title: Hybrid EEG-EOG brain-computer interface system for practical machine control.
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.
authors.affiliation: Department of Biomedical Engineering, Mahidol University, 25/25 Putttamonthon 4, Salaya, Nakornpathom 73170 Thailand. tietle@hotmail.com
authors.forename: Yunyong
authors.initials: Y
authors.lastname: Punsawad
authors.forename: Yodchanan
authors.initials: Y
authors.lastname: Wongsawat
authors.forename: Manukid
authors.initials: M
authors.lastname: Parnichkun
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D004585:Electrooculography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D006801:Humans; D008328:Man-Machine Systems; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface