Single trial independent component analysis for P300 BCI system.
A Brain Computer Interface (BCI) is a device that allows the user to communicate with the world without utilizing voluntary muscle activity (i.e., using only the electrical activity of the brain). It makes use of the well-studied observation that the brain reacts differently to different stimuli, as a function of the level of attention allotted to the stimulus stream and the specific processing triggered by the stimulus. In this article we present a single trial independent component analysis (ICA) method that is working with a BCI system proposed by Farwell and Donchin. It can dramatically reduce the signal processing time and improve the data communicating rate. This ICA method achieved 76.67% accuracy on single trial P300 response identification.
Li
Kun
K
Electrical Engineering Department, University of South Florida, Tampa, FL 33620-5350, USA. li@mail.usf.edu
Sankar
Ravi
R
Arbel
Yael
Y
Donchin
Emanuel
E
D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000502:physiology; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D006801:Humans; D008328:Man-Machine Systems; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D014584:User-Computer Interface