International Journal of Engineering Research in Electrical and Electronic Engineering (IJEREEE)

State Of Art :Design Of Robotic Architecture With Brain Mapped Wheelchair For Intelligent System Control

Author : Sagar Deshpande ¹ Nilesh Vernekar ² Sahana G Murnal ³ Smita S Puranik ⁴

Date of Publication :7th January 2016

Abstract: Independent mobility is core to being able to per-form activities of daily living by oneself. However, powered wheelchairs are not an option for a large number of people who are unable to use conventional interfaces, due to severe motor� disabilities. For some of these people, non�invasive brain� computer interfaces (BCIs) offer a promising solution to this interaction problem and in this article we present a shared control architecture that couples the intelligence and desires of the user with the precision of a powered wheelchair. We show how four healthy subjects are able to master control of the wheelchair using an asynchronous motor�imagery based BCI protocol and how this results in a higher overall task performance, compared with alternative synchronous P300�based approaches

Reference :

1. A. van Drongelen, B. Roszek, E. S. M. HilbersModderman,M. Kallewaard, and C. Wassenaar, ―Wheelchair incidents,‖ Rijksinstituut voor Volksgezondheid en Milieu RIVM, Bilthoven, NL, Tech. Rep.,November 2002, accessed Februaury,2010.
2. A. Frank, J. Ward, N. Orwell, C. McCullagh, and M. Belcher, ―Introduction of a new NHS electric-powered indoor/outdoor chair (EPIOC) service: benefits, risks and implications for prescribers,‖ Clinical Rehabilitation, no. 14, pp. 665–673, 2000.
3. R. C. Simpson, E. F. LoPresti, and R. A. Cooper, ―How many people would benefit from a smart wheelchair?‖ Journal of Rehabilitation Research and Development, vol. 45, no. 1, pp. 53–71, 2008.
4. T. Carlson and Y. Demiris, ―Collaborative control for a robotic wheelchair: Evaluation of performance, attention, and workload,‖ IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics,vol. 42, no. 3, pp. 876– 888, 2012.
5. B. Rebsamen, C. Guan, H. Zhang, C. Wang, C. Teo, M. Ang, and E. Burdet, ―A brain controlled wheelchair to navigate in familiar environments,‖ IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 18, no. 6, pp. 590–598, dec. 2010.
6. I. Iturrate, J. Antelis, A. K¨ubler, and J. Minguez, ―A noninvasive brainactuated wheelchair based on a P300 neurophysiological protocol and automated navigation,‖ IEEE Transactions on Robotics, vol. 25, no. 3,pp. 614–627, june 2009.