2692 results about "Electrical stimulations" patented technology

The invention relates to a closed-loop multi-guide multi-mode time domain interference electrical stimulation system and method. The method comprises the steps that a software part determines stimulation parameters; the automatic electrode position adjusting device adjusts the spatial position of the multi-conductive-electrode device, and the multi-conductive-electrode device stimulates the position of a target spot; the current output precision and impedance monitoring module monitors the precision and impedance information of electrode output current, and the core main control and functional circuit module adjusts a control signal according to the precision and impedance information; when the multi-conducting-electrode device conducts stimulation, the electroencephalogram device synchronously collects electroencephalogram signals and uploads the electroencephalogram signals to the electroencephalogram analysis algorithm module of the software part, the electroencephalogram analysis algorithm module evaluates and feeds back the effectiveness and the effect of stimulation, and the time domain interference electrical stimulation function module and the target area dynamic adjustment algorithm module optimize stimulation parameters according to the effectiveness and the effect of stimulation. Through the arrangement, a real-time closed-loop feedback control system is formed, continuous monitoring, real-time optimization and adjustment of electrical stimulation parameters and dynamic adjustment of a stimulated brain target region are realized, and the accuracy and safety of current output are ensured.

The invention relates to the technical field of medical data processing, in particular to an integrated rehabilitation training system based on motion capture and myoelectricity feedback, which comprises a motion data acquisition module, a motion evaluation and analysis module and a control module, and is specifically integrated on a training garment through inertial motion capture equipment and a surface myoelectricity sensor. The motion state and muscle activation condition of a patient are monitored in real time, actual motion data and actual electromyographic signal data of the patient are collected, and whether the motion state of the patient meets the standard or not is judged by comparing the data deviation condition between the actual motion of the patient and the standard motion. And according to the deviation analysis result, the electrical stimulation parameters can be dynamically adjusted through closed-loop control, so that personalized and precise spinal cord electrical stimulation rehabilitation training is realized.

An in vitro training method for training genioglossus muscle strength includes adhering an electrode patch of an in vitro training device to a bottom of a chin of a user during a non-sleep period. The electrode patch receives an electrical stimulation signal from an electrical stimulation module of the in vitro training device to stimulate the genioglossus muscle of the user through transdermal electrical stimulation. The electrode patch includes a body surface adhering face and an assembling face opposite to the body surface adhering face. The body surface adhering face is adhered to the bottom of the chin of the user to align with the genioglossus muscle. The electrical stimulation module is disposed on the assembling face and in electrical connection with the electrode patch. The electrical stimulation module sends an electrical stimulation signal to stimulate the genioglossus muscle through transdermal electrical stimulation.

Systems and methods are provided herein for monitoring electrical activity in ex vivo, resting donor organs. Systems and methods provided herein also include providing electrical stimulation to the donor tissue to maintain or increase viability during storage or transport. Donor organs can include ex vivo, resting hearts. Electrical activity can be used to determine donor organ viability, especially in instances where visual evaluation of a beating heart is not possible. The same electrodes or other sensing devices used to measure electrical activity can be used to apply a voltage / current to the tissue as well in order to maintain viability of the organ. In some embodiments, stimulation or depression may be provided in response to the measured electrical activity.

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 belongs to the field of cerebral apoplexy rehabilitation training, and provides a cerebral apoplexy upper limb dynamic rehabilitation method and system based on vagus nerve electrical stimulation, the excitement degree of a cortical spinal cord pathway of a patient is measured and evaluated by using motor evoked potential to obtain a motor function evaluation result, and an initial rehabilitation training task is set according to the motor function evaluation result; the training motion intention of the patient is determined by monitoring the electroencephalogram signal and the electromyographic signal of the patient, and percutaneous ear vagus nerve electrical stimulation is triggered; after percutaneous ear vagus nerve electrical stimulation, performing rehabilitation training analysis on basic clinical characteristics and multi-modal signals of the patient to determine intermuscular coordination, brain region connectivity and brain muscle coupling of the patient; the training condition of the patient is evaluated according to the rehabilitation training analysis result, and parameters of percutaneous ear vagus nerve electrical stimulation and training tasks are adjusted based on the evaluation result for iterative rehabilitation training; and stopping iteration until the rehabilitation training analysis result of the patient reaches a preset standard, and completing rehabilitation training.

