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275 results about "Evoked potential" patented technology

An evoked potential or evoked response is an electrical potential in a specific pattern recorded from a specific part of the nervous system, especially the brain, of a human or other animals following presentation of a stimulus such as a light flash or a pure tone. Different types of potentials result from stimuli of different modalities and types. EP is distinct from spontaneous potentials as detected by electroencephalography (EEG), electromyography (EMG), or other electrophysiologic recording method. Such potentials are useful for electrodiagnosis and monitoring that include detections of disease and drug-related sensory dysfunction and intraoperative monitoring of sensory pathway integrity.

Determining stimulation levels for transcranial magnetic stimulation

Induced movement in a patient is detected and correlated with a TMS stimulating pulse so as to determine the patient's motor threshold stimulation level. Direct visual or audible feedback is provided to the operator indicating that a valid stimulation has occurred so that the operator may adjust the stimulation accordingly. A search algorithm may be used to direct a convergence to the motor threshold stimulation level with or without operator intervention. A motion detector is used or, alternatively, the motion detector is replaced with a direct motor evoked potential (MEP) measurement device that measures induced neurological voltage and correlates the measured neurological change to the TMS stimulus. Other signals indicative of motor threshold may be detected and correlated to the TMS stimulus pulses. For example, left / right asymmetry changes in a narrow subset of EEG leads placed on the forehead of the patient or fast autonomic responses, such as skin conductivity, modulation of respiration, reflex responses, and the like, may be detected. The appropriate stimulation level for TMS studies are also determined using techniques other than motor cortex motor threshold methods. For example, a localized ultrasound probe may be used to determine the depth of cortical tissue at the treatment site. When considered along with neuronal excitability, the stimulation level for treatment may be determined. Alternatively, a localized impedance probe or coil and detection circuit whose Q factor changes with tissue loading may be used to detect cortical depth.
Owner:NEURONETICS

System and method for controlling brain computer interface (BCI) based on multimode fusion

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.
Owner:TONGJI UNIV

Brain-controlling animal robot system and brain-controlling method of animal robot

The invention discloses a brain-controlling animal robot system and a brain-controlling method of an animal robot. A corresponding control instruction is generated by collecting brain electrical signals of the brain and processing the brain electrical signals, the corresponding control instruction is used for controlling the animal robot to move, and a brain-to-brain normal form of two mixed modes can effectively control the brain-to-brain animal robot. The brain-controlling animal robot system and the brain-controlling method of the animal robot adopt two control modes, namely the mixed control mode based on ocular electricity / myoelectricity characteristics and motion imagery characteristics of the brain electrical signals and the mixed control mode based on visual evoked potential characteristics and the motion imagery characteristics, select a proper control mode according to the state of a user, and largely improve the real-time performance and reliability of control. The brain-controlling animal robot system can be applied to the fields of unknown environment exploration, brain function mechanism research, brain-to-brain network communication, life assistance and entertainment for the disabled and the like.
Owner:浙江浙大西投脑机智能科技有限公司

Hybrid brain-computer interface method based on steady state motion visual evoked potential and default stimulation response

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.
Owner:XI AN JIAOTONG UNIV

Three-stage brain-controlled upper limb rehabilitation method combining steady-state visual evoked potential and mental imagery

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.
Owner:SHANGHAI UNIV

N400 evoked potential lie detection method based on improved extreme learning machine

The invention provides an N400 evoked potential lie detection method based on an improved extreme learning machine; random parameters of the extreme learning machine are optimized on the basis of an artificial immune algorithm, and the electroencephalogram lie detection method based on an N400 evoked potential and the improved extreme learning machine is proposed; by virtue of the improved extreme learning machine, classification recognition rates of crime group subjects and control group subjects to detection stimulation and unassociated stimulation are calculated, and the classification recognition rates of the two groups of subjects are calculated and analyzed, so that a threshold parameter for distinguishing whether a subject lies or not is found out; and detection stimulation and unassociated stimulation time domain and frequency domain characteristics of 40 channel N400 induced electroencephalogram signals are extracted, so that the extracted electroencephalogram signal characteristics are more comprehensive; therefore, shortcomings in the prior art which conducts lie detection and judgment on the basis of a few of channels and by taking induced potential waveform geometric properties as characteristic parameter are overcome; and the lie detection method disclosed by the invention has the advantage that a stable lie identification right rate is effectively guaranteed.
Owner:SHAANXI NORMAL UNIV

Target selecting method based on transient visual evoked electroencephalogram

The invention relates to a target selecting method based on transient visual evoked electroencephalogram, comprising the following steps: VC + + writing visual stimulator evokes an electroencephalogram signal, 16-lead collecting device collects an electroencephalogram signal VEP which is amplified by an electroencephalogram amplifier and A / D converted, so that the signal is input into a computer and memorized in a memorizer in a way of signal voltage magnitude; B sample band biorthogonal wavelet method is used for extracting an electroencephalogram characteristic signal, in addition, corresponding results are classified, identified and output by the self-learning ability of BP neuronic network; wherein, the method also comprising the following steps of: designing the accurate timing visual stimulator by CPU timestamp; answering the output impulse of paralled port; collecting the electroencephalogram signal VEP by a collecting device; pretreating the collected signal; extracting the electroencephalogram signal by the B sample band biorthogonal wavelet method; and classifying characteristic quantity by the BP neuronic network. The method has the advantage that the BP neuronic network is used for effectively improving signal to the noise ratio and the recognition rate of visual evoked potential VEP.
Owner:BEIJING UNIV OF TECH

Two-dimensional cursor movement control system and method based on motor imagery and coded modulation visual evoked potential

The invention discloses a two-dimensional cursor movement control system and method based on motor imagery and coded modulation visual evoked potential. The system comprises an electrode cap, an electroencephalography acquisition instrument, a system control unit, a data processing module, a cursor control module and a visual stimulator, wherein the visual stimulator is provided for a user in an interface display way. The method comprises the following steps that: the user simultaneously executes a motor imagery task and a visual attention task according to a work interface instruction; the electrode cap collects an electroencephalography signal; the electroencephalography acquisition instrument carries out amplification, filtering and analog-digital conversion on the electroencephalography signal; the system control unit separates the electroencephalography data generated by the motor imagery and the visual attention, and then, the electroencephalography data is stored; the data processing module carries out preprocessing, feature extraction and classification identification on two classes of electroencephalography data in sequence; and the cursor control module controls a cursor to carry out continuous two-dimensional movement according to classification identification. The system has the advantages of being high in control accuracy, good in robustness and the like, the continuous movement of a two-dimensional cursor can be realized, and the system can be used for the movement control of a computer mouse.
Owner:NANCHANG UNIV
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