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 |
Appears in Collections: | Staff Publications Elements |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
10_3390_e19090466.pdf | 811.33 kB | Adobe PDF | OPEN | None | View/Download |
This item is licensed under a Creative Commons License