DocumentCode :
747934
Title :
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
Link To Document :
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