71 results about "Functional electrical stimulation" patented technology

The invention provides a motion intention recognition control method and system based on electroencephalogram signals, and relates to the technical field of motion intention recognition. According to the method, multi-channel electroencephalogram and peripheral physiological or motion data are collected, alignment, preprocessing and frequency band division are carried out, and space-frequency-time joint representation is constructed in combination with cross-channel association and time sequence statistics; the motion intention state probability, intensity and confidence coefficient are output through a graph time sequence decoder, and self-adaption is achieved based on feature distribution alignment; incremental updating is executed under confidence driving, and error learning is avoided in combination with an error correction mechanism; asynchronous judgment is realized through double-threshold hysteresis gating, and stable switching from unintentional state to intentional state is ensured; and finally mapping the motion intention and the intensity into a control instruction of an exoskeleton or a functional electrical stimulator under safety supervision. According to the method, a complete closed-loop link from electroencephalogram signal input to execution mechanism output is formed, and recognition precision, robustness, adaptability and safety are considered.

A device for functional electrical stimulation (FES), neuromuscular electrical stimulation (NMES), and / or in receiving electromyography (EMG) signals includes a sleeve and electrodes. The sleeve is sized and shaped to be worn on a human arm, and comprises a stretchable fabric The sleeve has a distal end disposed on or adjacent a wrist of the human arm when the sleeve is worn on the human arm and a proximal end opposite from the distal end. The electrodes are secured with the sleeve and positioned to contact skin of the human arm when the sleeve is worn on the human arm. The sleeve may include an inner sleeve contact with the skin and an outer sleeve disposed over the inner sleeve. The inner sleeve has openings in which the electrodes are disposed.

The invention relates to the crossing field of medical rehabilitation and brain-computer interface technology, and particularly discloses a lower limb exoskeleton rehabilitation training system and method based on AR glasses and brain-computer interface control. According to the system, motor imagery electroencephalogram decoding is used as core driving force, lightweight AR visual guidance, lower limb exoskeleton mechanical assistance and functional electrical stimulation feedback are fused, and real-time information interaction among multiple modules is achieved through wireless communication; therefore, a closed-loop rehabilitation system integrating sensing, decoding, execution, multi-mode feedback and self-adaptive adjustment is constructed. Under the framework, the subjective motion intention of the patient not only can directly participate in the exoskeleton control process, but also can continuously adjust training parameters and interaction modes through dynamic monitoring of physiological signals and emotional states, so that a patient-centered lower limb rehabilitation training mode which better conforms to the neuroplastic law is achieved.

The invention relates to the technical field of medical rehabilitation treatment, and discloses a self-adaptive functional electrical stimulation system based on bimodal feedback and a control method. The system comprises a main control module, a stimulation output module, an electroneurographic signal detection module, a biological impedance test module and a safety isolation module. The main control module comprises a safety current determination unit, a stimulation control unit and a dynamic calibration unit which are respectively used for determining an individualized initial safety current based on neural action potential feedback, controlling treatment stimulation output and dynamically calibrating a safety current upper limit according to biological impedance change before and after stimulation. According to the invention, through bimodal feedback of electroneurographic signals and biological impedance, individualized calibration and real-time dynamic optimization of stimulation parameters are realized, and the problem that the treatment effect and safety are difficult to guarantee due to the fact that traditional functional electrical stimulation depends on experience setting and lacks physiological feedback is solved; and the accuracy, safety and adaptability of rehabilitation treatment are remarkably improved.

The present invention relates to a method and a device for obtaining a pre-trained deep reinforcement learning (DRL) model. The invention further relates to a method and a device for obtaining an optimized control signal for controlling a Functional Electrical Stimulation (FES) system using said pre-trained DRL model.

Systems and methods for generating a finite element model (FEM) of current flow in an anatomical human forearm are disclosed. The disclosed FEM may assist in determining optimal stimulation parameters in electrical stimulation systems for achieving movement of paralyzed limbs or enhancement of able limbs. This model will allow users to determine which muscle groups are receiving stimulation under different parameters. Systems and methods which leverage electrical impedance tomography (EIT) for autonomous recalibration following garment donning are also disclosed. The method may comprise performing an EIT measurement across an electrode array of an electrode garment and constructing an anatomical model based on the EIT measurement. Next, one or more alignment variations may be estimated based on an alignment variation model. Finally, the electrode array is adjusted, automatically or manually, to accommodate the alignment variations using an alignment adjustment function.

