258 results about "Biofeedback" patented technology

The invention discloses an oral and maxillofacial head and neck tumor rehabilitation nursing system based on artificial intelligence, which belongs to the technical field of medical auxiliary systems and comprises a special data acquisition and monitoring module, a deep reinforcement learning analysis module, a biological feedback analysis module, a personalized rehabilitation plan generation module and the like. The system can monitor physiological parameters and biological feedback signals of a patient in real time, generate a personalized rehabilitation plan and provide real-time monitoring and early warning functions, in addition, the system further comprises a plurality of auxiliary modules such as a local database, a patient interaction module and an intelligent early warning and emergency intervention module, the reliability and practicability of the system are further improved, and the system is suitable for popularization and application. According to the system, the defects of a traditional rehabilitation nursing method can be overcome, the rehabilitation precision and effectiveness are improved, the participation degree and confidence of a patient are enhanced, and more comprehensive and efficient rehabilitation nursing service is provided for the oral and maxillofacial head and neck tumor patient.

The invention provides a motion fear intervention device based on virtual reality. The motion fear intervention device comprises a VR scene generation module; the subjective evaluation module presents the TSK scale to the user to obtain a TSK scale score of the user, and obtains a TSK grade corresponding to the TSK scale score according to the TSK scale score; the biological signal acquisition module is used for acquiring biological feedback of a user and calculating a comprehensive exercise fear grade according to the following formula: the comprehensive exercise fear grade = alpha * TSK grade + beta * HRV score + gamma * GSR score + delta * pupil change score + belonging to * EMG score; the dynamic intervention module is used for generating scene parameters in real time according to the comprehensive exercise fear level and inputting the scene parameters into the VR scene generation module to generate a corresponding scene; the dynamic intervention module is also used for providing forward excitation. According to the method and the device, the currently displayed VR hierarchical scene is adjusted through biological feedback, and closed-loop feedback adjustment of motion scene stimulation is realized.

The invention belongs to the technical field of medical robot control, and discloses a physiotherapy robot self-adaptive control method and system based on multi-mode biological feedback, and the method comprises the steps: carrying out the preprocessing of a biomechanical sensing signal obtained in advance, carrying out feature extraction and dynamic weight fusion on the preprocessed biomechanical sensing signal by utilizing wavelet transform and frequency domain transform to obtain a joint feature; establishing a system dynamics model based on a Lagrange equation, generating a time-varying impedance trajectory model by utilizing a joint state acquired in real time and combining a rolling optimization algorithm, and dynamically adjusting impedance parameters of the time-varying impedance trajectory model according to joint features to generate a safe motion trajectory; and performing double closed-loop control on the physiotherapy robot according to the safe movement track and a biomechanical sensing signal obtained in real time to obtain a control signal of the physiotherapy robot, and realizing joint motor driving of the physiotherapy robot based on the control signal. The device can be flexibly changed according to individual differences of patients and rehabilitation processes.

The invention relates to the technical field of data acquisition control, in particular to a breeding environment temperature control system for a pig farm, and the system comprises a temperature acquisition module which collects the temperature data of each monitoring point in the pig farm in real time, and converts the temperature data into a temperature value sequence. According to the method, temperature data of a plurality of monitoring points in a pig farm are collected in real time, a discrete temperature data sequence is converted into basic environment information such as average temperature and temperature difference, and trend and anomaly analysis is carried out on the basis, so that the opportunity and demand of temperature adjustment are determined, the future temperature change trend of the environment is predicted, and a corresponding regulation and control plan is generated; on the basis of prediction, real-time biological feedback information, such as heart rate and body temperature, of pigs is fused, dynamic evaluation is carried out on the comfort level of individual animals, and an environment temperature regulation and control strategy is further optimized by taking the comfort level of the animals as a benchmark, so that the regulation of the environment temperature is more accurately matched with the growth requirements of the pigs, and personalized and intelligent control of the breeding environment is realized.

