Analysis of Pregnancy Development by Complexity and Information-Based Analysis of Fetal Phonocardiogram (PCG) Signals

Abstract

One of the crucial areas of pregnancy research is to analyze the pregnancy development. For this purpose, scientists analyze the different conditions of fetuses to understand their development. In this paper, we conducted complexity and information-based analyses on Phonocardiogram (PCG) signals to investigate pregnancy development. We calculated the fractal dimension, approximate entropy, and sample entropy as the measures of complexity and the Shannon entropy as the measure of the information content of signals for 24 fetuses in four ranges of gestational weeks. Based on the obtained results, increasing the gestational age of fetuses is reflected on the increment of the complexity of their PCG signals. We also observed similar findings in the case of the information content of PCG signals. Among all calculated measures, the fractal dimension of PCG signals showed significant variations among different gestational weeks. The method of analysis can be used to evaluate the alterations of other biomedical signals of fetuses (e.g., heart rate) to investigate their development.