Detrended Fluctuation Analysis of uterine electromyography

In respect to the main goal of our ongoing work for predicting preterm birth, we analyze in this paper uterine EMG recordings of 11 pregnant and laboring women by means of Detrended Fluctuation Analysis (DFA), a scaling analysis method that quantifies a simple parameter to represent the correlation properties of a time series. Our study provides convincing evidence that pregnancy progress is typically associated to an alteration in the long-range correlation of the uterine EMG recordings. The results obtained from the analyzed data indicate that the correlation in the contractions increases during pregnancy. Furthermore, we demonstrate that the long-range parameter may discriminate between the two classes (pregnancy/labor). The results are supported by statistical analysis using t-test indicating good statistical significance with a confidence level of 95%. A surrogate data test is also performed to investigate the nature of the underlying dynamics of our experimental data. The results are very promising for monitoring pregnancy and detecting labor and may help identify preterm labor.

[1]  I. Verdenik,et al.  Uterine electrical activity as predictor of preterm birth in women with preterm contractions. , 2001, European journal of obstetrics, gynecology, and reproductive biology.

[2]  J D Wilson,et al.  Analysis of uterine contractions: a dynamical approach , 2003, The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians.

[3]  H. Stanley,et al.  Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. , 1995, Chaos.

[4]  Catherine Marque,et al.  Surveillance des grossesses à risque par électromyographie utérine , 1995 .

[5]  C. Marque,et al.  Use of the electrohysterogram signal for characterization of contractions during pregnancy , 1999, IEEE Transactions on Biomedical Engineering.

[6]  S M McGill,et al.  The importance of normalization in the interpretation of surface electromyography: a proof of principle. , 1999, Journal of manipulative and physiological therapeutics.

[7]  James Theiler,et al.  Testing for nonlinearity in time series: the method of surrogate data , 1992 .

[8]  M. Doret,et al.  L'électromyogramme utérin : principes et intérêt pour le diagnostic de travail prématuré , 2008 .

[9]  Catherine Marque,et al.  Mathematical modeling of electrical activity of uterine muscle cells , 2009, Medical & Biological Engineering & Computing.

[10]  Pedro Carpena,et al.  Study of the human postural control system during quiet standing using detrended fluctuation analysis , 2009 .

[11]  Ao Li,et al.  Detecting mental EEG properties using detrended fluctuation analysis , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[12]  Jose Alvarez-Ramirez,et al.  Detrended fluctuation analysis of heart intrabeat dynamics , 2007 .

[13]  C. Marque,et al.  Abdominal EHG on a 4 by 4 grid: mapping and presenting the propagation of uterine contractions , 2007 .

[14]  J. Terrien,et al.  Spatial analysis of uterine EMG signals: Evidence of increased in synchronization with term , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[15]  E. Oczeretko,et al.  Nonlinear Dynamics in Uterine Contractions Analysis , 2005 .

[16]  C Marque,et al.  Uterine electromyography: a critical review. , 1993, American journal of obstetrics and gynecology.