The invention belongs to the technical field of diving state monitoring, and relates to a diver state monitoring method based on biofeedback, and the method comprises the steps: aligning a sign signal with environment data through a timestamp, extracting motion features through acceleration data, constructing a motion noise model, and removing signal artifacts in real time; in the aspect of EEG signal purification, a db4 wavelet basis is adopted for carrying out wavelet packet decomposition, water pressure related frequency band characteristics are extracted, low-frequency drift is removed, meanwhile, heart rate signals are analyzed through nonlinear dynamics, a Lyapunov index is extracted to evaluate HRV changes, breathing and EEG # imgabs0 # wave coupling are analyzed through wavelet transformation, and the risk evaluation precision is further enhanced; in the aspect of environment compensation, through compensation of a depth and SpO2 relational expression and water temperature on respiratory frequency, in combination with SLTM network extraction time sequence features and a deep causal convolutional layer, risk trend prediction is performed, a diver risk level and a prediction curve are output in real time, a comprehensive risk index is finally calculated, the health state and potential risk of the diver are comprehensively evaluated, and safety is improved.

The invention discloses a remote proving method for a trusted data space, which relates to the technical field of computer and data security, and comprises the following steps: initializing a trusted environment and generating a dynamic identity key for a heterogeneous terminal containing a CPU (Central Processing Unit), a GPU (Graphic Processing Unit) and an FPGA (Field Programmable Gate Array) based on a hardware security module and a physical unclonable function, and generating a challenge value by a verifier by using a quantum random number; the method comprises the following steps of: firstly, transmitting to a proving party through quantum encryption and a neuromorphic photonic network, constructing proving by the proving party by adopting a tensor decomposition zero-knowledge proving protocol, finishing multi-stage verification on a verification party in combination with a space-time cause and effect graph and quantum signature aggregation, and finally realizing dynamic trust evaluation and adaptive strategy adjustment through a quantum Bayesian network, reinforcement learning and biological feedback. According to the method, the remote attestation performance of the trusted data space is improved, dynamic trust evaluation is realized by means of the quantum Bayesian network and biological feedback, attacks are effectively resisted, real-time requirements are met, trust is accurately evaluated, and the development of the trusted data space is promoted.

The invention relates to the technical field of electromyographic signal monitoring, and discloses a guided monitoring method and system based on a wireless surface electromyographic analysis feedback instrument. The method comprises the following steps: acquiring electromyographic signal time sequence data and limb movement track space coordinate information when a target muscle group moves through a multi-channel wireless surface electromyographic sensor; muscle activation intensity and fatigue change features are extracted, a joint activity angle change sequence is calculated, and a muscle-joint collaborative activity feature matrix is generated through space-time alignment fusion; analyzing signal transduction delay and amplitude matching degree in the matrix, and evaluating the nerve driving coordination level; according to the deviation from the preset standard mode, generating a real-time biological feedback signal containing an action correction instruction and a muscle activation intensity adjustment parameter; and converting into a tactile vibration mode and a visual guidance mark to be output. According to the method, synchronous acquisition and fusion analysis of multi-dimensional motion information are realized, and visual guidance is provided through multi-modal feedback.

A portable therapeutic exercise device is disclosed for strengthening leg muscles in patients with severe muscular weakness after bedrest. The device features a lightweight, compact base with longitudinal rails and a moving carriage equipped with an adjustable footplate, cushion, and straps for secure engagement. Resistance cords provide variable tension, and a lumbar bolster with an adjustable strap stabilizes the base. A distance sensor and Bluetooth-enabled microcontroller relay real-time data to mobile devices for interactive visual biofeedback, including gaming applications. The carriage offers smooth linear motion via bearing wheels with adjustable spacers. Designed for use in hospital beds, chairs, or on the floor, the device provides a safe, adaptable, and engaging solution for rehabilitation exercises.

The invention relates to the technical field of medical instruments, and discloses an intelligent device for monitoring the cardio-pulmonary function of a heart failure patient, the intelligent device comprises a multi-mode sensor module, an AI analysis module, a biological feedback module and a wearable carrier, the multi-mode sensor module is used for collecting heart rate, respiratory rate, oxyhemoglobin saturation and body movement data in real time, and the AI analysis module is used for analyzing the heart rate, the respiratory rate, the oxyhemoglobin saturation and the body movement data; monitoring modes can be dynamically switched in rest, motion and sleep scenes; the AI analysis module is used for detecting abnormity based on real-time data and predicting a heart failure deterioration risk in combination with historical data; and the biological feedback module is used for providing personalized intervention in a vibration or audio mode according to the analysis result. The heart rate, the respiration rate, the blood oxygen saturation and the body movement data are collected at the same time through the multi-mode sensor module, sleep apnea or periodic respiration is recognized in combination with the AI analysis module, the defect of separation of cardiopulmonary function monitoring and sleep mode analysis in the prior art is overcome, and therefore early intervention and treatment adjustment are supported.