The invention discloses a vagus nerve stimulation parameter closed-loop adjustment method and system based on electroencephalogram characteristics. The method comprises the steps that real-time electroencephalogram signals of a patient are obtained, and time domain information and frequency domain information of the electroencephalogram signals of all frequency bands in the real-time electroencephalogram signals are extracted; on the basis of the time domain information and the frequency domain information of the electroencephalogram signals of all the frequency bands, electroencephalogram signal index features are calculated, and the electroencephalogram signal index features comprise an electroencephalogram signal power spectrum, a brain dynamic symmetry feature, a brain function connection feature and a rhythm feature; determining the state type of the patient according to the electroencephalogram signal index characteristics; determining parameter configuration information of vagus nerve stimulation according to the state type of the patient; and adjusting parameters of the vagus nerve electrical stimulation equipment according to the parameter configuration information of vagus nerve stimulation. According to the invention, timely and accurate electrical stimulation can be applied to a patient, the treatment accuracy is improved, the stimulation efficiency and the treatment effect are enhanced, side effects are reduced, and more accurate and individualized treatment management is realized.

Systems, devices, and methods for electrically stimulating peripheral nerve(s) to treat various disorders are disclosed, as well as signal processing systems and methods for enhancing diagnostic and therapeutic protocols relating to the same. Personalized therapy based on algorithms and aggregated data are also provided.

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 discloses a nerve regulation system for cognitive impairment, and the system comprises a cognitive behavior evaluation module which is used for recognizing a cognitive defect field which needs to be improved by a target object; the image data acquisition module is used for acquiring and preprocessing task state nuclear magnetic data and T1 weighted structure images of a target object; the brain region activation analysis module is used for determining a neural regulation potential target spot according to the preprocessed task state nuclear magnetic data; the brain network analysis module is used for identifying key nodes related to cognitive defects; the stimulation target screening module is used for determining an individualized stimulation target of the target object according to the nerve regulation potential target and the key node of the target object; the time domain interference electrical stimulation simulation and implementation module is used for performing electrical stimulation on the individualized stimulation target spot; and the dynamic feedback adjustment module is used for dynamically adjusting the stimulation parameters and enhancing the personalized regulation and control effect. By adopting the method and the device, the specific brain region directly related to the cognitive impairment can be determined, so that the targeting and the accuracy of treatment are enhanced.

The invention discloses a transcranial electrical stimulation intracranial vector electric field detection device and method, and belongs to the transcranial electrical stimulation intracranial electric field detection technology, the device inputs an individual head model in a stimulation system, sets a target spot and calculates transcranial electrical stimulation parameters; the implantation position and angle of the vector detection electrode are planned through the navigation system, electrical stimulation is applied to a brain target area through the stimulation electrode, and intracranial electric signals are collected in real time through the vector detection electrode; performing high-precision amplification on the acquired weak signal, and converting the weak signal into a digital signal; the collected electric field signals are calculated and processed in real time, and electric field distribution generated by transcranial electrical stimulation in the brain is analyzed and visualized; according to the method, time domain and frequency domain analysis is carried out on electric signals before and after stimulation, the influence of stimulation on neural signals in a detection area is evaluated, and high-precision measurement of the intensity and direction of a three-dimensional electric field is achieved through the design of a high-precision and multi-layer vector detection electrode.

The invention relates to the technical field of neuromuscular electrical stimulation, and provides a multi-modal feedback self-adaptive adjustment neuromuscular regulation and control treatment system, which comprises wearable working equipment for outputting pulse electric signals to adjust nerves and muscles to form movement or adjustment feeling, electromyographic signals, motion data and user feeling input are collected to conduct feedback adjustment on output parameters of the output pulse electric signals; the handheld control equipment is used for being connected with the wearable working equipment and controlling the output working mode and the working state of the wearable working equipment; and the server-side equipment is used for managing user information and preference of the handheld control equipment, setting function authority of the handheld control equipment, acquiring data acquired by the wearable working equipment, and realizing self-adaptive output of output parameters of the pulse electric signals of the wearable working equipment based on a self-adaptive reinforcement learning algorithm. Adaptive optimization of millisecond-level dynamic electrical stimulation parameters is realized through a multi-modal feedback data fusion technology in combination with a layered reinforcement learning architecture.

