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Analysis of electrical uterine contractile activity for prediction of preterm delivery

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study is aimed at evaluation of the capability to indicate the preterm delivery risk analysing the features extracted from signals of electrical uterine activity. Free access database was used with signals acquired in two groups of pregnant women who delivered at term and preterm. Signal features comprised classical time domain and spectral parameters of contractile activity, as well as the sample entropy. Their mean values were calculated over all contraction episodes detected in each record and their statistical significance for separating the two groups of recordings was provided. Influence of electrodes location, band-pass filter settings and gestation week was investigated. The obtained results showed that a spectral parameter – the median frequency was the most promising indicator of the preterm delivery risk.
Rocznik
Tom
Strony
199--205
Opis fizyczny
Bibliogr. 17 poz., tab., wykr.
Twórcy
autor
  • Institute of Medical Technology and Equipment ITAM, 118 Roosevelt Str., 41-800 Zabrze
autor
  • Institute of Medical Technology and Equipment ITAM, 118 Roosevelt Str., 41-800 Zabrze
autor
  • Institute of Medical Technology and Equipment ITAM, 118 Roosevelt Str., 41-800 Zabrze
autor
  • Institute of Medical Technology and Equipment ITAM, 118 Roosevelt Str., 41-800 Zabrze
autor
  • Institute of Electronics, Silesian University of Technology, 16 Akademicka Str., 44-100 Gliwice
autor
  • Institute of Electronics, Silesian University of Technology, 16 Akademicka Str., 44-100 Gliwice
Bibliografia
  • [1] ALAMEDINE D., KHALIL M., MARQUE C. Comparison of different EHG feature selection methods for the detection of preterm labor. Comput. Math. Method. Med., 2013. pp. 1–9. Article ID 485684, http://dx.doi.org/10.1155/2013/485684 .
  • [2] DE LAU H., RABOTTI C., BIJLOO R., ROOIJAKKERS M. J., MISCHI M., OEI G. S. Automated conduction velocity analysis in the electrohysterogram for prediction of imminent delivery: A preliminary study. Comput. Math. Method Med., 2013. pp. 1–7. Article ID 627976.
  • [3] EULIANO T. Y., NGUYEN M. T., DARMANJIAN S., MCGORRAY S. P., EULIANO N., ONKALA A., GREGG A. R. Monitoring uterine activity during labor: a comparison of 3 methods. Am. J. Obstet. Gynecol., 2013, Vol. 208. pp. 66.e1– 6.
  • [4] FELE-ZORZ G., KAVSEK G., NOVAK-ANTOLIC Z., JAGER F. A comparison of various linear and non-linear signal processing techniques to separate uterine EMG records of term and pre-term delivery groups. Medical & Biological Engineering & Computing, 2008, Vol. 46. pp. 911–922.
  • [5] GOLDBERGER A. L., AMARAL L. A. N., GLASS L., HAUSDORFF J. M., IVANOV P. C., MARK R. G., MIETUS J. E., MOODY G. B., PENG C. K., STANLEY H. E. Physiobank, physiotoolkit, and physionet: Components of a new research resource for complex physiologic signals. Circulation, 2000, Vol. 101. pp. e215–20. http://circ.ahajournals.org/cgi/content/full/101/23/e215.
  • [6] HOROBA K., JEZEWSKI J., WROBEL J., MATONIA M., CZABANSKI R., JEZEWSKI M. Analysis of uterine contractile wave propagation in electrohysterogram for assessing the risk of preterm birth. Journal of Medical Imaging and Health Informatics, 2015, Vol. 5. pp. 1287–1294.
  • [7] JEZEWSKI J., HOROBA K., MATONIA A., WROBEL J. Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach. Physiological Measurement, 2005, Vol. 26. pp. 753– 767.
  • [8] JEZEWSKI J., MATONIA A., CZABANSKI R., HOROBA K., KUPKA T. Classification of uterine electrical activity patterns for early detection of preterm birth. Computer Recognition Systems 8 - CORES 2013, 2013, Vol. 226 of Advances in Intelligent Systems and Computing AISC. Springer Heidelberg, pp. 559–568.
  • [9] LA ROSA P. S., NEHORAI A., ESWARAN H., LOWERY C. L., PREISSL H. Detection of uterine EMG contractions using a multiple change point estimator and the K-means cluster algorithm. IEEE Trans. Biomed. Eng., 2008, Vol. 55. pp. 453–467.
  • [10] MANER W. L., GARFIELD R. E., MAUL H. Predicting term and preterm delivery with a transabdominal uterine electromyography. Obstet. Gynecol., 2003, Vol. 101. pp. 1254–1260.
  • [11] MOSLEM B., KHALIL M., MARQUE C., DIAB M. O. Complexity analysis of the uterine electromyography. 32nd Annual International Conference of the IEEE EMBS, 2010. Buenos Aires, Argentina, pp. 2802–2805.
  • [12] NOVY M. J., MCGREGOR J. A., LAMS J. A. New perspectives on prevention of extreme prematurity. Clin. Obstet. Gynecol., 1990, Vol. 38. pp. 790–780.
  • [13] RICHMAN J. S., MOORMAN J. R. Physiological time-series analysis using approximate entropy and sample entropy. Amer. J. Physiol. – Heart and Circulatory Physiol., 2000, Vol. 278. pp. 2039–2049.
  • [14] ROOIJAKKERS M. J., SONG S., RABOTTI C., OEI S. G., BERGMANS J. W. M., CANTATORE E., MISCHI M. Influence of electrode placement on signal quality for ambulatory pregnancy monitoring. Comput. Math. Method. Med., 2014. pp. 1–12. Article ID 960980, http://dx.doi.org/10.1155/2014/960980.
  • [15] SIKORA J., MATONIA A., CZABANSKI R., HOROBA K., JEZEWSKI J., KUPKA T. Recognition of premature threatening labour symptoms from bioelectrical uterine activity signals. Arch. Perinat. Med., 2011, Vol. 17. pp. 97–103.
  • [16] VERDENIK I., PAJNTAR M., LESKOSEK B. Uterine electrical activity as predictor of preterm birth in women with preterm contractions. Eur. J. Obstet. Gynecol. Reprod. Biol., 2001, Vol. 95. pp. 149–153.
  • [17] VRHOVEC J., MACEK-LEBAR A., RUDEL D. Evaluating uterine electrohysterogram with entropy. 11th Mediterranean Conf. Med. Biomed. Eng. Comp., 2007, Vol. 16 of IFMBE Proceedings. pp. 144–147.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f27065e1-b849-45af-b979-be4c3fceff69
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