Analyzing EEG of quasi-brain-death based on dynamic sample entropy measures.
To give a more definite criterion using electroencephalograph (EEG) approach on brain death determination is vital for both reducing the risks and preventing medical misdiagnosis. This paper presents several novel adaptive computable entropy methods based on approximate entropy (ApEn) and sample entropy (SampEn) to monitor the varying symptoms of patients and to determine the brain death. The proposed method is a dynamic extension of the standard ApEn and SampEn by introducing a shifted time window. The main advantages of the developed dynamic approximate entropy (DApEn) and dynamic sample entropy (DSampEn) are for real-time computation and practical use. Results from the analysis of 35 patients (63 recordings) show that the proposed methods can illustrate effectiveness and well performance in evaluating the brain consciousness states.
East China University of Science and Technology, Meilong Road 130, Shanghai 200237, China.
Li
L
Ni
Saitama Institute of Technology, 1690 Fusaiji, Fukaya-shi, Saitama 369-0293, Japan ; Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama 351-0198, Japan.
Jianting
J
Cao
East China University of Science and Technology, Meilong Road 130, Shanghai 200237, China.
Rubin
R
Wang
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000704:Analysis of Variance; D001921:Brain / Q000473:pathology*; D001926:Brain Death / Q000175:diagnosis* / Q000473:pathology*; D003936:Diagnosis, Computer-Assisted; D004569:Electroencephalography; D019277:Entropy; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D012984:Software; D055815:Young Adult