Efficient Implementation and Design of a New Single-Channel Electrooculography-Based Human-Machine Interface System

Jiafei Wu, Andersen Man Shun Ang, Kai Man Tsui, H. C. Wu, Yeung Sam Hung, Yong Hu, Joseph N. F. Mak, Shing-Chow Chan, Z. G. Zhang

Abstract: This brief introduces a new and practical human-machine interface (HMI) system based on single-channel electrooculography (EOG) signals. The proposed system uses a consumer wireless recording device to collect EOG and employs new encoding/decoding paradigms to convey users' intentions with EOG from eye movements including blinking and looking up. The simplicity and mobility of the system provides a comfortable and practical solution to HMI. Furthermore, to reduce the hardware complexity and power consumption of the signal processing modules of the EOG-based HMI system, a novel multiplierless implementation is developed, where all the algorithms involved, such as bandpass filtering, wavelet filtering, and support vector machine, can be realized using a limited number of adders and shifters only. Experimental results show that the proposed system offers a simple, practical, and yet reliable EOG-based HMI with low complexity and power consumption.