116 results about "Biofeedback" patented technology

The invention provides a biological characteristic closed-loop monitoring method, device and equipment based on terahertz signals, and the method comprises the steps: executing closed-loop regulation and control operation based on target biological characteristic information; wherein when the closed-loop regulation and control operation comprises environment self-adaptive regulation and control, the environment self-adaptive regulation and control comprises the steps of monitoring an environment parameter of an environment where the target organism is located, and dynamically adjusting a signal parameter used for transmitting a terahertz signal based on the environment parameter; when the closed-loop regulation and control operation comprises biological feedback regulation and control and it is judged that the target biological characteristic information meets a preset abnormal condition, the biological feedback regulation and control is used for dynamically adjusting communication network resources used for bearing terahertz signals. According to the method, the target biological characteristic information in the terahertz reflection signal and the auxiliary sensing signal is analyzed, traditional equipment does not need to be worn, and the accuracy and convenience of biological characteristic monitoring are improved; the robustness and intelligence of the whole biological characteristic monitoring system are improved through a double closed-loop mechanism of environment adaptive regulation and biological feedback regulation.

The invention relates to the field of closed-loop nerve regulation and function reconstruction, and discloses a closed-loop brain-spinal cord interface upper limb grasping function reconstruction method and system based on multi-modal biofeedback. According to the method, at least three kinds of feedback information such as joint angles, grabbing force and electromyographic signals are synchronously collected, and a comprehensive actual motion state is generated through weighted fusion; according to an error vector between an expected state and an actual state, a hierarchical adjustment strategy is creatively adopted to carry out differentiation and adaptive adjustment on parameters such as stimulation current intensity, frequency and pulse width; and fatigue indexes are calculated based on myoelectricity frequency domain characteristics (such as median frequency and average power frequency), and prospective intervention is carried out by superimposing a fatigue compensation strategy. The method effectively solves the problems that an existing system is low in control precision, insufficient in single feedback dimension information and insufficient in continuous motion ability, and the precision, adaptability and long-term stability of motion control are remarkably improved.

The invention relates to the technical field of automatic control, and discloses a pelvic and abdominal muscle group cooperative training self-adaptive control system based on biological feedback, which comprises a state drift observation module, a dynamic threshold value resolving module and a self-adaptive control module, and is characterized in that the system monitors the amplitude attenuation rate of a main constraint variable in real time to update an attenuation coefficient; constructing a dynamic safety envelope containing slew rate limitation and amplitude saturation; when the first-order time derivative of the disturbance variable exceeds the limit, the controller locks the output slope of the disturbance variable, and dynamic oscillation of the time-varying coupling system caused by high-frequency pulse disturbance is suppressed by establishing a dynamic mapping mechanism of the disturbance loading rate and the main variable response bandwidth. The adaptive compensation of the parameter drift of the controlled object and the steady-state maintenance of the control precision are realized.

The invention relates to the field of medical instruments, in particular to a self-adaptive inflatable medical protection restraint system and a monitoring control method. The system comprises a restraint strap body, a pneumatic control module, a biological feedback module and a system control module. An air bag array consisting of a plurality of independent air chambers is arranged in the restraint strap body; the pneumatic control module is used for inflating and deflating each air chamber; the biological feedback module is integrated on the belt body, comprises a pressure sensing unit and a blood supply sensing unit, and is used for monitoring and constraining interface pressure and limb blood supply state in real time; and the system control module receives the monitoring data, generates an instruction based on a preset safety parameter, and drives the pneumatic control module to perform self-adaptive pressure adjustment on the specified air chamber. According to the system, through dynamic monitoring and accurate adjustment, the problem that a traditional restraining device is prone to causing compression injury and blood supply disorder is effectively solved, and safety and comfort are remarkably improved.

The invention discloses a self-adaptive closed-loop ultrasonic stimulation system and method based on Actor-Critic reinforcement learning, and belongs to the field of neural regulation and control technologies and biomedical engineering, and the system comprises a signal collection module, a preprocessing module, an Actor strategy module, a Critic value module, an ultrasonic stimulation module, a safety monitoring module and a storage module. The Actor strategy module generates safe and controllable ultrasonic stimulation parameters according to the preprocessed electroencephalogram data; the safety monitoring module is used for checking whether the ultrasonic stimulation parameters generated by the Actor module meet safety standards or not; the ultrasonic stimulation module sends out an ultrasonic stimulation signal according to the ultrasonic stimulation parameter; and the Critic value module evaluates the electroencephalogram feedback effect after ultrasonic stimulation and provides feedback to the Actor module for optimizing the experimental strategy of the next step. The invention aims to intelligently adjust the ultrasonic stimulation parameters through the biofeedback data monitored in real time in combination with the reinforcement learning algorithm.

