Publication:
Hybrid EEG-EOG brain-computer interface system for practical machine control

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dc.contributor.authorYunyong Punsawaden_US
dc.contributor.authorYodchanan Wongsawaten_US
dc.contributor.authorManukid Parnichkunen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherAsian Institute of Technology Thailanden_US
dc.date.accessioned2018-09-24T08:56:32Z
dc.date.available2018-09-24T08:56:32Z
dc.date.issued2010-12-01en_US
dc.description.abstractPractical 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.en_US
dc.identifier.citation2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. (2010), 1360-1363en_US
dc.identifier.doi10.1109/IEMBS.2010.5626745en_US
dc.identifier.other2-s2.0-78650835053en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/28985
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78650835053&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.subjectMedicineen_US
dc.titleHybrid EEG-EOG brain-computer interface system for practical machine controlen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78650835053&origin=inwarden_US

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