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

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 si...

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Detalles Bibliográficos
Autores principales: Scherer, Reinhold, Schloegl, Alois, Lee, Felix, Bischof, Horst, Janša, Janez, Pfurtscheller, Gert
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2266812/
https://www.ncbi.nlm.nih.gov/pubmed/18350133
http://dx.doi.org/10.1155/2007/79826
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author Scherer, Reinhold
Schloegl, Alois
Lee, Felix
Bischof, Horst
Janša, Janez
Pfurtscheller, Gert
author_facet Scherer, Reinhold
Schloegl, Alois
Lee, Felix
Bischof, Horst
Janša, Janez
Pfurtscheller, Gert
author_sort Scherer, Reinhold
collection PubMed
description 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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spelling pubmed-22668122008-03-18 The Self-Paced Graz Brain-Computer Interface: Methods and Applications Scherer, Reinhold Schloegl, Alois Lee, Felix Bischof, Horst Janša, Janez Pfurtscheller, Gert Comput Intell Neurosci Research Article 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. Hindawi Publishing Corporation 2007 2007-08-30 /pmc/articles/PMC2266812/ /pubmed/18350133 http://dx.doi.org/10.1155/2007/79826 Text en Copyright © 2007 Reinhold Scherer et al. https://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Research Article
Scherer, Reinhold
Schloegl, Alois
Lee, Felix
Bischof, Horst
Janša, Janez
Pfurtscheller, Gert
The Self-Paced Graz Brain-Computer Interface: Methods and Applications
title The Self-Paced Graz Brain-Computer Interface: Methods and Applications
title_full The Self-Paced Graz Brain-Computer Interface: Methods and Applications
title_fullStr The Self-Paced Graz Brain-Computer Interface: Methods and Applications
title_full_unstemmed The Self-Paced Graz Brain-Computer Interface: Methods and Applications
title_short The Self-Paced Graz Brain-Computer Interface: Methods and Applications
title_sort self-paced graz brain-computer interface: methods and applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2266812/
https://www.ncbi.nlm.nih.gov/pubmed/18350133
http://dx.doi.org/10.1155/2007/79826
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