RECONSTRUCTION OF AN EVOLUTION OPERATOR AS A TECHNIQUE OF ANALYSIS OF EPILEPTIFORM ELECTRIC BRAIN ACTIVITY
Cite this article as:
Yakhno Y. V., Molkov . I., Mukhin D. N., Loskutov Е. М., Feigin А. М. RECONSTRUCTION OF AN EVOLUTION OPERATOR AS A TECHNIQUE OF ANALYSIS OF EPILEPTIFORM ELECTRIC BRAIN ACTIVITY. Izvestiya VUZ. Applied Nonlinear Dynamics, 2011, vol. 19, iss. 6, pp. 156-172. DOI: https://doi.org/10.18500/0869-6632-2011-19-6-156-172
We propose a new method for analysis of electroencephalograms. It is based on construction of a parameterized stochastic model of the observed process (evolution operator). A certain functional form of the evolution operator is proposed. This form describes deterministic properties of the investigated process, as well as stochastic ones. The parameters of the evolution operator are reconstructed from the experimental data by using the Bayesian approach. New («fast») dynamical variables, which allow for the peculiar features of electroencephalogram, are found. They make it possible to construct the evolution operator, which describes electroencephalogram on fewsecond intervals. The timevarying parameters of this operator and the amplitude of oscillations in electroencephalogram form «slow» variables, which describe changes in the oscillation properties during the entire recording period. It is possible to single out individual brain states with these variables and to present a result in an obviousdiagram. Moreover, changes in the singled-out brain states can be revealed. The proposed method was successfully applied to a specific physiological problem.
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BibTeX
author = {Yu. V. Yakhno and Ya. I. Molkov and D N. Mukhin and Е. М. Loskutov and А. М. Feigin},
title = {RECONSTRUCTION OF AN EVOLUTION OPERATOR AS A TECHNIQUE OF ANALYSIS OF EPILEPTIFORM ELECTRIC BRAIN ACTIVITY},
year = {2011},
journal = {Izvestiya VUZ. Applied Nonlinear Dynamics},
volume = {19},number = {6},
url = {https://old-andjournal.sgu.ru/en/articles/reconstruction-of-evolution-operator-as-technique-of-analysis-of-epileptiform-electric},
address = {Саратов},
language = {russian},
doi = {10.18500/0869-6632-2011-19-6-156-172},pages = {156--172},issn = {0869-6632},
keywords = {Electroencephalography,time series analysis,evolution operator reconstruction.},
abstract = {We propose a new method for analysis of electroencephalograms. It is based on construction of a parameterized stochastic model of the observed process (evolution operator). A certain functional form of the evolution operator is proposed. This form describes deterministic properties of the investigated process, as well as stochastic ones. The parameters of the evolution operator are reconstructed from the experimental data by using the Bayesian approach. New («fast») dynamical variables, which allow for the peculiar features of electroencephalogram, are found. They make it possible to construct the evolution operator, which describes electroencephalogram on fewsecond intervals. The timevarying parameters of this operator and the amplitude of oscillations in electroencephalogram form «slow» variables, which describe changes in the oscillation properties during the entire recording period. It is possible to single out individual brain states with these variables and to present a result in an obviousdiagram. Moreover, changes in the singled-out brain states can be revealed. The proposed method was successfully applied to a specific physiological problem. }}