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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...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2007
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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. |
format | Text |
id | pubmed-2233767 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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