The invention discloses a vocal cord problem recognition and feedback system for the ophthalmology and otorhinolaryngology department. The vocal cord problem recognition and feedback system comprises a sound collection module, an image collection module, a biological feedback module, a data processing module, an AI diagnosis module and a rehabilitation guidance module. The sound acquisition module comprises a microphone array and a self-adaptive noise reduction unit; the image acquisition module is provided with an endoscope camera and an image enhancement processor; the biological feedback module integrates a laryngeal myoelectricity sensor and a three-dimensional motion simulator; the data processing module executes multi-modal feature extraction and fusion; through mutual cooperation of the sound acquisition module, the image acquisition module, the biological feedback module and the data processing module, data can be accurately acquired, the early canceration detection rate is improved and the misdiagnosis rate is reduced through multi-modal fusion, the data acquired by the multi-modal structure is analyzed through the data processing module, the model is combined with a weekly updated disease map, and the early canceration detection rate is improved. And the recurrence prediction accuracy is improved.

The invention relates to the technical field of electric acupuncture apparatuses, and discloses a method and a system for automatically adjusting stimulation parameters of an electric acupuncture apparatus. According to the method, body surface electromyographic signals, skin impedance and capillary hemodynamic parameters of a user are collected in real time through a sensor set, feature extraction and analysis are conducted through a time sequence prediction model of a Transform architecture, and physiological feature data are generated. And then, constructing a user physiological state characterization model by adopting a multi-modal neural perception fusion algorithm, and carrying out collaborative optimization on the electrical stimulation parameters through an adaptive quantum particle swarm optimization algorithm to generate a stimulation parameter combination matched with the real-time neuromuscular response characteristics of the user. The system drives electrical stimulation output according to the parameter combination, monitors physiological data changes in real time, realizes closed-loop dynamic balance of stimulation parameters and biological feedback signals through the dynamic parameter compensation module, and improves the treatment effect and safety.

The invention provides a biofeedback type electrical stimulation regulation and control device based on multi-mode physiological signal monitoring and a control method, the regulation and control device comprises an electronic component layer, a circuit layer, a man-machine interaction part and an adhesion layer, physiological signal acquisition and electrical stimulation regulation technologies are utilized, and a multi-source biosensor and an intelligent processing module are integrated, so that the regulation and control of the biofeedback type electrical stimulation regulation and control device is realized. Dynamic monitoring and real-time analysis of physiological signals are achieved, self-adaptive adjustment of personalized parameters is conducted based on signal characteristics, and a non-invasive biological feedback regulation and control system is formed. Through integrated multi-mode detection and intelligent regulation and control functions, a non-invasive and convenient regulation and control means is provided for wearers with abnormal nerve or physiological states; a portable and comfortable attached structure is adopted, the device can be worn at the Neiguan point for a long time, physiological signal continuous monitoring and electrical stimulation closed-loop feedback adjustment are achieved, and the personalized health management requirement of a user is met.

A system for guiding a user with heart rate variability feedback may include a computing device comprising a heart rate sensor, one or more processors, and memory having stored thereon computer program code that, when executed by the one or more processors, is configured to cause the one or more processors to receive user input, responsive to receiving the user input, cause an audio output device to output an audio content associated with a default breathing pattern, dynamically receive interbeat interval data from the heart rate sensor, dynamically extract one or more characteristics from the interbeat interval data, cause the display to indicate a dynamic visual pattern based on the one or more characteristics, dynamically determine a second breathing pattern based on the one or more characteristics, and dynamically cause the audio content to change based on the second breathing pattern.

