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