EEG energy analysis for evaluating consciousness level using dynamic MEMD

Analysis of electroencephalography (EEG) energy is a useful technique in the brain signal processing. In this paper, we present a novel data analysis method based on a dynamic multivariate empirical mode decomposition (D-MEMD) algorithm to analyze EEG energy of three different conscious states such as normal awake, comatose and brain death. By using D-MEMD, we can not only denoise the original EEG data but also calculate the EEG energy of subjects in a dynamic time series. Moreover, from the result, we distinguish three consciousness levels. The results of healthy subject in normal awake, comatose patient and brain death will be shown. The analyzed results illustrate the effectiveness and performance of the proposed method in calculation of EEG energy for evaluating consciousness level.