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P300 Off-line Detection: A Fuzzy-based Support System

  • S. Giove
  • F. Piccione
  • F. Giorgi
  • F. Beverina
  • S. Silvoni
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 18)

Abstract

This article describes the implementation of a fuzzy logic based algorithm for the off-line detection of the so-called P300, an event-related potential signal (ERP) arising when a target stimulus is detected. The algorithm is based on a fuzzy-inferential engine which estimates some parameters on the averaged traces.

The resulting fuzzy inference system can analyse the averaged ERPs signals, and characterise, with some features, the most remarkable identified deflections. This characterisation can be used as a support for the physician diagnosis.

This activity may constitute the basis for the on-line P300 study, with the aim to implement a BCI device (Brain-Computer Interface), to be used as a man-machine interface and support.

Keywords

P300 Wave Fuzzy Inference System Local Extreme P300 Latency P300 Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • S. Giove
    • 1
  • F. Piccione
    • 2
  • F. Giorgi
    • 2
  • F. Beverina
    • 3
  • S. Silvoni
    • 3
  1. 1.Dept. of Applied MathematicsUniversity of Venice DorsoduroVeniceItaly
  2. 2.Dept. of Neuro-rehabilitationS. Camillo HospitalAlberoni, VeniceItaly
  3. 3.STMicroelectronics–AST GroupAgrate BrianzaItaly

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