International Journal of Technology Enhancements and Emerging Engineering Research (ISSN 2347-4289)

IJTEEE >> Volume 3 - Issue 3, March 2015 Edition

International Journal of Technology Enhancements and Emerging Engineering Research  
International Journal of Technology Enhancements and Emerging Engineering Research

Website: http://www.ijteee.org

ISSN 2347-4289

Man-Machine Interaction Using Double Channel Electrooculogram (Eog) Signals

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Shrushti Dixit, Pankaj Rahise, Saurabh Pokale, Rasika Manapure



Keywords: Brain computer interface, Electrooculogram, Electrodes, Robotic Prototype Model



ABSTRACT: Electrooculography (EOG/E.O.G.) is a technique for measuring the corneo-retinal standing potential that exists between the front and the back of the human eye. To measure eye movement, pairs of electrodes are typically placed either above and below the eye or to the left and right of the eye. If the eye moves from center position toward one of the two electrodes, this electrode "sees" the positive side of the retina and the opposite electrode "sees" the negative side of the retina. Consequently, a potential difference occurs between the electrodes. Assuming that the resting potential is constant, the recorded potential is a measure of the eye's position. The bio-potential signal also is one of the examples of human–machine interface using of nonverbal information such as electrooculography (EOG), electromyography (EMG), and electroencephalography (EEG) signals. The EOG and EMG signals are physiological changes; but here we are focusing the mainly on EOG signals for the human–machine interface. This paper has investigated that different EOG signals obtained from four different places around eye; (right, left, up, and down) have led to different level of distance and rotation of wheelchair. Those four signals are correspond to different levels of right and left steer, forward and backward motion.



[1] Pravin Balbudhe, Prof.Mirza Moiz Baig “Noval Approach of man machine interaction using Brain Waves Electric Signals” IJRITCC june 2014

[2] Min Lin, Bin Li “A Wireless EOG-based Human Computer Interface.”IEEE 2010 3rd International Conference on Biomedical Engineering And Informatics

[3] W.Tangsuksant ,C.Aekmunkhongpaisal, P.Cambua, T.CharoenpongT.Chanwimalueang“Directional Eye Movement Detection System For Virtual Keyboard Controller.”IEEE 2012 Biomedical Enginering International Conference.

[4] Anwesha Banerjee, SumantraChakraborty, Pratyusha Das, ShounakDatta ,AmitKonar, D.N.Tribarewala ,R.Janarthanan“Single Channel Electrooculogram Based Interface For Mobility Aid.”IEEE 2012 Proceeding of 4th International Conference on Intelligent Human Computer Interaction, Kharagpur, India, Dec 27-29,2012.

[5] Dong Ming, Yuhan Zhu, Hongzhi Qi ,Baikun Wan “Study on EEG-Based Mouse System By Using Brain- Computer Interface “ IEEE 2009 International Conference on Virtual Environment, Human-Computer Interfaces And Measurements System, Hong Kong, China.

[6] Shang-Lin Wu , Lun-De Liao and Shao-Wei Lu “Controlling a Human–Computer Interface System With a Novel Classification Method that Uses Electrooculography Signals” IEEE].

[7] Divya Swami Nathan,A.P.Vinod and Kavitha P. Thomas “An Electrooculogram Based Assistive Communication System with Improved Speed and accuracy using Multi-Directional eye movement. ” IEEE 2012.

[8] SunaePark , Jong-ho Choi, Hyun-Kyo Jung “Evaluation Of Features For electrode location Robustness in Brain computer interface.”IEEE2012

[9] School Of Electrical Engineering and Electromechanics Seoul National University ,Korea.

[10] Xiaoxiang, Z., Xin, L., Jun, L, Weidong, C., Yaoyao, H., “ A portablewireless eye movement-controlled Human-Computer Interface for thedisabled,” IEEE, 2008.

[11] Lawrence Y.Deng, Chun-Liang Hsu, Tzu-Ching Lin, Jui-Sen Tuan, Yung-hui Chen “EOG Based Signal Detection And Verification For HCI .” Proceeding of Eighth International Conference on Machine Learning and Cybernetics,Baoding,12-15 July 2009.

[12] Chung-HsienKuo,Yi-Chan,Hung-ChyunChou,andJia-WunSiao “Eyeglasses Based Electrooculography Human-Wheelchair Interface.” Proceeding of the 2009IEEE International Conference on System ,Man,and Cybernetics San Antonio , TX,USA-oct-2009.

[13] FeboCincotti, Donatella Mattia, Fabio Aloise, SimonaBufalari ,GerwinSchalk “Non-invasive Brain-Computer Interface System: Towards Its Application As Assistive Technolgy” IEEE 2008 Brain Research Bulletin 75(2008).