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 journalArticlepeer-review

96 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

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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