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Computational Intelligence and Neuroscience
Volume 2016 (2016), Article ID 7354082, 10 pages
Research Article

EOG-sEMG Human Interface for Communication

1Department of Environmental Robotics, University of Miyazaki, Miyazaki 889-2192, Japan
2Organization for Promotion of “Center of Community” Program, University of Miyazaki, Miyazaki 889-2192, Japan
3Interdisciplinary Graduate School of Agriculture and Engineering, University of Miyazaki, Miyazaki 889-2192, Japan
4Department of Electrical and Systems Engineering, University of Miyazaki, Miyazaki 889-2192, Japan

Received 26 November 2015; Revised 26 April 2016; Accepted 17 May 2016

Academic Editor: Hasan Ayaz

Copyright © 2016 Hiroki Tamura 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.


The aim of this study is to present electrooculogram (EOG) and surface electromyogram (sEMG) signals that can be used as a human-computer interface. Establishing an efficient alternative channel for communication without overt speech and hand movements is important for increasing the quality of life for patients suffering from amyotrophic lateral sclerosis, muscular dystrophy, or other illnesses. In this paper, we propose an EOG-sEMG human-computer interface system for communication using both cross-channels and parallel lines channels on the face with the same electrodes. This system could record EOG and sEMG signals as “dual-modality” for pattern recognition simultaneously. Although as much as 4 patterns could be recognized, dealing with the state of the patients, we only choose two classes (left and right motion) of EOG and two classes (left blink and right blink) of sEMG which are easily to be realized for simulation and monitoring task. From the simulation results, our system achieved four-pattern classification with an accuracy of 95.1%.