11 results about "Evoked potential" patented technology

The present application belongs to the technical field of medical signal processing and neural electrophysiological diagnosis, and particularly relates to a method for establishing an epilepsy diagnosis system based on time-varying brain network and evoked potential regulation. The present application aims to solve the problems that the prior art is difficult to capture the dynamic causal flow of neural activity, cannot accurately depict the transient reorganization characteristics of brain regions of juvenile myoclonic epilepsy (JME) patients, and lacks multi-modal feature integration analysis. The present application comprises the following steps: collecting whole brain electroencephalogram signals; extracting TMS evoked potential waveform after preprocessing; constructing a time-varying adaptive directional transfer function matrix; screening a time-varying brain network visualization atlas; performing baseline correction and superimposed averaging on the evoked potential; identifying the differences in connection and potential between JME patients and healthy controls and different clinical subgroups; and finally integrating the whole process to establish a standardized automated analysis system and a structured database. Through the method, the joint quantification of cortical excitability and time-varying causal connection is realized, and the objectivity, sensitivity and mechanism analysis ability of epilepsy diagnosis are significantly improved.

This invention relates to the field of brain-computer interface (BCI) data processing technology, and discloses a BCI data processing method that integrates steady-state motor visual evoked potentials and motor imagery. The method includes: generating a bimodal task configuration table; generating a bimodal synchronized stimulation sequence; acquiring and labeling multi-lead EEG signals; extracting visual response features and motor imagery response features; performing motor intention recognition; and generating rehabilitation feedback information. Compared to the single visual evoked paradigm in existing technologies, especially under conditions of significant differences in subjects' motor imagery abilities and low EEG noise ratios, this invention addresses the technical problem of failing to achieve stable motor intention recognition. By synchronously binding motor visual stimulation with motor imagery tasks and jointly extracting visual frequency response and motor imagery desynchronization features, stable recognition of motor intention is achieved, improving the recognition accuracy of rehabilitation BCI training.

This invention relates to the field of neuroelectric stimulation technology, specifically a method and system for current regulation during neuroelectric stimulation. The method identifies the target nerve location and depth based on tissue impedance distribution data and patient characteristic parameters, using a deep neural network model to obtain a recommended initial stimulation current value and a personalized target amplitude. It acquires the deviation between the evoked potential amplitude and the personalized target amplitude, and analyzes this deviation with waveform characteristic parameters to obtain a first current regulation step value to adjust the coarse stimulation current until the evoked potential amplitude exceeds the personalized target amplitude. At this point, the current coarse stimulation current value is recorded as the optimized stimulation current value, and a comprehensive quality score is obtained. Based on the comprehensive quality score, a second current regulation step value is dynamically calculated to adjust the fine-tuned stimulation current value. When the comprehensive quality score exceeds a preset quality score threshold, the final stimulation current value is obtained. This effectively improves the accuracy of current regulation during neuroelectric stimulation for different patients.

This invention relates to an instrument for treating neurological or psychiatric disorders using i-wave periodicity-dependent four-pulse theta burst stimulation (iQPS). The system includes a transcranial magnetic stimulation (TMS) stimulator configured to deliver test pulses to a target motor cortex region and therapeutic theta bursts to a treatment region, wherein the pulse frequency is customized according to the patient's individual i-wave periodicity. An electromyography (EMG) device records motor evoked potentials (MEPs) from the target muscles and analyzes the intervals between MEPs to determine the i-wave periodicity. Personalized stimulation enhances cortical plasticity by synchronizing stimulation with the brain's intrinsic neural timing. This invention is applicable to neurological and psychiatric conditions including depression, schizophrenia, stroke recovery, and neuropathic pain. Advantages include improved therapeutic efficacy, reduced patient response variability, and a non-invasive adaptive therapy model aligned with the patient's unique neurophysiological characteristics, thus providing a precise and scalable approach to brain stimulation.

Provided is a closed-loop neuromodulation system involving coordinated intervention of the brain, the spinal cord, and the lumbosacral region, which comprises a deep brain stimulation unit (401), a deep brain field potential sensing unit (402), a spinal cord stimulation unit (501), an evoked potential sensing unit (502), a control decision-making unit (10), a deep brain electrode (403), a spinal cord electrode (503), a lumbosacral electrode (602), a docking lead (601), a radio frequency transmission unit (20), and a wireless charging and power management unit (30). By constructing an application strategy for coordinated regulation of the brain, the spinal cord, and the lumbosacral region, only one neurostimulator needs to be implanted. It can be used alone for brain diseases or spinal cord-related diseases, and can also be used for coordinated stimulation for motor function reconstruction and recovery in paralyzed patients and patients with motor dysfunction, as well as for the treatment of urinary system complications. The whole system is modular in application, can be selectively used according to disease conditions, and has a wider application range.

