Addressing low frequency movement artifacts in EEG signal recorded during center-out reaching tasks.
Addressing low frequency movement artifacts in EEG signal recorded during center-out reaching tasks.
复制标题
解决在中心向外伸手任务期间记录的脑电图信号中的低频运动伪影。
DOI：
10.1109/embc.2014.6945116
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Principe,JoseC
中科院分区：
文献类型：
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作者：
Philips,GavinR;Hazrati,MehrnazKh;Daly,JanisJ;Principe,JoseC
无创脑机接口（BCI）在神经康复中的成功应用需要对低频运动伪影进行检查，并开发准确的新方法来纠正它们。为此，本研究采用自适应趋势提取方法对主动式和被动式中心伸出任务中记录的脑电图信号进行分析。发现了不同的模式，这与手臂运动学相关，但在本质上显示出很大程度上是人工的。值得注意的是，这些模式被发现与目前用于识别运动方向的特征相似，这表明在此类应用中利用EEG信号的低频内容时，需要谨慎和精确的信号处理方法。
The successful application of noninvasive brain-computer interfaces (BCI) to neurological rehabilitation requires examination of low frequency movement artifacts and development of accurate new methods for their correction. To this end, this study applies an adaptive trend extraction method to electroencephalogram (EEG) signals recorded during active and passive center-out reaching tasks. Distinct patterns are discovered, which correlate to arm kinematics, but are shown to be largely artifactual in nature. Notably, these patterns are found to be similar to features currently used for discrimination of movement direction, indicating a necessity for caution and precise signal processing methods when utilizing low frequency content of EEG signals in such applications.