Comparison of Cardiotocography and Fetal Heart Rate Estimators Based on Non-Invasive Fetal ECG

Abstract

Non-invasive fetal ECG (NI-FECG) extraction algorithms enable long-term continuous beat-to-beat monitoring of the fetal heart rate (FHR), as opposed to the gold standard in FHR monitoring, cardiotocography (CTG). We investigate how NI-FECG extraction algorithms selected from the CinC 2013 Challenge (CinC13) perform on data with low quality signals and how performance can be evaluated using CTG, when FQRS annotation is not possible.Four-channel NI-FECG was recorded simultaneously with a CTG trace on 22 pregnant women, gestational age 29-41 weeks. Seven algorithms were tested: The winning CinC13 entry from Varanini et al. and six algorithms from the unofficial top-scoring CinC13 entry by Behar et al. Two accuracy measures were used: 1) The RMSE between the FECG-based FHR and CTG traces; 2) The Pearson correlation coefficient r between the FECG-based FHR and CTG trace and its average over all recordings, $\bar r$.The algorithms with the lowest RMSE’s are Behar’s FUSE-SMOOTH, a constant FHR, and Varanini, while the Varanini algorithm delivers the best correlation with the CTG trace $(\bar r = 0.73)$ with 41% of the recordings having r > 0.8, whereas the other algorithms have $\bar r \leq 0.59$ and ≤ 29% of the recordings with r > 0.8. FHR was estimated accurately in some recordings and poorly in others, believed to be due to large differences in signal quality.