A Quantitative Analysis of an EEG Epileptic Record Based on Multiresolution Wavelet Coefficients

Entropy

Mariel Rosenblatt¹  Alejandra Figliola¹  Gustavo Paccosi¹  Eduardo Serrano² 

[1] Instituto del Desarrollo Humano, Universidad Nacional de General Sarmiento, Juan María Gutiérrez 1150, Provincia de Buenos Aires, Argentina; E-Mails:;Centro de Matemática Aplicada, Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Irigoyen 3100, Provincia de Buenos Aires, Argentina; E-Mail:

关键词: wavelet analysis;    wavelet leaders;    entropy;    statistical complexity;    local regularity;    EEG;   

DOI  :  10.3390/e16115976

来源: mdpi

【 摘 要 】

The characterization of the dynamics associated with electroencephalogram (EEG) signal combining an orthogonal discrete wavelet transform analysis with quantifiers originated from information theory is reviewed. In addition, an extension of this methodology based on multiresolution quantities, called wavelet leaders, is presented. In particular, the temporal evolution of Shannon entropy and the statistical complexity evaluated with different sets of multiresolution wavelet coefficients are considered. Both methodologies are applied to the quantitative EEG time series analysis of a tonic-clonic epileptic seizure, and comparative results are presented. In particular, even when both methods describe the dynamical changes of the EEG time series, the one based on wavelet leaders presents a better time resolution.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland