An empirical quantitative EEG analysis for evaluating clinical brain death.
In this paper, we apply qualitative tools and quantitative analysis for the EEG recordings of 23 adult patients. Specifically, independent component analysis (ICA) was applied to separate independent source components, followed by spectrum analysis. In terms of quantitative EEG analysis, we use several complexity measures to evaluate the differences between two groups of patients: the subjects in deep coma, and the subjects who were prejudged as brain death. For the first time, we report statistically significant differences of quantitative statistics in such a clinical study. The empirical results reported in this paper suggest some promising directions and valuable clues for clinical practice.
Chen
Zhe
Z
Neuroscience Statistics Research Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA. zhechen@neurostat.mgh.harvard.edu
Cao
Jianting
J
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001926:Brain Death / Q000175:diagnosis* / Q000503:physiopathology*; D004569:Electroencephalography; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests