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

Author

Punsawad, Yunyong ; Wongsawat, Yodchanan ; Parnichkun, Manukid

Author_Institution

Dept. of Biomed. Eng., Mahidol Univ., Salaya, Thailand

fYear

2010

fDate

Aug. 31 2010-Sept. 4 2010

Firstpage

1360

Lastpage

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.

Keywords

brain-computer interfaces; electro-oculography; electroencephalography; handicapped aids; medical control systems; medical signal processing; signal classification; 2-channel biosignals; BCI; EEG; EOG; classification accuracy; electroencephalogram; electrooculogram; hybrid brain-computer interface system; practical machine control; Accuracy; Brain computer interfaces; Classification algorithms; Electrodes; Electroencephalography; Electrooculography; Graphical user interfaces; Algorithms; Brain; Electroencephalography; Electrooculography; Evoked Potentials, Motor; Humans; Man-Machine Systems; Signal Processing, Computer-Assisted; User-Computer Interface;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Conference_Location

Buenos Aires

ISSN

1557-170X

Print_ISBN

978-1-4244-4123-5

Type

conf

DOI

10.1109/IEMBS.2010.5626745

Filename

5626745