Periodic Change Detection in Fetal Heart Rate Using Cardiotocograph

Since 1960s, Cardiotocography (CTG) has been considered the primary tool for monitoring fetal health during antepartum and intra-partum periods. It records both Fetal Heart Rate (FHR) and mother's Uterine Contraction Pressure (UCP) simultaneously. However, due to inter and intra-observer variations, the introduction of CTG in fetal care did little to reduce the fetal mortality and morbidity. To ensure that the signs of hypoxia are recognized at the onset it is needed to have a robust and automated clinical decision support system since the visual analysis (clinicians) can be error-prone. In this work, we proposed methods to identify the periodic changes i.e. acceleration and deceleration. Our method detected 987 accelerations and 1755 decelerations from the 556 CTG data. There were 96.6% and 97.3% agreements with the three clinicians estimate for acceleration and deceleration, respectively. Besides, we also proposed a novel method to detect Sinusoidal Heart Rate (SHR) pattern. With Random Forest classifier, the SHR classification accuracy was 93%. The sensitivity and specificity were 93% and 86%, respectively, while both Positive Predictive Value (PPV) and Negative Predictive Value (NPV) were found to be 100%. We conclude that the proposed method can be used as a "gold standard" for SHR identification.