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EEG-Based Brain-Computer Interface for Tetraplegics

Movement-disabled persons typically require a long practice time to learn how to use a brain-computer interface (BCI). Our aim was to develop a BCI which tetraplegic subjects could control only in 30 minutes. Six such subjects (level of injury C4-C5) operated a 6-channel EEG BCI. The task was to mov...

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Autores principales: Kauhanen, Laura, Jylänki, Pasi, Lehtonen, Janne, Rantanen, Pekka, Alaranta, Hannu, Sams, Mikko
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233767/
https://www.ncbi.nlm.nih.gov/pubmed/18288247
http://dx.doi.org/10.1155/2007/23864
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author Kauhanen, Laura
Jylänki, Pasi
Lehtonen, Janne
Rantanen, Pekka
Alaranta, Hannu
Sams, Mikko
author_facet Kauhanen, Laura
Jylänki, Pasi
Lehtonen, Janne
Rantanen, Pekka
Alaranta, Hannu
Sams, Mikko
author_sort Kauhanen, Laura
collection PubMed
description Movement-disabled persons typically require a long practice time to learn how to use a brain-computer interface (BCI). Our aim was to develop a BCI which tetraplegic subjects could control only in 30 minutes. Six such subjects (level of injury C4-C5) operated a 6-channel EEG BCI. The task was to move a circle from the centre of the computer screen to its right or left side by attempting visually triggered right- or left-hand movements. During the training periods, the classifier was adapted to the user's EEG activity after each movement attempt in a supervised manner. Feedback of the performance was given immediately after starting the BCI use. Within the time limit, three subjects learned to control the BCI. We believe that fast initial learning is an important factor that increases motivation and willingness to use BCIs. We have previously tested a similar single-trial classification approach in healthy subjects. Our new results show that methods developed and tested with healthy subjects do not necessarily work as well as with motor-disabled patients. Therefore, it is important to use motor-disabled persons as subjects in BCI development.
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spelling pubmed-22337672008-02-20 EEG-Based Brain-Computer Interface for Tetraplegics Kauhanen, Laura Jylänki, Pasi Lehtonen, Janne Rantanen, Pekka Alaranta, Hannu Sams, Mikko Comput Intell Neurosci Research Article Movement-disabled persons typically require a long practice time to learn how to use a brain-computer interface (BCI). Our aim was to develop a BCI which tetraplegic subjects could control only in 30 minutes. Six such subjects (level of injury C4-C5) operated a 6-channel EEG BCI. The task was to move a circle from the centre of the computer screen to its right or left side by attempting visually triggered right- or left-hand movements. During the training periods, the classifier was adapted to the user's EEG activity after each movement attempt in a supervised manner. Feedback of the performance was given immediately after starting the BCI use. Within the time limit, three subjects learned to control the BCI. We believe that fast initial learning is an important factor that increases motivation and willingness to use BCIs. We have previously tested a similar single-trial classification approach in healthy subjects. Our new results show that methods developed and tested with healthy subjects do not necessarily work as well as with motor-disabled patients. Therefore, it is important to use motor-disabled persons as subjects in BCI development. Hindawi Publishing Corporation 2007 2007-09-19 /pmc/articles/PMC2233767/ /pubmed/18288247 http://dx.doi.org/10.1155/2007/23864 Text en Copyright © 2007 Laura Kauhanen 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
Kauhanen, Laura
Jylänki, Pasi
Lehtonen, Janne
Rantanen, Pekka
Alaranta, Hannu
Sams, Mikko
EEG-Based Brain-Computer Interface for Tetraplegics
title EEG-Based Brain-Computer Interface for Tetraplegics
title_full EEG-Based Brain-Computer Interface for Tetraplegics
title_fullStr EEG-Based Brain-Computer Interface for Tetraplegics
title_full_unstemmed EEG-Based Brain-Computer Interface for Tetraplegics
title_short EEG-Based Brain-Computer Interface for Tetraplegics
title_sort eeg-based brain-computer interface for tetraplegics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233767/
https://www.ncbi.nlm.nih.gov/pubmed/18288247
http://dx.doi.org/10.1155/2007/23864
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