The invention relates to the technical field of medical instruments, in particular to a magnetic control pulse type pelvic floor nerve muscle stimulator and a parameter optimization system thereof. Comprising a host, a dynamic layered pulse waveform generation technology module, a multi-target reinforcement learning parameter optimization module, a multi-modal biofeedback fusion and VR enhancement module, and a flexible wearable stimulation array and ultrasonic targeting module. The system has the advantages that real-time data and deep learning are achieved, and personalized precise treatment is achieved, in the actual use process, the dynamic layered pulse waveform generation technology module predicts the requirements of muscles in the next stage through a deep learning model on the basis of pelvic floor electromyographic signals, pressure data and infrared thermal imaging which are collected in real time, and the treatment accuracy is improved. Dynamically generating a composite pulse waveform; the multi-objective reinforcement learning parameter optimization module constructs a'state-action-reward 'reinforcement learning framework, and takes patient treatment feedback, muscle force improvement, pain score and treatment compliance as reward signals.

The invention relates to the technical field of intelligent driving, and provides an intelligent driving method and system based on driver biofeedback. The method comprises the following steps: firstly, acquiring multi-mode biological signals such as heart rate, electrodermal response and eye movement track of a driver and a vehicle movement signal in real time through an in-vehicle sensor; carrying out cross-modal feature fusion and analysis on the signals by utilizing a driver state analysis model, carrying out parallel calculation on tensity, motion sickness and attention level indexes of the driver, and generating a quantized comfort level score; furthermore, in a trajectory planning stage, a comfort level score corresponding to each candidate trajectory is predicted through a personalized comfort level prediction model, the comfort level score is used as an optimization target parallel to safety and efficiency for comprehensive decision making, and finally an optimal trajectory is selected for execution. According to the invention, the automatic driving system can sense and respond to the subjective state of the driver in real time, the tension and motion sickness of passengers can be effectively relieved, and the riding comfort and personalized experience are improved.

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 discloses a kindergarten teacher emotional load evaluation system based on multi-modal biological feedback, and relates to the technical field of physiological parameter detection and emotional load intelligent evaluation; comprising a data acquisition module, a posture recognition module, a mismatch analysis module, a mode classification module, a load correction module and a fusion evaluation module; through acquisition of wrist photoplethysmography signals, wrist skin electricity signals and wrist motion posture signals, action-to-still candidate windows are recognized, skin electricity activation indexes, pulse morphology consistency, amplitude recovery ratios and cross-modal mismatch representation quantities are extracted, pressure bias pseudo-steady state probabilities are determined, and original cardiovascular load indexes are corrected accordingly; and emotional load evaluation results are obtained by fusing the corrected cardiovascular load indexes and the skin electricity activation indexes. The application can reduce the interference of wristband contact pressure bias on evaluation results, and improve the accuracy, continuity and interpretability of kindergarten teacher emotional load evaluation.

The present invention relates to attention training systems and methods, particularly for treating individuals with Attention-Deficit / Hyperactivity Disorder (ADHD). Specifically, the present invention is related to employing biofeedback and virtual reality technologies to enhance gaze control and attention measures. The claimed invention represents a system and method for attention training that improve the relevant technological field by providing and utilizing a highly informative real-time biofeedback reliably representing the user's ability to sustain attention.

The application discloses a kind of based on active learning and man-machine collaborative optimization's massaging robot control method, it is related to artificial intelligence, medical rehabilitation robot and complex contact type operation control cross technical field, this method relies on multimodal perception system, core computing hub and remote man-machine collaborative interface control platform, in turn complete the initial massaging strategy model construction of multi-source heterogeneous expert data, the uncertainty measurement based on bayesian neural network, man-machine collaborative key frame active learning trigger, reinforcement learning reward function design of fusion patient biological feedback and incremental learning of impedance control parameter and force-position hybrid output;The application greatly improves the clinical safety of massaging robot, exponentially reduces data acquisition cost, realizes individual physiological closed-loop rigid-flexible massaging, also overcome the catastrophic forgetting problem of neural network, endow system lifelong learning ability.

