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Computational Intelligence and Neuroscience
Volume 2010 (2010), Article ID 135629, 5 pages
http://dx.doi.org/10.1155/2010/135629
Research Article

On the Use of Electrooculogram for Efficient Human Computer Interfaces

1IRCCS Fondazione Santa Lucia, Via Ardeatina, 306, 00179, Rome, Italy
2Department of Technical Sciences, The NCO Academy, 10100 Balikesir, Turkey

Received 13 June 2009; Accepted 28 July 2009

Academic Editor: Fabrizio De Vico Fallani

Copyright © 2010 A. B. Usakli et al. 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.

Abstract

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.