Literature DB >> 20460202

Noninvasive estimation of the electrohysterographic action-potential conduction velocity.

Chiara Rabotti1, Massimo Mischi, S Guid Oei, Jan W M Bergmans.   

Abstract

Electrophysiological monitoring of the fetal-heart and the uterine-muscle activity, referred to as an electrohysterogram, is essential to permit timely treatment during pregnancy. While remarkable progress is reported for fetal-cardiac-activity monitoring, the electrohysterographic (EHG) measurement and interpretation remain challenging. In particular, little attention has been paid to the analysis of the EHG propagation, whose characteristics might be predictive of the preterm delivery. Therefore, this paper focuses, for the first time, on the noninvasive estimation of the conduction velocity of the EHG-action potentials. To this end, multichannel EHG recording and surface high-density electrodes are used. A maximum-likelihood method is employed for analyzing the EHG-action-potential propagation in two dimensions. The use of different weighting strategies of the derived cost function is introduced to deal with the poor signal similarity between different channels. The presented methods were evaluated by specific simulations proving the best weighting strategy to lead to an accuracy improvement of 56.7%. EHG measurements on ten women with uterine contractions confirmed the feasibility of the method by leading to conduction velocity values within the expected physiological range.

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Year:  2010        PMID: 20460202     DOI: 10.1109/TBME.2010.2049111

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


  17 in total

1.  On the nature of the electromyographic signals recorded during vibration exercise.

Authors:  Lin Xu; Chiara Rabotti; Massimo Mischi
Journal:  Eur J Appl Physiol       Date:  2015-01-10       Impact factor: 3.078

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.  Techniques for automated local activation time annotation and conduction velocity estimation in cardiac mapping.

Authors:  C D Cantwell; C H Roney; F S Ng; J H Siggers; S J Sherwin; N S Peters
Journal:  Comput Biol Med       Date:  2015-04-25       Impact factor: 4.589

Review 5.  Use of Non-invasive Uterine Electromyography in the Diagnosis of Preterm Labour.

Authors:  M Lucovnik; Z Novak-Antolic; R E Garfield
Journal:  Facts Views Vis Obgyn       Date:  2012

6.  Influence of electrode placement on signal quality for ambulatory pregnancy monitoring.

Authors:  M J Rooijakkers; S Song; C Rabotti; S G Oei; J W M Bergmans; E Cantatore; M Mischi
Journal:  Comput Math Methods Med       Date:  2014-02-03       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

8.  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

Review 9.  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

10.  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

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