44 results about "Arousal" patented technology

The invention discloses an emotion recognition method based on multi-modal signal fusion, and relates to the technical field of emotion recognition, and the method comprises the steps: obtaining an electroencephalogram signal and a peripheral physiological signal to form a multi-modal signal, and carrying out the preprocessing of down-sampling, baseline correction and band-pass filtering on the multi-modal signal; based on the preprocessed signal, extracting a difference entropy feature and a power spectrum density feature; mapping the extracted features into a standardized space grid to generate a feature tensor with a uniform structure; performing adaptive weighting on the mapped feature tensor by using a frequency band fusion attention mechanism, and generating a frequency band weight through global average pooling and a full connection layer; inputting the weighted features into a full connection layer of the parameterized hypermatrix, and performing feature compression and modeling through matrix decomposition and reconstruction; a multi-task learning framework is adopted, classification results of emotion titer and awakening degree are output at the same time based on compressed features, and multi-task collaboration is optimized through a shared feature layer and a dynamic loss weight.

The invention relates to the technical field of brain-computer interaction, in particular to a patient mental state assessment system for a clinician, which comprises a semantic manifold calibration module, a state trajectory projection module, a geometric curvature resolving module and an emotion transformation quantification module. According to the method, electroencephalogram data are collected and deeply analyzed, high-dimensional neural activity characteristics are converted into a visual three-dimensional state track in combination with titer and awakening degree information, continuous dynamic monitoring of the mental state of a patient is achieved, then the emotion conversion process is quantitatively analyzed according to the geometric curvature change rate of the state track, and therefore the mental state of the patient can be rapidly and accurately monitored. According to the method, rapid emotion fluctuation which is difficult to perceive in a traditional evaluation mode can be accurately recognized and marked, objective and fine data support is provided for clinical diagnosis, and the accuracy and instantaneity of mental state evaluation are remarkably improved.

The application belongs to the technical field of biomedical signal processing and computer vision, and specifically discloses a child emotion analysis method and system based on eye movement and micro-expression association, which comprises the following steps: synchronously acquiring an eye movement data stream and a facial video stream, triggering a dynamic analysis process by identifying a mode conflict between high physiological arousal and low emotional expression intensity after generating a physiological arousal and emotion hypothesis through preliminary analysis, generating a guide strategy according to a conflict degree, and enhancing original data in a time domain or a space domain to facilitate deep analysis, capturing suppressed micro-expression signals in the enhanced data to correct the preliminary emotion hypothesis, and finally fusing a physiological arousal level, a corrected emotion category and a quantified expression inhibition degree to output a multi-dimensional psychological state analysis result containing an emotion category, a physiological arousal level and an expression inhibition degree, so as to realize quantitative and multi-dimensional evaluation of real emotions of children.

The application relates to a medical engineering technology, in particular to a control method and system of a diagnosis and treatment robot for autistic children. The control method comprises the following steps: analyzing a human face video by using a deep learning model; generating a next-step intervention action recommendation list by using an LSTM state prediction model and a CPT action decision model; selecting or modifying one of the recommendation items and executing; retraining and updating the LSTM state prediction model and the CPT action decision model by using new interaction data. The control system comprises an execution module, a perception module, a memory module, an evolution module and a decision module. By introducing the quantification calculation of the concentration of the children and the valence and arousal of the facial expression, and by using the LSTM to predict the future state, the strategy can be adjusted in advance when it is predicted that the children will lose interest, so that the children's boredom or escape behavior is not easily caused, and meanwhile, the model is retrained and updated, so that the self-learning and adaptation capability is high, and the auxiliary diagnosis and treatment capability is relatively high.

This invention relates to the field of medical information processing and intelligent decision-making technology, and particularly to an autism decision assessment system based on multivariate data and knowledge graphs. The autism decision assessment system based on multivariate data and knowledge graphs includes the following components: a time-locked random calculation module: collecting endogenous and exogenous data, and determining time lock and random variables based on the endogenous and exogenous data; an arousal graph correction module: obtaining the endogenous arousal level based on the time lock and random variables, constructing a knowledge graph based on the endogenous and exogenous data and combining the endogenous arousal level, and correcting the knowledge graph; and a decision assessment output module: performing autism decision assessment based on the corrected knowledge graph. This invention integrates physiological and environmental time-series data, and through mutual information phase-locked detection, randomized causal graph construction, and individualized extreme value modeling, decouples endogenous and exogenous confusion, improving the accuracy and interpretability of autism assessment.

