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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

SIGNAL (programming language)Computer scienceArtificial intelligenceComputer visionEye movementInterference (communication)CorrectnessElectrooculographySensor fusionIdentification (biology)

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