Pattern Recognition in EEG Cognitive Signals Accelerated by GPU

  • Pavel Dohnálek
  • Petr Gajdoš
  • Tomáš Peterek
  • Marek Penhaker
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 189)

Abstract

Analysing of Electroencephalography (EEG) cognitive signals becomes more popular today due to availability of essential hardware (EEG headsets) and sufficient computation power of common computers. Fast and precise pattern matching of acquired signals represents one of the most important challenges. In this article, a method for signal pattern matching based on Non-negative Matrix Factorization is proposed. We also utilize short-time Fourier transform to preprocess EEG data and Cosine Similarity Measure to perform query-based classification. The recognition algorithm shows promising results in execution speed and is suitable for implementation on graphics processors to achieve real-time processing, making the proposed method suitable for real-world, real-time applications. In terms of recognition accuracy, our experiments show that accuracy greatly depends on the choice of input parameters.

Keywords

Electroencephalography cognitive signal pattern matching graphics processors matrix factorization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Pavel Dohnálek
    • 1
  • Petr Gajdoš
    • 1
  • Tomáš Peterek
    • 1
  • Marek Penhaker
    • 1
  1. 1.Department of Computer Science and Department of Measurement and Control, FEIVSB - Technical University of OstravaOstravaCzech Republic

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