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Multi-Functional System for Persons with Disabilities Using Electroencephalography Signals of Eye Blink


Affiliations
1 CSIR-Central Scientific Instruments Organization, Chandigarh 160 030, India
 

Here we report a system which can be operated using electroencephalography (EEG) signals generated during eye blink and thus may be useful for persons with locomotive and other disabilities for performing their day-to-day activities. EEG signals are processed by a microcontroller and based on programming, the microcontroller takes a decision to perform the desired task by actuating a corresponding device from several devices connected to the system. An important feature of the system is that it can be adapted to particular needs of the user and can be attached/detached for actuation of different appliances according to the user’s condition and requirements.

Keywords

Human–Machine Interface, Electroencephalography Signals, Eye Blinks, Persons with Disabilities.
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  • Ministry of Social Justice and Empowerment, Government of India; http://www.socialjustice.nic.in/adipmain.php (accessed on 25 April 2014).

  • Department of Social Services. Government of Australia; http://www.dss.gov.au/our-responsibilities/disability-and-carers/program-services/for-people-with-disability/better-start-forchildren-with-disability-initiative (accessed on 25 April 2014).

  • Department of Health and Community Services; http://www.health.gov.nl.ca/health/personsdisabilities/fundingprograms_hcs.html#sap (accessed on 25 April 2014).

  • Junker, A., Brain–body actuated system. US patent US005474082A, 12 December 1995.

  • Chowdary, P. A. R., Sarma, N. S. M., Sekhar, K. R. and Raj, V. D., An interface of human and machine with eye blinking. Int. J. Res. Comput. Commun. Technol., 2012, 1, 429–433.

  • Wang, Y., Gao, X., Hong, B. and Gao, S., Practical designs of brain–computer interfaces based on the modulation of EEG rhythms. In Computer Interfaces (eds Graimann, B. and Pfurtscheller, G.), Springer, Berlin, Heidelberg, 2010, pp. 137–154.

  • Wolpaw, J. and Wolpaw, E. W., Brain-Computer Interfaces: Principles and Practice, Oxford University Press, New York, 2012.

  • Chuang, C. H., Ko, L. W., Lin, Y. P., Jung, T. P. and Lin, C. T., Independent component ensemble of EEG for brain–computer interface. IEEE Trans. Neural Syst. Rehabil. Eng., 2014, 22, 230–238.

  • Hippe, Z. S. and Kulikowski, J. L., Human–computer Systems Interaction: Backgrounds and Applications, Springer-Verlag, Berlin, Heidelberg, 2009.

  • Manihar, S. R., Tiwari, N. and Rajpurohit, J., Goggle mouse controlled for handicapped and paralyzed people. IOSR J. Electr. Electron. Eng., 2012, 1, 25–28.

  • Kurylyak, Y., Lamonaca, F. and Mirabelli, G., Detection of the eye blinks for human’s fatigue monitoring. In IEEE Proceedings of Medical Measurements and Applications, Budapest, Hungary, 18–19 May 2012, pp. 1–4.

  • Rani, M. S. and Mansor, W., Detection of eye blinks from EEG signals for home lighting system activation. In Proceedings of the International Symposium on Mechatronics and its Applications, ISMA09, Sharjah, United Arab Emirates, 23–26 March 2009, ISMA091-4.

  • Arai, K. and Mardiyanto, R., Eyes based electric wheel chair control system. IJACSA, 2011, 2, 98–106.

  • Barea, R., Boquete, L., Mazo, M. and Lopez, E., System for assisted mobility using eye movements based on electrooculography. IEEE Trans. Neural Syst. Rehabil. Eng., 2002, 10, 209–218.

  • Gupta, S. S., Soman, S., Raj, P. G., Prakash, R., Sailaja, S. and Borgohain, R., Detecting eye movements in EEG for controlling devices. In IEEE International Conference on Computational Intelligence and Cybernetics, Bali, Indonesia, 12–14 July 2012, pp. 69–73.

  • McMullen, D. et al., Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic. IEEE Trans. Neural. Syst. Rehabil. Eng., 2013, 22, 1–12.

  • Ji, Z., Sugi, T., Goto, S., Wang, X. and Nakamura, M., Multi-channel template extraction for automatic EEG spike detection. In IEEE International Conference on Complex Medical Engineering, Harbin Heilongjiang, China, 22–25 May 2011, pp. 179–184.

  • Manoilov, P., EEG eye-blinking artifacts power spectrum analysis. In Proceedings of the International Conference on Computer Systems and Technologies, University of Veliko Tarnovo, Bulgaria, 15–16 June 2006, IIIA.3-1-5.

  • Rangayyan, R. M., Biomedical Signal Analysis, John Wiley & Sons, 2002.

  • Nunez, P. L. and Srinivasan, R., Electric Fields of the Brain: The Neurophysics of EEG, Oxford University Press, New York, 2006.

  • Garrett, D., Peterson, D. A., Anderson, C. W. and Thaut, M. H., Comparison of linear, nonlinear, and feature selection methods for EEG signal classification. IEEE Trans. Neural Syst. Rehabil. Eng., 2003, 11, 141–144.


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  • Multi-Functional System for Persons with Disabilities Using Electroencephalography Signals of Eye Blink

Abstract Views: 354  |  PDF Views: 128

Authors

Subhra Sankha Sarma
CSIR-Central Scientific Instruments Organization, Chandigarh 160 030, India
Piyush Kant
CSIR-Central Scientific Instruments Organization, Chandigarh 160 030, India
Rajkumar
CSIR-Central Scientific Instruments Organization, Chandigarh 160 030, India

Abstract


Here we report a system which can be operated using electroencephalography (EEG) signals generated during eye blink and thus may be useful for persons with locomotive and other disabilities for performing their day-to-day activities. EEG signals are processed by a microcontroller and based on programming, the microcontroller takes a decision to perform the desired task by actuating a corresponding device from several devices connected to the system. An important feature of the system is that it can be adapted to particular needs of the user and can be attached/detached for actuation of different appliances according to the user’s condition and requirements.

Keywords


Human–Machine Interface, Electroencephalography Signals, Eye Blinks, Persons with Disabilities.

References





DOI: https://doi.org/10.18520/cs%2Fv114%2Fi01%2F193-195