Summary
International Symposium on Nonlinear Theory and its Applications
2010
Session Number:C3L-A
Session:
Number:C3L-A3
Recurrence based complex network analysis of cardiovascular variability data to predict pre-eclampsia
Norbert Marwan, Niels Wessel, Holger Stepan, Jurgen Kurths,
pp.585-588
Publication Date:2010/9/5
Online ISSN:2188-5079
Summary:
Pre-eclampsia in pregnancy is a serious disease with high risk of fetal and maternal morbidity. The usual positive predictive value is 20?30%. Including cardiovascular variability, it has been recently shown that this predictive power can be improved. Here we propose a novel approach for analysing time series of systolic and diastolic blood pressure as well as heart rate variability measured in the 20th week of gestation in order to predict pre-eclampsia. For this aim, we identify the recurrence matrix (calculated from time series) with the adjacency matrix of a complex network and apply measures for the characterisation of complex networks to this recurrence matrix. We demonstrate the potential of the complex network measures for a further improvement of the positive predictive value of pre-eclampsia.