This application relates to the fields of biomedical engineering and rehabilitation engineering technology, and discloses a functional electrical stimulation method and system based on physiological simulation and adaptive closed-loop feedback. The method includes: calculating an ideal muscle activation curve based on a target trajectory; performing spatiotemporal asynchronous co-coding to generate a biomimetic stimulation pulse sequence by simulating temporal asynchrony, spatial and intensity modulation, and multi-muscle synergistic timing; simultaneously applying stimulation while monitoring the actual kinematic state and muscle physiological state in real time using sensors; and dynamically adjusting the internal parameters of the spatiotemporal asynchronous co-coding (T-S-C coding) based on the evaluation results of trajectory error and fatigue index to form an adaptive closed loop. This application, by combining biomimetic coding with an intelligent closed loop, fundamentally solves the problems of motion stiffness, muscle fatigue, and poor control precision caused by traditional FES, achieving smooth, sustained, and precise personalized motor function rehabilitation.

This invention discloses an intelligent upper limb motor rehabilitation device and its method, belonging to the field of rehabilitation device design. The device includes a motor training module and a functional electrical stimulation module. The motor training module includes a permanent magnet synchronous motor and its drive and transmission systems. The drive system can perform torque control, speed control, and position control on the permanent magnet synchronous motor. The transmission system is a worm gear structure, achieving the effects of deceleration and torque increase. This upper limb motor rehabilitation device has multiple training modes, which can exercise upper limb muscle strength, improve joint range of motion, and evaluate the torque applied by the user, assess muscle strength, and detect spasticity through a method based on a fully connected neural network. Furthermore, combined with the functional electrical stimulation module, it can electrically stimulate and activate relevant muscles based on the user's force application range. Compared to large rehabilitation training devices in hospitals, this device has a compact structure, rich functions, and is more suitable for everyday home use, reducing the workload of doctors and improving rehabilitation efficiency.

A device for functional electrical stimulation (FES), neuromuscular electrical stimulation (NMES), and / or in receiving electromyography (EMG) signals includes a sleeve and electrodes. The sleeve is sized and shaped to be worn on a human arm, and comprises a stretchable fabric The sleeve has a distal end disposed on or adjacent a wrist of the human arm when the sleeve is worn on the human arm and a proximal end opposite from the distal end. The electrodes are secured with the sleeve and positioned to contact skin of the human arm when the sleeve is worn on the human arm. The sleeve may include an inner sleeve contact with the skin and an outer sleeve disposed over the inner sleeve. The inner sleeve has openings in which the electrodes are disposed.

The present application relates to a rehabilitation system based on brain-computer interface (BCI) and functional electrical stimulation (FES) technology. Specifically, the present application relates to a system for detecting a user's exercise intention and promoting recovery of lower extremity functions through electrical stimulation according to same, and relates to a rehabilitation and assistance system for impaired persons suffering from paralysis or complete paralysis of the lower extremities. According to the present application, neural signals due to motor imagery of a user are analyzed in real time, and electrical stimulation is applied to a specific muscle group on the basis thereof to improve motor function.

The invention relates to the technical field of biomedical engineering and rehabilitation engineering, and discloses a functional electrical stimulation method and system based on physiological simulation and adaptive closed-loop feedback. The method comprises the following steps: calculating an ideal muscle activation curve based on a target trajectory; space-time asynchronous cooperative coding is executed, and a bionic stimulation pulse sequence is generated by simulating time asynchronism, space and intensity modulation and a multi-muscle cooperative time sequence; when stimulation is applied, the actual kinematics state and the muscle physiology state are monitored in real time through a sensor; and dynamically adjusting the internal parameters of the time-space asynchronous cooperative coding (T-S-C coding) based on the evaluation results of the trajectory error and the fatigue index to form a self-adaptive closed loop. According to the method, bionic coding and intelligent closed loop are combined, so that the problems of stiff movement, easy fatigue of muscles and poor control precision caused by traditional FES are fundamentally solved, and smooth, lasting and accurate personalized movement function rehabilitation is realized.

