Facial-Machine Interface-based Virtual Reality Wheelchair Control using EEG Artifacts of Emotiv Neuroheadset

This paper proposes a facial-machine interface system based on electroencephalogram (EEG) artifacts for mobility enhancement in people with paraplegia. We aim to employ the proposed system for cooperating with an EEG-based BCI system. Emotiv EPOC X neuroheadset used to acquire an EEG signal for verification of electrode positions and feature extraction algorithms. By using motion artifacts, two modalities of wheelchair control from only jaw movement and combing jaw and eye movements to online control a virtual reality wheelchair were proposed and evaluated the efficiency of the proposed control modalities. The results showed that combing eye and jaw movements can yield a high efficiency which can be used for a practical hybrid BCI system. We will further implement the proposed in a real power wheelchair.