Enhancement of Performance of an EEG-based Brain-Computer Interface by means of a Time-Frequency Approach

Author

Yamawaki, N. ; Wilke, C. ; Liu, Z.M. ; He, B.

Author_Institution

Dept. of Biomed. Eng., Minnesota Univ., Minneapolis, MN

fYear

2005

fDate

16-19 March 2005

Firstpage

94

Lastpage

96

Abstract

We have developed a novel time-frequency approach of classification of motor imagery (MI) tasks for brain-computer interface (BCI) applications. Through off-line data analysis on data collected during a "cursor control" experiment, we evaluated the capability of our proposed method in revealing the major features of the EEG control and enhancing MI classification accuracy. The pilot results in two human subjects are promising, with a mean accuracy rate of 87.9%, suggesting the feasibility of defining a new and more reliable EEG-based BCI

Keywords

electroencephalography; handicapped aids; medical signal processing; signal classification; time-frequency analysis; EEG-based brain-computer interface; cursor control; motor imagery tasks; off-line data analysis; time-frequency approach; Brain computer interfaces; Communication system control; Control systems; Data analysis; Electrodes; Electroencephalography; Humans; Laplace equations; Rhythm; Time frequency analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on

Conference_Location

Arlington, VA

Print_ISBN

0-7803-8710-4

Type

conf

DOI

10.1109/CNE.2005.1419561

Filename

1419561