@inproceedings{a93dffffe219467ab0037d6a29ff0dfa,
title = "Wavelet entropy method for EEG analysis: application to global brain injury",
abstract = "A novel method, {"}wavelet entropy,{"} is presented for the analysis of EEG signals recorded during injury and recovery following global cerebral ischemia. The EEG is recorded from rodent brains in a controlled experimental brain injury model by hypoxic-ischemic cardiac arrest. Wavelet analysis is used to decompose the EEG into standard clinical subbands. Entropy is then computed using these wavelet coefficients. The wavelet entropy helps segment periods of bursting in EEG signals. The residual entropy of the wavelet coefficients is also computed. It reflects the degree of synchronization of the brain rhythm generators.",
keywords = "Brain injuries, Brain modeling, Cardiac arrest, Electroencephalography, Entropy, Ischemic pain, Rodents, Signal analysis, Wavelet analysis, Wavelet coefficients",
author = "Al-Nashash, {H. A.} and Paul, {J. S.} and Thakor, {N. V.}",
note = "Publisher Copyright: {\textcopyright} 2003 IEEE. Copyright: Copyright 2015 Elsevier B.V., All rights reserved.; 1st International IEEE EMBS Conference on Neural Engineering ; Conference date: 20-03-2003 Through 22-03-2003",
year = "2003",
doi = "10.1109/CNE.2003.1196832",
language = "English (US)",
series = "International IEEE/EMBS Conference on Neural Engineering, NER",
publisher = "IEEE Computer Society",
pages = "348--351",
editor = "Wolf, {Laura J.} and Strock, {Jodi L.}",
booktitle = "Conference Proceedings - 1st International IEEE EMBS Conference on Neural Engineering",
}