Wavelet entropy for subband segmentation of EEG during injury and recovery

Hasan A. Al-Nashash, Joseph S. Paul, Wendy C. Ziai, Daniel F. Hanley, Nitish V. Thakor

Research output: Contribution to journalArticle

Abstract

A novel approach to segmentation of the fine changes in the subband electroencephalograph (EEG) measured during the period of recovery following a short instance of cerebral injury is presented. As such, distinct types of bursts had in general different types of frequency localizations and that the time-varying energies may be tracked by observing the temporal variations of the squares of the wavelet coefficients.

Original languageEnglish (US)
Pages (from-to)653-658
Number of pages6
JournalAnnals of biomedical engineering
Volume31
Issue number6
DOIs
StatePublished - Jul 3 2003

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Keywords

  • Burst patterns
  • Subband segmentation
  • Wavelet entropy

ASJC Scopus subject areas

  • Biomedical Engineering

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