Embodiments described herein relate to systems, devices, and methods for monitoring brain activity and delivering electrical brain stimulation to a patient. In some embodiments, a system can deliver responsive electrical stimulation in a closed-loop manner and can offer real-time or near real-time monitoring of induced neurophysiological effects. After detecting a targeted brain pattern (i.e., an epileptic seizure), the system may deliver high-intensity ultra-short electrical stimulation impulses non-invasively or minimal-invasively to diminish or stop the neural oscillations underlying the epileptic seizure. The stimuli are delivered in time and space, relative to the emerging seizure rhythm patterns, such that they diminish or terminate the seizure. The system may include an implantable device including one or more electrodes electrically coupled to one or more processors. The processor(s) may be operatively coupled to a memory, one or more communication modules, and may optionally be coupled to a battery and one or more additional sensor(s).

The invention relates to a neuromuscular electrical stimulation multi-objective self-tuning optimization method, which comprises the following steps: dynamically establishing a framework for muscle response in a time window sliding modeling mode, and describing short-term excitability change and fatigue accumulation by the framework according to historical stimulation frequency density and total energy integral accumulation variable; introducing a short-time response curve recognition mechanism: after stimulation, according to micro changes of an electromyogram and a force output curve, judging whether a nerve and muscle coupling state is in a deviation trend or not; when the output trend is evolved towards the target improvement direction, current strategy fine tuning is kept; if the trend is stagnated or reversed, the weight combination or the step length is actively adjusted; constructing a multi-target co-integration matrix for analyzing whether the current response changes of different targets are in a consistent direction; when it is detected that two certain targets have an inverse correlation change, the system carries out conflict decomposition processing once; interference compromising is carried out on conflict indexes, and short-term power down-regulation is carried out; and forming a dynamic strategy framework.

A device and algorithm for controlling an autonomic function in an individual. A controller device that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure. A control interface and algorithm for controlling an autonomic function in a subject. For instance, an algorithm that utilizes physiological measurements (such as blood pressure) to regulate spinal cord electrical stimulation to stabilize blood pressure.

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.

The invention discloses a rehabilitation training method and system based on transcranial time domain interference electrical stimulation. Comprising a physiological signal acquisition module used for acquiring a multi-modal physiological signal of a user; the software processing module is used for determining a target stimulation target of a user based on the multi-modal physiological signal and generating an electrical stimulation parameter scheme of the target stimulation target; and the electrical stimulation module is used for performing transcranial time domain interference electrical stimulation on the user based on the electrical stimulation parameter scheme. According to the rehabilitation training method and system, the characteristics of the deep nuclei can be accurately regulated and controlled by using the transcranial time domain interference electrical stimulation technology, and the deep focus is accurately stimulated. Meanwhile, a more effective individualized stimulation scheme is provided for the user through the guidance of the multi-modal physiological signals. The system can be applied to dyskinesia rehabilitation in hospitals, communities and homes, and a non-invasive, convenient and efficient solution is provided.

The invention provides a muscle stimulation adjusting method and system based on gait detection. The method comprises the following steps: acquiring lower limb biomechanical data; performing phase recognition according to a dynamic programming algorithm, and constructing a pressure center track to perform feature extraction to obtain gait features; carrying out feature analysis on the gait features through a reverse dynamics model and a machine learning model, and carrying out output judgment according to a double-model collaborative decision-making mechanism to obtain a stimulation parameter decision-making result; generating an electrical stimulation waveform according to the decision result, and applying differential electrical stimulation to the target muscle in the gait cycle to obtain a stimulation scheme; and monitoring stimulated myoelectricity feedback signals and gait changes, and carrying out parameter updating by calculating a signal change rate and analyzing a motion track error to obtain an updating scheme. According to the method, through a double decision-making mechanism of the reverse dynamics model and the machine learning model and a real-time feedback regulation mechanism, the gait phase recognition precision is improved, and precise regulation and control of stimulation parameters are realized.

A system and method for providing therapy to a patient can include a monitoring unit and a therapy unit. The monitoring unit can have a user interface and one or more sensors to measure patient data. The therapy unit can have a stimulator for generating electrical stimulation and a microcontroller for controlling the generation of the electrical stimulation based on the measured patient data.