Biometric metric wearable systems and methods are disclosed for detecting intended limb motion and invoking pain mitigation. Biometric signal data of a user is sensed by biosensor(s) that form part of respective sensor pod(s) of a biometric wearable device while the user performs an intended limb motion. The sensor pod(s) include biofeedback indicator(s). Processor(s) communicatively connected to the biometric wearable device analyze the biometric signal data to learn in real time or near real time user-specific biosignal pattern(s) detected when the user performs the intended limb motion, and generates therefrom learned user intent data configured for at least one of: (1) visualizing a virtual limb, (2) visually controlling a graphical aspect, and / or (3) visualizing the one or more user-specific biosignal patterns on a display device. The processor(s) then visualize the learned user intent data on the display device for invoking a pain mitigation effect with the user corresponding to the given limb.

1. Name of the product in this design: Multifunctional Biofeedback Electrotherapy Head. 2. Purpose of this design: Electrotherapy. 3. The key design feature of this product is its shape. 4. The picture or photo that best illustrates the key design points: Design 1 3D diagram 1. 5. Design 1 is designated as the basic design.

The invention relates to a household rehabilitation training method and device based on a lower limb exoskeleton and a storage medium, and is applied to the technical field of rehabilitation training, and the method comprises the steps: obtaining multi-modal data, and unifying the multi-modal data (an electroencephalogram signal, a muscle signal and a foot pressure signal) into dynamic control input through a covariance matrix fusion algorithm; an exoskeleton assistance strategy is optimized in real time in combination with a reinforcement learning model (PPO algorithm); the user performs force application adjustment through biological feedback visual display of an electroencephalogram feature vector, a muscle feature vector and a foot pressure feature vector, the walking intention of the user is recognized through a personalized CNN model according to an electroencephalogram signal subjected to force application adjustment, and the user is assisted in walking through an exoskeleton assistance strategy; a closed loop for the patient to actively adjust the force is formed, and the nerve remodeling effect is enhanced.

A computer-implemented method enables conversational personalization of therapeutic outputs using biomarker-specific retrieval-augmented generation. Physiological biomarkers and their relational mapping, integral coherence scores, and causal chains are provided as context to a large language model or specialized AI assistants. The system generates tailored explanations, asks clarifying questions, and iteratively refines suggestions based on user responses and updated biomarker data. Specialized assistants, each focused on a subset of biomarkers or categories, interact with the user to modify therapeutic protocols in real time. Live biofeedback can be triggered during dialogue to re-compute features and adapt outputs, achieving highly individualized coherence restoration and health and wellness guidance.

This invention discloses a knee joint range of motion trainer combining angle sensing and biofeedback, belonging to the field of rehabilitation assistive device technology. The trainer includes a hinged support frame and a lower leg frame. The support frame consists of a base and a nested thigh frame, with height adjustable via threaded pins and positioning holes. The lower leg frame includes a telescopic frame and a swing frame to accommodate different lower leg lengths. The telescopic frame is equipped with a pedal and a fixing strap for securing the lower leg. The hinge axis features an angle slot, a limiting pin, and a linkage structure of an active rod, a driven rod, and a slider. An angle sensor is installed at the left end of the hinge axis and electrically connected to an embedded calculation and control module. A detachable electric push rod is also provided. This invention allows for flexible switching of training modes, precise monitoring of knee joint range of motion angle and speed, and provides tactile feedback to indicate when the angle has reached the target, adapting to different rehabilitation stages and patient body types.

A method and system for personalized biofeedback from a wearable device that can include collecting a set of biometric inputs comprising at least heart activity data; generating a heart rate variability signal from the heart activity data; determining a feedback treatment plan which is based at least in part by processing of biometric inputs which comprises analyzing the heart rate variability signal; and delivering feedback based on the feedback treatment plan.

The present application relates to the technical field of cognitive impairment rehabilitation, in particular to a brain cognitive recovery training scheme analysis system and method for cognitive impairment, comprising five units of basic information acquisition, cognitive test execution, test report generation, norm updating and training scheme analysis, wherein the norm database is modeled in multiple dimensions according to age, educational background and medical history, a regional correction factor is introduced, data freshness is verified by means of blockchain storage, an adaptive sequence is generated for cognitive test, multi-modal data such as correct answer rate, touch screen trajectory and eye movement data are collected, time domain signal separation and denoising are performed, the training scheme analysis unit locates cognitive defects, matches the training module, monitors the brain electrical theta wave and P300 latency through biological feedback, dynamically adjusts the training intensity and frequency, promotes neural circuit reorganization and improves rehabilitation accuracy.