Systems, devices, and methods are provided for performing a sleep study of a subject. The methods include obtaining data from one or more body signals, the one or more body signals being non-brain signals, and determining an arousal or arousal-associated event of the subject using the data from one or more body signals. In a preferred embodiment, the one or more body signals include data obtained from one or more RIP belts.

The application discloses a method and system for emotion perception and empathetic interaction adjustment of embodied agents. Non-contact acquisition of user physiological signals: millimeter wave radar measures respiratory rate and heart rate, a camera measures heart rate and / or heart rate variability through remote photoplethysmography rPPG, and wearable device signals can be optionally fused; real-time evaluation of signal quality of each mode and adaptive fusion, estimation of emotional / stress state containing physiological arousal based on individualized baseline; adjustment of robot behavior strategy based on the estimation, output of embodied behavior parameters such as speech speed, action amplitude, close distance and dialogue content; the behavior strategy adopts reinforcement learning, and physiological arousal is included in the reward function, so that the robot learns embodied behaviors for reducing user discomfort and improving comfort, and an empathetic interaction closed loop of perception-estimation-decision-execution-re-perception is formed. The application does not need long-term wearing, can more truly reflect the internal state, is robust, safe and privacy-friendly, and is suitable for companion and education robots.

An arousal state control system includes a sensor, a stimulation control unit, and a stimulator. The sensor acquires biological information of a user. The stimulation control unit determines, based on the biological information, one or more types of stimuli to control a state of arousal of the user. The stimulator applies the one or more types of stimuli determined by the stimulation control unit to the user.

An arousal estimation system is proposed herein that estimates a human psychophysiological state on an arousal scale, using an arousal detection model that outputs a single arousal score characterizing arousal, rather than a particular target state, such as drowsiness, stress, or cognitive load. Based on an estimated arousal score, the human state can be characterized as either within or outside a desired range of arousal levels associated with optimal performance of relevant tasks. The arousal detection model is trained on a wider set of sensor data than may be applicable to a specific mental state. By training the arousal detection model on the wider set of sensor data associated with different arousal levels, an arousal score generated by the arousal detection model may generate a more accurate estimation of the human state than the conventional single state detectors, even when combined.

A system and method for objectively determining interpersonal compatibility by correlating synchronized multimodal biometric responses to humorous stimuli. The system presents categorized media content to a user while simultaneously capturing asynchronous data streams, including facial video, audio vocalizations, and galvanic skin response (GSR). A synchronization engine aligns these streams, applying a latency correction algorithm to correlate delayed physiological arousal peaks (phasic SCR) with antecedent visual micro-expressions (Action Units 6 and 12). By validating visual smiles with physiological arousal, the system distinguishes genuine Duchenne responses from social masking. These validated responses are fused via a tensor network into a multidimensional “Humor Response Vector.” Compatibility is determined by calculating the cosine similarity between users' vectors in a latent space, providing a quantification of psychological alignment that transcends self-reported bias. Embodiments include privacy-preserving edge extraction and homomorphic encryption of profile vectors.

To accurately estimate a work state of a user by using brain activity information of the user.SOLUTION: The method includes a step (ST1) of acquiring brain activity information of a user and a step (ST2) of estimating a work state of the user based on the acquired brain activity information, and the step of estimating the work state of the user is a step of estimating an arousal level of the user. The step (ST2) of estimating the arousal level of the user includes a step (ST11) of acquiring a central executive network (CEN) activity value at an active site of a CEN obtained based on the acquired brain activity information, a step (ST12) of comparing the acquired CEN activity value with a preset arousal level threshold value, and a step (ST12) of determining that the work state of the user is a suitable state when the CEN activity value is determined to be equal to or greater than the arousal level threshold value (YES in ST13).SELECTED DRAWING: Figure 5

Provided are a method and apparatus for caring for a psychological status based on biometric information. The method includes acquiring real-time biometric information of the user from a wearable device worn by the user, analyzing arousal and valence of the user based on the acquired real-time biometric information, determining a psychological status of the user based on an analysis result of the arousal and valence of the user, and generating control information including information on pressure control provided from the wearable device based on the determined psychological status of the user.