The invention relates to the technical field of exercise rehabilitation, and discloses a percutaneous spinal nerve electrical stimulation system and method, and the system comprises a power module which is used for converting an external alternating current into a stabilized power supply; the MCU module controls the pulse signal generation module; the pulse signal generation module is used for generating an electrical stimulation waveform; the DAC module receives the digital signal; the modulation module is used for receiving analog signals; the amplification module is used for receiving modulation waveforms; the multi-channel gating module is used for distributing stimulation current to a plurality of channels; the current detection module monitors the magnitude of current output by each channel in real time; and the ADC module performs digital conversion on the current analog signal output by the electrical stimulator. According to the invention, multi-channel and real-time modulation electrical stimulation signals can be output through modulation of two paths of stimulation signals, spinal cord sensory nerves are activated through the non-invasive epidermal electrode, amputation hand feeling is induced, the defect that electromyographic signals are interfered by the tail end of a stump in the prior art is improved, and the accuracy of an electromyographic signal decoding algorithm is also improved.

The invention discloses a method and system capable of improving time domain interference electrical stimulation focusing, and the method comprises the steps: TI electric field simulation software obtains an initial electrical stimulation parameter according to a target region selected on a human brain structure model, and carries out the evaluation of a stimulation effect under the electrical stimulation parameter through introducing a focusing evaluation index, if the focusing evaluation index does not reach the preset value, the electrical stimulation parameter is optimized until the focusing evaluation index reaches the preset value, and then the multi-channel TI system upper computer software issues an instruction of the optimized electrical stimulation parameter to the stimulation electrode control circuit; and the stimulating electrode control circuit carries out excitation output on the stimulating electrodes according to the received optimized electrode derivative, electrode current, frequency and position so as to improve the target stimulation focusing property.

Embodiments of the present invention provide systems and methods for the treatment of pain through activation of select neural fibers. The neural fibers may comprise one or more afferent neural fibers and / or one or more efferent neural fibers. If afferent fibers are stimulated, alone or in combination with efferent fibers, a therapeutically effective amount of electrical stimulation is applied to activate afferent pathways in a manner approximating natural afferent activity. The afferent fibers may be associated with primary receptors of muscle spindles, golgi tendon organs, secondary receptors of muscle spindles, joint receptors, touch receptors, and other types of mechanoreceptors and / or proprioceptors. If efferent fibers are stimulated, alone or in combination with afferent fibers, a therapeutically effective amount of electrical stimulation is applied to activate intrafusal and / or extrafusal muscle fibers, which results in an indirect activation of afferent fibers associated therewith.

The invention belongs to the technical field of medical electronic equipment, and discloses a control system for alternative electrical stimulation of idiopathic tremor, and the system comprises a signal collection module which is used for obtaining tremor motion data of a patient in real time; the signal processing module is used for analyzing tremor frequency, amplitude and phase characteristics; the dynamic parameter generation module is used for generating an alternate stimulation mode according to the tremor characteristics; and the electrode array module comprises at least two stimulating electrodes and a reference electrode. The invention provides a non-invasive and dynamically optimized alternate electrical stimulation control system which is used for inhibiting hand tremor of an idiopathic tremor patient, regulation and control of a tremor network can be enhanced by alternately stimulating different peripheral nerves, the curative effect can be improved through closed-loop feedback optimization parameters, long-acting and safe tremor inhibition is achieved, and the treatment effect is improved. The problems of insufficient curative effect, nerve adaptability, surgical risk and the like in the prior art are solved.

A system and method for providing therapy to a patient can include a monitoring unit and a therapy unit. The monitoring unit can have a user interface and one or more sensors to measure patient data. The therapy unit can have a stimulator for generating electrical stimulation and a microcontroller for controlling the generation of the electrical stimulation based on the measured patient data.

The invention discloses an intelligent brain-controlled muscle electrical stimulation rehabilitation therapeutic apparatus, and relates to the technical field of electrical stimulation rehabilitation therapeutic apparatuses, the intelligent brain-controlled muscle electrical stimulation rehabilitation therapeutic apparatus comprises an electroencephalogram signal acquisition module, an electromyographic signal acquisition module and a mixed signal processing module, the mixed signal processing module is connected with the electroencephalogram signal acquisition module and the electromyographic signal acquisition module; the method is used for preprocessing electroencephalogram and electromyogram signals, fusing multi-modal features and classifying motion intentions. By installing the mixed signal processing module, preprocessing, multi-modal feature fusion and motion intention classification of electroencephalogram and electromyogram signals are achieved, a preprocessing unit can effectively remove ocular artifacts and power frequency noise, meanwhile, independent component analysis and a dynamic baseline calibration strategy are adopted, the signal quality is further improved, and the accuracy of motion intention classification is improved. According to the multi-mode signal processing mode, the limitation of single signal processing in the prior art is overcome, and the accuracy and effectiveness of rehabilitation treatment are improved.

