Title :
Single trial independent component analysis for P300 BCI system
Author :
Li, Kun ; Sankar, Ravi ; Arbel, Yael ; Donchin, Emanuel
Author_Institution :
Electr. Eng. Dept., Univ. of South Florida, Tampa, FL, USA
Abstract :
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.
Keywords :
bioelectric phenomena; brain-computer interfaces; data communication; independent component analysis; medical signal processing; neurophysiology; P300 BCI system; brain computer interface; brian electrical activity; data communication rate; medical signal processing; single trial independent component analysis; stimulus stream; voluntary muscle activity; Algorithms; Artificial Intelligence; Brain; Data Interpretation, Statistical; Electroencephalography; Event-Related Potentials, P300; Humans; Man-Machine Systems; Pattern Recognition, Automated; Reproducibility of Results; Signal Processing, Computer-Assisted; Time Factors; User-Computer Interface;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5333745