Bhattacharyya bound based channel selection for classification of motor imageries in EEG signals

Author

He, Lin ; Yu, Zhuliang ; Gu, Zhenghui ; Li, Yuanqing

Author_Institution

Coll. of Autom. Sci. & Technol., South China Univ. of Technol., Guangzhou, China

fYear

2009

fDate

17-19 June 2009

Firstpage

2353

Lastpage

2356

Abstract

In EEG-based brain computer interfaces (BCIs), channel selection is important for the classification of mental task, such as motor imagery. In this paper, a channel selection method is presented for motor imagery. The Bhattacharyya bound of common spatial pattern (CSP) features is used as the optimal index, and a fast sequential forward search is applied to find the optimal combination of channels. The data analysis results show the improvement of classification accuracy.

Keywords

brain-computer interfaces; cognitive systems; electroencephalography; spatial reasoning; statistical analysis; Bhattacharyya bound; brain computer interfaces; channel selection method; common spatial pattern; electroencephalography signals; mental task classification; motor imagery; sequential forward search; Automation; Brain computer interfaces; Communication system control; Data analysis; Educational institutions; Electroencephalography; Electronic mail; Helium; Positron emission tomography; Rhythm; Bhattacharyya Bound; Common Spatial Pattern; EEG; Motor Imagery; Sequential Forward Search;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2009. CCDC '09. Chinese

Conference_Location

Guilin

Print_ISBN

978-1-4244-2722-2

Electronic_ISBN

978-1-4244-2723-9

Type

conf

DOI

10.1109/CCDC.2009.5192711

Filename

5192711