Copyright © 2003 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Identification of the pregnant woman prone to develop pre-eclampsia later during her course of the pregnancy is a clinical challenge in clinical obstetrics. A new and non-invasive approach to detect abnormalities in pre-eclamptic women that differentiate from women with uneventful pregnancies is presented here. We applied non-linear and fractal features for classifying the dynamical complexity of the heart rate (HR) patterns corresponding to seven normal subjects and eight pre-eclamptic patients. Significant differences in the estimated largest Lyapunov exponent and in the correlation dimension between normotensive women and those with pre-eclampsia were found, suggesting they may have potential as new markers for pre-eclampsia. HR patterns in healthy and pre-eclamptic pregnancies correspond to complex non-linear dynamics, which could arise from the contribution of stochastic and chaotic components. HR of pre-eclamptic patients also revealed a more regular dynamic behavior than those belonging to normal pregnancies, corroborating the general observation that diseased states may be associated with regular HR patterns.