EOG Controlled Motorized Wheelchair for Disabled Persons

Authors: A. Naga Rajesh, S. Chandralingam, T. Anjaneyulu, K. Satyanarayana

Abstract:

Assistive robotics are playing a vital role in advancing the quality of life for disable people. There exist wide range of systems that can control and guide autonomous mobile robots. The objective of the control system is to guide an autonomous mobile robot using the movement of eyes by means of EOG signal. The EOG signal is acquired using Ag/AgCl electrodes and this signal is processed by a microcontroller unit to calculate the eye gaze direction. Then according to the guidance control strategy, the control commands of the wheelchair are sent. The classification of different eye movements allows us to generate simple code for controlling the wheelchair. This work was aimed towards developing a usable and low-cost assistive robotic wheel chair system for disabled people. To live more independent life, the system can be used by the handicapped people especially those with only eye-motor coordination.

Keywords: Electrooculography, Microcontroller, Motors, Wheelchair.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1337385

References:

[1] Young L.R and Sheena D, "Eye-movement measurement techniques”, In Encyclopedia of Medical Devices and Instrumentation, ed. JG Webster, New York, 1988, PP: 1259-69.
[2] Keegan J, Burke E, Condron J and Coyle E, "Improving Electrooculogram-based Computer Mouse Systems: the Accelerometer Trigger”, Bioengineering In Ireland, January 28-29, 2011.
[3] Bulling A and Roggen D, "Recognition of Visual Memory Recall Processes Using Eye Movement Analysis”, UbiComp'11, Beijing, September 17-21, 2011.
[4] Barea R, Boquete L, Mazo M and López E, "Guidance of a wheelchair using electrooculography", Proceeding of the 3rd IMACS International Multiconference on Circuits, Systems, Communications and Computers (CSCC'99), 1999.
[5] Barea R , Boquete L, Ortega S, López E and Rodríguez-Ascariz J.M, "EOG-based eye movements codification for human computer interaction”, Expert Systems with Applications, Vol. No. 39, Elsevier, 2012, PP: 2677-2683.
[6] Tanaka K, Matsunaga K and Wang H, "Electroencephalogram-Based Control of an Electric Wheelchair”, IEEE Transactions On Robotics, Vol. No. 21, No. 4, 2005.
[7] Joseph J, James G, Peter Olivieri C, Linen P and Michael C, "Eye movement control of computer functions, "International Journal of Psychophysiology”, 1998, PP:319-325.
[8] Yathunanthan S, Chandrasena L. U. R, Umakanthan A, Vasuki V, and Munasinghe S. R, "Controlling a Wheelchair by Use of EOG Signal, Proceedings of IEEE ICIAFS, 2008, PP: 283-288, 2008.
[9] Kim-Tien N and Truong-Thinh N, "Using Electrooculogram and Electromyogram for powered wheelchair, Proceedings of the IEEE International Conference on Robotics and Biomimetics, Thailand, December 7-11, 2011.
[10] Andre´s U´ beda, Eduardo Ia´n˜ez, and Jose´ M. Azor´ın, "Wireless and Portable EOG-Based Interface for Assisting Disabled People”, IEEE/ASME Transactions On Mechatronics, Vol. No. 16, No. 5, October 2011.
[11] Lin M and Li B, "A Wireless EOG-based Human Computer Interface”, 3rd International Conference on Biomedical Engineering and Informatics (BMEI), 2010.
[12] Vehkaoja A, Verho J, Puurtinen M, Nöjd N, Lekkala J and Hyttinen J, "Wireless Head Cap for EOG and Facial EMG Measurements‖, Proceedings of the IEEE Engineering in Medicine and Biology 27th Annual Conference Shanghai, September 1-4, 2005.
[13] Jobby K. Chacko, Deepu Oommen, Kevin K. Mathew, Noble Sunny and Babu N, "Microcontroller Based EOG Guided Wheelchair”, International Journal of Medical, Pharmaceutical Science and Engineering, Vol. No. 7, No.11, 2013, pp. 63-66