Computational Intelligence and Neuroscience
Volume 2007 (2007), Article ID 79826, 9 pages
doi:10.1155/2007/79826
Research Article

The Self-Paced Graz Brain-Computer Interface: Methods and Applications

Reinhold Scherer,1,2 Alois Schloegl,3 Felix Lee,4 Horst Bischof,4 Janez Janša,5 and Gert Pfurtscheller1,2

1Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology, Krenngasse 37, Graz 8010, Austria
2NeuroCenter Styria, Krenngasse 37/I, Graz 8010, Austria
3Intelligent Data Analysis Group, Fraunhofer-Institut für Rechnerarchitektur und Softwaretechnik, FIRST, Kekulestrasse 7, Berlin 12489, Germany
4Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, Graz 8010, Austria
5Aksioma - Institute for Contemporary Art, Neubergerjeva 25, Ljubljana 1000, Slovenia

Received 25 February 2007; Revised 13 June 2007; Accepted 19 July 2007

Academic Editor: Fabio Babiloni

Copyright © 2007 Reinhold Scherer 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.

Abstract

We present the self-paced 3-class Graz brain-computer interface (BCI) which is based on the detection of sensorimotor electroencephalogram (EEG) rhythms induced by motor imagery. Self-paced operation means that the BCI is able to determine whether the ongoing brain activity is intended as control signal (intentional control) or not (non-control state). The presented system is able to automatically reduce electrooculogram (EOG) artifacts, to detect electromyographic (EMG) activity, and uses only three bipolar EEG channels. Two applications are presented: the freeSpace virtual environment (VE) and the Brainloop interface. The freeSpace is a computer-game-like application where subjects have to navigate through the environment and collect coins by autonomously selecting navigation commands. Three subjects participated in these feedback experiments and each learned to navigate through the VE and collect coins. Two out of the three succeeded in collecting all three coins. The Brainloop interface provides an interface between the Graz-BCI and Google Earth.