The invention relates to the field of intelligent creation of personalized music, and discloses an intelligent creation system of personalized music, comprising a non-residual music gene modeling module for constructing a structured feature tensor; the user state sensing and trajectory planning module is used for acquiring physiological state data of a user in real time and planning a target emotion parameter trajectory sequence for guiding the emotion state of the user; the constraint optimization generation module is used for generating an optimal music feature tensor sequence by solving a dynamic constraint optimization problem; and the multi-modal synthesis and presentation module synthesizes the music feature tensor sequence into audio synchronous with the virtual playing action and outputs the audio. According to the method, a scheme of combining user physiological state perception and predictive emotion trajectory planning is adopted, so that dynamic and prospective guidance of user emotion is realized; the music is converted into an active and personalized biological feedback tool from a passive listening medium, so that the effectiveness of the music in emotion regulation application is remarkably improved.

The invention relates to the field of pelvic floor muscle recovery treatment, in particular to a female pelvic floor muscle recovery treatment device and an adjusting structure thereof.The female pelvic floor muscle recovery treatment device comprises a movable base, a control box is arranged on the surface of the movable base, a hydraulic rod is installed on one side of the control box, and a recovery supporting plate is installed at the top of the hydraulic rod; a massage repairing device capable of massaging female pelvic floor muscles is installed on the upper surface of the repairing supporting plate, a movable structure is installed in the repairing supporting plate, and a lifting adjusting structure capable of freely moving is arranged above the repairing supporting plate. The top of the lifting adjusting structure is provided with an abdomen repairing structure capable of repairing female abdomen muscle tissue, and the matrix type layout of the massage vibrators can stimulate pelvic floor muscle groups in a partitioned mode, so that the biological feedback effect is enhanced. The leg repairing structure drives a sliding ball to move in an arc groove through an electric telescopic rod, switching between resistance training and passive stretching is achieved, and lower limb venous thrombosis is effectively prevented.

The invention provides a pelvic floor muscle function exercise method and system based on remote digital guidance, and relates to the technical field of remote rehabilitation guidance, and the method comprises the steps: arranging a multi-channel micro sensor array at a preset position of a pelvic floor muscle group, and collecting electromyographic signals and tissue deformation data in resting and contraction states; generating a biomechanical model through Fourier transform and multi-dimensional mapping calculation; performing convolutional neural network analysis on the model and a standard physiological database to generate functional damage positioning data; the remote medical data center calculates a neural pathway activation parameter based on the injury positioning data, generates a training instruction and converts the training instruction into a biological feedback control signal; collecting real-time biomechanical data in the training process, calculating a muscle group synergy efficiency value and generating a fatigue characteristic curve; training parameters are adjusted in real time through wavelet transformation and deep reinforcement learning network analysis, a training scheme iteration closed loop is formed, and precise remote guidance of pelvic floor functional rehabilitation is achieved.

Disclosed are devices, systems and methods for acquiring, analyzing, and utilizing neurofeedback to promote brain coherence. Neurofeedback is a form of biofeedback that allows an individual to regulate his / her brain activity by providing a visual metaphor of brain function, thereby making it accessible for manipulation. In some embodiments of the present technology, a system includes a brain signal detection device wearable by a subject and a computer device including a display and a brain-computer interface (BCI) configured to monitor brain signals and display visual, auditory, and / or tactile stimuli to the subject according to a neurofeedback threshold-based protocol to deliver brain signal coherence between the left and right hemispheres of a subject's brain.

The invention belongs to a lumbar vertebra brace, and particularly relates to an intelligent self-adaptive lumbar vertebra rehabilitation brace combining targeted physiotherapy and biological feedback, which comprises a shell consisting of a front piece, side wings and a rear piece, the treatment module is arranged in the through hole area of the front piece and integrates a vibration actuating array, a flexible warming piece and a TENS electrode; the sensor module is provided with an overall detachable patch, and the sensor module integrates an interface pressure array, an IMU, an sEMG, an NTC and a PPT micro probe; the multi-cavity air bags are arranged along transition areas of the side wings and the front piece in a partitioned mode, and the micropump and the electromagnetic valve are connected with the multi-cavity air bags. One end of the self-adaptive winding adjusting module is arranged on the rear piece, the other end of the self-adaptive winding adjusting module is located in a winding cavity of the side wing and connected through a pull rope, the side wing end can be wound and stretched to adjust the tightness degree, vibration, heat and TENS parameter self-adaption are carried out on a pain point through PPT and sEMG feedback, lumbago can be reduced in a short time, and the curative effect can be quantified through PPT and myoelectricity.

