Use of piecewise stationary segmentation as a pre-treatment for synchronization measures

The analysis of the synchronization between biological signals can be helpful for the characterization of biological functions. Biological signals are however often strongly non stationary. This is in contradiction to the assumption of commonly used synchronization measures which assume that the signal is stationary. We propose to use a piecewise stationary pre-segmentation (PSP) of the signals of interest, before the computation of synchronization measures. We show on synthetic as well as real biological signals (EEG and uterine EMG) that the proposed piecewise stationary pre-segmentation approach increases the accuracy of the measures by making a good tradeoff between the stationary assumption and length of the analyzed segments, when compared to the classical windowing method.