Lead selection for SSVEP-based brain-computer interface

被引：0
|
作者：
Wang, YJ [1 ]
Zhang, ZG [1 ]
Gao, XR [1 ]
Gao, SK [1 ]
机构：
[1] Tsinghua Univ, Dept Biomed Engn, Beijing, Peoples R China
来源：
PROCEEDINGS OF THE 26TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7 | 2004年 / 26卷
关键词：
brain-computer interface; steady-state visual evoked potential; independent component analysis; lead selection;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
SSVEP-based brain-computer interface (BCI) has potential advantage of high information transfer rate. However, individual difference greatly affects its practical applications. This paper presents a method of lead selection to improve the applicability of SSVEP-based BCI system. Independent component analysis (ICA) is employed to decompose EEGs over visual cortex into SSVEP signal and background noise. Optimal bipolar lead is selected by comparing signal correlation and noise correlation between different channels. The system with one optimal bipolar lead has reached an average transfer rate about 42bits/min for normal subjects. It has also been successfully applied to an environmental controller for the motion-disabled.
引用
收藏
页码：4507 / 4510
页数：4
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