The Self-Paced Graz Brain-Computer Interface: Methods and Applications
Author(s) -
Reinhold Scherer,
A. Schloegl,
Felix Lee,
Horst Bischof,
Janez Janša,
Gert Pfurtscheller
Publication year - 2007
Publication title -
computational intelligence and neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.605
H-Index - 52
eISSN - 1687-5273
pISSN - 1687-5265
DOI - 10.1155/2007/79826
Subject(s) - brain–computer interface , interface (matter) , motor imagery , computer science , electroencephalography , human–computer interaction , brain activity and meditation , signal (programming language) , sensorimotor rhythm , virtual keyboard , artificial intelligence , speech recognition , psychology , neuroscience , computer hardware , bubble , maximum bubble pressure method , parallel computing , programming language
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.
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