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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/28985
Title: Hybrid EEG-EOG brain-computer interface system for practical machine control
Authors: Yunyong Punsawad
Yodchanan Wongsawat
Manukid Parnichkun
Mahidol University
Asian Institute of Technology Thailand
Keywords: Computer Science;Engineering;Medicine
Issue Date: 1-Dec-2010
Citation: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. (2010), 1360-1363
Abstract: Practical issues such as accuracy with various subjects, number of sensors, and time for training are important problems of existing brain-computer interface (BCI) systems. In this paper, we propose a hybrid framework for the BCI system that can make machine control more practical. The electrooculogram (EOG) is employed to control the machine in the left and right directions while the electroencephalogram (EEG) is employed to control the forword, no action, and complete stop motions of the machine. By using only 2-channel biosignals, the average classification accuracy of more than 95% can be achieved. © 2010 IEEE.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78650835053&origin=inward
http://repository.li.mahidol.ac.th/dspace/handle/123456789/28985
Appears in Collections:Scopus 2006-2010

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