The invention relates to the technical field of intelligent medical rehabilitation, in particular to an abdominal respiration training method and system based on an intelligent guiding algorithm. The continuous real-time breathing data sequence contains at least one of a breathing frequency periodic change characteristic, a breathing amplitude dynamic change characteristic and a breathing phase accurate definition characteristic which change along with time; comprehensively evaluating the continuous real-time breathing data sequence according to a statistical analysis algorithm based on dynamic threshold setting and multi-dimensional feature fusion to obtain a comprehensive breathing health index for evaluating the breathing state of the user; according to the comprehensive respiratory health index, based on inference rules in a knowledge base, a customized respiratory training plan is generated through an intelligent decision engine combining a deep learning algorithm and a biological feedback mechanism. By implementing the method, potential information in the respiration data can be deeply mined, so that a more scientific and personalized respiration training plan is generated.

The invention provides a hypertension VR intervention method based on dynamic biofeedback and individualized modeling, and provides a hypertension VR intervention system based on dynamic biofeedback and individualized modeling. The method comprises the following steps: performing state analysis on dynamic biological feedback indexes of a hypertensive patient, namely a predicted pressure index (SPI) and an exercise intensity index (EII), deciding a hypertension VR intervention decision matched with the state of the dynamic biological feedback indexes, activating a VR scene of the corresponding decision in a system, and actively enabling the hypertensive patient to perform adaptive intervention training through VR equipment. Therefore, dynamic biological feedback intervention is realized by utilizing an intelligent decision training mode of the intelligent model. According to the method, training mode recommendation can be accurately carried out according to the patient state, state reward can be carried out according to the blood pressure change amplitude and the patient compliance score, so that the patient training mode is optimized, intelligent training is achieved, and the method has high guiding significance.

The invention relates to the technical field of fatigue driving detection, in particular to a fatigue driving early warning method and system based on combination of instantaneous oil consumption and biofeedback, comprehensive analysis is carried out in combination with the vehicle running state and the biological characteristic data of a driver, the fatigue state of the driver can be judged more accurately, and misjudgment and missed judgment are reduced. According to the method, a dynamic time warping algorithm is adopted to eliminate time sequence deviation of multi-source data, a nonlinear mapping relation between an instantaneous oil consumption fluctuation curve and an eye movement frequency curve is constructed, and the problem of time sequence deviation of physiological signals and operation signals is solved.

The invention discloses an intelligent cabin healthy light environment adjusting system and method based on biological feedback, and belongs to the technical field of intelligent cabin and vehicle control. The method comprises the following steps: collecting a multi-modal physiological signal of a passenger; physiological signals are processed in parallel through two paths; determining a feed-forward control weight based on the dynamic change degree between the current steady-state emotional state and the future emotional state trajectory; according to the feed-forward control weight, performing weighted fusion on the current steady-state emotional state and the future emotional state track to generate a comprehensive light environment adjustment instruction; according to the comprehensive light environment adjusting instruction, a dynamic light and shadow relieving strategy is generated and executed, and the strategy at least comprises at least one of the color temperature, the brightness or the dynamic rhythm of the cabin light environment. By introducing the feedforward control mechanism, the emotional fluctuation of the passenger can be predicted and intervened in advance, the response delay of the system is reduced, the conversion from passive response to active prediction is realized, and the timeliness and accuracy of emotional relief are improved.

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 a wearable fitness monitoring system that uses advanced sensor technology to track real-time muscle engagement, posture, and fatigue levels during physical activity. The system comprises a capacitive sensor system, incorporating elastic silver fiber cloth and medical-grade silicone, for precise muscle movement detection; a motion sensor for tracking movement along multiple axes; and an AI-powered processing unit to provide ergonomic feedback, prevent injuries, and optimize performance. It features dynamic self-calibrating sensors that adjust to user-specific movements using machine learning algorithms. The system offers personalized workout plans, adjusting in real-time based on biometric feedback, environmental conditions, and muscle fatigue. Additionally, it integrates Bluetooth Low Energy (BLE) for wireless communication, haptic feedback for posture correction, and AR / VR for immersive workout guidance. The system includes cloud-based data storage with encryption and supports blockchain for secure data management, offering a comprehensive, personalized fitness experience that improves workout efficiency and safety.

