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Multifractal analysis of uterine electromyography signals to differentiate term and preterm conditions. | LitMetric

Multifractal analysis of uterine electromyography signals to differentiate term and preterm conditions.

Proc Inst Mech Eng H

Non-Invasive Imaging and Diagnostic (NIID) Laboratory, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, India.

Published: March 2019

AI Article Synopsis

  • The study investigates the multifractality of uterine electromyography signals to differentiate between term and preterm pregnancies using a specific analysis technique.
  • The data is sourced from a publicly available database and includes signals recorded during the second trimester, which are preprocessed to examine their multifractal nature.
  • Key findings indicate that multifractal characteristics are present in both types of pregnancies, with certain statistical features being significant for distinguishing between term and preterm conditions, suggesting this analysis could assist in diagnosing delivery outcomes.

Article Abstract

In this study, an attempt has been made to identify the origin of multifractality in uterine electromyography signals and to differentiate term (gestational age > 37 weeks) and preterm (gestational age ≤ 37 weeks) conditions by multifractal detrended moving average technique. The signals obtained from a publicly available database, recorded from the abdominal surface during the second trimester, are used in this study. The signals are preprocessed and converted to shuffle and surrogate series to examine the source of multifractality. Multifractal detrended moving average algorithm is applied on all the signals. The presence of multifractality is verified using scaling exponents, and multifractal spectral features are extracted from the spectrum. The variation of multifractal features in term and preterm conditions is analyzed statistically using Student's t-test. The results of scaling exponents show that the uterine electromyography or electrohysterography signals reveal multifractal characteristics in term and preterm conditions. Further investigation indicates the existence of long-range correlation as the primary source of multifractality. Among all extracted features, strength of multifractality, exponent index, and maximum and peak singularity exponents are statistically significant ( p < 0.05) in differentiating term and preterm conditions. The coefficient of variation is found to be lower for strength of multifractality and peak singularity exponent, which reveal that these features exhibit less inter-subject variance. Hence, it appears that multifractal analysis can aid in the diagnosis of preterm or term delivery of pregnant women.

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Source
http://dx.doi.org/10.1177/0954411919827323DOI Listing

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