A brain state recognition method, device, equipment and storage medium are disclosed. The brain state recognition method comprises: acquiring multi-channel electroencephalogram data generated by a user under a preset evoked potential stimulation mode; performing rhythm component and non-rhythm component separation processing on each channel of electroencephalogram data to obtain rhythm data and non-rhythm data corresponding to each channel of electroencephalogram data; extracting first rhythm features from the rhythm data corresponding to each channel of electroencephalogram data, and extracting first non-rhythm features from the non-rhythm data corresponding to each channel of electroencephalogram data to obtain first rhythm features and first non-rhythm features corresponding to each channel of electroencephalogram data; constructing a fusion rhythm feature set according to the first rhythm features and the first non-rhythm features corresponding to each channel of electroencephalogram data; and inputting the fusion rhythm feature set into a preset brain state recognition model to obtain a brain state recognition result output by the brain state recognition model.

The application provides a dynamic adjustment micro-current stimulation and training method and system for ophthalmology. The application integrates various sensors through a wearable periocular device, collects physiological data such as corneal impedance, intraocular pressure signals, blinking behavior and visual evoked potential in real time, combines denoising, normalization, dimensionality reduction and multi-modal fusion processing, and constructs a standardized eye physiological state vector. The vector and incremental clustering are used to identify the micro-current stimulation tolerance inflection point, generate an individual safety upper limit initial value, combine a hierarchical fuzzy reasoning system and a dynamic comprehensive risk index, realize adaptive adjustment of the safety current limiting threshold, and finally smooth the micro-current output through a PID controller. The system can also update the model through cross-course memory data closed loop to improve the personalization and safety of the regulation. The application can dynamically adapt to individual physiological differences, effectively guarantee the biological safety of micro-current stimulation, and meet the needs of continuous and long-term adaptive fine intervention.

The application discloses a kind of based on brain-heart coupling feature's children hyperactivity autism comorbid auxiliary evaluation system, comprising: signal acquisition module, for synchronous acquisition of the subject under the two resting states of open eye rest and closed eye rest Electroencephalogram and electrocardiogram signal;Signal pre-processing module is used to filter and artifact removal to the collected electroencephalogram, and R wave detection and marking are carried out to electrocardiogram;Heartbeat evoked potential feature extraction module is used to extract heartbeat evoked potential feature;Heartbeat evoked brain network feature extraction module is used to construct heartbeat evoked brain network based on the functional connection change in R wave before and after time window, and graph theory feature is extracted;Auxiliary evaluation module is used to output the auxiliary evaluation result of brain-heart coupling state based on heartbeat evoked potential feature and graph theory feature.Using the application, the objective auxiliary evaluation of children attention deficit hyperactivity disorder comorbid autism spectrum disorder related brain-heart coupling abnormality can be realized.

Methods and systems for providing stimulation to a patient's brain using one or more electrode leads implanted in the patient's brain are described. The methods and systems use evoked potentials (EPs) and other indicators of therapeutic effectiveness / side effects to provide closed-loop control of the stimulation. Some embodiments involve recording EPs and using one or more features of the EPs to model how the stimulation activates networks within the patient's brain. A control algorithm can be used to maintain the network activation within a predetermined ranges.

This invention provides a method and system for generating intelligent diagnostic reports based on electromyography (EMG) and evoked potential (EVP) data, belonging to the field of medical diagnostic technology. First, it acquires the subject's EMG and EVP data sets, performs difference compensation and association mapping on the two types of data, establishes dynamic association relationships, and obtains a cross-data type association feature set. Then, it calls a multi-round iterative intelligent diagnostic reasoning model to perform symptom association analysis and generate a preliminary diagnostic conclusion. Next, it integrates the preliminary diagnostic conclusion with clinical reference information to obtain an optimized diagnostic conclusion. Finally, it generates a structured intelligent diagnostic report based on the optimized diagnostic conclusion, including an electrophysiological evidence chain, association analysis details, clinical matching results, and phased suggestions. Each part can be viewed through an associated index, improving diagnostic accuracy and efficiency.

This invention relates to the field of neurophysiological signal acquisition technology, and proposes an olfactory evoked potential acquisition system and method based on respiratory gas flow triggering. The system includes preprocessing the acquired inspiratory flow signal, identifying the inspiratory signal, and determining a valid inspiratory event when the inspiratory flow value, inspiratory flow rate of change, inspiratory duration, and local inspiratory integral value simultaneously meet preset conditions. A labeling signal is then sent to the EEG acquisition device to obtain a labeled event. For each labeled event's time node, waveforms within a set time period before and after the obtained EEG signal are extracted. The waveforms extracted from all labeled events are then superimposed and averaged to obtain the olfactory evoked potential signal waveform. This invention constructs a closed-loop triggered olfactory evoked potential acquisition architecture based on real inspiratory behavior, achieving precise synchronization between stimulus input and EEG labeling.