Slope of Tangent (SOT): A New Automatic Method for Segmenting Uterine Muscular Contraction Bursts from the Electrohysterogram

The use of electrohysterogram (EHG) - uterine muscular activity signals - along with artificial intelligence models would help in the prediction of preterm delivery and thereby save the lives of many early-delivered infants through the necessary early medical care. The informative portions in the EHG recording which could aid in the prediction of this risky delivery are the ones related to the uterine muscular contractions. Hence, the more we perform a precise segmentation of these contraction signals, the more valuable and discriminative are the data provided to the AI models, which will in turn reflect a better learning process and prediction outcome. This paper presents a new algorithm called Slope of Tangent (SOT) for an enhanced segmentation of uterine muscular contraction signals. The method is further compared to the up-to-date uterine contraction automatic segmentation methods. The results showed that the method allowed a higher number of full detections (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$F D=90$</tex>) and partial detections (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P D=263$</tex>) in comparison to the wavelet <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H 2$</tex> nonlinear correlation method (wavh2) (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$F D=42$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P D=145$</tex>) and the sample entropy method (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$F D=13$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P D=138$</tex>). Further work should be done in order to reduce the number of false detections given by the SOT method. In addition, the method should be further validated on open-source databases.