Analysis of Electromyography Burst Signals using Topological Feature Extraction for Diagnosis of Preterm Birth

摘要

Preterm birth (gestation ≤ 37 weeks) is the leading cause of neonatal mortality and morbidity worldwide. Early diagnosis of Preterm is crucial for increasing the survival rate of infants. Surface uterine Electromyography (uEMG) records the electrical activity of uterus during contraction. It quantitatively assesses the intensity, duration and frequency of uterine contractions. These contractions are characterized by a slow cyclic pattern of bursts followed by a period of quiescence. Analysis of these bursts using uEMG signals has high sensitivity in detecting Preterm labor sign. Significant information from these complex signals can be obtained using topological data analysis as it extracts the underlying shape characteristics of the signal. Hence, in this study, an attempt has been made to differentiate Term (gestation > 37 weeks) and Preterm conditions using uEMG signals and topological features.