Literature DB >> 18437439

A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups.

G Fele-Zorz1, G Kavsek, Z Novak-Antolic, F Jager.   

Abstract

Various linear and non-linear signal-processing techniques were applied to three-channel uterine EMG records to separate term and pre-term deliveries. The linear techniques were root mean square value, peak and median frequency of the signal power spectrum and autocorrelation zero crossing; while the selected non-linear techniques were estimation of the maximal Lyapunov exponent, correlation dimension and calculating sample entropy. In total, 300 records were grouped into four groups according to the time of recording (before or after the 26th week of gestation) and according to the total length of gestation (term delivery records--pregnancy duration >or=37 weeks and pre-term delivery records--pregnancy duration <37 weeks). The following preprocessing band-pass Butterworth filters were tested: 0.08-4, 0.3-4, and 0.3-3 Hz. With the 0.3-3 Hz filter, the median frequency indicated a statistical difference between those term and pre-term delivery records recorded before the 26th week (p = 0.03), and between all term and all pre-term delivery records (p = 0.012). With the same filter, the sample entropy indicated statistical differences between those term and pre-term delivery records recorded before the 26th week (p = 0.035), and between all term and all pre-term delivery records (p = 0.011). Both techniques also showed noticeable differences between term delivery records recorded before and after the 26th week (p <or= 0.001).

Mesh:

Year:  2008        PMID: 18437439     DOI: 10.1007/s11517-008-0350-y

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  19 in total

1.  Use of the electrohysterogram signal for characterization of contractions during pregnancy.

Authors:  H Leman; C Marque; J Gondry
Journal:  IEEE Trans Biomed Eng       Date:  1999-10       Impact factor: 4.538

2.  Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach.

Authors:  Janusz Jezewski; Krzysztof Horoba; Adam Matonia; Janusz Wrobel
Journal:  Physiol Meas       Date:  2005-07-01       Impact factor: 2.833

3.  Identification of human term and preterm labor using artificial neural networks on uterine electromyography data.

Authors:  William L Maner; Robert E Garfield
Journal:  Ann Biomed Eng       Date:  2007-01-17       Impact factor: 3.934

4.  Electrical activity of the human uterus during pregnancy as recorded from the abdominal surface.

Authors:  C Buhimschi; M B Boyle; R E Garfield
Journal:  Obstet Gynecol       Date:  1997-07       Impact factor: 7.661

5.  Frequency of uterine contractions and the risk of spontaneous preterm delivery.

Authors:  Jay D Iams; Roger B Newman; Elizabeth A Thom; Robert L Goldenberg; Eberhard Mueller-Heubach; Atef Moawad; Baha M Sibai; Steve N Caritis; Menachem Miodovnik; Richard H Paul; Mitchell P Dombrowski; Gary Thurnau; Donald McNellis
Journal:  N Engl J Med       Date:  2002-01-24       Impact factor: 91.245

6.  Denoising of the uterine EHG by an undecimated wavelet transform.

Authors:  P Carré; H Leman; C Fernandez; C Marque
Journal:  IEEE Trans Biomed Eng       Date:  1998-09       Impact factor: 4.538

Review 7.  Uterine electromyography: a critical review.

Authors:  D Devedeux; C Marque; S Mansour; G Germain; J Duchêne
Journal:  Am J Obstet Gynecol       Date:  1993-12       Impact factor: 8.661

8.  Characterization of abdominally acquired uterine electrical signals in humans, using a non-linear analytic method.

Authors:  William L Maner; Lynette B MacKay; George R Saade; Robert E Garfield
Journal:  Med Biol Eng Comput       Date:  2006-03       Impact factor: 2.602

9.  Comparing uterine electromyography activity of antepartum patients versus term labor patients.

Authors:  Robert E Garfield; William L Maner; Lyn B MacKay; Dietmar Schlembach; George R Saade
Journal:  Am J Obstet Gynecol       Date:  2005-07       Impact factor: 8.661

Review 10.  Prediction and early detection of preterm labor.

Authors:  Jay D Iams
Journal:  Obstet Gynecol       Date:  2003-02       Impact factor: 7.661

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  33 in total

1.  A signal invariant wavelet function selection algorithm.

Authors:  Girisha Garg
Journal:  Med Biol Eng Comput       Date:  2015-08-08       Impact factor: 2.602

2.  Mathematical modeling of electrical activity of uterine muscle cells.

Authors:  Sandy Rihana; Jeremy Terrien; Guy Germain; Catherine Marque
Journal:  Med Biol Eng Comput       Date:  2009-03-20       Impact factor: 2.602

3.  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

4.  Conduction velocity of the uterine contraction in serial magnetomyogram (MMG) data: event based simulation and validation.

Authors:  Adrian Furdea; Hubert Preissl; Curtis L Lowery; Hari Eswaran; Rathinaswamy B Govindan
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

Review 5.  Use of uterine electromyography to diagnose term and preterm labor.

Authors:  Miha Lucovnik; Ruben J Kuon; Linda R Chambliss; William L Maner; Shao-Qing Shi; Leili Shi; James Balducci; Robert E Garfield
Journal:  Acta Obstet Gynecol Scand       Date:  2010-12-07       Impact factor: 3.636

6.  Review and Study of Uterine Bioelectrical Waveforms and Vector Analysis to Identify Electrical and Mechanosensitive Transduction Control Mechanisms During Labor in Pregnant Patients.

Authors:  R E Garfield; Lauren Murphy; Kendra Gray; Bruce Towe
Journal:  Reprod Sci       Date:  2020-10-22       Impact factor: 3.060

7.  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

Review 8.  Artificial intelligence: A rapid case for advancement in the personalization of Gynaecology/Obstetric and Mental Health care.

Authors:  Gayathri Delanerolle; Xuzhi Yang; Suchith Shetty; Vanessa Raymont; Ashish Shetty; Peter Phiri; Dharani K Hapangama; Nicola Tempest; Kingshuk Majumder; Jian Qing Shi
Journal:  Womens Health (Lond)       Date:  2021 Jan-Dec

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.  Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography.

Authors:  Félix Nieto-Del-Amor; Gema Prats-Boluda; Jose Luis Martinez-De-Juan; Alba Diaz-Martinez; Rogelio Monfort-Ortiz; Vicente Jose Diago-Almela; Yiyao Ye-Lin
Journal:  Sensors (Basel)       Date:  2021-05-12       Impact factor: 3.576

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