The invention further relates to compounds, pharmaceutical compositions and methods for treating a subject for sexual function, such as sexual disorder or sexual dysfunction (SD), for inducing subject weight loss, for effectuating weight maintenance by a subject, whether or not the weight maintenance is used alone or in combination with a subject's weight loss, and / or for improving a subject's subjective state of well-being, self-esteem and / or self-confidence. Examples of SD contemplated by the present invention include but are not limited to female sexual disorder (FSD), female sexual arousal disorder (FSAD), female sexual interest / arousal disorder (FSIAD), female hypoactive sexual desire disorder (HSDD), female orgasmic disorder (FOD), female sexual pain disorder (FSPD), sexual interest arousal disorder (SIAD), male sexual disorder (MSD), male hypoactive sexual desire disorder (MSHDD), erectile dysfunction (ED), Pyronine's disease (PD), male premature ejaculation (MPE), male delayed ejaculation (MDE), male decreased libido (MDL), male dry orgasm (MDO).

A method, system, and device for providing user-associated physiological state insights is described. The method includes the steps of: receiving user-associated physiological data from a wearable device; obtaining user-associated physiological baselines based on user-associated baseline physiological data; receiving additional user-associated physiological data from a wearable device; obtaining current user arousal data based on the additional user-associated physiological data; identifying trigger conditions for providing user-associated physiological state insights related to vehicle-involved travel events based on a comparison between current user arousal data and baseline user arousal data; and causing a user device to provide user-associated physiological state insights.

The application discloses a signal processing method for an electroencephalogram emotion recognizer. First, a one-dimensional EEG time series signal is converted into a two-dimensional time-frequency spectrogram containing time and frequency information through continuous wavelet transform. Then, the time-frequency spectrogram is segmented into a series of image blocks and processed through linear projection, addition of classification identifiers and position coding to construct an input sequence suitable for a Vision Transformer model. The method can effectively capture the global context information and long-range dependencies of the signal by using the multi-head self-attention mechanism inside the ViT encoder, overcoming the problem of limited receptive field of traditional convolutional neural networks. Finally, the model outputs the prediction values of the activation and arousal of emotions through an MLP classification head. The average prediction accuracy of the method on the activation and arousal reaches 95.2% and 93.4% respectively, verifying the effectiveness and robustness of the method in improving the performance of emotion recognition.

This invention provides an application of the combined use of rhizoma sarcodactylis and ginsenosides in the prevention and / or treatment of neuropsychiatric disorders, relating to the field of biomedical technology. The combined use of rhizoma sarcodactylis and ginsenosides demonstrates significant effects in improving symptoms of post-traumatic stress disorder (PTSD) and depression, exhibiting a synergistic effect. It effectively alleviates invasive symptoms caused by post-traumatic stress events; reduces fear-avoidance of trauma-related stimuli in mice; effectively improves hypervigilance states such as arousal and sleep disturbances; significantly reduces anxiety levels in stressed mice; reverses stress-induced anhedonia; not only fades traumatic memories but also protects and improves normal neutral memory function; and for depression, it effectively reduces anxiety-like and depression-like behaviors in depressed model mice, overcoming the memory generalization problem that may arise from traditional treatments.

This disclosure provides compositions and methods for improving human cognitive function, mood, and / or arousal. In one embodiment, the method comprises administering an edible composition to a person in need of improvement in condition, the composition comprising a combination of gamma-aminobutyric acid and caffeine. The edible composition has a weight ratio of total gamma-aminobutyric acid to total caffeine of about 1:50 to about 10:1.

The invention discloses a non-invasive obstructive sleep apnea awareness cause assessment method and a non-invasive obstructive sleep apnea awareness cause assessment system. The method comprises the following steps: acquiring an end position of each OSA event of an OSA patient; acquiring a lower jaw myoelectricity signal and an electroencephalogram signal of the OSA patient, and based on the ending position of each OSA event, calculating the proportion of the lower jaw myoelectricity change prior to the electroencephalogram change in the ending period of all the OSA events as an awakening pathogenesis index of the OSA patient; and obtaining anatomical clinical parameters, PSG parameters, CT parameters and awakening cause indexes of an OSA patient, and inputting the obtained parameters into a preset OSA operation curative effect prediction model to output a postoperative AHI prediction result of the patient. The invention provides an awakening disease cause index capable of quantifying muscle functions and an awakening threshold value at the same time, the awakening disease cause index is used for establishing a subtype suitable for an operation, an OSA operation curative effect prediction model is constructed in combination with anatomy related parameters, and the operation effect can be effectively predicted.

