EEG energy analysis based on MEMD with ICA pre-processing
Yunchao Yin, Jianting Cao, Toshihisa Tanaka · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference · 2012
Analysis of EEG energy is a useful technique in the brain signal processing. This paper presents a data analysis method based on multivariate empirical mode decomposition (MEMD) with ICA pre-processing to calculate and evaluate the energy of EEG recorded from the quasi brain deaths. The main advantage of introducing ICA pre-processing is that we can reduce the noise and other unexpected components. The simulation results illustrate the effectiveness and performance of the proposed method in brain death determination.