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On the Use of Electrooculogram for Efficient Human Computer Interfaces

The aim of this study is to present electrooculogram signals that can be used for human computer interface efficiently. Establishing an efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amy...

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Detalles Bibliográficos
Autores principales: Usakli, A. B., Gurkan, S., Aloise, F., Vecchiato, G., Babiloni, F.
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2763213/
https://www.ncbi.nlm.nih.gov/pubmed/19841687
http://dx.doi.org/10.1155/2010/135629
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author Usakli, A. B.
Gurkan, S.
Aloise, F.
Vecchiato, G.
Babiloni, F.
author_facet Usakli, A. B.
Gurkan, S.
Aloise, F.
Vecchiato, G.
Babiloni, F.
author_sort Usakli, A. B.
collection PubMed
description The aim of this study is to present electrooculogram signals that can be used for human computer interface efficiently. Establishing an efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amyotrophic Lateral Sclerosis or other illnesses that prevent correct limb and facial muscular responses. We have made several experiments to compare the P300-based BCI speller and EOG-based new system. A five-letter word can be written on average in 25 seconds and in 105 seconds with the EEG-based device. Giving message such as “clean-up” could be performed in 3 seconds with the new system. The new system is more efficient than P300-based BCI system in terms of accuracy, speed, applicability, and cost efficiency. Using EOG signals, it is possible to improve the communication abilities of those patients who can move their eyes.
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spelling pubmed-27632132009-10-19 On the Use of Electrooculogram for Efficient Human Computer Interfaces Usakli, A. B. Gurkan, S. Aloise, F. Vecchiato, G. Babiloni, F. Comput Intell Neurosci Research Article The aim of this study is to present electrooculogram signals that can be used for human computer interface efficiently. Establishing an efficient alternative channel for communication without overt speech and hand movements is important to increase the quality of life for patients suffering from Amyotrophic Lateral Sclerosis or other illnesses that prevent correct limb and facial muscular responses. We have made several experiments to compare the P300-based BCI speller and EOG-based new system. A five-letter word can be written on average in 25 seconds and in 105 seconds with the EEG-based device. Giving message such as “clean-up” could be performed in 3 seconds with the new system. The new system is more efficient than P300-based BCI system in terms of accuracy, speed, applicability, and cost efficiency. Using EOG signals, it is possible to improve the communication abilities of those patients who can move their eyes. Hindawi Publishing Corporation 2010 2009-10-15 /pmc/articles/PMC2763213/ /pubmed/19841687 http://dx.doi.org/10.1155/2010/135629 Text en Copyright © 2010 A. B. Usakli 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
Usakli, A. B.
Gurkan, S.
Aloise, F.
Vecchiato, G.
Babiloni, F.
On the Use of Electrooculogram for Efficient Human Computer Interfaces
title On the Use of Electrooculogram for Efficient Human Computer Interfaces
title_full On the Use of Electrooculogram for Efficient Human Computer Interfaces
title_fullStr On the Use of Electrooculogram for Efficient Human Computer Interfaces
title_full_unstemmed On the Use of Electrooculogram for Efficient Human Computer Interfaces
title_short On the Use of Electrooculogram for Efficient Human Computer Interfaces
title_sort on the use of electrooculogram for efficient human computer interfaces
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2763213/
https://www.ncbi.nlm.nih.gov/pubmed/19841687
http://dx.doi.org/10.1155/2010/135629
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