Robust Characterization of the Uterine Myoelectrical Activity in Different Obstetric Scenarios

• Main Authors: J. Mas-Cabo, Y. Ye-Lin, J. Garcia-Casado, A. Diaz-Martinez, A. Perales-Marin, R. Monfort-Ortiz, A. Roca-Prats, A. Lopez-Corral, G. Prats-Boluda
• Format: Article
• Language: English
• Published: MDPI AG 2020-07-01
• Series: Entropy
• Subjects: Electrohysterogram (EHG); myoelectric uterine activity; postpartum; spectral content; sample entropy; spectral entropy
• Online Access: https://www.mdpi.com/1099-4300/22/7/743

Electrohysterography (EHG) has been shown to provide relevant information on uterine activity and could be used for predicting preterm labor and identifying other maternal fetal risks. The extraction of high-quality robust features is a key factor in achieving satisfactory prediction systems from EHG. Temporal, spectral, and non-linear EHG parameters have been computed to characterize EHG signals, sometimes obtaining controversial results, especially for non-linear parameters. The goal of this work was to assess the performance of EHG parameters in identifying those robust enough for uterine electrophysiological characterization. EHG signals were picked up in different obstetric scenarios: antepartum, including women who delivered on term, labor, and post-partum. The results revealed that the 10^th and 90^th percentiles, for parameters with falling and rising trends as labor approaches, respectively, differentiate between these obstetric scenarios better than median analysis window values. Root-mean-square amplitude, spectral decile 3, and spectral moment ratio showed consistent tendencies for the different obstetric scenarios as well as non-linear parameters: Lempel–Ziv, sample entropy, spectral entropy, and SD1/SD2 when computed in the fast wave high bandwidth. These findings would make it possible to extract high quality and robust EHG features to improve computer-aided assessment tools for pregnancy, labor, and postpartum progress and identify maternal fetal risks.