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Abstract:

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.

Registro:

Documento: Artículo
Título:Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures
Autor:Pereyra, M.E.; Lamberti, P.W.; Rosso, O.A.
Filiación:Facultad de Matemática, Astronomía y Física, Universidad Nacional de Córdoba, Ciudad Universitaria, 5000 Córdoba, Argentina
Chaos and Biology Group, Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Pabellon II, Ciudad Universitaria, 1428 Ciudad Autonoma de Buenos Aires, Argentina
Palabras clave: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
Año:2007
Volumen:379
Número:1
Página de inicio:122
Página de fin:132
DOI: http://dx.doi.org/10.1016/j.physa.2006.12.051
Título revista:Physica A: Statistical Mechanics and its Applications
Título revista abreviado:Phys A Stat Mech Appl
ISSN:03784371
CODEN:PHYAD
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v379_n1_p122_Pereyra

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Citas:

---------- APA ----------
Pereyra, M.E., Lamberti, P.W. & Rosso, O.A. (2007) . Wavelet Jensen-Shannon divergence as a tool for studying the dynamics of frequency band components in EEG epileptic seizures. Physica A: Statistical Mechanics and its Applications, 379(1), 122-132.
http://dx.doi.org/10.1016/j.physa.2006.12.051
---------- CHICAGO ----------
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" . Physica A: Statistical Mechanics and its Applications 379, no. 1 (2007) : 122-132.
http://dx.doi.org/10.1016/j.physa.2006.12.051
---------- MLA ----------
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" . Physica A: Statistical Mechanics and its Applications, vol. 379, no. 1, 2007, pp. 122-132.
http://dx.doi.org/10.1016/j.physa.2006.12.051
---------- VANCOUVER ----------
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. Phys A Stat Mech Appl. 2007;379(1):122-132.
http://dx.doi.org/10.1016/j.physa.2006.12.051