EEG analysis using wavelet-based information tools

O. A. Rosso*, M. T. Martin, A. Figliola, K. Keller, A. Plastino

*Corresponding author for this work
149 Citations (Scopus)


Wavelet-based informational tools for quantitative electroencephalogram (EEG) record analysis are reviewed. Relative wavelet energies, wavelet entropies and wavelet statistical complexities are used in the characterization of scalp EEG records corresponding to secondary generalized tonic-clonic epileptic seizures. In particular, we show that the epileptic recruitment rhythm observed during seizure development is well described in terms of the relative wavelet energies. In addition, during the concomitant time-period the entropy diminishes while complexity grows. This is construed as evidence supporting the conjecture that an epileptic focus, for this kind of seizures, triggers a self-organized brain state characterized by both order and maximal complexity.

Original languageEnglish
JournalJournal of Neuroscience Methods
Issue number2
Pages (from-to)163-182
Number of pages20
Publication statusPublished - 15.06.2006


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