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. Copyright © 2010 A. B. Usakli et al.
Usakli, A. B., Gurkan, S., Aloise, F., Vecchiato, G., & Babiloni, F. (2010). On the use of electrooculogram for efficient human computer interfaces. Computational Intelligence and Neuroscience, 2010. https://doi.org/10.1155/2010/135629