277 results about "Motor evoked potentials monitoring" patented technology

A method and apparatus for performing rapid brain assessment may provide emergency triage to head trauma patients by analyzing a combination of spontaneous and evoked brain potentials. The spontaneous and evoked potentials are analyzed, and the results classified, to present a real-time assessment of a patient's brain, diagnosing any potential abnormalities therein.

A system and method are described for automatically detecting diaphragmatic stimulation (DS) based on evoked response signals, electrogram data and/or thoracic impedance measurements. In addition, several optional modalities are described to circumvent this problem and alleviate symptoms related to DS while preserving LV pacing.

The subject invention is directed to new and useful neurostimulation systems that include an implantable pulse generator dimensioned and configured for implantation in the skull of a patient. The implantable pulse generator has an electrode operatively associated with a distal end portion thereof and can be provided with adjustment means, such as an adjustable biasing member or spring arranged between the electrode to the distal end portion of the pulse generator. The subject invention is also directed to systems involving networked neurostimulators that are configured and adapted to work jointly in accordance with prescribed treatment protocol to effect a desired recovery from brain injury. Such networked neurostimulation systems are particularly advantageous for effecting relatively large and/or relatively distant regions of the brain. The subject invention is further directed to systems and methods for motor-evoked potential (MEP)-based neuromodulation. Further, AC and/or DC stimulation can be utilized, depending on the precise implementation.

System and method for rehabilitating a muscle and monitoring such rehabilitation are provided, the system including a user input receiver for receiving stimulation parameter inputs from a user, a stimulator for generating stimulations to be applied to a patient's body based on the stimulation parameter inputs, a signal receiver to receive, detect, and record a signal containing an evoked potential generated by the body in response to the stimulations, a signal processor for processing the recorded signal, for example, by amplifying, filtering, digitizing and temporal averaging the recorded signal, a trigger detector to alert the signal processor module when stimulations are generated to enable synchronization of the response signal with the stimulus for accurate temporal averaging, and an output display for providing data representative of the evoked potential to the user.

The invention provides a system and method for controlling a brain computer interface (BCI) based on multimode fusion. The system comprises a brain electrostimulation and feedback module, an electroencephalogram (EEG) signal acquisition module, an EEG signal processing module and an execution module, wherein the brain electrostimulation and feedback module is used for evoking an SSVEP (Steady State Visual Evoked Potential) and inducing an MI (Motor Imagery); the EEG signal acquisition module is used for acquiring EEG signals; the EEG signal processing module is used for extracting, identifying and classifying SSVEP characteristics and MI EEG characteristics in the EEG signals and feeding classified results which respectively correspond to the SSVEP characteristics and the MI EEG characteristics back to the brain electrostimulation and feedback module; and the execution module is used for executing the classified results. According to the system and the method, a multimode fusion BCI is constructed, so that the information transmission rate, reliability and flexibility of a control system are improved, the low information transmission rate of a BCI in a single MI mode is reduced, meanwhile, the visual burden under a single SSVEP task is reduced, and the adaptation crowds of the BIC-based control system are increased.

A method and apparatus for providing an objective assessment of the neurological state of a patient using a field-portable neuro-assessment device is described. The method includes placing an electrode set on the patient's head, acquiring spontaneous brain electrical signals and evoked potential signals from the patient through the electrode set, processing the signals using a handheld base unit, and displaying a result indicating the probability of the patient's neurological signal being normal or abnormal. The neuro-assessment device allows for a rapid, on-site neurological evaluation by an emergency medical technician, triage nurse, or any other medical personnel to identify patients with neurological disorders who may require immediate medical attention.

Systems and methods for closed loop spinal cord stimulation are provided. The systems and methods position a first electrode proximate to a dorsal column. The first electrode is electrically coupled to an implantable pulse generator (IPG). The systems and methods further program the IPG to deliver excitation pulses to the first electrode based on a stimulation level. The excitation pulses are emitted from the first electrode. The systems and methods further position a second electrode proximate to a dorsal root. The second electrode is electrically coupled to the IPG. The systems and methods further measure at the second electrode a first evoked potential waveforms resulting from the excitation pulses.

The invention discloses an intelligent wheelchair system based on SSVEP (steady-state visual evoked potential), and aims to solve the problems of high requirements on a user, less control commands and imperfect wheelchair functions of existing device during the process of using electroencephalogram to control a wheelchair. The intelligent wheelchair system comprises an LED strobe stimulator (1), an electrode cap (2), an electroencephalogram pre-processing circuit (3), a wireless transmission system (4), an upper computer (5), a wheelchair control circuit (6), an electric wheelchair (7), and an automatic obstacle avoidance module (8). Electroencephalogram signals collected by the electrode cap (2) are pre-processed through the electroencephalogram pre-processing circuit (3) and then are transmitted to the upper computer (5) through the wireless transmission system (4) to process and generate control signals, and the control signals are transmitted through the wireless transmission system (4) to the wheelchair control circuit (6) to control the wheelchair. The intelligent wheelchair system has the advantages of convenience in operation and safety in use, and can serve as an assisting tool for the old and the disabled.

The application provides a system and a method of cursor control based on a brain-computer interface. The system comprises a visual evoked simulation module, an electroencephalogram acquisition instrument and a processor, wherein the visual evoked simulation module is used for providing P300 evoked potential stimulation and SSVEP (Steady State Visual Evoked Potential) stimulation for a user in an interface display manner; the electroencephalogram acquisition instrument is used for acquiring the electroencephalogram signal of the user in real time and carrying out amplification and analog-to-digital conversion, and carrying out signal transmission through data wires and the processor; and the processor is used for receiving and processing the electroencephalogram signal, and judging the control purpose of the user and controlling cursor movement.

