169 results about "Physiological reaction" patented technology

The invention relates to an intelligent dialogue system and method based on an AI multi-mode large model. The method comprises the following steps: collecting biological characteristic data of a user in real time; cloning a personalized expression mode of the user by using the generative adversarial network; driving the audio avatar to perform multi-round dialogue interaction with the user, capturing a real-time physiological signal of the user through an expression recognition module, and generating a dynamic response content suggestion in combination with a dialogue context; and analyzing the interaction process based on the reinforcement learning model. The multi-modal deep fusion of the voice rhythm features, the language structure features and the facial dynamic features is realized, so that the limitation of single-modal or simple feature splicing in the prior art is broken through, the emotional state of the user can be accurately and comprehensively captured, the intention is expressed and the fine physiological reaction is expressed, and the user experience is improved. And a solid foundation is laid for constructing high-fidelity user representation.

A method for treating a patient via high-frequency (HF) electrostimulation therapy at an external target body location comprises generating a tonic motor activation (TOMAC) electrostimulation waveform using a power source supplying less than 100 volts zero-to-peak voltage amplitude per phase. The waveform has a frequency of 1,000 Hz to 5,000 Hz, a zero-to-peak current amplitude of 10-50 mA, and a duty cycle greater than 25%. The waveform is configured to overcome skin capacitance, induce proprioceptive afferent activity, and induce sustained tonic motor activation of a muscle. The method involves delivering the waveform to the external target body location over a specified duration during the patient's sleep period and receiving at least one TOMAC efficacy indication. The efficacy indication may relate to sleep efficiency, sleep stage, sleep onset latency, daytime sleepiness, CPAP compliance, or patient physiological response indicating TOMAC.

The invention provides an interactive interface design parameterization method guided by tactile feedback. The method comprises the following steps: acquiring physiological features, use habits and use scene information of a user, and presetting basic tactile feedback parameters according to a scene-parameter mapping rule; during interaction, touch parameters such as vibration frequency and amplitude are dynamically adjusted based on user operation behaviors, physiological reactions and scenes by using a deep learning model; and meanwhile, a multi-modal parameter fusion model is established, so that tactile, visual and auditory parameters have a synergistic effect, for example, when a button is clicked, the three parameters are mutually associated to enhance a feedback effect. After the operation is completed, the feedback effect is evaluated through objective indexes such as the subjective score of the user and the operation accuracy, and the user personalized model and the parameter adjustment model are optimized. According to the method, the problems that traditional parameters are fixed, and multi-modal fusion is insufficient are solved, accurate and personalized man-machine interaction is achieved, and the user experience is improved.

The invention discloses a sensory nerve quantitative detection method and system based on electroencephalogram characteristics, and relates to the technical field of electroencephalogram measurement, and the method comprises the steps: building detection files in one-to-one correspondence with users; respectively wearing the current stimulation module and the electroencephalogram detection module on the wrist and the head of the user; current stimulation is applied to a user step by step through a current stimulation module, and gamma waves in electroencephalogram signals of the user are collected in real time through an electroencephalogram detection module; gamma waves in the electroencephalogram signals of the user are analyzed, and whether the intensity of current applied to the user by the current stimulation module exceeds a physical stimulation sensing threshold value of the subject or not is judged; and analyzing severity grades of sensory disorders. The method has the advantages that detection is carried out through brain wave signals without relying on subjective feedback of a patient, interference of factors such as emotion and psychology is avoided, and even a special patient who cannot carry out self-perception report can complete sensory nerve quantitative detection through objective physiological reaction of brain waves.

The present invention provides a method and system for fabricating complex human tissues by integrating bio-electrospraying, cell electrospinning merged with 3D multi material microfluidic bioprinting, and future additions of magnetic and acoustic levitation technologies. The fabricated tissues serve as an alternative to animal testing in drug discovery processes, aiding in the prediction of human physiological responses to various drug compounds.

The invention provides a classroom student concentration degree monitoring system and method based on computer vision. The system comprises a vision collection module, an edge calculation unit and a cloud analysis platform. A multi-dimensional sensing mode combining head posture analysis, eye state tracking, facial expression recognition and body movement detection is adopted to evaluate the concentration degree, through a dynamic feature fusion mechanism, the system can intelligently adjust the weight ratio of different modal features, the limitation of single-dimensional analysis in a traditional method is effectively solved, and the accuracy of the system is improved. The system adopts edge calculation and cloud analysis, ensures high efficiency of data processing, ensures reliability of complex algorithm operation, and has important value for improving classroom teaching quality and learning efficiency. According to the invention, through multi-modal visual analysis, behavior characteristics and physiological reactions of students in class are monitored in real time, the concentration level of the students is comprehensively evaluated, and objective teaching feedback and improvement basis are provided for teachers.

