EEG analysis using wavelet-based information tools

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

*Korrespondierende/r Autor/-in für diese Arbeit
149 Zitate (Scopus)

Abstract

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.

OriginalspracheEnglisch
ZeitschriftJournal of Neuroscience Methods
Jahrgang153
Ausgabenummer2
Seiten (von - bis)163-182
Seitenumfang20
ISSN0165-0270
DOIs
PublikationsstatusVeröffentlicht - 15.06.2006

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