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

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

105 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

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:sajda@columbia.edu; adg71@columbia.edu). K.-R. Müller and B. Blankertz are with Fraunhofer FIRST, D-12489 Berlin, Germany (e-mail: klaus@first.fraunhofer.de, blanker@first.fraunhofer.de). L. Parra is with Sarnoff Corporation, Princeton, NJ 08540 USA (e-mail: lparra@sarnoff.com). 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
Neuroscience(all)
Biomedical Engineering

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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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author = "Paul Sajda and Adam Gerson and M{\"u}ller, {Klaus Robert} and Benjamin Blankertz and Lucas Parra",

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:sajda@columbia.edu; adg71@columbia.edu). K.-R. M{\"u}ller and B. Blankertz are with Fraunhofer FIRST, D-12489 Berlin, Germany (e-mail: klaus@first.fraunhofer.de, blanker@first.fraunhofer.de). L. Parra is with Sarnoff Corporation, Princeton, NJ 08540 USA (e-mail: lparra@sarnoff.com). Digital Object Identifier 10.1109/TNSRE.2003.814453",

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AU - Parra, Lucas

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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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