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Fast Multi-command SSVEP Brain Machine Interface without Training

  • Pablo Martinez Vasquez
  • Hovagim Bakardjian
  • Montserrat Vallverdu
  • Andrezj Cichocki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5164)

Abstract

We propose a new multi-stage procedure for a real time brain machine/computer interface (BMI) based on the Steady State Visual Evoked Potentials (SSVEP) paradigm elicited by means of flickering checkerboards. The developed system work in asynchronous mode and it does not require training phase and its able to detect fast multiple independent visual commands. Up to 8 independent commands, were tested at the presented work and the proposed BMI system could be extended to more independent commands easily. The system has been extensively experimented with 4 young healthy subjects, confirming the high performance of the proposed procedure and its robustness in respect to artifacts.

Keywords

Singular Value Decomposition Blind Source Separation Recursive Least Square Asynchronous Mode Recursive Least Square Algorithm 
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 2008

Authors and Affiliations

  • Pablo Martinez Vasquez
    • 1
  • Hovagim Bakardjian
    • 1
  • Montserrat Vallverdu
    • 2
  • Andrezj Cichocki
    • 1
  1. 1.Laboratory for Advanced Brain Signal ProcessingRIKEN Brain Science InstituteWako-shi SaitamaJapan
  2. 2.Universidad Politécnica de CataluñaBarcelonaSpain

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