The application provides a muscle force prediction method under functional electrical stimulation, which can be applied to the field of electrical stimulation technology. The muscle force prediction method comprises the following steps: obtaining muscle fiber length information and muscle fiber velocity information of a target object; processing electrical stimulation parameters by using a neural activation model to obtain a neural activation value; the neural activation model represents the correlation between the predetermined electrical stimulation parameters and the predetermined neural activation value; the neural activation value represents the neural activation degree of the electrical stimulation parameters on the nerve; processing the neural activation value by using a muscle activation model to obtain a muscle activation value; the muscle activation model represents the correlation between the predetermined neural activation value and the predetermined muscle activation value; the muscle activation value represents the activation degree of the target muscle under the condition that the nerve of the target muscle is in the neural activation degree; processing the muscle fiber length information, the muscle fiber velocity information and the muscle activation value by using a muscle force prediction model to predict muscle force information of the target muscle.

The invention discloses a functional electrical stimulation and pneumatic muscle exoskeleton cooperative control method based on dynamic angle distribution. The method comprises the steps that S1, an expected track is generated according to parameters input by a user; s2, elbow joint motion angle parameters are collected in real time to generate an actual track; s3, constructing a function for dynamically distributing angles of functional electrical stimulation and pneumatic muscle exoskeleton according to an error angle between an expected trajectory and an actual trajectory; s4, constructing two iterative learning controllers for performing iterative learning on the angles of the functional electrical stimulation and the pneumatic muscle exoskeleton respectively, and outputting functional electrical stimulation control parameters and pneumatic muscle exoskeleton control parameters; s5, the electrical stimulator outputs an electric pulse according to the pulse width signal; meanwhile, the micro pump outputs an air source to inflate the pneumatic muscle exoskeleton according to a regulating signal of the proportional valve. Error angles are dynamically distributed, output of functional electrical stimulation and pneumatic muscle exoskeleton is adjusted, the auxiliary effect of the functional electrical stimulation and the pneumatic muscle exoskeleton on the upper limb joints is adjusted, the upper limb joints complete expected movement, control precision is guaranteed, muscle fatigue possibly caused by electrical stimulation is reduced, damage to muscles is relieved, and the effect of controlling the upper limb joints is achieved. The application value of the hybrid rehabilitation system in the exercise rehabilitation field is improved.

The application relates to the technical field of biomedical engineering and neural rehabilitation, and discloses a functional electrical stimulation method and system based on central intention and peripheral collaborative decoding of a central-peripheral collaborative mode. In a training stage, central brain signals of a diseased side and peripheral multi-channel electromyographic signals of a healthy side are synchronously collected, the central brain signals of the diseased side are input into a central intention feature extraction module to output low-dimensional central intention latent space feature sequences, the peripheral multi-channel electromyographic signals of the healthy side are decomposed to obtain a collaborative primitive matrix and a collaborative activation coefficient sequence, a mapping model is trained with the central intention latent space feature sequences as input and the collaborative activation coefficient sequence as target; in an application stage, the central brain signals of the diseased side are collected in real time to output the central intention latent space feature sequences, the mapping model is input to predict the collaborative activation coefficient sequence, and the multi-channel functional electrical stimulation instructions are reconstructed by using the collaborative primitive matrix and the collaborative activation coefficient sequence and applied to the limbs of the diseased side. The method realizes coordinated natural rehabilitation movements, and improves system robustness and individualization.

The invention belongs to the technical field of rehabilitation medical treatment and power-assisted robots, and particularly relates to a functional electrical stimulation-fused lower limb power-assisted exoskeleton robot, which comprises an exoskeleton mechanical body for fitting the lower limbs of a human body and providing mechanical support and motion guidance; the device has the beneficial effects that three core functions of functional electrical stimulation, mechanical massage and air bag assistance are integrated, an activation, circulation and support synergistic system is constructed, the rehabilitation and exercise assisting effect is greatly improved, the first electrode slice realizes reciprocating dynamic discharge through air-driven control, the first electrode slice is matched with the fixed arc plate for linkage adjustment, the leg is tightly attached, and the rehabilitation effect is greatly improved. A target muscle group is accurately activated, a rubber massage ball is matched with a sliding protrusion through a spiral groove, composite massage, circulation promotion through cooperation with electrical stimulation and fatigue relieving are completed, an air bag and a hollow sliding frame share an air path, acupoint stimulation is strengthened during expansion, auxiliary fitting is achieved, and meanwhile the adjustable support, the adaptive structure and the elastic buffering design can be flexibly adapted to different leg characteristics. And the adaptability and the comfort are both considered.

