Use of Multiscale Entropy to Characterize Fetal Autonomic Development

Abstract

The idea that uterine environment and adverse events during fetal development could increase the chances of the diseases in adulthood was first published by David Barker in 1998. Since then, investigators have been employing several methods and methodologies for studying and characterizing the ontological development of the fetus, e.g., fetal movement, growth and cardiac metrics. Even with most recent and developed methods such as fetal magnetocardiography (fMCG), investigators are continuously challenged to study fetal development; the fetus is inaccessible. Finding metrics that realize the full capacity of characterizing fetal ontological development remains a technological challenge. In this thesis, the use and value of multiscale entropy to characterize fetal maturation across third trimester of gestation is studied. Using multiscale entropy obtained from participants of a clinical trial, we show that MSE can characterize increasing complexity due to maturation in the fetus, and can distinguish a growing and developing fetal system from a mature system where loss of irregularity is due to compromised complexity from increasing physiologic load. MSE scales add a nonlinear metric that seems to accurately reflect the ontological development of the fetus and hold promise for future use to investigate the effects of maternal stress, intrauterine growth restriction, or predict risk for sudden infant death syndrome.