Literature DB >> 23192483

Better pregnancy monitoring using nonlinear correlation analysis of external uterine electromyography.

Malunoud Hassan1, Jérémy Terrien, Charles Muszynski, Asgeir Alexandersson, Catherine Marque, Brynjar Karlsson.   

Abstract

The objective of this paper is to evaluate the novel method for analyzing the nonlinear correlation of the uterine electromyography (EMG). The application of this method may improve monitoring in pregnancy, labor detection, and preterm labor detection. Uterine EMG signals recorded from a 4 × 4 matrix of electrodes on the subjects' abdomen are used here. The propagation was analyzed using the nonlinear correlation coefficient h(2). Signals from 49 women (36 during pregnancy and 13 in labor) at different gestational age were used. ROC curves were computed to evaluate the potential of three methods to differentiate between 174 contractions recorded during pregnancy and 115 contractions recorded during labor. The results indicate considerably better performance of the nonlinear correlation analysis (area under curve = 0.85) when compared to classical frequency parameters (area under curve = 0.76 and 0.66) in distinguishing labor contractions from normal pregnancy contractions. We conclude that the analysis of the propagation of the uterine electrical activity using the nonlinear correlation coefficient h(2) is a promising way of improving the usefulness of uterine EMG signals for clinical purposes, such as monitoring in pregnancy, labor detection, and prediction of preterm labor.

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Year:  2012        PMID: 23192483     DOI: 10.1109/TBME.2012.2229279

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  15 in total

1.  Relevant Features Selection for Automatic Prediction of Preterm Deliveries from Pregnancy ElectroHysterograhic (EHG) records.

Authors:  Nafissa Sadi-Ahmed; Baya Kacha; Hamza Taleb; Malika Kedir-Talha
Journal:  J Med Syst       Date:  2017-11-11       Impact factor: 4.460

2.  Vaginal electrohysterography: the design and preliminary evaluation of a novel device for uterine contraction monitoring in an ovine model (.).

Authors:  Nate Sunwoo; Karin Hwang; Karin J Blakemore; Abimbola Aina-Mumuney
Journal:  J Matern Fetal Neonatal Med       Date:  2015-11-23

3.  Recurring patterns in stationary intervals of abdominal uterine electromyograms during gestation.

Authors:  Luigi Yuri Di Marco; Costanzo Di Maria; Wing-Chiu Tong; Michael J Taggart; Stephen C Robson; Philip Langley
Journal:  Med Biol Eng Comput       Date:  2014-07-10       Impact factor: 2.602

4.  Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals.

Authors:  Peng Ren; Shuxia Yao; Jingxuan Li; Pedro A Valdes-Sosa; Keith M Kendrick
Journal:  PLoS One       Date:  2015-07-10       Impact factor: 3.240

5.  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

6.  Comparison of different EHG feature selection methods for the detection of preterm labor.

Authors:  D Alamedine; M Khalil; C Marque
Journal:  Comput Math Methods Med       Date:  2013-12-23       Impact factor: 2.238

7.  Automated conduction velocity analysis in the electrohysterogram for prediction of imminent delivery: a preliminary study.

Authors:  Hinke de Lau; Chiara Rabotti; Rianne Bijloo; Michael Johannes Rooijakkers; Massimo Mischi; S Guid Oei
Journal:  Comput Math Methods Med       Date:  2013-12-29       Impact factor: 2.238

Review 8.  Electrodes in external electrohysterography: a systematic literature review.

Authors:  Thierry R Jossou; Aziz Et-Tahir; Zakaria Tahori; Abdelmajid El Ouadi; Daton Medenou; Abdelmajid Bybi; Latif Fagbemi; Mohamed Sbihi; Davide Piaggio
Journal:  Biophys Rev       Date:  2021-05-09

9.  Automatic evaluation of progression angle and fetal head station through intrapartum echographic monitoring.

Authors:  Sergio Casciaro; Francesco Conversano; Ernesto Casciaro; Giulia Soloperto; Emanuele Perrone; Gian Carlo Di Renzo; Antonio Perrone
Journal:  Comput Math Methods Med       Date:  2013-09-09       Impact factor: 2.238

10.  Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

Authors:  Yiyao Ye-Lin; Javier Garcia-Casado; Gema Prats-Boluda; José Alberola-Rubio; Alfredo Perales
Journal:  Comput Math Methods Med       Date:  2014-01-09       Impact factor: 2.238

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