The BCI competition 2003: Progress and perspectives in detection and discrimination of EEG single trials

Benjamin Blankertz, Klaus Robert Müller, Gabriel Curio, Theresa M. Vaughan, Gerwin Schalk, Jonathan R. Wolpaw, Alois Schlögl, Christa Neuper, Gert Pfurtscheller, Thilo Hinterberger, Michael Schröder, Niels Birbaumer

Research output: Contribution to journalReview articlepeer-review

555 Citations (Scopus)


Interest in developing a new method of man-to-machine communication-a brain-computer interface (BCI)-has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms.

Original languageEnglish
Pages (from-to)1044-1051
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Issue number6
Publication statusPublished - 2004 Jun


  • Augmentative communication
  • Beta rhythm
  • Brain-computer interface (BCI)
  • EEG
  • Event-related potentials (ERPs)
  • Imagined hand movements
  • Lateralized readiness potential
  • Mu rhythm
  • P300
  • Rehabilitation
  • Single-trial classification
  • Slow cortical potentials

ASJC Scopus subject areas

  • Biomedical Engineering


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