The invention relates to an audience emotion analysis method and device based on multi-modal data, equipment and a medium thereof. The method comprises the following steps: screening a plurality of historical reference films of a target type from a historical film library, and fusing audience skin electrical response and electrocardio data to establish a type film emotion reference curve; collecting same-mode physiological data of a to-be-tested film to generate a to-be-tested film emotion curve, comparing the continuous time periods when the recognition values of the two curves are continuously lower than the reference, and positioning the continuous time period when emotion arousing is weak. By adopting the method, the emotional valley in the movie can be accurately positioned by using objective physiological data, and the defect that traditional subjective evaluation cannot quantify time-period play is overcome.

This application relates to a neural modulation method, system, and medium for controlling premature ejaculation based on multimodal biosensing and AI algorithms, belonging to the field of communication stimulation control technology. The neural modulation method for controlling premature ejaculation includes: monitoring and collecting and processing different physiological activities of the human perineum to obtain multidimensional physiological response signal clusters; calculating the comprehensive arousal level based on historical multidimensional physiological signals and a preset physical pattern, and constructing an arousal curve model; identifying and judging the multidimensional physiological response signal clusters based on the arousal curve model, determining the type of arousal node, and matching behavioral intervention strategies; updating and optimizing the arousal curve model based on active behavioral actions and implicit feedback mechanisms; and by monitoring the user's biophysiological signals in real time, using AI algorithms to analyze the trend of arousal changes, and performing physical intervention through electrical stimulation at key nodes, thereby reducing sensitivity, delaying the ejaculation threshold, and achieving the goal of prolonging sexual intercourse time.

The invention provides a sleep difficulty classification method and system based on electrophysiology, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining a brain wave signal and a physiological signal within a specified time, and calculating a cognitive awakening index within each specified time according to the brain wave signal data, according to the physiological signal data, calculating a physiological awakening index in each specified time period; respectively calculating contribution values to the difficulty in falling asleep according to the cognitive wakefulness index, the physiological wakefulness index and the theta wave time ratio in the corresponding specified time; therefore, the contribution values are compared, and the main reason of the difficulty in falling asleep is judged. According to the method, complex physiological and psychological problems are converted into a computable and comparable quantitative model, accurate classification of reasons of difficulty in falling asleep is achieved, and therefore the success rate of sleep-aiding intervention and the user experience can be remarkably improved.

A method for calculating a numerical data pair representing an emotional state may include: —acquiring: a first series of physiological signals by at least one GSR and / or EDA electrodermal sensor, a second series of PPG physiological signals by a heart rate sensor, transmitting to a remote server the timestamped signals as well as an identifier of the acquisition device, processing each of the signals in order to characterize an Sarousal, Svalence data pair, characterized in that: the processing of the first series of signals is of the EMD type over a sliding time window, to provide the first Sarousal value of the pair, the processing of the second series of signals includes a step of band-pass filtering of frequencies comprised between 0.04 and 0.26 Hz and of peak detection and RR inter-peak time measurement, over the sliding time window, the to provide the second Svalence value of said pair.

Infrasonic musical vibrations may be induced into various compartments of the body for therapeutic purposes, ranging from relaxation to arousal or focus, but also specifically activating physiologic responses due to vibration sensitive receptors in these spaces. These include vibration of the wall of the enteral track to control appetite, vibration of the effacing cervix to augment the birthing reflex, augmentation of bladder urge control in training against incontinence, and inducing relief from craving in relapse prone individuals with various addictions. Exemplary embodiments facilitate induction of such harmonized and phased oscillations in a seated embodiment, and also their measurement at target locations as an integrated, individualized method for treatment.

