110 results about "Functional electrical stimulation" patented technology

The invention discloses a brain-computer hybrid intelligent closed-loop swallowing rehabilitation system for treating dysphagia after stroke, and relates to the field of artificial intelligence medical instruments. The system is composed of a plurality of key modules: an intelligent swallowing brain-computer interface module for accurately identifying a swallowing intention through multi-modal physiological signal acquisition and processing; the intelligent swallowing functional electrical stimulation module is used for finely regulating and controlling stimulation parameters according to the condition of the patient; the AI auxiliary online integrated module is used for realizing non-invasive brain-controlled swallowing and high-precision AI regulation and control; the closed-loop intelligent feedback regulation and control module is used for real-time monitoring, early warning and self-adaptive optimization of electrical stimulation; the cloud platform remote monitoring and data storage module supports remote diagnosis and treatment of doctors; and the man-machine interaction interface display and printing module optimizes doctor-patient interaction. According to the system, a brain-computer interface and FES are combined, a personalized, safe and efficient rehabilitation scheme is provided for a patient based on data driving and an artificial intelligence algorithm, swallowing function recovery can be accelerated, complications are reduced, and the system has great clinical and social values.

The invention relates to the technical field of brain-computer interfaces, and discloses a self-adaptive dynamic feedback brain-computer interface training method and system based on virtual reality. The training method comprises the steps that a user performs motor imagery according to a training scene presented by the VR display device; the electroencephalogram acquisition equipment acquires electroencephalogram signals; configuring a data processing module, and operating a motor imagery continuous control model to calculate characteristic parameters by taking the electroencephalogram signals as input; under the condition that the task exists, the characteristic parameters are used as input, and a dynamic self-adaptive characteristic-feedback mapping model is operated to calculate control parameters; sending the control parameters to a functional electrical stimulation device to load electrical stimulation of corresponding intensity to the muscle to obtain tactile feedback; meanwhile, the dynamic adaptive feature-feedback mapping model is dynamically updated according to latest input feature parameters; the control parameters are sent to the VR display device to present visual feedback, and the user adjusts the motor imagery based on the visual feedback and the haptic feedback. The participation sense of the user and the training efficiency can be improved.

The invention relates to a mechanical exoskeleton rehabilitation training system and method based on a brain-computer interface. The system comprises electroencephalogram acquisition equipment, a preprocessing unit, a feature extraction unit, a motion intention decoding unit, a mechanical exoskeleton control unit, a muscular tension state monitoring unit and a self-adaptive functional electrical stimulation feedback unit. The method comprises the following steps: preprocessing electroencephalogram and electromyographic signals; electroencephalogram and myoelectricity time-frequency features are obtained through feature extraction; an electroencephalogram decoding model is used for decoding to obtain the movement intention of the patient, and an exoskeleton control instruction is generated to control a mechanical exoskeleton control unit to drive the limb movement of the rehabilitation patient for rehabilitation training; meanwhile, the muscular tension state of the patient is analyzed according to the time-frequency characteristics of electroencephalogram and myoelectricity, functional electrical stimulation of different intensities is applied in a self-adaptive mode, stimulation feedback is enhanced, and the muscular tension state of the patient is adjusted. According to the invention, deep fusion of brain-controlled exoskeleton training and low-frequency nerve electrical stimulation adjustment can be realized, and the rehabilitation effect of a stroke patient is improved.

A device and method for functional electrical stimulation intended to be positioned on an upper limb of a user for stimulation of the user's upper limb, includes an electrode configured to be disposed on an upper limb of the user, the electrode having a number of electrode pads adapted to generate stimulating electrical signals on the upper limb of the user, and a stimulator having an embedded sensor configured to detect a movement of the stimulator, and a control component configured to process the sensor measurements and determine an intention of the user to perform an action with his / her upper limb on which the electrode is disposed, and to control the activation and / or deactivation of the electrode pads based on the sensor measurements.

An upper-body sensorized exoskeleton is configured to interface with external systems, such as FES, advanced cognitive systems, and VR / AR interaction programs, in order to facilitate rehabilitation and assistance of patients affected by upper-limb impairments. The sensorized upper limb exoskeleton delivers anti-gravitational support at the shoulder level, enables upper-limb configuration limits for shoulder and elbow ranges of motion, and reads kinematic data that may be analyzed by users and clinicians. The sensorized upper limb exoskeleton is equipped with electronic processing and communication means that support bidirectional communication between exoskeleton and external systems.