The invention relates to the technical field of medical instruments, in particular to a high-precision time interference non-invasive brain deep electrical stimulation method, equipment and system, and solves the problems that two stimulation electrodes are used for each pair of current in traditional time interference-based non-invasive brain deep electrical stimulation, so that the current distribution is relatively dispersed, and the stimulation focusing performance is relatively poor. According to the method, high-precision 4 * 1 electrode configuration is used, two electrodes for applying a stimulation current are changed into a 4 * 1 electrode form, the flowing path of the current is effectively limited, the current is more focused, and the focusing performance of the interference current is further improved. According to the device, high-precision current control is realized through the anti-phase output circuit, the 4 * 1 voltage division circuit, the constant current source module and the impedance detection module; the system supports forward and reverse electrode position optimization, a personalized real finite element head model simulation system based on MRI data is used for guiding practical application, the focusing performance of each pair of current in a target brain region is improved, and therefore the overall stimulation precision in the target brain region is improved.

The invention discloses a closed-loop optimization method for cerebral apoplexy electrical stimulation treatment, and belongs to the technical field of PID control optimization, and the method specifically comprises the steps: 1, constructing a cerebral apoplexy electrical stimulation control model; step 2, improving a sled dog optimization algorithm, wherein an improved strategy is as follows: D1, generating an initial population by using a chaotic mapping optimization strategy fused with a Halton sequence; d2, using a dynamic mixed collaborative search strategy to improve a mathematical model in an obstacle avoidance stage; d3, using an elite Levy dynamic navigation strategy to improve the mathematical model of the lost direction stage; 3, setting parameters of a PID controller module in the cerebral apoplexy electrical stimulation control model by using an improved sled dog optimization algorithm, and obtaining optimal Kp, Ki and Kd parameters through optimization; and step 4, inputting the obtained optimal Kp, Ki and Kd parameters into a cerebral apoplexy electrical stimulation control model, and optimizing a control effect.

A system that can deliver haptic feedback by applying an electrical stimulation to a first area of a user's body to induce a second area of the user's body to experience a level of natural sensation in response to an action occurring in a simulated remote environment and an intensity of the action is described. The system includes a controller to set parameters for the electrical stimulation based on the action occurring in the simulated remote environment and an intensity of the action. The system also includes a signal generator to generate the electrical stimulation comprising the parameters. The system also includes a skin surface electrode placed at a first location on a user's body remote from a second location on the user's body to deliver the electrical stimulation with the parameters to a nerve at or near the first area of the user's body.

The invention discloses a closed-loop noninvasive spinal cord electrical stimulation regulation and control method and system based on motion data, and the system is provided with a flexible electrode array patch which is attached to the skin surface of a to-be-tested human body; the sensing module is used for collecting electromyographic signals or acceleration signals of a user; the signals are processed, and characteristic values related to actions and motions are extracted; the closed-loop feedback module compares the characteristic value with a model set characteristic / threshold value, and judges whether to start stimulation site and stimulation parameter adjustment or not; automatically selecting an optimal electrode unit and a corresponding stimulation parameter based on a judgment result; the dynamic regulation and control module controls the optimal electrode unit to output stimulation current, and regulates the activity of corresponding spinal cord neurons; and continuously performing closed-loop adjustment on the electrode unit and the stimulation parameters according to the motion feedback data. According to the method and system, precise stimulation and closed-loop regulation and control based on the motion response of the patient are achieved, and the problems that stimulation target positioning depends on artificial experience, parameter adjustment is not timely, and individualized and closed-loop feedback capacity is lacked are solved.

The disclosure describes devices and methods for providing transdermal electrical stimulation therapy to a subject including positioning a stimulator electrode over a glabrous skin surface overlying a palm of the subject and delivering electrical stimulation via a pulse generator transdermally through the glabrous skin surface and to a target nerve or tissue within the hand to stimulate the target nerve or tissue within the hand so that pain felt by the subject is mitigated. The pulses generated during the electrical stimulation therapy may include pulses of two different magnitudes.