P300 Based Single Trial Independent Component Analysis on EEG Signal
Document Type
Conference Proceeding
Publication Date
2009
Keywords
Independent Component Analysis, Brain Computer Interface, P300 Response, Independent Component Analysis Algorithm
Digital Object Identifier (DOI)
https://doi.org/10.1007%2F978-3-642-02812-0_48
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.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
International Conference of Foundations of Augmented Cognition, p. 404-410
Scholar Commons Citation
Li, Kun; Sankar, Ravi; Arbel, Yael; and Donchin, Emanuel, "P300 Based Single Trial Independent Component Analysis on EEG Signal" (2009). Psychology Faculty Publications. 349.
https://digitalcommons.usf.edu/psy_facpub/349
