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

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

doi:10.1109/TNSRE.2003.814453

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

Paul Sajda^*, Adam Gerson, Klaus Robert Müller, Benjamin Blankertz, Lucas Parra

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

125 Citations (Scopus)

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.

Original language	English
Pages (from-to)	184-185
Number of pages	2
Journal	IEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume	11
Issue number	2
DOIs	https://doi.org/10.1109/TNSRE.2003.814453
Publication status	Published - 2003 Jun
Externally published	Yes

Bibliographical note

Funding Information:
Manuscript received August 16, 2002; revised April 29, 2003. This work was supported by the Defense Advanced Research Projects Agency (DARPA). P. Sajda and A. Gerson are with the Department of Biomedical Engineering, Columbia University, New York, NY 10027 USA (e-mail:[email protected]; [email protected]). K.-R. Müller and B. Blankertz are with Fraunhofer FIRST, D-12489 Berlin, Germany (e-mail: [email protected], [email protected]). L. Parra is with Sarnoff Corporation, Princeton, NJ 08540 USA (e-mail: [email protected]). Digital Object Identifier 10.1109/TNSRE.2003.814453

Keywords

Brain computer interface (BCI)
Data analysis competition
Electroencephalography (EEG)
Machine learning

ASJC Scopus subject areas

Internal Medicine
General Neuroscience
Biomedical Engineering
Rehabilitation

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10.1109/TNSRE.2003.814453

Cite this

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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.",

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doi = "10.1109/TNSRE.2003.814453",

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

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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