Literature DB >> 21497127

Comparison between approximate entropy, correntropy and time reversibility: application to uterine electromyogram signals.

Mahmoud Hassan1, Jérémy Terrien, Catherine Marque, Brynjar Karlsson.   

Abstract

Detection of nonlinearity should be the first step before any analysis of nonlinearity or nonlinear behavior in biological signal. The question is which method should be used in each case and which one can best respect the different characteristics of the signals under investigation. In this paper we compare three methods widely used in nonlinearity detection: approximate entropy, correntropy and time reversibility. The false alarm rates with the numbers of surrogates for the three methods were computed on linear, nonlinear stationary and nonlinear nonstationary signals. The results indicate the superiority of time reversibility over the other methods for detecting linearity and nonlinearity in different signal types. The application of time reversibility on uterine electromyographic signal showed very good performance in classifying pregnancy and labor signals.
Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21497127     DOI: 10.1016/j.medengphy.2011.03.010

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  17 in total

1.  Nonlinear estimation of coupling and directionality between signals: application to uterine EMG propagation.

Authors:  A Diab; M Hassan; S Boudaoud; C Marque; B Karlsson
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

2.  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

3.  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

4.  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

5.  Prediction of preterm deliveries from EHG signals using machine learning.

Authors:  Paul Fergus; Pauline Cheung; Abir Hussain; Dhiya Al-Jumeily; Chelsea Dobbins; Shamaila Iram
Journal:  PLoS One       Date:  2013-10-28       Impact factor: 3.240

6.  Automatic epileptic seizure detection using scalp EEG and advanced artificial intelligence techniques.

Authors:  Paul Fergus; David Hignett; Abir Hussain; Dhiya Al-Jumeily; Khaled Abdel-Aziz
Journal:  Biomed Res Int       Date:  2015-01-29       Impact factor: 3.411

7.  Estimation of preterm labor immediacy by nonlinear methods.

Authors:  Iker Malaina; Luis Martinez; Roberto Matorras; Carlos Bringas; Larraitz Aranburu; Luis Fernández-Llebrez; Leire Gonzalez; Itziar Arana; Martín-Blas Pérez; Ildefonso Martínez de la Fuente
Journal:  PLoS One       Date:  2017-06-01       Impact factor: 3.240

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 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

10.  A Comparative Study of Vaginal Labor and Caesarean Section Postpartum Uterine Myoelectrical Activity.

Authors:  Alba Diaz-Martinez; Javier Mas-Cabo; Gema Prats-Boluda; Javier Garcia-Casado; Karen Cardona-Urrego; Rogelio Monfort-Ortiz; Angel Lopez-Corral; Maria De Arriba-Garcia; Alfredo Perales; Yiyao Ye-Lin
Journal:  Sensors (Basel)       Date:  2020-05-26       Impact factor: 3.576

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