A subband-based information measure of EEG during brain injury and recovery after cardiac arrest.
We propose an improved quantitative measure of EEG during brain injury and recovery after cardiac arrest. In our previous studies, we proposed a measure, information quantity (IQ), to detect the early effects of temperature manipulation on the EEG signals recorded from the scalp. IQ incorporates the wavelet transform and the Shannon entropy in full bands from delta to gamma. Unlike IQ, here we separately calculate IQ in each subband, i.e., the new measure is IQ in each subband. We will call it subband IQ (SIQ). We demonstrate the performance of the proposed method by comparing SIQ with IQ in terms of how well the meausres predict actual neurological outcomes. Thirteen rats, based on 7-min cardiac arrest were used. The experimental results show that the proposed measure was more highly correlated to neurological outcome than IQ.
Shin
Hyun-Chool
HC
Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA. shinhc@ssu.ac.kr
Jia
Xiaofeng
X
Nickl
Robert
R
Geocadin
Romergryko G
RG
Thakor Ast
Nitish V
NV
D000465:Algorithms; D001930:Brain Injuries / Q000175:diagnosis* / Q000209:etiology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006323:Heart Arrest / Q000150:complications* / Q000175:diagnosis*; D006801:Humans; D020127:Recovery of Function; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity