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QUANTIFYING MOTOR FUNCTION USING BEG SIGNALS

机译:使用BEG信号量化电机功能

摘要

A motor control score is automatically generated for a subject based on electroencephalography (EEG) data represented as a plurality of EEG waveforms obtained from a plurality of EEG electrodes. Each waveform is separated into at least one window, containing a portion of the EEG waveform representative of neural activity corresponding to a movement performed by the subject. At least one or more frequency components and/or signal components are determined from the EEG data in the window, and a motor control score is determined based on these components. The frequency components may correspond to event-related desynchronization (ERD) response frequency band and event-related synchronization (ERS) response frequency band. In other embodiments, the frequency components correspond to a phase response and the signal components correspond to a signal power spectrum density of the window, which are provided to a primary neural network model to determine the motor control score.
机译:基于脑电图(EEG)数据自动生成对象的运动控制评分,脑电图数据表示为从多个EEG电极获得的多个EEG波形。每个波形被分成至少一个窗口,该窗口包含代表与受检者执行的运动相对应的神经活动的EEG波形的一部分。从窗口中的EEG数据确定至少一个或多个频率分量和/或信号分量,并且基于这些分量确定电动机控制得分。频率分量可以对应于事件相关的去同步(ERD)响应频带和事件相关的同步(ERS)响应频带。在其他实施例中,频率分量对应于相位响应,信号分量对应于窗口的信号功率谱密度,其被提供给初级神经网络模型以确定电动机控制得分。

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