基于联合提示和神经反馈的运动想象脑电-脑机接口的特征
Characteristics of motor imagery based EEG-brain computer interface using combined cue and neuro-feedback.
作者信息
Lee Youngbum, Kim Jinkwon, Lee Sangjoon, Lee Myoungho
机构信息
Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4238-41. doi: 10.1109/IEMBS.2010.5627378.
In this paper, we evaluated BCI algorithm using CSP for finding out about realistic possibility of BCI based on CSP. BCI algorithm that was comprised of CSP and least square linear classifier was evaluated in 10 persons. According to the result of the experiment, the effect of combined cue and neurofeedback is evaluated. In case of combined cue, the correlation of combined cue and visual cue is higher than other conditions. And in case of neurofeedback, some subject is exceptional but general trend shows the performance improvement by neurofeedback.
在本文中，我们评估了使用共空间模式（CSP）的脑机接口（BCI）算法，以探究基于CSP的BCI的现实可能性。由CSP和最小二乘线性分类器组成的BCI算法在10名受试者身上进行了评估。根据实验结果，对组合提示和神经反馈的效果进行了评估。在组合提示的情况下，组合提示与视觉提示的相关性高于其他条件。而在神经反馈的情况下，虽然有一些受试者是例外，但总体趋势显示神经反馈能提高性能。
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