Novel Early EEG Measures Predicting Brain Recovery after Cardiac Arrest

• Main Authors: Kab-Mun Cha, Nitish V. Thakor, Hyun-Chool Shin
• Format: Article
• Language: English
• Published: MDPI AG 2017-09-01
• Series: Entropy
• Subjects: quantitative EEG; ischemic brain injury; cardiac arrest; entropy
• Online Access: https://www.mdpi.com/1099-4300/19/9/466

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).