The invention discloses a self-adaptive closed-loop functional electrical stimulation system based on muscle coordination, and the system can adaptively adjust an electrical stimulation signal at a next moment based on the response of human muscles to an electrical stimulation signal at a moment, thereby achieving the self-adaptive adjustment of the electrical stimulation signal at the next moment. The monitoring and control of the electrical stimulation signal are realized; due to the fact that closed-loop control is executed according to the electromyographic signals and the motion signals, and the electromyographic signals and the motion signals actually comprise personalized feature information of the object human body, the self-adaptive closed-loop functional electrical stimulation system based on muscle collaboration can establish evaluation and feedback of the electrical stimulation intervention effect. Therefore, the effectiveness and the safety of electrical stimulation are supervised by utilizing the self-adaptive regulation and control values of the electromyographic signals and the motion signals, and self-adaptive regulation electrical stimulation signal parameters conforming to the individual muscle motion characteristics of the object can be stably output. The device is widely applied to the technical field of rehabilitation training.

A device (1) and method for functional electrical stimulation intended to be positioned on an upper limb of a user for stimulation of the user's upper limb, comprising an electrode (2) configured to be disposed on an upper limb of the user, the electrode (2) having a plurality of electrode pads (3) adapted to generate stimulating electrical signals on the upper limb of the user, and a stimulator (4) comprising an embedded sensor (5) configured to detect a movement of the stimulator (4), and control means (6) configured to process the sensor measurements and determine an intention of the user to perform an action with his / her upper limb on which the electrode (2) is disposed, and to control the activation and / or deactivation of the electrode pads (3) based on the sensor measurements.

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.

The invention discloses a wavelet enhancement cooperative activation method for FES multi-target time sequence regulation and control, and relates to the technical field of biomedical engineering. According to the model, an overlapped sliding window is analyzed through a multi-channel surface electromyographic signal, a time-frequency energy significant feature matrix is constructed by combining an energy ratio, and meanwhile, an inter-muscle co-activation matrix is constructed in the multi-channel electromyographic signal sliding window; constructing a multi-channel high-dimension matrix by using each single-channel time-frequency energy significant feature matrix and the multi-channel inter-muscle co-activation matrix, and performing data dimension reduction on the multi-channel high-dimension matrix to obtain a multi-channel multi-dimension time-frequency energy-inter-muscle co-activation matrix; and a muscle activation time sequence vector is screened by using a self-adaptive threshold logic combination rule, and finally an activation time sequence is applied to an FES experiment. According to the method, the movement of the hand on the sagittal plane is accurately predicted by analyzing the multi-channel surface electromyogram signals and the multi-target muscle co-activation characteristics, functional electrical stimulation FES parameters are dynamically adjusted, and accurate control over the muscle activity stage is achieved.

The invention belongs to the cross technical field of rehabilitation engineering and neural engineering, and relates to an exercise rehabilitation system and method based on layered stimulation navigation and a closed-loop brain-computer interface, and the exercise rehabilitation system comprises a layered stimulation navigation module, a brain-computer interaction module, a multi-channel functional electrical stimulation module and an exercise feedback module. The layered stimulation navigation module outputs different stimulation schemes for the superficial layer muscle stimulation area and the deep layer muscle stimulation area; the brain-computer interaction module is used for outputting a decoding result capable of representing the motion intention of the convalescent; the multi-channel functional electrical stimulation module calls a stimulation scheme according to a decoding result, loads an injection current to a working electrode determined by the stimulation scheme, implements electrical stimulation and generates a motion response; the motion feedback module collects and fuses the multi-mode feedback signals under the motion response, generates a stimulation parameter adjustment signal used for adjusting a stimulation scheme executed in the previous rehabilitation period, and outputs a neural feedback signal used for guiding the rehabilitation person to adjust the motion imagination.

The invention discloses an ankle joint mixed exoskeleton system fused with functional electrical stimulation. The ankle joint mixed exoskeleton system comprises a leg support used for being fixed to a shank, a foot fixing plate hinged to the bottom of the leg support, a driving mechanism arranged on the leg support and used for driving the foot fixing plate to swing and a system module matched with the driving mechanism. The invention further provides an assisting torque distribution method. The system provided by the invention can effectively assist the patient in keeping the correct position of the foot in the walking process, so that the foot drop is effectively prevented, and the walking safety and efficiency are improved.

