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ICA and Committee Machine-Based Algorithm for Cursor Control in a BCI System

机译:基于ICA和委员会的BCI系统光标控制算法

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In recent years, brain-computer interface (BCI) technology has emerged very rapidly. Brain-computer interfaces (BCIs) bring us a new communication interface technology which can translate brain activities into control signals of devices like computers, robots. The preprocessing of electroencephalographic (EEG) signal and translation algorithms play an important role in EEG-based BCIs. In this study, we employed an independent component analysis (ICA)-based preprocessing method and a committee machine-based translation algorithm for the offline analysis of a cursor control experiment. The results show that ICA is an efficient preprocessing method and the committee machine is a good choice for translation algorithm.
机译:近年来,脑电脑界面(BCI)技术已经非常迅速出现。脑电脑接口(BCIS)为我们带来了一种新的通信接口技术,可以将大脑活动转化为计算机,机器人等设备的控制信号。脑电图(EEG)信号和翻译算法的预处理在基于EEG的BCIS中起重要作用。在本研究中,我们采用了独立的分量分析(ICA)的基于预处理方法和基于委员会的转换算法,用于光标控制实验的离线分析。结果表明,ICA是一个有效的预处理方法,委员会机器是翻译算法的良好选择。

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