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Epileptic Seizure Prediction Using Lyapunov Exponents and Support Vector Machine

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Adaptive and Natural Computing Algorithms (ICANNGA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4432))

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Abstract

The paper presents the method of predicting the epileptic seizure on the basis of EEG waveform analysis. The Support Vector Machine and the largest Lyapunov exponent characterization of EEG segments are employed to predict the incoming seizure. The results of numerical experiments will be presented and discussed.

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Authors and Affiliations

  1. Warsaw University of Technology, Warsaw, Poland, Koszykowa 75, 00-662 Warsaw, Poland

    Bartosz Świderski, Stanisław Osowski & Andrzej Cichocki

  2. Military University of Technology, Warsaw, Poland

    Stanisław Osowski

  3. Brain Science Institute, RIKEN, Japan

    Andrzej Cichocki

  4. Banach Hospital, Warsaw, Poland

    Andrzej Rysz

Authors
  1. Bartosz Świderski
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  2. Stanisław Osowski
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  3. Andrzej Cichocki
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  4. Andrzej Rysz
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Editor information

Bartlomiej Beliczynski Andrzej Dzielinski Marcin Iwanowski Bernardete Ribeiro

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© 2007 Springer Berlin Heidelberg

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Świderski, B., Osowski, S., Cichocki, A., Rysz, A. (2007). Epileptic Seizure Prediction Using Lyapunov Exponents and Support Vector Machine. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71629-7_42

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  • DOI: https://doi.org/10.1007/978-3-540-71629-7_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71590-0

  • Online ISBN: 978-3-540-71629-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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