content processing method and device, electronic equipment and a storage medium, in the process of playing target media content, a face data sequence of a watching user is collected through camera equipment, a face action unit combination sequence is analyzed from the face data sequence, and the target media content is played according to the face action unit combination sequence. And determining an emotional state data sequence of the watching user, and determining a target fragment meeting a set condition from the target media content according to the emotional state data sequence. According to the mode, the target fragment is determined from the target media content based on the collected emotional state of the user, an objective and quantifiable emotional evaluation standard is established, the fragment causing emotional resonance of the user can be accurately captured, multiple types of media contents can be adapted, editing depending on artificial experience is avoided, and the user experience is improved. The efficiency and the quality of fragment extraction and editing are improved, and the cost is reduced at the same time.

The invention provides a dual-heart health early warning system and method based on millimeter wave radar and electronic equipment, and relates to the technical field of non-contact physiological signal processing, the system comprises a signal acquisition and processing module used for extracting a target respiration signal and a target heartbeat signal in an original echo signal; the multi-parameter adaptive classification module is used for carrying out heart function parameter extraction processing to obtain a target respiratory rate, a target heart rate, target heart rate variability and target cardiopulmonary coupling; the psychological and emotion evaluation module is used for obtaining a target psychological state evaluation result and a target emotion state evaluation result; and the fusion decision module is used for inputting the target respiratory rate, the target heart rate, the target heart rate variability, the target cardiopulmonary coupling, the target psychological state evaluation result and the target emotional state evaluation result into the double-heart linkage early warning model to obtain a physiological parameter early warning result. According to the method, physiological signals with higher precision are extracted, and effective early warning of psychological and heart parameters is realized.

The application discloses a kind of user emotion evaluation method, device and related medium based on multi-modal.It is described as follows.The method includes in the topic level emotion score prediction stage, for the user answer sample of single question, obtain multi-modal data and respectively carry out feature extraction and retain emotion score prediction ability, then generate each modality weight by modality weight routing mechanism and carry out weighted fusion, output corresponding question emotion prediction score and emotional feature representation;In the sample level risk assessment stage, the emotional feature representation and / or emotion prediction score of multiple questions are input, and the weight parameters of each question are generated, the prediction results of multiple questions are weighted and fused under the premise of retaining the prediction ability of single question, and finally the emotion evaluation result is generated.The application realizes hierarchical modeling and fusion of multi-modal emotional information by introducing weighting mechanism at modal level, question level and sample level, and improves the accuracy and robustness of overall user emotion evaluation.

The invention provides a state monitoring method and system based on heart rate variability map analysis, and relates to the technical field of data intelligent analysis, the method comprises the following steps: collecting a heart rate data set of a first user, generating a periodic waveform map, carrying out characteristic analysis on the periodic waveform map, obtaining waveform per second interval characteristics, and further carrying out heart rate variability index analysis; the method comprises the steps of obtaining a real-time heart rate variability index, calling a historical heart rate variability index set, calculating a preset heart rate variability index, comparing the preset heart rate variability index with the real-time heart rate variability index, and generating an emotion evaluation result. The technical problems that in the prior art, evaluation can only be carried out in a fixed scene, the convenience of an evaluation mode is insufficient, and meanwhile the final evaluation result is not accurate enough are solved, and the dynamic responsiveness and accuracy of emotion evaluation can be effectively improved through conversion of heart rate data and comprehensive analysis and evaluation of multiple emotion influence factors.

An object of the system according to the embodiment is to accurately grasp the health condition and emotion of the pet and provide appropriate advice to the owner.SOLUTION: A system according to an embodiment includes a data collection unit, a data transmission unit, a data analysis unit, an emotion estimation unit, and an advice providing unit. The data collection part collects data of pulse, body temperature and the number of steps by using a sensor attached to a collar of the pet. The data transmission unit transmits the data collected by the data collection unit to the server. The data analysis part analyzes the data transmitted by the data transmission part and determines the weight and excretion action of the pet. The emotion estimator reads the emotion of the pet based on the data analyzed by the data analyzer. The advice providing unit provides advice to the owner based on the feeling read by the feeling estimation unit.SELECTED DRAWING: Figure 1

The invention relates to a three-dimensional immersion type psychological problem diagnosis and treatment auxiliary analysis method and system, and relates to the technical field of psychological health diagnosis and treatment, and the method comprises the steps: collecting an interaction instruction, a brain wave signal and a facial micro-expression image of a visitor; analyzing and outputting a physiological evaluation result according to the brain wave signal; analyzing and outputting a micro-expression recognition result according to the facial micro-expression image; in combination with the interaction instruction, the physiological evaluation result and the micro-expression recognition result, dialogue output information or a scene construction instruction is generated; performing voice output based on the dialogue output information, or constructing a three-dimensional scene according to the scene construction instruction to form three-dimensional scene display information; and performing comprehensive analysis processing on the three-dimensional scene display information, the physiological evaluation result, the micro-expression recognition result, the interaction instruction and the dialogue output information, and outputting an emotion evaluation result. The method has the effect that professional psychological consultants or therapists can conveniently know the psychological health problems of visitors in time.

To share music information between vehicles in consideration of a driving load and an emotion of a driver.SOLUTION: A music information sharing device 3 calculates an adaptation degree indicating a matching degree of preference between a driver of a self vehicle and a user of the other vehicle, calculates a driving load value which is set in accordance with a magnitude of a driving load on the driver of the self vehicle and calculates an emotion estimation value estimating an emotion of the driver of the self vehicle. On the basis of the adaptation degree, the driving load value and the emotion estimation value, a grouping score for determining whether or not the driver of the self vehicle and the user of the other vehicle can be matched is calculated and in a case where the grouping score is larger than a predetermined threshold, the driver of the self vehicle and the user of the other vehicle are matched. Music information provided from the matched user of the other vehicle is adjusted based on the driving load value and the emotion estimation value, and the adjusted music information is provided to the driver of the self vehicle.SELECTED DRAWING: Figure 3

An object of a system according to an embodiment is to efficiently perform mental health care of employees.SOLUTION: A system according to an embodiment includes a counseling reception unit, a response generation unit, an emotion estimation unit, and a cognitive behavioral therapy unit. The counseling reception unit receives counseling. The response generation unit generates a response based on the counseling content received by the counseling reception unit. The emotion estimation unit estimates the employee's emotion based on the response generated by the response generation unit. The cognitive behavioral therapy unit provides cognitive behavioral therapy based on the emotion estimated by the emotion estimation unit.SELECTED DRAWING: Figure 1