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Recent Advances in Intelligent Engineering Systems pp 361–381Cite as

Computational Intelligence in Multi-channel EEG Signal Analysis

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 378))

Abstract

Computational intelligence and signal analysis of multi-channel data form an interdisciplinary research area based upon general digital signal processing methods and adaptive algorithms. The chapter is restricted to their use in biomedicine and particularly in electroencephalogram signal processing to find specific components of such multi-channel signals. Methods presented include signal de-noising, evaluation of their fundamental components and segmentation based upon feature detection in time-frequency and time-scale domains using both the discrete Fourier transform and the discrete wavelet transform. Resulting pattern vectors are then classified by self-organizing neural networks using a specific statistical criterion proposed to evaluate distances of individual feature vector values from corresponding cluster centers. Results achieved are compared for different data sets and selected mathematical methods to detect segments features. Proposed methods verified in the MATLAB environment using distributed data processing are accompanied by the appropriate graphical user interface that enables convenient and user friendly time-series processing.

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Author information

Authors and Affiliations

  1. Department of Computing and Control Engineering, Institute of Chemical Technology in Prague, Czech Republic

    Aleš Procházka, Martina Mudrová, Oldřich Vyšata & Lucie Gráfová

  2. Universidad de Las Palmas de G.C., Spain

    Carmen Paz Suárez Araujo

Authors
  1. Aleš Procházka
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  2. Martina Mudrová
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  3. Oldřich Vyšata
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  4. Lucie Gráfová
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  5. Carmen Paz Suárez Araujo
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Editor information

Editors and Affiliations

  1. Institute of Intelligent Engineering Systems, Óbuda University, Bécsi út 96/b, H-1034, Budapest, Hungary

    János Fodor

  2. Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, 27 Wybrzeze Wyspianskiego st., 50-372, Wrocław, Poland

    Ryszard Klempous

  3. Departamento de Informática y Sistemas, Universidad de Las Palmas de Gran Canaria, Instituto Universitario de Ciencias y Tecnologías Cibernéticas, Campus Universitario de Tafira s/n, 35017, Las Palmas de Gran, Canaria, Spain

    Carmen Paz Suárez Araujo

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Procházka, A., Mudrová, M., Vyšata, O., Gráfová, L., Araujo, C.P.S. (2012). Computational Intelligence in Multi-channel EEG Signal Analysis. In: Fodor, J., Klempous, R., Suárez Araujo, C.P. (eds) Recent Advances in Intelligent Engineering Systems. Studies in Computational Intelligence, vol 378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23229-9_17

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  • DOI: https://doi.org/10.1007/978-3-642-23229-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23228-2

  • Online ISBN: 978-3-642-23229-9

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