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An EEG pre-processing technique for the fast recognition of motor imagery movements

机译:脑电预处理技术,用于快速识别运动图像运动

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In this paper we propose a new pre-processing technique of Electroencephalography (EEG) signals produced by motor imagery movements. This technique results to an accelerated determination of the imagery movement and the command to carry it out, within the time limits imposed by the requirements of brain-based real-time control of rehabilitation devices, making thus feasible to drive these devices according to patient's will. Based on event related de-synchronization and synchronization (ERD/ERS) of motor imagery, the received patient signal is first subjected to the removal of environmental, system and interference noise which correspond to normal human activities such as eye-blinking and cardiac motion. Next, power and energy features of the processed signal are compared with the same features of classified signals from an available database and the class to which the processed signal belongs, is identified. The database classification is done off-line by using the SVM algorithm.
机译:在本文中,我们提出了一种由运动图像运动产生的脑电图(EEG)信号的新预处理技术。该技术可在基于大脑的康复设备实时控制要求所施加的时间限制内,加快图像运动的确定和执行图像的命令,从而使根据患者意愿驱动这些设备变得可行。基于事件相关的运动图像非同步和同步(ERD / ERS),首先对接收到的患者信号进行环境,系统和干扰噪声的清除,这些噪声,干扰和噪声与正常的人类活动(例如眨眼和心脏运动)相对应。接下来,将处理后信号的功率和能量特征与来自可用数据库的分类信号的相同特征进行比较,并确定处理后信号所属的类别。数据库分类是使用SVM算法离线完成的。

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