On the Use of Electrooculogram for Efficient Human Computer Interfaces
Joint Authors
Gurkan, S.
Babiloni, Fabio
Aloise, Fabio
Usakli, Ali Bulent
Vecchiato, Giovanni
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-10-15
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Usakli, Ali Bulent& Gurkan, S.& Aloise, Fabio& Vecchiato, Giovanni& Babiloni, Fabio. 2009. On the Use of Electrooculogram for Efficient Human Computer Interfaces. Computational Intelligence and Neuroscience،Vol. 2010, no. 2010, pp.1-5.
https://search.emarefa.net/detail/BIM-448492
Modern Language Association (MLA)
Usakli, Ali Bulent…[et al.]. On the Use of Electrooculogram for Efficient Human Computer Interfaces. Computational Intelligence and Neuroscience No. 2010 (2010), pp.1-5.
https://search.emarefa.net/detail/BIM-448492
American Medical Association (AMA)
Usakli, Ali Bulent& Gurkan, S.& Aloise, Fabio& Vecchiato, Giovanni& Babiloni, Fabio. On the Use of Electrooculogram for Efficient Human Computer Interfaces. Computational Intelligence and Neuroscience. 2009. Vol. 2010, no. 2010, pp.1-5.
https://search.emarefa.net/detail/BIM-448492
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-448492