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Early diagnosis of threatened premature labor by electrohysterographic recordings – The use of digital signal processing

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Prevention and early diagnosis of imminent preterm labor are considered to be the most important perinatal challenge nowadays. Significant progress has been observed on postnatal care of premature infants, but without reducing the prevalence of preterm delivery. Our study was focused on comparison of three methods of spectral analysis of electro-hysterographic (EHG) signals: fast Fourier transform (FFT), wavelet transform (WT) and autoregressive modeling (AR). Complexity of the electrohysterographic signals was analyzed by using: the approximate entropy (ApEn), Lempel–Ziv complexity measure (L–Z). Additionally, the work evaluated the applicability of EHG in diagnosing imminent premature labor. EHG signals were recorded among 60 patients with threatened preterm labor symptoms between the 24th and 34th week of pregnancy. Patients included to the study had a shortened cervix (less than 20 mm) without regular uterine contractions recorded on regular cardiotocography (CTG). The women were divided into two groups: those delivering within 7 days – group A (n = 15) and women delivering after 7 days – group B (n = 45). The study confirmed differences in bioelectrical activity of uterus between patients delivering prematurely within 7 days and after from the EHG registration for all analyzed methods.
Twórcy
  • Medical University of Bialystok, Faculty of Medicine, Department of Perinatology, Białystok, Poland
autor
  • Bialystok University of Technology, Faculty of Mechanical Engineering, Department of Materials and Biomedical Engineering, Białystok, Poland
autor
  • Medical University of Bialystok, Faculty of Medicine, Department of Perinatology, Białystok, Poland
autor
  • Medical University of Bialystok, Faculty of Medicine, Department of Perinatology, Białystok, Poland
  • Medical University of Bialystok, Faculty of Medicine, Department of Perinatology, Białystok, Poland
  • Medical University of Bialystok, Faculty of Medicine, Department of Perinatology, Białystok, Poland
autor
  • Bialystok University of Technology, Faculty of Mechanical Engineering, Department of Materials and Biomedical Engineering, Wiejska 45C, 15-351 Białystok, Poland
Bibliografia
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Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3fc902b1-4297-4303-a68a-ce36d44d3836
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