Commenced in January 2007
Paper Count: 31225
Eyeball Motion Controlled Wheelchair Using IR Sensors
Abstract:This paper presents the ‘Eye Ball Motion Controlled Wheelchair using IR Sensors’ for the elderly and differently abled people. In this eye tracking based technology, three Proximity Infrared (IR) sensor modules are mounted on an eye frame to trace the movement of the iris. Since, IR sensors detect only white objects; a unique sequence of digital bits is generated corresponding to each eye movement. These signals are then processed via a micro controller IC (PIC18F452) to control the motors of the wheelchair. The potential and efficiency of previously developed rehabilitation systems that use head motion, chin control, sip-n-puff control, voice recognition, and EEG signals variedly have also been explored in detail. They were found to be inconvenient as they served either limited usability or non-affordability. After multiple regression analyses, the proposed design was developed as a cost-effective, flexible and stream-lined alternative for people who have trouble adopting conventional assistive technologies.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107563Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6114
 www.prsindia.org/billtrack/the-right-of-persons-with-disabilities-bill- 2014-3122/
 R. A. Cooper, M. L. Boninger, A. Kwarciak, and B. Ammer, Engineering in Medicine and Biology, 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint (Volume: 3)/23-26 Oct. 2002.
 R. Berjoøøn, M. Mateos, A. L. Barriuso, I. Muriel and G. Villarrubia, "Alternative human-machine interface system for powered wheelchairs", IEEE 1st International Conference on Digital Object Identifier, Serious Games and Applications for Health (SeGAH), 2011.
 Monika Jain and Hitesh Joshi, Tongue Operated Wheelchair for Physically Disabled People, International Journal of Latest Trends in Engineering and Technology (IJLTET).
 Rafael Barea, Luciano Boquete, Manuel Mazo and Elena López, System for Assisted Mobility Using Eye Movements based on Electrooculography, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 10, no. 4, December 2002.
 S. H. Fairclough and K. Gilleade (eds.), Advances in Physiological Computing, 39 Human–Computer Interaction Series, DOI: 10.1007/978- 1-4471-6392-3_3, Ó Springer-Verlag, London, 2014.
 Jobby K. Chacko, Deepu Oommen, Kevin K. Mathew, Noble Sunny and N. Babu, Microcontroller Based EOG Guided Wheelchair, World Academy of Science, Engineering and Technology (WASET) International Journal of Medical, Health, Biomedical and Pharmaceutical Engineering, Vol. 7, No. 11, 2013.
 Hansen DW and Ji Q, In the eye of the beholder: a survey of models for eyes and gaze, IEEE Trans Pattern Anal Mach Intell 32(3):478–500, 2009.
 Ding Q, Tong K and Li G, Development of an EOG (ElectroOculography) based human-computer interface, In Proceedings of the 27th Annual International Conference of the Engineering in Medicine and Biology Society, pp 6829–6831, EMBS, 2005.
 Kohei Arai and Ronny Mardiyanto, Eyes Based Eletric Wheel Chair Control System, International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 2, No. 12, 2011.
 Poonam S. Gajwani & Sharda A. Chhabria, Eye Motion Tracking for Wheelchair Control, International Journal of Information Technology and Knowledge Management, Volume 2, No. 2, pp. 185-187, July- December 2010.
 M. Reitbauer, Keep an Eye on Information Processing: Eye Tracking Evidence for the Influence of Hypertext Structures on Navigational Behaviour and Textual Complexity, LSP and Professional Communication, Vol. 8, No. 2 (16), Winter 2008.
 DW Hansen and P Majaranta, Basics of camera-based gaze tracking, In: Majaranta P et al (eds) Gaze interaction and applications of eye tracking: advances in assistive technologies, Medical Information Science Reference, Hershey, pp 21–26, 2012.
 J.Millanetal, “Noninvasive brain-actuated control of a mobile robot by human EEG,” IEEE Trans. Biomed. Eng., vol. 51, no. 6, pp. 1026–1033, June 2004.
 Kazuo Tanaka, Kazuyuki Matsunaga, and Hua O. Wang, Electroencephalogram-Based Control of an Electric Wheelchair, IEEE Transactions on Robotics, Vol. 21, no. 4, August 2005.
 Gunda Gautam, Gunda Sumanth, Karthikeyan K C, Shyam Sundar and D. Venkataraman Eye, Movement Based Electronic Wheel Chair for Physically Challenged Persons, International Journal of Scientific & Technology Research, volume 3, issue 2, February 2014.