Automated systems and methods are presented for determining the physiological response of human or suitable animal subjects to physical exertion. The methods and systems can include monitoring sensors that capture the motion of the subject along with corresponding physiological data, and can track such motion for the duration of a period of physical exertion. The system is able to acquire an initial stream of physiological data from the subject during a range of physical exertion activities that are representative of the events intended to be monitored with the proposed method and system, enabling a corresponding dynamic physiological response model to be created. The motion tracking system and physiological response model can then be used to predict the physiological response to physical exertion events under a prescribed framework, including applications during real-time event monitoring.

The invention provides a remote data acquisition and analysis method and system for a baby stroller, and the method comprises the steps: synchronously acquiring environmental stimulation and passenger physiological reaction data through multiple modules on the baby stroller, locally processing the environmental data into cumulative stress indexes, and processing the physiological data such as sound production into state classification labels. And when the passenger has negative stress states such as crying, screaming and the like, the system automatically packs the accumulated stress index sequence in the previous period of time to form a stress event data packet. And the data packet and baseline data in a normal state are transmitted to a remote server together, and a specific environment mode causing the negative stress of the passenger is identified through comparative analysis. According to the method, through event-triggered data acquisition and comparative analysis, specific external factors causing discomfort of infants can be accurately identified and understood.

The invention relates to the technical field of signal analysis, in particular to an acute pain assessment method and system based on an EDA signal, and the method comprises the following steps: collecting a skin electrical activity EDA signal of a subject; calculating an individual time-varying sympathetic nerve activity TVSymp curve; the method comprises the following steps: constructing a priori knowledge base containing a standardized pain response sympathetic nerve SpainSymp template; inputting the EDA signal and the individual TVSymp curve into a PCVAE model, fusing features and decoupling the features into pain common features and individual specific features; carrying out pain intensity classification, and reconstructing and generating a standardized SpainSymp curve of which individual specific characteristics are removed; and outputting the pain intensity classification result and the dynamic change trend of the standardized SpainSymp curve in real time. By adopting the method, the pain-induced physiological reaction and individual baseline variation can be effectively decoupled and separated from the mixed EDA signal, the interference of individual difference is avoided, and the method has the characteristics of high accuracy and strong real-time performance.

The invention provides a primary and secondary school indoor environment health benefit assessment and health environment index determination method in combination with a VR scene. According to the method, a highly-restored school indoor environment model is constructed by using a VR technology, so that accurate control on environment parameters is realized; meanwhile, physiological response data of the children are collected in real time through the physiological monitoring device, the influence of improvement of different environment scenes on different indexes related to children health can be effectively and quantitatively evaluated in combination with subjective questionnaire survey of the children, and refined guidance can be provided for improvement of environment quality of different types of indoor scenes in primary and secondary schools.

The invention is applied to the technical field of intelligent health and biological feedback, and discloses a VR motion sickness state detection method based on multi-modal physiological parameter fusion, and the detection method comprises the following steps: S1, carrying out data acquisition through a data acquisition module: fixing an electrocardiosignal around a heart in the form of three-lead number electrode points, setting the sampling frequency to be 1024Hz, and setting the sampling time to be 1h; the skin electric signal acquisition is arranged at the tail end of a finger in a 2-lead number electrode point form, the sampling frequency is 64Hz, and the central electric signal and the skin electric signal in the VR operation process are respectively acquired from a heart signal and a finger skin surface layer signal of an operator. According to the VR motion sickness state detection method based on multi-modal physiological parameter fusion, the activity of an autonomic nervous system and the activity of a sympathetic nerve are reflected through electrocardio signals and skin electric signals respectively, physiological reactions of motion sickness are captured from different dimensions, and physiological state information when the motion sickness occurs is extracted more accurately through multi-modal fusion analysis.

The invention discloses a physiologically-driven standardized intelligent simulation patient system, which comprises an adult simulation patient, a computer, a computer, a computer, a computer, a computer, a computer, a computer and a computer, wherein the adult simulation patient is made of a simulation man-made high polymer material, is environment-friendly and pollution-free, has obvious anatomical marks, touches two nipples, ribs, sternum and xiphoid processes, is flexible in joints, and realizes various operation body positions; wherein the physiological data comprises the heart rate, the blood pressure and the respiratory rate, the data is combined with a built-in physiological model to simulate the physiological state of a patient in real time, a monitor is simulated, real-time physiological data monitoring and feedback are provided, and the vital signs, the heart rate, the blood pressure and the oxyhemoglobin saturation of the simulated patient are displayed; the system has strong physiologically-driven standardized intelligent comprehensive simulation patient, can perform situational teaching according to a real clinical environment, effectively assesses the clinical thinking and personal operation skills of students, can greatly improve the team cooperation spirit of the students, and simulates the real physiological response and clinical scene.

