Please use this identifier to cite or link to this item: https://doi.org/10.3390/e19090466
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dc.titleNovel early EEG measures predicting brain recovery after cardiac arrest
dc.contributor.authorCha, K.-M
dc.contributor.authorThakor, N.V
dc.contributor.authorShin, H.-C
dc.date.accessioned2020-10-22T07:37:48Z
dc.date.available2020-10-22T07:37:48Z
dc.date.issued2017
dc.identifier.citationCha, 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
dc.identifier.issn10994300
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/179094
dc.description.abstractIn 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.
dc.publisherMDPI AG
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20201031
dc.typeArticle
dc.contributor.departmentELECTRICAL AND COMPUTER ENGINEERING
dc.description.doi10.3390/e19090466
dc.description.sourcetitleEntropy
dc.description.volume19
dc.description.issue9
dc.description.page466
dc.published.statePublished
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