Network centrality and multiscale transition asymmetry in the heart rate variability analysis of normal and preeclamptic pregnancies

In the present work we define and apply a new methodology for the analysis of time series that involves a network representation. In this methodology, time series are transformed into a network with the subsequent calculation of some centrality indexes as well as the asymmetry of the transition frequency matrix, across different scales. The properties of the proposed indexes were analyzed with short-length simulated and physiological time series. In this case, we use RR time intervals, obtained from electrocardiographic records. The proposed indexes are compared with common complexity indexes in the analysis of the RR time series in normal and preeclamptic pregnancies.