The invention discloses an acupuncture data monitoring system based on a brain-computer interface, which belongs to the field of acupuncture data monitoring and comprises a data acquisition module, an acupuncture difference analysis module, a brain wave judgment module and an acupuncture scheme dynamic adjustment and feedback module. The data acquisition module is used for acquiring WorldClim temperature data, Ketz climate classification data, brain wave basic value data of people of different regions and ages, real-time electroencephalogram signals of patients and acupuncture and moxibustion parameters; according to the acupuncture data monitoring system based on the brain-computer interface, acupuncture sensitivity degrees, brain wave threshold values and acupuncture suggestions of patients under different resident climates can be rapidly obtained, accurate matching of personalized treatment schemes is achieved, pertinence and effectiveness of acupuncture treatment are improved, meanwhile, doctors are assisted in dynamically adjusting strategies according to physiological responses of the patients, and the accuracy of acupuncture treatment is improved. And the treatment process is simplified.

The invention discloses a wearable device and meta universe fusion interaction system and method. The method comprises the following steps: S10, collecting user data through a wearable device; s20, data processing and analysis: analyzing the data collected in the step S10, and generating personalized content through an analysis result; s30, interactive experience generation, wherein the personalized content generated in the step S20 is applied to the meta universe environment; and S40, performing feedback circulation, and optimizing the system by analyzing the user experience data. The system comprises a server, an integrated software platform, a meta universe platform, a wearable device and a sensor network. The server completes information interaction between the user and the meta universe platform through the wearable device; the integrated software platform supports the API butt joint with the meta universe platform; digital display is constructed on the meta universe platform; a wearable device and a sensor network capture actions and physiological responses of a user. Technical support and innovative thoughts are provided for development of the intelligent exhibition hall, and the exhibition industry is promoted to develop in the more intelligent, interactive and immersive direction.

An adaptive stimulation system optimizes pain relief, pleasure enhancement, and healing through closed-loop physiological effectiveness monitoring. The system comprises a stimulation device, sensors measuring physiological responses indicative of stimulation effectiveness, and a processor implementing real-time adaptive control. The system measures unconscious physiological responses that users cannot voluntarily control and involuntary reactions to objectively assess whether stimulation achieves desired outcomes. Through proxy learning, system sensors correlate with sophisticated clinical measurements via machine learning, enabling clinical-grade optimization using accessible devices. The system continuously explores multidimensional parameter spaces to discover optimal stimulation patterns personalized to individual users, automatically adapting parameters based on measured physiological effectiveness rather than subjective user control or preset patterns. Applications include medical devices, wellness products, and intimate stimulation systems.

A kit (100) and method (200) are provided for administering an active ingredient (112) to a subject to elicit a response. The kit comprises a first container (110) with an active ingredient (112) and a second container (120) with an adjuvant (122). The containers permit the ingredients to be admixed to form a compounded preparation for delivery into the subject's tissue. The active ingredient can comprise an allergen. The kit can also include temperature control and mixing components, potentially involving a third container (130). The method comprises providing the kit (100), admixing the ingredients, and injecting the compounded form into the subject's tissue such as a lymph node. The injection can be monitored and repeated. The approach can elicit various responses such as desensitization according to the type of active ingredient used. Overall, the kit (100) and method (200) provide targeted delivery of active ingredients to efficiently provoke a localized response in the subject.

One or more embodiments described herein relate to predicting, using adaptive artificial intelligence techniques, typical and aberrant physiological reactions of a patient to psychiatric counseling. Treatment plans can be determined and calculated based on previously-gathered demographic and / or biometric data, and / or modifications to treatment plans can be determined and / or implemented based on emergent recognition of reaction types, such as reclassifying reactions that would previously have been deemed typical as aberrant (or vice versa).

The present disclosure provides a method of performing and evaluating a treatment procedure, the method comprising: navigating a treatment device to a target tissue; transitioning the treatment device from a first linear configuration to a second deployed configuration such that a plurality of electrodes on the treatment device engage the target tissue; applying a pulse of neurostimulation energy having at least two phases to the target tissue via the plurality of electrodes, the neurostimulation energy comprising an anode phase and a cathode phase, where the phase of neurostimulation is switched from anode to cathode or from cathode to anode for each consecutive pulse; observing a physiological response to the nerve stimulation energy indicative of a nerve response; performing denervation on the nerves of the target tissue; and applying the neurostimulation energy to the target tissue, wherein less than a physiological response than a threshold indicates successful denervation of the nerves of the target tissue.