An athlete fatigue recovery auxiliary system based on biofeedback belongs to the field of fatigue recovery assistance and comprises a data acquisition module, a processing extraction module, a state evaluation module, a scheme making module, an adjustment monitoring module and an evaluation feedback module. According to the method, the fatigue state of the athlete is comprehensively evaluated based on various physiological signals, and the physiological and exercise load state of the athlete can be effectively and accurately reflected. According to the method, personalized recovery suggestions can be provided according to individual differences of all athletes. The recovery strategy can be dynamically adjusted to meet the actual requirements of different athletes, so that the recovery effect is improved, and the risk of excessive recovery or insufficient recovery is reduced.

Aspects relate to apparatuses and methods for individualized polygraph testing. The apparatus including at least an interface configured to communicate questions to the user, at least a sensor configured to detect biofeedback signals as a function of a biofeedback of a user, wherein the biofeedback is associated with at least an answer to at least a question, and at least a computing device including at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to receive the biofeedback signals, generate a user state classifier, train the user state classifier as a function of a user state training set, wherein the user state training set includes biofeedback signals correlated to answers of known veracity, and classifying a biofeedback signal of the biofeedback signals to a user state as a function of the user state classifier.

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 discloses a virtual reality-based positive-feeling biofeedback system, which comprises a user evaluation module for acquiring psychological state information of a user through a psychological state evaluation questionnaire; the virtual reality equipment is used for providing a virtual reality scene for the user to carry out training; the guidance information is displayed in the virtual reality scene; the physiological signal detection device is used for collecting a physiological signal of the user in the process that the user executes the mind training by utilizing the virtual reality equipment; the physiological signals are synchronously displayed in the virtual reality scene; the electroencephalogram device is used for collecting electroencephalogram signals of the user in the process that the user executes the mind training through the virtual reality device; and the data analysis module is used for analyzing the psychological state cause of the user according to the psychological state information, the physiological signals and the electroencephalogram signals, generating an evaluation report according to an analysis result, and giving a mentality training suggestion according to the evaluation report, so that the intervention effect of mentality training on psychological diseases is improved.

The invention relates to the technical field of medical instruments, in particular to a multi-mode biological feedback ear vagus nerve self-adaptive stimulation device and method.The device comprises a host, a stimulation electrode, a signal collection bracelet and an electroencephalogram collection module, and the host comprises core hardware configuration and a power management system; the signal acquisition bracelet comprises an ECG module, a PPG module, a GSR module, a six-axis acceleration sensor and the like. The ear vagus nerve stimulation parameter can be dynamically adjusted through real-time analysis of multi-mode data such as electrocardio, electroencephalogram, heart rate variability, respiration-heart rate synchronism and emotional state, personalized precise treatment is achieved, meanwhile, the wearing comfort and the durability of the device are improved, and the application range is wide. The traditional Chinese medicine composition can be used for auxiliary treatment of various diseases such as inflammatory bowel disease, epilepsy, chronic insomnia, depression, chronic pain, anxiety disorder, post-traumatic stress disorder and autonomic nerve dysfunction, and the functions of a nervous system are adjusted and the symptoms of a patient are improved by accurately stimulating the vagus nerve in the auricular concha area.

The invention relates to the technical field of physiotherapy, in particular to a multi-mode physiotherapy system integrating ion release and electromagnetic stimulation. The system comprises a biological feedback sensing module, an intelligent control module, a space-time cooperative control module, a multi-channel ion release module, a multi-band electromagnetic generation module and a self-adaptive optimization module. Firstly, skin impedance, blood flow and temperature parameters are collected by the system, and a collaborative strategy is generated through multi-parameter analysis of an intelligent control module; the time-space cooperative control module synchronously adjusts the ion release and electromagnetic field excitation time sequence; the multi-channel ion release module realizes quantitative release of multiple types of ions by utilizing microfluidics; the multi-band electromagnetic generation module outputs low-frequency, medium-frequency and high-frequency programmable electromagnetic fields; the adaptive optimization module dynamically corrects treatment parameters based on the electrophysiological feedback. According to the system, multi-modal fusion of iontophoresis and electromagnetic stimulation is realized, and the accuracy and individualization level of treatment are improved.