Title :
Common Spatial Pattern and Particle Swarm Optimization for Channel Selection in BCI
Author :
Lv, Jun ; Liu, Meichun
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou
Abstract :
Common spatial pattern algorithm (CSP) is famous for extracting ERD/ERS feature from multi-channel BCIs based on motor imagery. However, if channel number is large, CSP will tend to overfitting and it is inconvenient for clinical operation. In this study, CSP filters´ discrimination and channel number are integrated under one roof. Then binary particle swarm optimization (BPSO) is employed to select the best channel groups. Experimental results of BCI2003 dataset IV and BCI2005 dataset I show that good classification accuracies can be achieved only with 914 channels.
Keywords :
evolutionary computation; human computer interaction; particle swarm optimisation; BPSO; CSP; binary particle swarm optimization; channel groups; channel selection; common spatial pattern; multichannel BCIs; multichannel brain-computer interfaces; Covariance matrix; Data mining; Electroencephalography; Feature extraction; Filters; Linear discriminant analysis; Particle swarm optimization; Robustness; Testing; Topology;
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
DOI :
10.1109/ICICIC.2008.196
