A Statistical Evaluation of Fetal Heart Rate Derived Parameters Between Healthy and IUGR Fetuses in Active and Quiet States.

The evaluation of fetal behavioral states, specifically the active and quiet phases, plays a crucial role in understanding fetal development during pregnancy. Pathological conditions such as intrauterine growth restriction (IUGR) can disrupt these states, affecting fetal heart rate (FHR) variability and other physiological parameters. This study utilizes a large dataset, comprising 13,652 healthy pregnancies and 7,047 IUGR cases, to analyze the differences in FHR parameters between active and quiet states across both healthy and IUGR pregnancies. A neural network-based approach, based on a previous model developed by our research team, was used to identify these fetal states within FHR signals. Our analysis highlights significant variations in terms of the most common FHR parameters between healthy and IUGR cases, providing valuable insights into the effects of pathological conditions on FHR dynamics.Clinical Relevance- By systematically analyzing the differences in fetal states between healthy and IUGR pregnancies, this study provides insights into the pathophysiology of IUGR and its impact on fetal autonomic and neural development. The ability to identify and quantify these differences in clinical settings can enhance non-invasive fetal monitoring, improving early detection of high-risk pregnancies and ultimately aiding in better clinical decision-making.