Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures

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We develop a quantitative method of analysis of EEG records. The method is based on the wavelet analysis of the record and on the capability of the Jensen-Shannon divergence (JSD) to identify dynamical changes in a time series. The JSD is a measure of distance between probability distributions. Ther...

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Autores principales: Pereyra, M.E., Lamberti, P.W., Rosso, O.A.
Formato: JOUR
Materias:
EEG
Epileptic seizure
Jensen-Shannon divergence
Wavelets analysis
Electroencephalography
Probability distributions
Statistical mechanics
Time series analysis
Wavelet transforms
Frequency band component dynamics
Jensen Shannon divergence
Frequency bands
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03784371_v379_n1_p122_Pereyra
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_03784371_v379_n1_p122_Pereyra
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spelling todo:paper_03784371_v379_n1_p122_Pereyra2023-10-03T15:32:50Z Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures Pereyra, M.E. Lamberti, P.W. Rosso, O.A. EEG Epileptic seizure Jensen-Shannon divergence Wavelets analysis Electroencephalography Probability distributions Statistical mechanics Time series analysis Wavelet transforms Epileptic seizure Frequency band component dynamics Jensen Shannon divergence Wavelets analysis Frequency bands We develop a quantitative method of analysis of EEG records. The method is based on the wavelet analysis of the record and on the capability of the Jensen-Shannon divergence (JSD) to identify dynamical changes in a time series. The JSD is a measure of distance between probability distributions. Therefore for its evaluation it is necessary to define a (time dependent) probability distribution along the record. We define this probability distribution from the wavelet decomposition of the associated time series. The wavelet JSD provides information about dynamical changes in the scales and can be considered a complementary methodology reported earlier [O.A. Rosso, S. Blanco, A. Rabinowicz, Signal Processing 86 (2003) 1275; O.A. Rosso, S. Blanco, J. Yordanova, V. Kolev, A. Figliola, M. Schürmann, E. Başar, J. Neurosci. Methods 105 (2001) 65; O.A. Rosso, M.T. Martin, A. Figliola, K. Keller, A. Plastino, J. Neurosci. Methods 153 (2006) 163]. In the present study we have demonstrated it by analyzing EEG signal of tonic-clonic epileptic seizures applying the JSD method. The display of the JSD curves enables easy comparison of frequency band component dynamics. This would, in turn, promise easy and successful comparison of the EEG records from various scalp locations of the brain. © 2007 Elsevier B.V. All rights reserved. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03784371_v379_n1_p122_Pereyra
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic EEG
Epileptic seizure
Jensen-Shannon divergence
Wavelets analysis
Electroencephalography
Probability distributions
Statistical mechanics
Time series analysis
Wavelet transforms
Epileptic seizure
Frequency band component dynamics
Jensen Shannon divergence
Wavelets analysis
Frequency bands
spellingShingle EEG
Epileptic seizure
Jensen-Shannon divergence
Wavelets analysis
Electroencephalography
Probability distributions
Statistical mechanics
Time series analysis
Wavelet transforms
Epileptic seizure
Frequency band component dynamics
Jensen Shannon divergence
Wavelets analysis
Frequency bands
Pereyra, M.E.
Lamberti, P.W.
Rosso, O.A.
Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
topic_facet EEG
Epileptic seizure
Jensen-Shannon divergence
Wavelets analysis
Electroencephalography
Probability distributions
Statistical mechanics
Time series analysis
Wavelet transforms
Epileptic seizure
Frequency band component dynamics
Jensen Shannon divergence
Wavelets analysis
Frequency bands
description We develop a quantitative method of analysis of EEG records. The method is based on the wavelet analysis of the record and on the capability of the Jensen-Shannon divergence (JSD) to identify dynamical changes in a time series. The JSD is a measure of distance between probability distributions. Therefore for its evaluation it is necessary to define a (time dependent) probability distribution along the record. We define this probability distribution from the wavelet decomposition of the associated time series. The wavelet JSD provides information about dynamical changes in the scales and can be considered a complementary methodology reported earlier [O.A. Rosso, S. Blanco, A. Rabinowicz, Signal Processing 86 (2003) 1275; O.A. Rosso, S. Blanco, J. Yordanova, V. Kolev, A. Figliola, M. Schürmann, E. Başar, J. Neurosci. Methods 105 (2001) 65; O.A. Rosso, M.T. Martin, A. Figliola, K. Keller, A. Plastino, J. Neurosci. Methods 153 (2006) 163]. In the present study we have demonstrated it by analyzing EEG signal of tonic-clonic epileptic seizures applying the JSD method. The display of the JSD curves enables easy comparison of frequency band component dynamics. This would, in turn, promise easy and successful comparison of the EEG records from various scalp locations of the brain. © 2007 Elsevier B.V. All rights reserved.
format JOUR
author Pereyra, M.E.
Lamberti, P.W.
Rosso, O.A.
author_facet Pereyra, M.E.
Lamberti, P.W.
Rosso, O.A.
author_sort Pereyra, M.E.
title Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
title_short Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
title_full Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
title_fullStr Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
title_full_unstemmed Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
title_sort wavelet jensen-shannon divergence as a tool for studying the dynamics of frequency band components in eeg epileptic seizures
url http://hdl.handle.net/20.500.12110/paper_03784371_v379_n1_p122_Pereyra
work_keys_str_mv AT pereyrame waveletjensenshannondivergenceasatoolforstudyingthedynamicsoffrequencybandcomponentsineegepilepticseizures
AT lambertipw waveletjensenshannondivergenceasatoolforstudyingthedynamicsoffrequencybandcomponentsineegepilepticseizures
AT rossooa waveletjensenshannondivergenceasatoolforstudyingthedynamicsoffrequencybandcomponentsineegepilepticseizures
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