Enhancing P300 Component by Spectral Power Ratio Principal Components for a Single Trial Brain-Computer Interface
S. Andrews, Ramaswamy Palaniappan, Andrew Teoh and Loo chu Kiong
DOI : 10.3844/ajassp.2008.639.644
American Journal of Applied Sciences
Volume 5, Issue 6
Here we present a novel approach to detect P300 wave in single trial Visual Event Related Potential (VERP) signals using improved principal component analysis to enable a faster brain-computer interface (BCI) design. In the process, the principal components (PCs) are selected using novel methods, namely spectral power ratio (SPR) and sandwich spectral power ratio (SSPR). We set out to assess the improved performances of our proposed methods, SPR and SSPR over standard PC selection methods like Kaiser and residual power for speller BCI design. Concluding, the P300 parameters extracted through our proposed SPR and SSPR methods showed improved detection of target characters in the speller BCI.
© 2008 S. Andrews, Ramaswamy Palaniappan, Andrew Teoh and Loo chu Kiong. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.