Classification of FHR Signals Based on Morphological Features

• Published in: ECS transactions Vol. 107; no. 1; pp. 1637 - 1648
• Main Authors: Akkanapalli, Ushasri, Mudigonda, Malini
• Format: Journal Article
• Language: English
• Published: The Electrochemical Society, Inc 24.04.2022
• ISSN: 1938-5862; 1938-6737
• DOI: 10.1149/10701.1637ecst

Electronic fetal monitoring is a non-invasive procedure employed to assess the fetal health before and during labor. In this method, fetal heart rate (FHR) is measured by placing electrodes on the mother’s abdomen. The corresponding FHR signal is recorded on the graph called Cardiotocograph (CTG). During intrapartum, CTG records the changes in FHR in response to uterine contractions and helps in identifying the symptoms of fetal distress that may occur during the labor. In the present study, an algorithm is developed to calculate the features of fetal heart rate variability (FHRV). According to the RCOG guidelines, these features can be used to classify the subjects with normal, suspicious, and abnormal FHRV. Correctly interpreting the FHR variability enables early detection of fetal distress, thereby reducing fetal mortality rate. FHRV analysis also helps the obstetricians in efficient clinical decision making and avoiding unnecessary caesarean sections.