This invention relates to the fields of rehabilitation medicine, brain-computer interfaces, and functional electrical stimulation, and discloses an alternating synergistic stimulation control method suitable for asymmetric gait. The invention collects various baseline data from the patient's healthy and affected sides, calculates the initial asymmetry, and initializes training parameters based on the baseline data. After configuration, the patient undergoes rehabilitation training, and various training data are collected in real time. The training process is controlled in real time, and the phase synchronization rate and cumulative asymmetry are calculated based on the training data, thereby optimizing the training parameters in a closed-loop manner. This invention solves the specific problem of asymmetric gait in hemiplegic patients, significantly improves gait coordination and neural remodeling efficiency, and is applicable to lower limb rehabilitation devices such as brain-computer interface rehabilitation treadmills, possessing extremely high clinical application value.

A portable and wearable hand-grasp neuro-orthosis is configured for use in a home environment to restore volitionally controlled grasp functions for a subject with a cervical spinal cord injury (SCI). The neuro-orthosis may include: a wearable sleeve with electrodes; electronics for operating the wearable sleeve to perform functional electrical stimulation (FES) and electromyography (EMG), the electronics configured for mounting on a wheelchair; and a controller configured for mounting on a wheelchair. The controller controls the electronics to read EMG via the sleeve, decode the read EMG to determine an intent of the user, and operate the electronics to apply FES via the sleeve to implement the intent of the user. The neuro-orthosis may restore hand function. The controller may include a display arranged to be viewed by the subject, for example mounted on an articulated arm attached to the wheelchair.

1. The name of the design product: individual brain event-related brain function analysis graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 interface change state diagram 2. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the present graphical user interface is used for individual brain event-related brain function analysis. 7. The human-computer interaction mode of the graphical user interface: design 1 main view is a patient management interface, which can create a patient file and add a task; clicking icon A of design 1 main view enters design 1 interface change state diagram 1 to create an individual brain background, which shows the position of electrodes on the patient's brain, and the specific interface is shown in design 1 interface change state 1 reference diagram; clicking "next step" of design 1 interface change state diagram 1 enters design 1 interface change state diagram 2 to create a task-based brain function area positioning map, which characterizes the activation degree of electrode nodes by color. Design 2 main view is a patient management interface, which can create a patient file and add a task; clicking icon B of design 2 main view enters design 2 interface change state diagram 1 to create an individual brain background, which shows the position of electrodes on the patient's brain, and the specific interface is shown in design 2 interface change state 1 reference diagram; clicking "enter Mapping" of design 2 interface change state diagram 1 enters design 2 interface change state diagram 2, which can create and edit intraoperative and bedside functional electrical stimulation on the individual brain background.

Transvascular diaphragm pacing systems (TDPS) and methods are disclosed for providing respiratory therapy to a patient. The TDPS can provide rapid insertion and deployment of endovascular pacing electrodes in critically ill patients who require intubation and invasive PPMV in order to support the physiological requirements of the human ventilatory system. The systems and methods make best use of the contractile properties of the diaphragm muscle and prevent muscle disuse and muscle atrophy. This can be carried out by engaging the phrenic nerves using patterned functional electrical stimulation applied to endovascular electrodes that are temporarily and reversibly inserted in central veins of the patient, such as the left subclavian vein and the superior vena cava. The TDPS can be designed to seamlessly interface with any commercially available positive-pressure ventilatory assistance / support equipment such as is commonly in use in hospital intensive care units (ICU) for treating critically ill patients with breathing insufficiencies, pain, trauma, sepsis or neurological diseases or deficits.

The application discloses a myoelectricity-driven multi-channel functional electric stimulation upper limb rehabilitation platform and a method thereof. The platform comprises a myoelectricity collection device, a myoelectricity collection data processing system, a host computer and an electric stimulation system. The input end of the myoelectricity collection data processing system is connected with the myoelectricity collection device. The output end of the myoelectricity collection data processing system is connected with the input end of the host computer in a wireless or wired mode. The output end of the host computer is connected with the myoelectricity collection device and the electric stimulation system in a wireless or wired mode. The myoelectricity collection device collects myoelectricity signals on the surface of a healthy limb of a patient. The myoelectricity collection data processing system filters and processes the collected myoelectricity signals of the healthy limb of the patient to obtain myoelectricity data. The host computer performs gesture recognition processing according to the myoelectricity data to obtain electric stimulation parameter configuration and sends the electric stimulation system. The electric stimulation system outputs matched waveform stimulation signals on the surface of a diseased limb of the patient according to the electric stimulation parameter configuration. The application realizes bilateral fine movement by subjective movement control of the healthy limb of the patient on the diseased limb, and accelerates the rehabilitation process.

