2022 results about "Electrical stimulations" patented technology

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.

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 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.

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 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.

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.

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.

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 invention relates to the technical field of medical rehabilitation, and particularly discloses a finger rehabilitation electrical stimulation parameter control method and system, and the method comprises the steps: obtaining a multi-channel surface electromyogram signal and finger joint kinematics data of a patient; according to the multi-channel surface electromyogram signals, target fine actions of the patient are recognized; according to the target fine motion and the finger joint kinematics data, a multi-muscle group cooperative activation mode and an expected motion trail are obtained through analysis; generating an electrical stimulation parameter combination for different muscle groups according to a multi-muscle group collaborative activation mode; outputting multi-channel electrical stimulation to the patient based on the electrical stimulation parameter combination, and continuously adjusting the electrical stimulation parameter combination on line according to the deviation between the kinematics data of the finger joints and the expected motion trail; the method solves the problems that an existing method is difficult to effectively simulate complex multi-muscle group coordination, complex in parameter adjustment and difficult to adapt to dynamic changes of a patient, and the effect of assisting the patient in complex and fine finger action training is achieved.

The invention discloses an electrical stimulation type nerve regeneration method based on calcium signal regulation and control, and relates to the technical field of electrical stimulation type nerve regeneration, and the method comprises the following steps: based on a Schwann cell population calcium signal response feature set, identifying whether the calcium ion concentration is in a microliter stage which breaks through a lowest activation threshold and does not reach a stable state; judging whether the target nervous tissue is in a calcium signal activation critical state or not based on the behavior mode change of the Schwann cell population; based on the judgment result of the calcium signal activation critical state, an electrical stimulation adjustment control instruction is generated in real time in combination with the calcium ion concentration fluctuation trend and Schwann cell population response characteristics, and the calcium ion concentration stability is optimized and the activation state is maintained by adjusting the electrical stimulation intensity, the electrical stimulation pulse width, the electrical stimulation waveform type and the electrical stimulation application time sequence. According to the method, the problem that a calcium signal is difficult to recognize and dynamically optimize in a microliter stage is solved, and precise maintenance of Schwann cell activation and improvement of nerve regeneration efficiency are realized.

The invention relates to the technical field of neural engineering and brain-computer interfaces, in particular to a closed-loop multi-modal nerve stimulation system and method based on time interference, and the system comprises a multi-modal stimulation module which is used for integrating electrical stimulation, magnetic stimulation and optical genetic stimulation, and generating a time interference field domain; the neural state sensing module is used for collecting real-time electroencephalogram signals, blood oxygen concentration and neural metabolite level data; the neural control center is used for fusing neural state data and stimulation parameters, and dynamically adjusting time interference frequency and stimulation intensity through an adaptive algorithm; the time sequence cooperation engine predicts a neural response time phase based on a deep learning model, and optimizes a stimulation time sequence and a mode switching strategy; and the visual interaction platform is used for rendering the nerve activation thermodynamic diagram and the stimulation parameter adjustment curve in real time. Therefore, the problems of adjustment strategy solidification, low adjustment precision, insufficient energy conversion efficiency and the like in the prior art are solved.

The invention relates to the field of medical instruments, and discloses an anesthesia injury monitoring evaluation and management system for pain monitoring and rehabilitation acceleration. Comprising a sensor module configured to collect acupuncture point skin temperature data in a percutaneous acupuncture point electrical stimulation process, current parameter data output by an electrical stimulation device and skin impedance change data in real time; the control module is used for inputting the temperature data, the current parameter data and the skin impedance data which are acquired in real time into a multi-parameter risk assessment model, calculating a real-time risk value and generating a parameter change curve containing a time sequence; when the real-time risk value exceeds a preset safety threshold value, or any single parameter in the parameter change curve reaches a temperature change rate threshold value, an accumulated electrical stimulation energy threshold value or a skin impedance abnormal fluctuation threshold value, triggering a multi-stage early warning signal; according to the early warning level of the early warning module, the output power, the pulse frequency or the action time of the electrical stimulation device is automatically adjusted, or electrical stimulation is forcibly terminated when early warning is performed at the highest level.

The invention relates to the technical field of acupuncture, in particular to an intelligent acupuncture point precise positioning and stimulation regulation and control system based on combination of traditional Chinese medicine and western medicine, and the system firstly collects body surface acupuncture point information of a user, analyzes sensitivity and generates visual data. The information processing module fuses the data, generates acupoint comprehensive characteristics and marks a target acupoint. And the virtual visualization module generates a virtual acupoint image and marks a target acupoint. The needling instrument massage module formulates a needling instrument pushing scheme according to acupuncture point characteristics and needling instrument parameters, and the needling instrument pushing scheme is executed by the body surface needling instrument pushing device. Meanwhile, the electrical stimulation regulation and control module generates parameters, the electrical stimulation intensity, frequency and time are controlled, and the electric acupuncture massage device is combined with body surface acupuncture massage operation to execute treatment. According to the system, accurate acupoint positioning, personalized needle pushing scheme making and electrical stimulation regulation and control are achieved, the effect and safety of needle pushing treatment are improved, and innovative technical support is provided for modernization of traditional Chinese medicine.

