Title :
Lead selection for SSVEP-based brain-computer interface
Author :
Wang, Yijun ; Zhang, Zhiguang ; Gao, Xiaorong ; Gao, Shangkai
Author_Institution :
Dept. of Biomedical Eng., Tsinghua Univ., Beijing, China
Abstract :
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.
Keywords :
electroencephalography; handicapped aids; independent component analysis; medical signal processing; noise; visual evoked potentials; EEG decomposition; brain-computer interface; environmental controller; high information transfer rate; independent component analysis; lead selection; motion-disabled; noise correlation; optimal bipolar lead; signal correlation; steady-state visual evoked potentials; visual cortex; Background noise; Band pass filters; Brain computer interfaces; Electroencephalography; Frequency; Independent component analysis; Light emitting diodes; Motion control; Steady-state; Working environment noise; Brain-computer interface; independent component analysis; lead selection; steady-state visual evoked potential;
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
DOI :
10.1109/IEMBS.2004.1404252
