A subband-based information measure of EEG during brain injury and recovery after cardiac arrest

Hyun Chool Shin, Xiaofeng Jia, Robert Nickl, Romergryko G. Geocadin, Nitish V. Thakor

Research output: Contribution to journalArticle

Abstract

We propose an improved quantitative measure of EEG during brain injury and recovery after cardiac arrest. In our previous studies, we proposed a measure, information quantity (IQ), to detect the early effects of temperature manipulation on the EEG signals recorded from the scalp. IQ incorporates the wavelet transform and the Shannon entropy in full bands from delta to gamma. Unlike IQ, here we separately calculate IQ in each subband, i.e., the new measure is IQ in each subband. We will call it subband IQ (SIQ). We demonstrate the performance of the proposed method by comparing SIQ with IQ in terms of how well the meausres predict actual neurological outcomes. Thirteen rats, based on 7-min cardiac arrest were used. The experimental results show that the proposed measure was more highly correlated to neurological outcome than IQ.

Original languageEnglish (US)
Article number10
Pages (from-to)1985-1990
Number of pages6
JournalIEEE Transactions on Biomedical Engineering
Volume55
Issue number8
DOIs
StatePublished - Aug 1 2008

Keywords

  • Brain injury
  • Cardiac arrest
  • EEG
  • Entropy
  • Hypothermia
  • Subband
  • Wavelet

ASJC Scopus subject areas

  • Biomedical Engineering

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