A portable respiration and cardiac monitoring device includes a detection finger band and a wearable heart rate relay watch. The detection finger band comprises a light emission unit for emitting a detection light beam and a response light receiver unit for receiving a physiological response signal. The detection light beam enters the user's fingertip to generate the physiological response signal. The wearable heart rate relay watch is connected to the detection finger band via a connecting cable. The wearable heart rate relay watch receives the physiological response signal and includes a gravitational accelerometer. The gravitational accelerometer detects the acceleration of the wearable heart rate relay watch to generate an acceleration detection signal. A detection datum comprises the acceleration detection signal and the corresponding physiological response signal.The wearable heart rate relay watch transmits the detection data to an external device. A wearable, artificial intelligence-based system for monitoring respiration and cardiac status includes a control system that communicates with the wearable respiration and cardiac status monitoring device.

This application relates to a device for detecting organ function and its control method, as well as a dietary management method and system, belonging to the technical field of medical device testing. The control method compares and analyzes changes in the microscopic features of the same area of ​​the tongue before and after eating, and calculates the corresponding metabolic index change rate, constructing a mapping relationship between the tongue's microscopic morphology and organ function, providing a basis for assessing internal physiological function through external characterization. Simultaneously, the dietary management method uses physiological responses before and after eating as real-time biofeedback signals to generate dynamically adjusted dietary management plans, forming a personalized health management closed loop of "monitoring-assessment-intervention-remonitoring," achieving precise adaptive adjustment of intervention strategies.

The application relates to the technical field of intelligent sensors and big data processing, in particular to a smart watch multi-source data fusion method and system based on environment sensing. The method comprises the following steps: obtaining an original data set through a smart watch; generating a data frame sequence according to a preprocessing result of the original data set, and generating a fusion feature vector based on the data frame sequence; inputting each fusion feature vector into a preset health mode classification model, and outputting an initial recognition result; generating a health risk level and an environmental influence factor according to the initial recognition result, and outputting user feedback information; extracting features such as a heart rate variation interval, a body temperature change rate and an air quality fluctuation cycle, constructing a fusion feature vector, combining a pre-trained health mode classification system, analyzing a linkage relationship between environmental changes and physiological reactions, and accurately identifying a stress mode caused by environmental pollution; and finally outputting personalized health prompt information based on a risk score mechanism and a historical mode library.

Various implementations disclosed herein include devices, systems, and methods that determine an interaction event during presentation of an interaction element. For example, an example process may include obtaining physiological data associated with a pupil during presentation of an interaction element, determining, based on the obtained physiological data, a pupillary response during the presentation of the interaction element, determining that the pupillary response corresponds to attention response characteristics associated with attention of a region of the regions of the interaction element based on the different illumination characteristics of the regions, and determining an interaction event during the presentation of the interaction element based on determining that the pupillary response corresponds to directing attention to the region during the presentation of the interaction element.

The invention relates to the technical field of data processing and data analysis, in particular to a food quantification method and system for a digestive nursing patient, and the method comprises the following steps: obtaining multi-source heterogeneous time sequence data related to the adjustment of the food of the digestive nursing patient, and carrying out the integration and standardization processing of the obtained multi-source heterogeneous time sequence data, the data after integration and standardization processing are obtained; on the basis of the integrated and normalized data, individual time sequence correlation characteristics between meal adjustment events and subsequent physiological reactions or symptom changes of the digestive nursing patient are mined, and the individual time sequence correlation characteristics are obtained; the problems that real-time or near-real-time individualized adjustment is difficult to realize and an effective feedback optimization mechanism is lacked in the prior art are solved by acquiring multi-source data, mining individualized time sequence correlation features, setting dynamic influence factor weights, generating individualized suggestions and optimizing the weights based on feedback iteration.

A method of monitoring stress of a user includes receiving a plurality of time-series data inputs from a plurality of biometric sensor electrodes of a wearable computing device. The time-series data inputs includes continuous electrodermal activity data and at least one of heart rate data, skin temperature data, and heart rate variability data. The method also includes processing the time-series data inputs using a plurality of filtering techniques in sequence. Further, the method includes selecting a model from a plurality of models based on types of data inputs received as the time-series data inputs to calculate an indicator of a physiological response of the user at a certain time. Thus, the selected model is tailored to use all of the time-series data inputs in the calculation of the indicator of the physiological response. Further, the method includes controlling a function of the device when the indicator of the physiological response exceeds a threshold.

