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Computational Intelligence and Neuroscience
Volume 2007, Article ID 84386, 8 pages
Research Article

Towards Development of a 3-State Self-Paced Brain-Computer Interface

1Electrical and Computer Engineering Department, University of British Columbia, Vancouver, BC, Canada V6T 1Z4
2Terry Fox Laboratory, British Columbia Cancer Research Center, Vancouver, BC, Canada V5Z 1L3
3Brain Interface Laboratory, Neil Squire Society, Suite 220, 2250 Boundary Road, Burnaby, BC, Canada V5M 3Z3
4Institute for Computing, Information & Cognitive Systems, Vancouver, BC, Canada V6T 1Z4

Received 15 February 2007; Accepted 22 August 2007

Academic Editor: Andrzej Cichocki

Copyright © 2007 Ali Bashashati et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Most existing brain-computer interfaces (BCIs) detect specific mental activity in a so-called synchronous paradigm. Unlike synchronous systems which are operational at specific system-defined periods, self-paced (asynchronous) interfaces have the advantage of being operational at all times. The low-frequency asynchronous switch design (LF-ASD) is a 2-state self-paced BCI that detects the presence of a specific finger movement in the ongoing EEG. Recent evaluations of the 2-state LF-ASD show an average true positive rate of 41% at the fixed false positive rate of 1%. This paper proposes two designs for a 3-state self-paced BCI that is capable of handling idle brain state. The two proposed designs aim at detecting right- and left-hand extensions from the ongoing EEG. They are formed of two consecutive detectors. The first detects the presence of a right- or a left-hand movement and the second classifies the detected movement as a right or a left one. In an offline analysis of the EEG data collected from four able-bodied individuals, the 3-state brain-computer interface shows a comparable performance with a 2-state system and significant performance improvement if used as a 2-state BCI, that is, in detecting the presence of a right- or a left-hand movement (regardless of the type of movement). It has an average true positive rate of 37.5% and 42.8% (at false positives rate of 1%) in detecting right- and left-hand extensions, respectively, in the context of a 3-state self-paced BCI and average detection rate of 58.1% (at false positive rate of 1%) in the context of a 2-state self-paced BCI.