EEG data analysis based on EMD for coma and quasi-brain-death patients

Electroencephalography (EEG) is widely used in evaluating the absence of cerebral cortex function for the determination of brain death. Since EEG recorded signal is always corrupted by some artefacts and various interfering noise, extracting active or nonactive features from noisy EEG signals and evaluating their significance is therefore crucial in the process of brain death diagnosis. This article presents an EEG-based preliminary examination system associated with empirical mode decomposition (EMD) technique to extract informative brain activity features from real-world recorded clinical EEG data. Moreover, the power spectrum technique is applied to evaluate the significant differences between the group of comatose patients and the group of quasi-brain-deaths. Our experimental results show effectiveness and some promising directions of applying the EMD method to the clinical EEG analysis.