Detection of phase synchronization in EEG with Bivariate Empirical Mode Decomposition

Abstract

In recent years, the phase synchronization phenomenon in the electroencephalograph (EEG) has been widely used to observe interactions between separate areas of the cortex. However, the traditional coherence to measure the phase synchronization need target signals to be stationary. In this paper, we propose a technique to measure the phase synchrony of non-stationary signals by the Phase Locking Value (PLV) with Hilbert transform and the Bivariate Empirical Mode Decomposition (BEMD). We analyzed the phase synchronization of EEG signals which were recorded during Dynamical Dot Quartet (DDQ) tasks using the conventional method and the proposed method. The analysis result suggests that proposed method more suitable for detecting the phase synchrony during the DDQ tasks than the conventional methods.