Control Signal from EOG Analysis and Its Application

Authors: Myoung Ro Kim, Gilwon Yoon

Abstract:

A game using electro-oculography (EOG) as control signal was introduced in this study. Various EOG signals are generated by eye movements. Even though EOG is a quite complex type of signal, distinct and separable EOG signals could be classified from horizontal and vertical, left and right eye movements. Proper signal processing was incorporated since EOG signal has very small amplitude in the order of micro volts and contains noises influenced by external conditions. Locations of the electrodes were set to be above and below as well as left and right positions of the eyes. Four control signals of up, down, left and right were generated. A microcontroller processed signals in order to simulate a DDR game. A LCD display showed arrows falling down with four different head directions. This game may be used as eye exercise for visual concentration and acuity. Our proposed EOG control signal can be utilized in many other applications of human machine interfaces such as wheelchair, computer keyboard and home automation.

Keywords: DDR game, EOG, eye movement.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1088566

References:

[1] E. Ianez, A. Ubeda, and J. M. Azorin, "Multimodal human-machine interface based on a brain-computer interface and an electrooculography interface", in Proc. Engineering in Medicine and Biology Society, 2011 Annual International Conference of the IEEE , pp. 4572-4575.
[2] Chung-Hsien Kuo, Yi-Chang Chan, Hung-Chyun Chou, and Jia-Wun Siao, "Eyeglasses Based Electrooculography Human-wheelchair Interface", .in Proc. Int. Conf. Systems, Man and Cybernetics, 2009, Man and Cybernetics, San Antonio, Tx, pp. 4746-4751.
[3] H. Tamura, M. Miyashita, K. Tanno, Y. Fuse, “Mouse cursor control system using electrooculogram signals”, in 2010 Proc. World Automation Congress, pp.1-6.
[4] Rafael Barea, Luciano Boquete, Manuel Mazo, Elena Lopez, "System for Assisted Mobility Using Eye Movements Based on Electrooculography", IEEE Trans on Neural Systems and Rehabilitation Engineering, vol. 10, no. 4, pp. 209-218, Dec 2002.
[5] Su Jong Kim, Ho Sun Ryu, Young Chol Kim, "Development of Interface device with EOG Signal", The Korean Institute of Electrical Engineers, 37th Proceedings of the Korean Institute of Electrical Engineers, 2006.7, pp 1821-1823.
[6] Yonugmin Kim, Nakju Doh, Youngil Youm, and Wan Kyun Chung, "Development of Human-mobile Communication System using Electrooculogram Signals", in Proc. IEEE/RSJ International Conference on Intelligent Robotics and Systems, Maui, Hawaii, USA, 2001, pp 2160-2165.
[7] A. Bulling, J. A. Ward, H. Gellersen, and G. Troster, "Eye Movement Analysis for Activity Recognition Using Electrooculography", IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 33, no. 4, pp. 741-753, April 2011.
[8] T.C. Chieh, M. M. Marzuki, H. Aini, H. S. Farshad, M. B. Yeop, "Development of vehicle driver drowsiness detection system using electrooculogram (EOG)", in Proc. Int. Conf. Computer, Communications, & Signal Processing with Special Track on Biomedical Engineering 2005, pp. 165-168.
[9] Mingmin Yan, Hiroki Tamura, Koichi Tanno, "Gaze Estimation using Electrooculogram Signals and its Mathematical Modeling", in Proc. IEEE 43rd International Symposium on Multiple-Valued Logic (ISMVL) 2013, pp. 18-22.
[10] Park Gee-Ho, Choi Byung-Jin, Joo Dong-Hwan, "The Change of Visual Acuity through Eye Exercise for Elementary School Children", INHA UNIV. Sports Science Institute, Journal of Sports Sciences 14, 2002.12, pp 63-75.
[11] http://en.wikipedia.org/wiki/Dance_Dance_Revolution
[12] M Trikha, A Bhandari, T Gandhi, "Automatic Electrooculogram Classification for Microcontroller Based Interface Design", in Proc. IEEE Systems and Information Engineering Design Symposium (SIEDS) 2007, pp. 1 - 6.
[13] D. H. Lee, J. H. Yu ,D. H. Kim, "Extraction of gaze point on screen using EOG signal" ,Rehabilitation Engineering and Assistive Technology Society of Korea, Proceedings of RESKO , 11. 2011, pp 62-64.
[14] A. Bulling, J. A. Ward, H. Gellersen and G. Troster , "Eye Movement Analysis for Activity Recognition using Electrooculography", IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 33, no. 4, pp. 741-753, April 2011.