The application belongs to the technical field of emotion recognition, and in particular to an emotion recognition method based on left and right brain emotion lateralization; the method specifically comprises the following steps: S1, electroencephalogram signal acquisition electrode and processing: obtaining standard electroencephalogram signals; S2, time domain feature and frequency domain feature extraction of electroencephalogram signals of left and right brains: extracting Hjorth and differential entropy features; S3, calculating edge weights of a dynamic graph convolutional neural network based on feature differences of left and right brains: calculating weights by using a CRITIC weight method; S4, calculating an adjacency matrix of the dynamic graph convolutional neural network based on inter-channel correlation of electroencephalogram signals: calculating phase locking values to construct the adjacency matrix; S5, emotion recognition by using an improved dynamic graph convolutional neural network: iteration and training; the application extracts the same features from the time domain and the frequency domain of the left and right brains respectively, thereby better recognizing that the left brain is more sensitive to positive emotions and the right brain is more sensitive to negative emotions, and solving the problem of low accuracy of emotion recognition in the two dimensions AV of valence and arousal.

The present invention provides a method for determining a state of negative arousal in a healthy animal from the order Carnivora to be tested, the method comprising: (i) providing one or more saliva sample(s) from said animal; (ii) measuring the concentration and / or amount of amylase in said sample; wherein a state of negative stress arousal is determined based on the concentration and / or amount of amylase measured. The invention also provides the use of salivary alpha amylase as a biomarker for determining a state of negative arousal and assay devices and kits for carrying out the methods of the invention.

The invention provides a quantitative analysis method and system for spatial environment emotion arousal based on human factor engineering, and the method comprises the steps: building a spatial node system based on the functional features of a target space, and presetting at least one dominant emotion type for each spatial node; presenting the environment information of each space node to the subject, and collecting quantitative questionnaire data fed back by the subject for each space node; carrying out reliability analysis and factor analysis on the quantitative questionnaire data, and extracting the actual dominant emotion type of each space node; based on the actual dominant emotion type of each space node, generating an emotion distribution diagram corresponding to the space node system, and based on the emotion distribution diagram, analyzing the emotion arousing effect of the target space; according to the method, quantitative analysis is carried out on spatial emotion arousal based on the human factor engineering technology, and a reliable technical basis can be provided for building design and spatial environment research.

Provided is a data collection method for use in learning for estimation based on a human facial expression, the data collection method comprising: a step for acquiring arousal and valence for each data item contained in a dataset of human facial expressions; a step for plotting the acquired arousal and valence in an arousal-valence coordinate space; a step for determining a data-deficient region in the coordinate space; a step for synthesizing new data corresponding to the data-deficient region by using a plurality of data items that are contained in the dataset and for which the arousal and valence are known; and a step for adding the new synthesized data to the dataset.

This invention provides an adaptive personal care massage device control system and method based on multimodal perception, aiming to solve the problems of traditional massage devices, such as single control mode, poor personalization adaptability, high privacy risks, insufficient security protection, and narrow scene adaptability. This invention adopts a local closed-loop architecture of "perception-modeling-decision-control," using a personalized physiological arousal quantification model deployed on the device side to quantitatively evaluate the user's multi-dimensional physiological parameters in real time. Based on the dynamic mapping rules between arousal scores and device parameters, stepless adjustment control commands are generated to achieve physiologically driven adaptive closed-loop control. The system can be modularly equipped with posture perception, calibration-free operation, intelligent voice control, physiological safety protection, and multimodal human-computer interaction modules. It supports offline operation on the device side, has strong hardware compatibility, real-time response, and high privacy security, and can be widely used in the fields of home massage and rehabilitation therapy equipment.

This application provides a targeted neuromodulation method and system for disorders of consciousness, relating to the field of neural network modulation technology. The method includes acquiring multi-lead EEG data from a user; extracting target EEG biomarkers related to consciousness, single analytical features reflecting the complexity of each lead, and joint analytical features reflecting the functional connectivity of any two leads from the EEG data; calculating the consciousness index of the corresponding node in each lead using the EEG biomarkers and single analytical features; identifying candidate stimulation nodes with abnormally weakened functional connectivity in the consciousness network based on the joint analytical features; determining a personalized target modulation strategy by combining the consciousness index and candidate stimulation nodes to achieve objective quantitative assessment and early identification of the level of consciousness; executing the target modulation strategy to provide electrical stimulation to the user, forming a closed-loop control during the stimulation process, and significantly improving the safety and effectiveness of arousal therapy by dynamically optimizing stimulation parameters.