Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/38093
Title: Performance of common spatial pattern under a smaller set of EEG electrodes in brain-computer interface on chronic stroke patients : a multi-session dataset study
Authors: Tam, WK
Tong, KY 
Ke, Z
Keywords: Brain-computer interfaces
Electroencephalography
Filtering theory
Medical disorders
Medical signal processing
Patient rehabilitation
Issue Date: 2011
Source: 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'11), Boston, MA, USA, August 30 - September 3, 2011, p. 6344-6347 How to cite?
Abstract: Brain-computer interface (BCI) uses non-muscular channel of the nervous system for communication. Common Spatial Pattern (CSP) is a popular spatial filtering method used to reduce the effect of volume conduction on EEG signals. It is thought that CSP requires a large number of electrodes to be effective. Using a 20-session dataset of motor imagery BCI usage by 5 stroke patients, we demonstrated that after channel selection, CSP can still maintain a high accuracy with low number of electrodes using a newly proposed channel selection method called CSP-rank (higher than 90% with 8 electrodes). The results showed that using only the first session for channel selection, a high accuracy can be maintained in subsequent sessions. CSP-rank has been compared to the popular support vector machine recursive feature elimination (SVM-RFE). The results showed that the CSP-rank required less electrodes to maintain accuracy higher than 90% (a minimum of 8 compared to 12 of SVM-RFE) and it attained a higher maximum accuracy (91.7% compared with 90.7% of SVM-RFE). This could support clinicians to apply more BCI in routine rehabilitation.
URI: http://hdl.handle.net/10397/38093
ISBN: 978-1-4244-4121-1
978-1-4244-4122-8 (E-ISBN)
DOI: 10.1109/IEMBS.2011.6091566
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