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Complex Analysis of EEG Signal for Biometrical Classification Purposes

  • Jaromir SvejdaEmail author
  • Roman Zak
  • Roman Senkerik
  • Roman Jasek
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 289)

Abstract

Aim of this article is to clarify the potential utilization of complex EEG signal in modern information age. Brain Computer Interface (BCI) represents the connection of brain waves with output device through some interface.

It was investigated whether the correlation analysis of the EEG signal may be used for finding appropriate classification parameters. EEG signal was measured in the idle state of mind of 3 subjects. Complex correlation analysis was performed for 16 samples of each obtained signal history. Moreover, the position of maximal correlation was also recorded.

Keywords

Maximal Correlation Probabilistic Neural Network Idle State Brain Computer Interface Classification Parameter 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Jaromir Svejda
    • 1
    Email author
  • Roman Zak
    • 1
  • Roman Senkerik
    • 1
  • Roman Jasek
    • 1
  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlinCzech Republic

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