A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces

Author

Sajda, Paul ; Gerson, Adam ; Müller, Klaus-Robert ; Blankertz, Benjamin ; Parra, Lucas

Author_Institution

Dept. of Biomed. Eng., Columbia Univ., New York, NY, USA

Volume

11

Issue

2

fYear

2003

fDate

6/1/2003 12:00:00 AM

Firstpage

184

Lastpage

185

Abstract

We present three datasets that were used to conduct an open competition for evaluating the performance of various machine-learning algorithms used in brain-computer interfaces. The datasets were collected for tasks that included: 1) detecting explicit left/right (L/R) button press; 2) predicting imagined L/R button press; and 3) vertical cursor control. A total of ten entries were submitted to the competition, with winning results reported for two of the three datasets.

Keywords

electroencephalography; handicapped aids; medical signal processing; brain-computer interfaces; data analysis competition; explicit left/right button press detection; imagined button press; machine learning algorithms evaluation; machine-learning algorithms; vertical cursor control; Algorithm design and analysis; Brain computer interfaces; Computer interfaces; Data analysis; Electroencephalography; Fingers; Machine learning; Machine learning algorithms; Measurement; Testing; Algorithms; Artificial Intelligence; Brain; Databases, Factual; Electroencephalography; Evoked Potentials, Visual; Feedback; Fingers; Humans; Movement; Patient Compliance; Photic Stimulation; Thinking;

fLanguage

English

Journal_Title

Neural Systems and Rehabilitation Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1534-4320

Type

jour

DOI

10.1109/TNSRE.2003.814453

Filename

1214716