The invention provides an intracranial neuron electrical stimulation system for treating epilepsy and other brain diseases involving epileptic seizure, which can immediately apply intracranial neuron electrical stimulation to the interseizure epilepsy activity in a personalized manner after detecting the interseizure epilepsy pattern each time. And the stimulation is activated by intracranial electroencephalogram (EEG) detection. The intracranial stimulation for epileptic activities in the epileptic seizure period continuously acts along with time, the forming process of an epileptic network can be blocked, the neuronal super-synchronization risk is reduced, and therefore the control effect on epileptic seizure is improved. The invention also includes the use of nerve adjustment biomarkers, thereby dynamically optimizing the detectability and providing more accurate overall assessment for the patient's treatment progress. Finally, according to the scheme, by detecting the intracranial EEG mode and the high-risk state mode (such as the epileptic state and the sudden accidental death risk in epilepsy) in the attack period, an instant alarm is given to the patient / nursing personnel, and it is ensured that safe treatment measures are taken for the patient in time.

The invention discloses a closed-loop deep brain regulation and control system for epilepsy treatment, and the system comprises an electroencephalogram signal collection module which collects neural electrophysiological signals in real time by implanting a recording electrode in a cerebral cortex or hippocampal brain area; the electroencephalogram signal real-time analysis module is used for outputting the epileptic seizure period prediction probability xi through a seven-layer full-connection neural network based on the 33-dimensional feature vector so as to realize epileptic seizure early warning; when the zeta is greater than or equal to a threshold value, the electrical stimulation regulation and control module is used for triggering electrical stimulation, filtering out a frequency band required to be regulated and controlled according to filtering, calculating and predicting electrical stimulation intensity and then correcting and outputting pulse stimulation, so that personalized electrical stimulation regulation and control are carried out on a specific frequency band, and detection is continuously carried out until the frequency band becomes normal; and the medicine intervention module is used for triggering a micro-injection pump to carry out medicine infusion through a pulse signal. According to the system, epilepsy treatment is improved from empirical parameter adjustment to accurate regulation and control based on real-time nerve physiological signals, and a safer and more effective treatment choice is provided for a drug-refractory epilepsy patient.

A cuff lead arrangement includes a first cuff lead having a first cuff body; first stimulation emitters (for example, electrodes) disposed on an interior surface of the first cuff body; a first lead body coupled to the first cuff body; first conductors electrically coupled to the first stimulation emitters and extending along the first lead body; and at least one first connection element. The cuff lead arrangement further includes a second cuff lead having a second cuff body; second stimulation emitters disposed on an interior surface of the second cuff body; a second lead body coupled to the second cuff body; second conductors electrically coupled to the second stimulation emitters and extending along the second lead body; and at least one second female connection element configured to receive the at least one first male connection element to conjoin the first cuff lead to the second cuff lead.

The invention provides an electronic acupuncture closed-loop control method and system based on multi-modal information feedback. The method comprises the following steps: acquiring long-term, short-term and real-time representation information of a testee under an initial stimulation scheme; the long-term and short-term characterization information is input into a collaborative generative network model for learning, a target stimulation scheme is output, the collaborative generative network model comprises traditional Chinese and western medicine agents, the traditional Chinese and western medicine agents learn the long-term and short-term characterization information, and a corresponding traditional Chinese medicine treatment scheme and an electrical stimulation scheme are output. The collaborative generation network model carries out collaborative training on traditional Chinese and western medicine agents; calculating an index deviation between the real-time characterization information and the standard characterization information to generate a real-time information deviation matrix; inputting the target electrical stimulation scheme and the real-time information deviation matrix into a parameter deviation prediction agent for learning and prediction; and performing parameter adjustment on the target stimulation scheme based on the predicted stimulation parameter deviation matrix to realize long / short time and real-time double-layer closed-loop control of the electronic acupuncture.

