Abstract
Living creatures especially human, always aimed to commune every process or incident that take place within the environment, to lead an easy and luxurious life. Everyday a person has to execute certain basic tasks to control their body movements or particular parts of the body. Paralyzed people do not have control over some of their body parts. However, there are persons who are severely paralyzed and they cannot move themselves. They need some assistive technologies to fulfill their needs. A person with disabilities, mainly total paralysis is often unable to exploit the biological communication channels such as voice and action. One such condition was massive Brainstem Lesions, Stupor, Guillain-Baree Syndrome and Traumatic Brain Injury. In these conditions they cannot move their muscles, but they can able to control their eye movement, which leads to a condition called locked in state. In this state the person were unable to control all the motor neural activity which leads to other communication technique to convey their thoughts with others using eye movements. To solve this problem eye controlled interfaces are needed. Human Computer Interfaces help individuals with disabilities to communicate through a computer using a digital channel and make life more prosperous for the paralyzed patients and further enhance their quality of life with the support of bio-based HCI.
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References
Anwesha Banerjee: Electrooculogram based Control Drive for Wheelchair realized with Embedded Processors. M.E Thesis, Jadavpur University, Kolkata, (2012).
Tecce, James Gips, C. Peter Oliveri, Linen J. Pok, Michael R. Consiglio.: Eye Movement Control of Computer Functions. International Journal of Psychophysiology, 29, 319–325 (1998).
Yash Shaileshkumar Desai: Natural Eye Movement & its application for paralyzed patients. International Journal of Engineering Trends and Technology, 4, 679–686 (2013).
Karray, F., Alemzadeh, M., Saleh, J.A. and Arab, M.N.: Human-Computer Interaction: Overview on State of the Art. International Journal on Smart Sensing and Intelligent Systems, 1(1), (2008).
A. Dix, J. Finlay, G. Abowd, and R. Beale.: Human-computer interaction, 3rd, New York: Prentice Hall, (2003).
Chalmers P.: The role of cognitive theory in human–computer interface. In: Computers in Human Behavior, 19, 593–560 (2003).
Luis Cruz: Developing a Human-Computer-Interaction method with a low budget, (2011) In: http://www.ees.intelsath.com.
Nolan, Y.M.: Control and communication for physically disabled people, based on vestigial signals from the body. Ph.D., Thesis, National University of Ireland, Dublin, 7–18 (2005)
Jobin Jose: Development of EOG Based Human Machine Interface Control System for Motorized Wheelchair, M.E., Thesis, National Institute Of Technology Rourkela, India, (2013)
Ramkumar, S., Sathesh Kumar, K., Dhiliphan Rajkumar, T., Ilayaraja, M., Sankar, K.: A review-classification of electrooculogram based human computer interfaces, Biomedical Research, 29(6), 1078–1084 (2018).
Ramkumar, S., Hema, C.R.: Recogniti on Movement Electrooculogram Signals Using Neural Networks, KJCS, 6, 12–20 (2013).
Hema, C.R., Paulraj, M.P., Ramkumar, S.: Classification of Eye Movements Using Electrooculography and Neural Networks, International Journal of Human Computer Interaction, 5(4),51–63 (2014a).
Hema, C. R., Ramkumar, S., Paulraj, M. P.: Idendifying Eye Movements using Neural Networks for Human Computer Interaction, International Journal of Computer Applications, 105(8), 18–26, (2014b).
Ramkumar, S., SatheshKumar, K., Emayavaramban, G.: EOG Signal Classification Using Neural Network for Human Computer Interaction, International Journal of Computer Theory and Applications, 9(24),223–231 (2016).
Ramkumar, S., Satheshkumar, K., Emayavaramban, G.: Nine States HCI using Electrooculogram and Neural Networks, International Journal of Engineering and Technology, 8(6), 3056–3064 (2017).
Ramkumar, S., Satheshkumar, K., Emayavaramban, G.: A feasibility study on eye movements using electrooculogram based HCI, International Conference on Intelligent Sustainable Systems (ICISS), 380–383 (2017).
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We thank the Kalasalingam Academy of Research and Education for the motivation and encouragement for giving the opportunity to do this research work as successful one.
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Ramkumar, S., Muthu Kumar, M., Venkata Subramani, G., Karuppaiah, K.P., Anandharaj, C. (2020). A Mini Review on Electrooculogram Based Rehabilitation Methods Using Bioengineering Technique for Neural Disorder Persons. In: Smys, S., Iliyasu, A.M., Bestak, R., Shi, F. (eds) New Trends in Computational Vision and Bio-inspired Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-41862-5_93
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DOI: https://doi.org/10.1007/978-3-030-41862-5_93
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