The invention belongs to the field of flight personnel state monitoring, and discloses a meta-consciousness ability training method and system based on a neural biofeedback technology. The system can obtain neural activity data directly related to the distraction state in a real and continuous task situation, hysteresis and unreliability caused by dependence on subjective reports or behavioral expressions are avoided, and the accuracy and objectivity of distraction monitoring are improved from the source. The decoding model is embedded into a closed-loop neural feedback training system, so that an acoustic feedback signal can be triggered in time when a distraction state occurs, a trainee is prompted to perceive attention deviation, and the self consciousness state is autonomously regulated and controlled without external guidance. The closed-loop feedback can strengthen a conditioned reflex mechanism paying attention to a regression task, and the self-monitoring and self-adjusting capability of meta-awareness is remarkably improved.

The invention relates to the technical field of intelligent health equipment, in particular to a massage chair intelligent adjusting system fusing biological feedback signals and a control method thereof, and the system comprises a multi-mode biological signal acquisition array, a signal conditioning and feature calculation unit, a physiology-massage coupling model, a mechanical-electrical integration execution assembly and a closed-loop correction loop; according to the method, multi-dimensional quantification of fatigue, muscular tension and stress level of the user is completed through synchronous acquisition and feature extraction of multi-modal physiological signals, optimal massage excitation parameters adaptive to the physiological state of the user are solved in combination with a physiology-massage coupling model, and dynamic optimization of the massage process is achieved through a closed-loop correction loop. According to the method, personalized generation and full-process closed-loop regulation and control of the massage scheme are achieved, the real-time physiological state of the user is accurately adapted, and the effectiveness and comfort of the massage effect are effectively improved.

The invention provides self-adaptive 40Hz acousto-optic cooperative equipment and application thereof in cognitive disorder treatment, belongs to the field of cognitive disorder treatment equipment, and solves the problems that the existing acousto-optic cooperative equipment is uncomfortable in strong light, easy to shift and the like. Comprising a 3D structured light scanner and a rear hoop clamping cover, side connecting plate pieces are arranged on the left side and the right side of the 3D structured light scanner, the two side connecting plate pieces are in transmission connection with the rear hoop clamping cover, a top bandage assembly is arranged between the upper side of the 3D structured light scanner and the upper side of the rear hoop clamping cover, and acoustic assemblies are arranged on the left side and the right side of the rear hoop clamping cover. A control panel is arranged above the rear hoop clamping cover, a lower bandage assembly is arranged below the 3D structured light scanner and the rear hoop clamping cover, and the system further comprises a full-closed-loop biofeedback system, a multi-sensory collaborative stimulation system, a coupling monitoring mechanism, a digital therapy platform, a self-adaptive control system and an equipment fitness AI scoring system. The system is stable to wear, direct targeting brain gamma oscillation can be fed back in real time, and nerve regulation and control are accurate.

The present disclosure relates to a device (100) for the treatment and / or prevention and / or testing of bruxism or craniomandibular dysfunction, sleep apnea and other parafunctional movements such as tongue thrusting, which is designed to be arranged between the upper and lower jaw of a user in a dental appliance or to form a dental appliance, the device comprising a biofeedback unit, in particular a mechanism as a simultaneous sensor and feedback transmitter for biofeedback or in particular a mechanism,which, upon reaching a predetermined threshold of jaw movement and / or the force resulting from a jaw movement, snaps from a first state to a second state with a switching behavior, generating feedback to the user via one or more of the human senses, and returns to the first state when the force from the jaw movement ceases, or a sensor offset towards the occlusal surfaces, or an arrangement in a section of a mandibular occlusal splint that spans or bridges the legs (bridging section). Further devices and methods for manufacturing are also disclosed.

