Automatic detection and characterization of uterine contraction using Electrohysterography

Abstract

Preterm birth is the leading cause of perinatal morbidity and mortality. In clinical practice, the information of uterine contraction is an important reference for preterm delivery. The commonly used tocography method for detecting uterine contractions has low sensitivity and is not suitable for long-term measurement. The electrohysterography (EHG) can record the electrical activity of uterine muscle cells associated with contractions through electrodes on the abdomen. Therefore, this paper proposes a new automatic detection method of uterine contractions based on EHG signals. Specifically, utilizing the nonlinear property of entropy analysis, contraction and spike noise are distinguished in the complexity domain to highlight contraction activity. Then, the location of the contraction is detected by an adaptive thresholding method. Finally, the detected contractions are analyzed for pregnancy and labor. The results show that compared with the existing root mean square methods, the proposed method is less affected by spike noise, and the contraction detection rate on the Icelandic EHG database reaches 87.9%. Meanwhile, features extracted from detected contractions have significant differences between non-labor and labor categories. This demonstrates the feasibility of contraction detection by EHG signal, which can contribute to better care for high-risk pregnant women.