Human fetuses have nonlinear cardiac dynamics

Approximate entropy (ApEn) is a statistic that quantifies regularity in tim e series data, and this parameter has several features that make it attract ive for analyzing physiological systems. In this study, ApEn was used to de tect nonlinearities in the heart rate (HR) patterns of 12 low-risk human fe tuses between 38 and 40 wk of gestation. The fetal cardiac electrical signa l was sampled at a rate of 1,024 Hz by using Ag-AgCl electrodes positioned across the mother's abdomen, and fetal R waves were extracted by using adap tive signal processing techniques. To test for nonlinearity, ApEn for the o riginal HR time series was compared with ApEn for three dynamic models: tem porally uncorrelated noise, linearly correlated noise, and linearly correla ted noise with nonlinear distortion. Each model had the same mean and SD in HR as the original time series, and one model also preserved the Fourier p ower spectrum. We estimated that noise accounted for 17.2-44.5% of the tota l between-fetus variance in ApEn. Nevertheless, ApEn for the original time series data still differed significantly from ApEn for the three dynamic mo dels for both group comparisons and individual fetuses. We concluded that t he HR time series, in low-risk human fetuses, could not be modeled as tempo rally uncorrelated noise, linearly correlated noise, or static filtering of linearly correlated noise.