A New Directional Intention Identification Approach for Intelligent Wheelchair Based on Fusion of EOG Signal and Eye Movement Signal
Tongbo Li, Junyou Yang, Dianchun Bai, Yina Wang
- Year
- 2018
- Citations
- 7
Abstract
The use of electro-oculogram(EOG) signal to control robots is becoming more and more popular. However, the electro-oculogram signal is a relatively weak bioelectricity signal which is easily disturbed by the external environment, and the accuracy of the electro-oculogram signal is poor and the recognition rate is low because of the interference of the invalid electro-oculogram signal. The high recognition rate of eye movement signal makes up for the low recognition rate of eye signals. In this paper, a method of combining electro-oculogram signal and eye movement signal is proposed. According to the tracking of eye movement track, the invalid electro-oculogram signal can be removed. The accuracy of electro-oculogram signal is improved and the accuracy of classification recognition is improved. Finally, the correctness of the view is proved by experiments.
Keywords
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