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Computational and Mathematical Methods in Medicine
Volume 2014, Article ID 470786, 11 pages
http://dx.doi.org/10.1155/2014/470786
Research Article

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

1Grupo de Bioelectrónica (I3BH), Universitat Politècnica de València, Camino de Vera s/n Ed.8B, 46022 Valencia, Spain
2Servicio de Obstetricia, H. U. La Fe, Valencia, Spain

Received 31 May 2013; Accepted 14 October 2013; Published 9 January 2014

Academic Editor: Catherine Marque

Copyright © 2014 Yiyao Ye-Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.