The invention discloses a closed-loop feedback functional electrical stimulation control method and device, a medium and equipment, and relates to the technical field of computers. According to the invention, the current target motion angle of the healthy side limb of the patient and the actual motion angle of the affected side limb of the patient under the current functional electrical stimulation control signal are obtained, and the error between the target motion angle and the actual motion angle and the change rate of the error are determined; then, an adaptive weight fuzzy iterative learning control closed-loop feedback control algorithm is adopted to accurately adjust control parameters through learning of historical control experience, so that the affected-side limb of the patient can quickly approach a target movement track of the unaffected-side limb of the patient, and the iterative learning frequency of the iterative learning control algorithm is reduced; the limb movement reconstruction real-time performance is improved, the target trajectory tracking precision is improved, and the accomplishment degree of the limb movement on the affected side of the patient is improved.

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 provides a gait camouflage method for resisting biological recognition. The gait camouflage method comprises the following steps: wearing a gait camouflage device on a key part of a user; the method comprises the following steps: acquiring acceleration characteristics, angular velocity characteristics and magnetic field signal data of a user through a gait camouflage device, fusing the acceleration characteristics, the angular velocity characteristics and the magnetic field signal data to form a super vector, and performing time sequence coding to obtain a sample super vector of a current time slice; calculating the Hamming distance between the sample supervector and the reference supervector in the subspace, and taking the Hamming distance as a classification basis; optimizing an electrical stimulation intervention strategy based on the gait recognition model; through functional electrical stimulation regulation and control of specific lower limb muscles, joint motion angles are influenced, space-time and kinematics parameters of gaits are changed, and thus gait characteristics with a camouflage effect are realized. Electrical stimulation is applied to lower limb muscles according to different gait stages, so that human gait features are effectively changed, and the gait camouflage target is achieved; by analyzing gait parameter differences under different camera visual angles, an intervention mode of maximizing gait changes is selected, and gait features can be effectively camouflaged.

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 utility model discloses a wireless intraoral genioglossus myoelectricity acquisition device and a functional electrical stimulation system thereof. According to the myoelectricity acquisition device, the electrode, the myoelectricity acquisition circuit and the wearable tooth socket are fixedly assembled and are subjected to waterproof packaging, and the technical scheme of wireless transmission and wireless charging is matched, so that the accuracy of signal acquisition and the wearing comfort of a user are effectively improved, and the myoelectricity acquisition device is suitable for being worn in a humid oral environment for a long time. According to the corresponding closed-loop functional electrical stimulation system, electromyographic signal monitoring and electrical stimulation are integrated, the activity state of genioglossus can be monitored in real time, and electrical stimulation is provided when necessary, so that the smoothness of the airway is maintained, and the breathing problem caused by airway collapse is effectively prevented. The system can also automatically adjust stimulation parameters according to real-time feedback of electromyographic signals, improves the accuracy and curative effect of treatment, and is particularly suitable for treating obstructive sleep apnea.

The invention discloses a myoelectricity-driven multi-channel functional electrical stimulation upper limb rehabilitation platform and a method thereof. The platform comprises a myoelectricity acquisition device, a myoelectricity acquisition data processing system, an upper computer and an electrical stimulation system, the input end of the myoelectricity acquisition data processing system is connected with the myoelectricity acquisition device; the output end of the microprocessor is connected with the input end of the upper computer in a wireless or wired manner; the output end of the upper computer is connected with the electromyographic system and the electrical stimulation system in a wireless or wired mode. The myoelectricity acquisition device acquires myoelectricity signals on the surface of the healthy side limb of a patient; the myoelectricity collection data processing system is used for filtering the collected myoelectricity signals on the uninjured side of the patient to obtain myoelectricity data; the upper computer carries out gesture recognition processing according to the myoelectricity data to obtain electrical stimulation parameter configuration and sends the electrical stimulation parameter configuration to the electrical stimulation system; the electrical stimulation system outputs a matched waveform stimulation signal to the limb surface of the diseased side of the patient according to electrical stimulation parameter configuration; the affected side limbs are controlled through subjective movement of the healthy side limbs of the patient to achieve bilateral fine movement, and the rehabilitation process is accelerated.

The invention provides a functional electrical stimulation method and system based on fuzzy control, and the method comprises the steps: applying an electrical stimulation signal with an initial electrical stimulation parameter to the muscle of a to-be-stimulated point of a patient, and obtaining an electromyographic signal in the process of applying the electrical stimulation to the muscle of the to-be-stimulated point; performing data processing on the acquired electromyographic signals to extract time-frequency domain features corresponding to the electromyographic signals, and analyzing to obtain root-mean-square values of the electromyographic signals and median frequencies of electromyographic signal power spectrums to represent the strength and fatigue degree of the electromyographic signals; and obtaining real-time electrical stimulation time according to the intensity of the electromyographic signals and the fatigue degree and based on a preset fuzzy control strategy, and performing electrical stimulation rehabilitation on the muscles of the patient according to the electrical stimulation time. The purpose of automatically controlling the electrical stimulation time can be achieved, the control efficiency is improved, the intelligent rehabilitation training of a patient can be assisted, and then the good rehabilitation effect is achieved.