A product dispenser refillable from a donor container, the product dispenser including a housing for receiving and storing liquid product, a dispensing module including a dispenser mechanism for dispensing liquid product from the product dispenser, and a refilling module including a funnel through which liquid product is filled into the housing from the donor container; and a refilling module cap including a plug for secure mounting on the funnel and dismounting therefrom for corresponding sealing the funnel and enabling the housing to be filled with liquid product from the donor container. Abdominal biofeedback apparatus including a biofeedback device having a rigid strap ring and a reciprocal strap ring, and a strap having two opposite free strap ends each having a securing device for securing on the rigid strap ring and the reciprocal strap ring for enabling removal of the strap from the biofeedback device.

Analog breathing biofeedback device The invention relates to an analog respiratory biofeedback device for visualizing the respiratory rate or breathing movement of a person. characterized by the fact that The breathing movement of the user is detected by a sensor (5) lying on the stomach and lightly attached with a Velcro strap (6). A strain gauge built into the sensor (5) detects the person's breathing movement and transmits the signal to a control unit (7), which amplifies the signal proportionally and passes it on analogously to an LED display (4).

The Global Resonance App enables synchronized meditation by aggregating and harmonizing frequencies across multiple users globally. Users select individual frequencies that dynamically contribute to a collective frequency pool, creating immersive visual and auditory experiences enhanced by optional biofeedback integration.

This application discloses a personalized rehabilitation system for cochlear implant surgery based on multimodal data fusion, belonging to the field of rehabilitation equipment technology. The system includes: a data acquisition and processing module for acquiring the original electrically evoked compound action potential (EEP) signals of the test subject and generating a neural response feature vector based on the original EEP signals; a personalized parameter mapping module for generating the test subject's subjective comfort threshold for the maximum electrical stimulation level based on the neural response feature vector and the test subject's clinical data; adjusting the subjective comfort threshold based on real-time biofeedback signals; and a rehabilitation training module for constructing a VR training scenario, electrically stimulating the test subject's cochlea according to the subjective comfort threshold, and acquiring the test subject's real-time biofeedback signals in the VR training scenario. This application effectively applies objective original EEP signals to personalized parameter mapping of the cochlear implant, reducing reliance on the test subject's subjective feedback and improving the accuracy and efficiency of mapping.

An apparatus to analyze and manipulate biofeedback data is described. The apparatus includes a display that renders a simulated environment. The simulated environment is experienced by a user. The simulated environment is generated by a software program executing on a computer. A biofeedback sensor is coupled to the scalp of the user. The biofeedback sensor measures the electrical activity of the brain of the user when the user experiences the simulated environment. The biofeedback sensor generates electrical signals corresponding to the electrical activity such that the user is able to modify the simulated environment by manipulating the electrical activity in the brain.

The application discloses a male massager intelligent adjustment model establishment method based on biological feedback monitoring, relates to the male massager adjustment technical field, and comprises the following steps: installing a multi-modal sensor in the massager; real-time monitoring of the biological feedback of a user is carried out to obtain feedback data; feedback features of different feedback data are extracted; the feedback features of a test personnel are extracted as test features, and the adjustment expectation of the test personnel on the adjustment parameter is recorded; the adjustment correlation between different feedback features and the adjustment parameter is analyzed based on the test features and the adjustment expectation; and the adjustment parameter of the massager is intelligently adjusted based on the feedback features and the adjustment correlation; the application is used for solving the problem that the existing male massager adjustment technology is not intelligent enough in the adjustment of the massage parameter, the user needs to frequently set the massager, and the use experience of the user is reduced.

The invention discloses an electromagnetic interference-free ultrashort wave intelligent physiotherapy self-adaptive regulation and control system based on biofeedback, and belongs to the technical field of medical physiotherapy. The system solves the problems that an existing system cannot carry out real-time adjustment according to the physiological reaction of a patient individual, and treatment parameters are difficult to accurately regulate and control, and auxiliary features are generated by obtaining the individual features and real-time physiological data of the patient and combining context features; predicting probability distribution of tissue reaction by using a neural network model, calculating a confidence interval of the probability distribution, and automatically generating an initial treatment mode by comparing the confidence interval with a threshold value; the treatment effect is simulated, and possible complications and adverse reactions are predicted; evaluating curative effects and risks under different treatment parameter combinations by combining a Pareto frontier map, and automatically generating an optimal treatment parameter combination; treatment parameters are adjusted in time according to the real-time response of the patient, and the dynamic adaptability of the treatment process is ensured, so that personalized treatment is realized, and the treatment effect and the patient satisfaction are improved.