Literature DB >> 21096805

Nonlinearity of EHG signals used to distinguish active labor from normal pregnancy contractions.

M Hassan1, J Terrien, A Alexandersson, C Marque, B Karlsson.   

Abstract

Labor prediction using the electrohysterogram has immediate clinical applications and has been the aim of several studies in recent years. Studies using various linear methods such as classic spectral analysis do not give clinically useful results. In this paper we present the use of two methods that investigate nonlinearity to predict normal labor. We show the comparison between a linear method that is known from the literature (mean power frequency) and two nonlinear methods (approximate entropy and time reversibility) using ROC analysis. The comparison indicates that the best method for pretreatment to classify pregnancy and labor signals is time reversibility. The results indicate that time reversibility is a very promising tool for distinguishing between labor and physiological contractions during pregnancy. This could be the first step in developing a clinical application method to predict preterm labor.

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Year:  2010        PMID: 21096805     DOI: 10.1109/IEMBS.2010.5627413

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  3 in total

1.  The Icelandic 16-electrode electrohysterogram database.

Authors:  Asgeir Alexandersson; Thora Steingrimsdottir; Jeremy Terrien; Catherine Marque; Brynjar Karlsson
Journal:  Sci Data       Date:  2015-04-28       Impact factor: 6.444

2.  Evaluation of convolutional neural network for recognizing uterine contractions with electrohysterogram.

Authors:  Dongmei Hao; Jin Peng; Ying Wang; Juntao Liu; Xiya Zhou; Dingchang Zheng
Journal:  Comput Biol Med       Date:  2019-08-19       Impact factor: 4.589

3.  Phase Entropy Analysis of Electrohysterographic Data at the Third Trimester of Human Pregnancy and Active Parturition.

Authors:  José Javier Reyes-Lagos; Adriana Cristina Pliego-Carrillo; Claudia Ivette Ledesma-Ramírez; Miguel Ángel Peña-Castillo; María Teresa García-González; Gustavo Pacheco-López; Juan Carlos Echeverría
Journal:  Entropy (Basel)       Date:  2020-07-22       Impact factor: 2.524

  3 in total

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