Quantitative EEG and effect of hypothermia on brain recovery after cardiac arrest

Hyun Chool Shin, Shanbao Tong, Soichiro Yamashita, Xiaofeng Jia, Romergryko G. Geocadin, Nitish V. Thakor

Research output: Contribution to journalArticlepeer-review


In this paper, we provide a quantitative electroencephalogram (EEG) analysis to study the effect of hypothermia on the neurological recovery of brain after cardiac arrest. We hypothesize that the brain injury results in a reduction in information of the brain rhythm. To measure the information content of the EEG a new measure called information quantity (IQ), which is the Shannon entropy of decorrelated EEG signals, is developed. For decorrelating EEG signals, we use the discrete wavelet transform (DWT) which is known to have good decorrelating properties and to show a good match to the standard clinical bands in EEG. In measuring the amount of information, IQ shows better tracking capability for dynamic amplitude change and frequency component change than conventional entropy-based measures. Experiments are carried out in rodents (n = 30) to monitor the neurological recovery after cardiac arrest. In addition, EEG signal recovery under normothermic (37°C) and hypothermic (33°C) resuscitation following 5, 7, and 9 min of cardiac arrest is recorded and analyzed. Experimental results show that the IQ is greater for hypothermic than normothermic rats, with an IQ difference of more than 0.20 (0.20±0.11 is 95% condidence interval). The results quantitatively support the hypothesis that hypothermia accelerates the electrical recovery from brain injury after cardiac arrest.

Original languageEnglish (US)
Article number1634495
Pages (from-to)1016-1023
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Issue number6
StatePublished - Jun 2006


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

ASJC Scopus subject areas

  • Biomedical Engineering


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