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

Yunyong Punsawad; Yodchanan Wongsawat; Manukid Parnichkun

doi:10.1109/IEMBS.2010.5626745

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

Annu Int Conf IEEE Eng Med Biol Soc. 2010:2010:1360-3. doi: 10.1109/IEMBS.2010.5626745.

Authors

Yunyong Punsawad¹, Yodchanan Wongsawat, Manukid Parnichkun

Affiliation

¹ Department of Biomedical Engineering, Mahidol University, 25/25 Putttamonthon 4, Salaya, Nakornpathom 73170 Thailand. tietle@hotmail.com

PMID: 21096331
DOI: 10.1109/IEMBS.2010.5626745

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Brain / physiology*
Electroencephalography / methods*
Electrooculography / methods*
Evoked Potentials, Motor / physiology*
Humans
Man-Machine Systems*
Signal Processing, Computer-Assisted*
User-Computer Interface*