P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface

  • Nikolay Chumerin
  • Nikolay V. Manyakov
  • Adrien Combaz
  • Johan A. K. Suykens
  • Refet Firat Yazicioglu
  • Tom Torfs
  • Patrick Merken
  • Herc P. Neves
  • Chris Van Hoof
  • Marc M. Van Hulle
Conference paper

DOI: 10.1007/978-3-642-04617-9_43

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5803)
Cite this paper as:
Chumerin N. et al. (2009) P300 Detection Based on Feature Extraction in On-line Brain-Computer Interface. In: Mertsching B., Hund M., Aziz Z. (eds) KI 2009: Advances in Artificial Intelligence. KI 2009. Lecture Notes in Computer Science, vol 5803. Springer, Berlin, Heidelberg

Abstract

We propose a new EEG-based wireless brain computer interface (BCI) with which subjects can “mind-type” text on a computer screen. The application is based on detecting P300 event-related potentials in EEG signals recorded on the scalp of the subject. The BCI uses a simple classifier which relies on a linear feature extraction approach. The accuracy of the presented system is comparable to the state-of-the-art for on-line P300 detection, but with the additional benefit that its much simpler design supports a power-efficient on-chip implementation.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Nikolay Chumerin
    • 1
  • Nikolay V. Manyakov
    • 1
  • Adrien Combaz
    • 1
  • Johan A. K. Suykens
    • 2
  • Refet Firat Yazicioglu
    • 3
  • Tom Torfs
    • 3
  • Patrick Merken
    • 3
  • Herc P. Neves
    • 3
  • Chris Van Hoof
    • 3
  • Marc M. Van Hulle
    • 3
  1. 1.Laboratorium voor Neuro- en PsychofysiologieK.U. LeuvenLeuvenBelgium
  2. 2.ESAT-SCDK.U. LeuvenHeverleeBelgium
  3. 3.IMECLeuvenBelgium

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