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Stochastic processes of demarkovization and markovization in chaotic signals of human brain electric activity from EEGs during epilepsys

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Abstract

We study the stochastic processes of markovization and demarkovization in chaotic signals of human electroencephalograms (EEGs) during epilepsy using various measures of demarkovization and markovization, namely, the statistical spectrum of a non-Markovity parameter, power spectra of the time correlation function and memory functions of junior orders, and local relaxation and kinetic parameters. The results demonstrate the superiority of the new measures in comparison to the traditional nonlinear measures. We conclude that the applied measures are more appropriate for the quantification of markovization and demarkovization in EEG data and the prediction of epilepsy seizure.

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Authors and Affiliations

  1. Kazan State Pedagogical University, Kazan, 420021, Russia

    R. M. Yulmetyev & F. M. Gafarov

  2. University of Augsburg, D-86135, Augsburg, Germany

    P. Hänggi

Authors
  1. R. M. Yulmetyev
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  2. P. Hänggi
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  3. F. M. Gafarov
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Additional information

From Zhurnal Éksperimental’no\(\overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\smile}$}}{l}\) i Teoretichesko\(\overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\smile}$}}{l}\) Fiziki, Vol. 123, No. 3, 2003, pp. 643–652.

Original English Text Copyright © 2003 by Yulmetyev, Hänggi, Gafarov.

This article was submitted by the authors in English.

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Yulmetyev, R.M., Hänggi, P. & Gafarov, F.M. Stochastic processes of demarkovization and markovization in chaotic signals of human brain electric activity from EEGs during epilepsys. J. Exp. Theor. Phys. 96, 572–580 (2003). https://doi.org/10.1134/1.1567432

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  • DOI: https://doi.org/10.1134/1.1567432

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