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

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    114 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 languageEnglish
    Pages (from-to)184-185
    Number of pages2
    JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
    Volume11
    Issue number2
    DOIs
    Publication statusPublished - 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:[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

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