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.

中文翻译：

---

通过胎儿心音图 (PCG) 信号的复杂性和基于信息的分析来分析妊娠发展

妊娠研究的关键领域之一是分析妊娠发展。为此，科学家分析胎儿的不同状况以了解其发育。在本文中，我们对心音图 (PCG) 信号进行了复杂性和基于信息的分析，以调查妊娠发展。我们计算了分形维数、近似熵和样本熵作为复杂性的衡量标准，香农熵作为衡量四个孕周范围内 24 个胎儿信号信息内容的衡量标准。根据所得结果，胎儿胎龄的增加反映在其 PCG 信号复杂度的增加上。在 PCG 信号的信息内容方面，我们也观察到了类似的发现。在所有计算的措施中，PCG信号的分形维数在不同孕周之间表现出显着差异。该分析方法可用于评估胎儿其他生物医学信号（例如，心率）的变化，以研究它们的发展。