Automatic Contraction Detection Using Uterine Electromyography

Electrohysterography (EHG) is a promising technique for pregnancy monitoring and preterm risk evaluation. It allows for uterine contraction monitoring as early as the 20th gestational week, and it is a non-invasive technique based on recording the electric signal of the uterine muscle activity from...

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Bibliographic Details
Main Authors: Filipa Esgalhado, Arnaldo G. Batista, Helena Mouriño, Sara Russo, Catarina R. Palma dos Reis, Fátima Serrano, Valentina Vassilenko, Manuel Duarte Ortigueira
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/10/20/7014
Description
Summary:Electrohysterography (EHG) is a promising technique for pregnancy monitoring and preterm risk evaluation. It allows for uterine contraction monitoring as early as the 20th gestational week, and it is a non-invasive technique based on recording the electric signal of the uterine muscle activity from electrodes located in the abdominal surface. In this work, EHG-based contraction detection methodologies are applied using signal envelope features. Automatic contraction detection is an important step for the development of unsupervised pregnancy monitoring systems based on EHG. The exploratory methodologies include wavelet energy, Teager energy, root mean square (RMS), squared RMS, and Hilbert envelope. In this work, two main features were evaluated: contraction detection and its related delineation accuracy. The squared RMS produced the best contraction (97.15 ± 4.66%) and delineation (89.43 ± 8.10%) accuracy and the lowest false positive rate (0.63%). Despite the wavelet energy method having a contraction accuracy (92.28%) below the first-rated method, its standard deviation was the second best (6.66%). The average false positive rate ranged between 0.63% and 4.74%—a remarkably low value.
ISSN:2076-3417