The invention discloses a nerve regulation and control intervention system based on time domain interference electrical stimulation, and the system comprises a magnetic resonance image registration module which receives and registers an imported magnetic resonance image, and obtains a to-be-processed MRI image; the head model tissue segmentation module is used for performing head model tissue segmentation on the to-be-processed MRI image; the stimulation simulation module is used for performing stimulation simulation based on the tissue segmentation structure to obtain a front lead field matrix; the intervention coordinate selection module is used for determining a target brain region corresponding to a target spot brain region coordinate position needing stimulation intervention and putting the target brain region into a running sequence; the electrode position arrangement optimization module is used for verifying, optimizing and finely adjusting the electric field intensity of the target brain region under different electrode arrangement schemes to obtain an electrode configuration parameter result and displaying the electrode configuration parameter result; the parameter importing module is used for receiving the selected electrode configuration parameters and imported preset electrical stimulation parameters; and the electrical stimulation module is used for performing electrical stimulation on the target brain region of the target object. According to the application, the accuracy and the effectiveness of nerve regulation and control treatment can be realized.

The invention discloses a patient improvement effect analysis method for controlling spinal cord electrical stimulation through an implantable brain-computer interface, and relates to the technical field of medical rehabilitation, and the method comprises the steps: multi-dimensional collaborative data collection: implanting electrodes in a target brain region and below a spinal cord injury segment, installing a detection element at an exoskeleton key part, and carrying out multi-dimensional collaborative data collection; a sensor is attached to a lower limb preset muscle group, electroencephalogram signals, SCS stimulation parameters, EXS motion data and neuromuscular response data are synchronously collected, and time correlation marks are embedded; according to the method, the reliability of motion intention decoding is remarkably improved by adopting a mode of combining multi-source signal preprocessing and a multi-mode intention recognition model, and in the signal preprocessing stage, the self-adaptive filtering algorithm combining Kalman filtering and wavelet threshold denoising is applied, so that the motion intention decoding efficiency is improved. SCS electrical stimulation interference, EXS motor noise and physiological noise in the electroencephalogram signals are effectively removed.

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

The invention discloses an intelligent acupuncture optimization method, system and device based on acupoint electric signal feedback, and relates to the field of electric data processing, the method comprises the following steps: obtaining associated acupoints of a target diagnosis and treatment mode and treatment parameters corresponding to the associated acupoints; controlling an electric needle to apply electric stimulation to associated acupuncture points according to the treatment parameters; after the electrical stimulation is applied to the associated acupuncture points, acquiring an electrical stimulation feedback signal in the target diagnosis and treatment mode, and determining a signal characteristic parameter according to the electrical stimulation feedback signal; the current treatment state is evaluated according to the signal characteristic parameters, and treatment parameters are adjusted according to the evaluation result. The electrical stimulation feedback signals of intelligent acupuncture in different diagnosis and treatment modes are analyzed in real time, the treatment state is evaluated, the treatment parameters of the acupuncture diagnosis and treatment equipment are correspondingly adjusted, real-time feedback and dynamic optimization of acupuncture treatment are achieved, and the accuracy and the curative effect of acupuncture treatment are improved.

Disclosed herein are systems, devices, and methods for stimulating nerves, including electrically stimulating peripheral nerve(s) to treat various diseases and disorders, as well as systems and methods for applying stimulation waveforms for improving the therapeutic benefit, outcomes, and / or experience relating to the same. Some systems and methods generate a biphasic stimulation waveform that includes a plurality of pulses with alternating leading phases. Some systems and methods vary one or more parameters of the stimulation waveform to correlate with a characteristic of the user. Example characteristic of the user include a phase of a tremor exhibited by the user and a respiratory cycle of the user. For some systems and methods, the stimulation waveform includes a plurality of burst with each burst ramping up in amplitude. For some systems and methods, the stimulation waveform is delivered during a time period that includes an on-cycle portion and an off-cycle portion with the stimulation waveform only being delivered during the on-cycle portion of the time period.

The invention provides a transcranial deep electrical stimulation closed-loop regulation and control system and method based on fNIRS dynamic guidance. The method comprises the steps that a transcranial alternating current electrical stimulation module applies an electrical signal to a target deep brain region according to preset parameters to carry out electrical stimulation regulation and control; the synchronous triggering module is used for realizing millisecond-level synchronization of a stimulation task and near-infrared brain function data acquisition; the brain function monitoring module analyzes the concentration change of cortex oxyhemoglobin in real time through the multi-channel head cap; the electrical stimulation-response coupling mapping module positions a significant activation channel by adopting statistical test, and establishes an oxyhemoglobin concentration variable and electrical stimulation current amplitude quantitative model; and the dynamic parameter adjusting module optimizes the output current in real time. Personalized closed-loop regulation and control of non-invasive deep brain stimulation can be achieved, cerebral cortex blood oxygen signals are monitored in real time through near-infrared brain function imaging, stimulation parameters are dynamically adjusted, and the accuracy and individualization level of deep brain stimulation are remarkably improved.