The invention discloses an animal breeding screening method and system based on digital traditional Chinese medicine pulse diagnosis, and relates to the technical field of animal breeding and breeding (breeding) screening, and the method comprises the following steps: building an animal physical sign digital gene bank, building a physical genetic digital gene identification model through an animal physical sign data large model, and establishing a physical genetic digital gene identification model; according to the method, female animals and male animals with corresponding excellent genetic genes are effectively identified according to breeding cultivation indexes, so that through continuous monitoring and re-evaluation, on one hand, a stable genetic gene variety can be formed, and on the other hand, female animals and male animals which temporarily have health problem markers due to short-term physiological reaction can be effectively identified; by means of the method, misjudgment caused by physiological reactions and other short-term signs is greatly reduced, it is guaranteed that female animals and male animals which have excellent physical genetic genes but are affected by temporary conditions are not mistakenly eliminated, and meanwhile it is guaranteed that female animals and male animals which really have physical genes and have defects can be accurately recognized and screened out.

Automated systems and methods are presented for determining the physiological response of human or suitable animal subjects to physical exertion. The methods and systems can include monitoring sensors that capture the motion of the subject along with corresponding physiological data, and can track such motion for the duration of a period of physical exertion. The system is able to acquire an initial stream of physiological data from the subject during a range of physical exertion activities that are representative of the events intended to be monitored with the proposed method and system, enabling a corresponding dynamic physiological response model to be created. The motion tracking system and physiological response model can then be used to predict the physiological response to physical exertion events under a prescribed framework, including applications during real-time event monitoring.

Methods, systems and devices are provided to stimulate the vestibular system in such a way as to influence the neurological components of the autonomic nervous system and reduce an anxiety level in a subject. A device with one or more electrodes placed over a subject's scalp provides vestibular nerve stimulation (VeNS) to the vestibular nerve, which is then carried into the vestibular nucleus in the brainstem and thereafter transmitted to the neurological components of the autonomic nervous system to reduce a physiological reaction to an anxiety event. The characteristics of the stimulation signal and duration of the treatment are configured to allow the treatment to be delivered before, during or after an anxiety event to potentially prevent or at the very least reduce an anxiety response in the subject.

Various components, methods, and systems are provided herein for monitoring physiological responses associated with force-impact events using a mouth-wearable sensing device positioned within an oral cavity of a subject. In some embodiments, the device integrates inertial sensing, force sensing, temperature sensing, and optical physiological sensing on a compact intraoral substrate and transmits physiological data wirelessly to an external computing device for analysis and reporting. In some embodiments, the mouth-wearable sensing device is customized using intraoral scan data to generate a three-dimensional oral cavity model and to position one or more sensors to align with anatomical landmarks when worn.

This invention relates to the field of health and medical data processing technology, and particularly to a method for chronic disease risk management based on community grids. The method includes constructing an initial spatial environmental potential field based on point-of-interest weights; calculating the risk exposure integral sequence and instantaneous potential gradient by combining user trajectories; if the gradient exceeds a threshold, adjusting parameters and using a matrix contour algorithm to extract stress-related abnormal motifs from physiological monitoring data; reconstructing the potential field by statistically analyzing the frequency of group motif attacks; finally, calculating the cross-correlation between the exposure integral and the attack frequency sequence to obtain a causal index; and combining this with health records to output a chronic disease risk rating and intervention instructions. In this invention, by introducing an instantaneous potential gradient to feedforward and regulate the extraction parameters of physiological motifs, the technical problem of traditional fixed-parameter sampling easily missing environmental stress physiological responses is solved, enabling the underlying algorithm to accurately capture users' stress-related abnormal physiological motifs during sudden environmental changes.

The invention relates to an intravenous anesthesia instantaneous dose regulation and control method and device based on operation stage recognition, and belongs to the technical field of medical big data and intelligent control. A deep learning model is used for carrying out high-dimensional feature fusion and time sequence mode analysis, current and future surgical operation stages are dynamically and accurately identified and predicted, an ideal target drug concentration is dynamically set by querying a built-in knowledge base generated by big data mining, and a model prediction controller is driven to calculate an optimal instant infusion rate, so that the optimal instant infusion rate is obtained. Advanced and accurate drug regulation and control are achieved, a closed-loop feedback mechanism is introduced, parameters are adaptively adjusted on line according to actual physiological reactions, and control individualization and safety are ensured. According to the invention, the crossing from passive feedback to active predictive control is realized, the stability and safety of anesthesia depth are obviously improved, and the method has great clinical application value.