This invention discloses a wavelet-enhanced co-activation method for multi-target temporal modulation of functional electrical stimulation (FES), relating to the field of biomedical engineering technology. The model constructs a time-frequency energy salient feature matrix by analyzing multi-channel surface electromyography (SEMG) signals using an overlapping sliding window combined with energy proportions. Simultaneously, it constructs an intermuscular co-activation matrix within the multi-channel SEMG sliding window. Each single-channel time-frequency energy salient feature matrix and the multi-channel intermuscular co-activation matrix are then combined to form a multi-channel high-dimensional matrix. This high-dimensional matrix is ​​then dimensionality-reduced to a multi-channel, multi-dimensional time-frequency energy-intermuscular co-activation matrix. An adaptive threshold logic combination rule is used to filter muscle activation temporal vectors, and finally, the activation temporal sequence is applied to FES experiments. This invention, by analyzing multi-channel SEMG signals and multi-target muscle co-activation characteristics, accurately predicts hand movements in the sagittal plane and dynamically adjusts FES parameters, achieving precise control over muscle activity phases.

The invention discloses a self-adaptive functional electrical stimulation method based on motion intention recognition. The method comprises the following steps: firstly, synchronously acquiring a surface electromyogram signal and an inertial motion unit IMU signal of a lower limb of a human body through wearable equipment; performing data synchronization on the collected heterogeneous signals with two different sampling rates; inputting the synchronized multi-modal characteristic data into a PSO-LSTMAT (Particle Swarm Optimization-Long Short Term Memory) network model based on particle swarm optimization, and carrying out real-time STS period six-stage posture recognition; and according to the identified specific motion stage, applying adaptive functional electrical stimulation to the target muscle group to form a closed-loop rehabilitation process. According to the method, the PSO-LSTMAT hybrid neural network is introduced, so that cross-modal time sequence alignment can be effectively realized when a multi-sensor combined signal is processed, the recognition precision of each stage in STS motion is remarkably improved, and the recognition error of a traditional single sensor method in an action transition stage is avoided.

Provided herein are systems for treating a paralysis patient in need of controlled motion to improve quality of life, and related methods. The systems comprise an implantable system formed from a hub, various electrodes, such as spinal cord (upstream) electrode, periphery nerve (downstream) electrode and an external system formed of communication pod implanted just under the skin, a computing core, and a plurality of motion sensors. A software system, providing AI compatibility are used to supply the computing core, and thereby implanted electrodes, with signal. In this manner, the specially positioned electrodes, upstream of the spinal cord injury and downstream of the spinal cord injury, can provide safe and reliable patient motion.

The invention discloses a functional electrical stimulation personalized hand rehabilitation system and method based on reinforcement learning, and belongs to the technical field of medical rehabilitation training. The system comprises an upper computer, an angle acquisition module, a modular electrical stimulator, an electrode array, a power supply module and a safety control module. The upper computer runs a reinforcement learning control program, communicates with the electrical stimulator through a serial port, receives hand multi-degree-of-freedom angle information in real time and calculates electrical stimulation parameters. The modularized electrical stimulator adopts an STM32F103C8T6 single-chip microcomputer as a control core, and three channel expansion modules are cascaded through an SPI bus to form 24-channel independent high-voltage output. The electrode array is of a flexible wearable structure and is attached to the forearm of a patient to conduct electrical stimulation on multiple muscle groups. And the reinforcement learning control module realizes dynamic optimization of electrical stimulation parameters through a pre-training model and a policy network based on truncation near-end policy optimization (PPO), and realizes balance of stimulation precision and convergence speed in individualized rehabilitation training in combination with a multi-component reward function. The system is provided with an emergency stop switch and a pulse width protection mechanism, so that the safety and stability of the rehabilitation training process are ensured. According to individual differences and rehabilitation processes of patients, personalized and self-adaptive multi-muscle-group collaborative rehabilitation training can be realized, and the rehabilitation efficiency and the control precision are remarkably improved.

