Neural network based detection of fetal heart rate patterns

Abstract

Automated detection of fetal heart rate (FHR) patterns can potentially improve intra-partum care by providing consistent and reliable measures that assist health-care professionals in their assessment of the state of the fetus. We use the combined tools of signal processing and neural networks to detect the FHR patterns of baseline, acceleration and deceleration. Comparison to previous results reported in the literature are provided.