Provided herein are a method and system are provided for the localization of clinically relevant electrophysiological signals necessary for the proper placement of the electrodes for nervous system stimulation. The system provides electrical and mechanical means to stimulate or excite neural structures in order to elicit specific neural responses. The method can include mechanical vibratory stimulation, cutaneous electrical stimulation, electrical stimulation of the peripheral nerves, or photic stimulation, and recording of local field potentials and extracting evoked potentials in response to stimulation. The method also includes extracting components of the evoked potentials that relate the signal in the evoked potentials to specific anatomical structures and localization of the source of the evoked potentials recorded so as to identify the location of the source relative to the recording electrode with high resolution by sampling the evoked potentials with a relative large (macro) electrode that is moved in small incremental steps.

The invention discloses a hybrid brain-computer interface method based on steady state motion visual evoked potential and default stimulation response. The method includes the steps that 1, a testee wears an electrode cap, a reference electrode, a ground electrode and a testing electrode on the electrode cap make contact with the head of the testee, and the vision and the computer screen are in the eye level through visual inspection; 2, a steady state motion visual evoked potential and default stimulation response mixed normal form program is compiled through MATLAB in advance, the testee selects a stimulation target to stare according to a target prompt, and electroencephalogram signals acquired by the electrode cap are stored in a computer; 3, steady state motion visual evoked potential features and default stimulation response features are subjected to feature extraction respectively, and then the stimulation target is subjected to classified recognition; 4, the computer screen displays the stimulation target recognition result, and visual feedback is conducted on the testee; 5, the steps are repeated, and the next round is conducted till the program is ended. According to the hybrid brain-computer interface method, two types of feature recognition information is adopted, and the method has the advantages that operation is simple, less training time is needed, and less electrodes are needed.

The invention belongs to the field of brain electricity and identity identification, providing an identity identification method which can effectively describe the components of the characteristic of the brain electricity and can achieve the requirement for improving the identification rate. The technical scheme is that the identity identification method based on visual evoked potential (VEP) comprises the following steps of: applying some image stimulation to a subject; selecting a proper scalp leading electrode to capture the visual evoked potential of the subject; preprocessing an original brain electricity signal in a de-noising way; extracting a gamma wave band power spectrum to be taken as the characteristic of the brain electricity to be researched; processing the characteristic of the brain electricity with Fisher linear discrimination; and studying and testing the optimized characteristic parameter in a classifying way through a BP neural network to realize the identity identification. The method is mainly applied to the identity identification.

The invention relates to a three-stage brain-controlled upper limb rehabilitation method combining steady-state visual evoked potential and mental imagery (MI). The method comprises the following steps: (1) the first stage of VR video guidance training: a patient is made to be familiar with upper limb rehabilitation movements through VR video guidance; (2) the second stage of VR-SSVEP training: the patient needs to concentrate to observe pictures that represent different upper limb movements and flicker with a specific frequency, EEG signals of the patient are collected in real-time to analyzeintentions of the patient, and visual feedback is provided to the patient through VR animation to make the patient learn to concentrate; and (3) the third stage of VR-MI training: EEG signals of theleft and right upper limbs of the patient during MI are collected during off-line training, and a mental imagery intention recognition model is established. The EEG signals of mental imagery of the patient are analyzed according to the model during online training, movement intentions of the patient are recognized, and movements of a 3D character in an interface are controlled in real time, so that brain central nerve remodeling is facilitated through MI. The method exhibits a good immersion property, enables active rehabilitation to be realized, enables rehabilitation to proceed step by step,and is a new method for upper limb rehabilitation of a cerebral stoke patient.

A steady-state visual evoked potential signal classification method based on a convolutional neural network comprises the following steps: firstly, presenting checkerboard stimuli flipped at differentfrequencies to a user at the same time, and acquiring an electroencephalogram signal when the user watches a specific target by using an electroencephalogram acquisition device; making original multi-channel electroencephalogram signals when the user watches different stimulation targets into a data set with labels, and dividing the data set into a training set, a verification set and a test set;inputting the training set into a designed deep convolutional neural network model for training, performing network optimal parameter selection by using a verification set, and finally inputting thetest set into the trained deep convolutional neural network model to complete the recognition of the stimulation target. Accurate identification of steady-state visual evoked potential signals can beachieved, the characteristic of adaptively extracting signal characteristics is achieved, manual preprocessing is not needed, and meanwhile individual difference can be better adapted through data learning.

A method and apparatus for processing a composite signal generated by a transient signal generation mechanism to extract a repetitive low SNR transient signal, such as an evoked potential (EP) appearing in an electroencephalogram (EEG) generated in response to sensory stimulation, by: (a) dynamically identifying, via a learning process, the major transient signal types in the composite signal; (b) decomposing the identified major transient signal types into their respective constituent components; (c) synthesizing a parametric model emulating the transient signal generation mechanism; and (d) utilizing the model and the constituent components to identify and extract the low SNR transient signal from the composite signal.

The invention discloses a multi-frequency time sequence combined steady-stage visual evoked potential brain-computer interface method. The method comprises the following steps of: putting a measurement electrode on the head of a subject and connecting the measurement electrode with an electroencephalogram amplifier, a computer and a computer screen; and forming n different representation targets by using n stimulus frequencies, wherein n is an integer more than 1; and realizing the representation of the visual targets and the visual feedback of the subject by using the computer screen. The method improves the information transmission rate of the brain-computer interface by constructing a plurality of representation targets from a few stimulus frequencies, has the advantages of multiple representation targets and high specificity of the detection result, can realize communication between the disabled having normal mind but suffering from paralysis of the neuromuscular system and an external apparatus, and is suitable for a normal person on occasions that the limbs are inconvenient to control.