This invention discloses a closed-loop control method for functional electrical stimulation (fEP) that combines muscle activation and deep learning. It integrates muscle activation analysis with an LSTM model from deep learning to design and develop a closed-loop control method for fEP based on muscle activation and LSTM. This method can automatically learn appropriate fEP parameters based on real-time analysis of electromyographic signals to determine muscle state. This allows the method to automatically adjust the fEP parameters according to changes in muscle activation when the patient clenches their fist on the healthy side, making the grip strength on the affected and healthy sides more consistent. Furthermore, the LSTM model continuously learns and optimizes the output fEP parameters as the input dataset increases. This solves the problems in clinical fEP treatment where parameters cannot be adjusted in real-time according to the user's muscle state, parameter adjustment relies entirely on experience, patient participation is low, and active rehabilitation is not possible.

The invention relates to medical rehabilitation training and assisting equipment, in particular to a shoulder joint exoskeleton device based on a humanoid movement mechanism. Comprising a back plate, a shoulder joint mechanism and a functional electrical stimulation system, the shoulder joint mechanism is arranged on one side or two sides of the back plate, the shoulder joint mechanism comprises a fixed shoulder joint, a driving wheel, a scissor-fork type shoulder blade following mechanism and a shoulder supporting piece, the fixed shoulder joint is arranged on the back plate, the driving wheel is installed on the fixed shoulder joint through a symmetric center rotating shaft, and the scissor-fork type shoulder blade following mechanism is connected with the shoulder supporting piece. One end of the shear-fork type shoulder blade following mechanism is connected with the symmetric center rotating shaft, the other end of the shear-fork type shoulder blade following mechanism is connected with the shoulder supporting piece, and the shear-fork type shoulder blade following mechanism is used for passively following forward stretching and backward retracting movement of the shoulder blade of the human body; the abduction and adduction movement of the shoulder joint is realized by rotating the driving wheel; the functional electrical stimulation system is used for assisting in activating the target muscle. The device is simple in structure and portable to wear, active movement and electrical stimulation collaborative rehabilitation can be achieved, and the rehabilitation efficiency is effectively improved.

Functional electrical stimulation devices and methods of operating the same are described. For example, a device includes a high-efficiency power boost circuit configured to step a low battery voltage to a boosted output voltage, an open-loop charge pump circuit coupled to the power boost circuit to further increase the boosted voltage, and a switched capacitor output stage to generate high-slew-rate, charge-balanced stimulation pulses. The switched capacitor stage may produce symmetric or asymmetric bi-phasic pulses with adjustable amplitudes, widths, and frequencies over an operating range. The boost and charge pump stages may operate in discontinuous conduction and discontinuous voltage modes to achieve soft switching and improved efficiency at high conversion ratios. The devices may be incorporated into wearable electrical stimulators using textile electrodes. Methods are also provided for operating the power boost circuit, the charge pump circuit, and the switched capacitor stage to deliver controlled stimulation to electrically excitable tissue.

The utility model discloses a lower limb functional electrical stimulator which comprises a stimulation host, an electrode wire is installed on the stimulation host in an inserted mode, a wearing belt is arranged at the end, away from the stimulation host, of the electrode wire, a common peroneal nerve locator is installed on the wearing belt, and a muscle electrode is installed on the wearing belt. The common peroneal nerve locator and the muscle electrode are electrically connected with the stimulation host through electrode wires, a plurality of keys are installed on the front face of the stimulation host and are arranged at equal intervals in the length / width direction of the stimulation host, a Type-C charging interface is formed in one side of the stimulation host, an OLED screen is installed on the front face of the stimulation host and located beside the keys, and the Type-C charging interface is connected with the Type-C charging interface. A central controller is installed in the stimulation host and used for receiving information and executing instructions, and a lithium battery is installed in the stimulation host and electrically connected with the central controller through an electric wire. The novel earphone is simple in function, small and exquisite in design, convenient to wear and clear in wearing position.

This invention discloses a method, device, terminal, and medium for filtering electrical stimulation interference based on fabric electrodes. The method includes the following steps: acquiring a first electromyography (EMG) signal; identifying a second EMG signal after selective blanking processing based on the first EMG signal; performing CEEMDAN decomposition on the second EMG signal to obtain multiple intrinsic pattern functions (IPFs), and identifying a reconstructed IPF associated with the second EMG signal among the multiple IPFs; and reconstructing the signal based on the reconstructed IPFs to obtain a filtered signal after artifact filtering. Therefore, this invention can effectively eliminate motion artifacts, interference noise, and functional electrical stimulation artifacts in EMG signals acquired based on fabric electrodes by combining selective blanking processing and signal reconstruction methods.