A tremor suppression device includes a garment wearable on an anatomical region and including electrodes contacting the anatomical region when the garment is worn on the anatomical region, and an electronic controller configured to: detect electromyography (EMG) signals as a function of anatomical location and time using the electrodes; identify tremors as a function of anatomical location and time based on the EMG signals; and apply neuromuscular electrical stimulation (NMES) at one or more anatomical locations as a function of time using the electrodes to suppress the identified tremors.

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.

A wireless intraoral genioglossus electromyography collection apparatus, and a closed-loop functional electrical stimulation system comprising the apparatus. In the electromyography collection apparatus, electrodes (5, 50), electromyography collection circuits (2, 3, 4) and a wearable dental appliance (1) are fixedly assembled and are subject to waterproof packaging, so that the accuracy of signal collection and the wearing comfort of a user are effectively improved, and the apparatus is suitable for being worn for a long time in an intraoral humid environment. The closed-loop functional electrical stimulation system integrates electromyographic signal monitoring and electrical stimulation, can monitor the activity state of the genioglossus in real time, and provides electrical stimulation when necessary to maintain airway patency, and thus effectively prevents breathing problems caused by airway collapse. The system can also automatically adjust stimulation parameters according to real-time feedback of electromyographic signals, such that the treatment accuracy and the treatment effect are improved, and the system is particularly suitable for treating obstructive sleep apnea.

The invention discloses a personalized functional electrical stimulation rehabilitation system capable of being customized, and belongs to the technical field of medical electronics, the personalized functional electrical stimulation rehabilitation system comprises a functional electrical stimulation rehabilitation system, the functional electrical stimulation rehabilitation system is connected with an intelligent medical query system and a communication module, and the communication module is connected with a central control system and a BCI detection device. The central control system is connected with a data acquisition module and a rehabilitation equipment control module, and the central control system is electrically connected with the BCI detection equipment. By means of the mode, data information of patients and therapists is collected, the patient information list and the therapist information list are generated, the patient information list is analyzed, the personalized matching module screens and matches the therapists according to the patient information list, and the function of matching the therapists according to the conditions of the patients is achieved; and the function that a therapist specifies a treatment scheme in a targeted manner according to the condition of a patient is also realized.

The invention relates to a flexible conductive intravenous stent based on functional electrical stimulation. The invention belongs to the fields of biomedical engineering and the like. The PCL-Gr extravascular stent is prepared by utilizing an electrostatic spinning technology, and the PCL-Gr extravascular stent wraps the periphery of the transplanted vein to provide necessary mechanical support for the transplanted vein so as to maintain the structural stability of the transplanted vein, so that the risk of restenosis caused by hemodynamic change is reduced. And meanwhile, functional electrical stimulation is accurately applied to transplanted veins by utilizing conductivity, so that double mechanisms of promoting endothelialization and inhibiting smooth muscle cell proliferation are achieved, and the risk of intimal hyperplasia is effectively reduced.

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.

The present disclosure provides a plug-and-play functional electrical stimulation system and method. The system includes a main controller connected to at least two series-connected electrical stimulators via a bus; the main controller is configured to receive and execute motion task files, and coordinate the output logic timing of the multi-channel electrical stimulators via the bus; the motion task files are composed of control parameters set based on the patient's degree of muscle damage; the control parameters include: the number of different states of a customizable state machine corresponding to the functional training task, the trigger conditions required for state transitions, and the functional electrical stimulation output parameters for each state.

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 utility model provides a movable brain-computer interface and functional electrical stimulation stroke rehabilitation training device which comprises a frame body, an operation platform arranged above the frame body and a movable platform arranged below the frame body. An all-in-one computer is arranged above the operation platform, a telescopic platform is arranged below the operation platform, and a bearing platform is arranged on one side of the operation platform; the telescopic platform is horizontally mounted on the operation platform in a sliding manner, and an input device connected with the computer all-in-one machine is arranged on the telescopic platform; an equipment platform is arranged at the position, corresponding to the position between the movable platform and the operation platform, of one side of the frame body, and a protection piece is arranged on the other side of the frame body and corresponds to the equipment platform. The movable brain-computer interface and functional electrical stimulation stroke rehabilitation training device has the advantages of being simple in structure, light in weight and easy to use and move.