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

Paul Sajda, Adam Gerson, Klaus Muller, Benjamin Blankertz, Lucas Parra

Research output: Contribution to journalArticle

79 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 1
Externally publishedYes

Fingerprint

Brain-Computer Interfaces
Brain computer interface
Learning algorithms
Learning systems
Datasets
Machine Learning

Keywords

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

ASJC Scopus subject areas

  • Biophysics
  • Bioengineering
  • Rehabilitation
  • Health Professions(all)

Cite this

A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces. / Sajda, Paul; Gerson, Adam; Muller, Klaus; Blankertz, Benjamin; Parra, Lucas.

In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 11, No. 2, 01.06.2003, p. 184-185.

Research output: Contribution to journalArticle

Sajda, Paul ; Gerson, Adam ; Muller, Klaus ; Blankertz, Benjamin ; Parra, Lucas. / A data analysis competition to evaluate machine learning algorithms for use in brain-computer interfaces. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2003 ; Vol. 11, No. 2. pp. 184-185.
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