Please use this identifier to cite or link to this item: https://doi.org/10.3390/e19090466
Title: Novel early EEG measures predicting brain recovery after cardiac arrest
Authors: Cha, K.-M
Thakor, N.V 
Shin, H.-C
Issue Date: 2017
Publisher: MDPI AG
Citation: Cha, K.-M, Thakor, N.V, Shin, H.-C (2017). Novel early EEG measures predicting brain recovery after cardiac arrest. Entropy 19 (9) : 466. ScholarBank@NUS Repository. https://doi.org/10.3390/e19090466
Rights: Attribution 4.0 International
Abstract: In this paper, we propose novel quantitative electroencephalogram (qEEG) measures by exploiting three critical and distinct phases (isoelectric, fast progression, and slow progression) of qEEG time evolution. Critical time points where the phase transition occurs are calculated. Most conventional measures have two major disadvantages. Firstly, to obtain meaningful time-evolution over raw electroencephalogram (EEG), these measures require baseline EEG activities before the subject's injury. Secondly, conventional qEEG measures need at least 2~3 h recording of EEG signals to predict meaningful long-term neurological outcomes. Unlike the conventional qEEG measures, the two measures do not require the baseline EEG information before injury and furthermore can be calculated only with the EEG data of 20~30 min after cardiopulmonary resuscitation (CPR). © 2017 by the authors.
Source Title: Entropy
URI: https://scholarbank.nus.edu.sg/handle/10635/179094
ISSN: 10994300
DOI: 10.3390/e19090466
Rights: Attribution 4.0 International
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