During a healthy pregnancy, the mother’s body is continuously adapting to the growing needs of the maternal-fetal pair. These changes are in large part facilitated by the autonomic nervous system (ANS). However, in approximately 15% of pregnancies, maternal physiology is not able to appropriately adapt, resulting in pregnancy complications such as hypertensives disorders of pregnancy or gestational diabetes which result in perinatal morbidity and mortality. Correspondingly, such complications are associated with abnormal regulation by the ANS when compared to healthy pregnancies.

Detecting pregnancy complications early, i.e., before the onset of typical symptoms, would allow for the implementation of existing risk-mitigating interventions, which lessens the impact of these complications. Assessing autonomic regulation – which can be done via tracking heart rate variability (HRV) – may hold potential for the early detection of these complications. Subsequently, in our work, we investigate the feasibility of using HRV to track maternal health. We address the following topics, amongst others: the differences in autonomic regulation between pregnant and non-pregnant women, the factors (e.g., gestational age, parity) that affect maternal HRV, and the HRV features potentially best suited for detecting these complications.

Bio

Maretha Bester is a final year PhD candidate in the Biomedical Diagnostics research group at the Electrical Engineering department of the Eindhoven University of Technology, the Netherlands. Her work focuses on improving maternal health by finding ways to better detect pregnancy complications. This work is done in collaboration with Philips Research in Eindhoven and the Máxima Medical Center in Veldhoven, both in the Netherlands. Prior to her PhD research, she attained her bachelor’s and master’s degrees in mechatronic engineering at the University of Stellenbosch, South Africa, where her master’s research focused on assessing the breathing patterns of premature infants.