Back to Search Start Over

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

Authors :
Punitha, N.
Ramakrishnan, S.
Source :
Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Sage Publications, Ltd.); Mar2019, Vol. 233 Issue 3, p362-371, 10p
Publication Year :
2019

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09544119
Volume :
233
Issue :
3
Database :
Complementary Index
Journal :
Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Sage Publications, Ltd.)
Publication Type :
Academic Journal
Accession number :
135484342
Full Text :
https://doi.org/10.1177/0954411919827323