Multiscale entropy analysis of eeg for assessment of post-cardiac arrest neurological recovery under hypothermia in rats

Xiaoxu Kang, Xiaofeng Jia, Romergryko G. Geocadin, Nitish V. Thakor, Anil Maybhate

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


Neurological complications after cardiac arrest (CA) can be fatal. Although hypothermia has been shown to be beneficial, understanding the mechanism and establishing neurological outcomes remains challenging because effects of CA and hypothermia are not well characterized. This paper aims to analyze EEG (and the α-rhythms) using multiscale entropy (MSE) to demonstrate the ability of MSE in tracking changes due to hypothermia and compare MSE during early recovery with long-term neurological examinations. Ten Wistar rats, upon post-CA resuscitation, were randomly subjected to hypothermia (32 °C-34 °C, N = 5) or normothermia (36.5 °C-37 °C, N = 5). EEG was recorded and analyzed using MSE during seven recovery phases for each experiment: baseline, CA, and five early recovery phases (R1-R5). Postresuscitation neurological examination was performed at 6, 24, 48, and 72 h to obtain neurological deficit scores (NDSs). Results showed MSE to be a sensitive marker of changes in α-rhythms. Significant difference ( p < 0.05) was found between the MSE for two groups during recovery, suggesting that MSE can successfully reflect temperature modulation. A comparison of short-term MSE and long-term NDS suggested that MSE could be used for predicting favorability of long-term outcome. These experiments point to the role of cortical rhythms in reporting early neurological response to ischemia and therapeutic hypothermia.

Original languageEnglish (US)
Article number4760210
Pages (from-to)1023-1031
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Issue number4
StatePublished - Apr 2009


  • Cardiac arrest (CA)
  • Entropy
  • Neurological injury
  • Quantitative EEG

ASJC Scopus subject areas

  • Biomedical Engineering


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