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Recurring patterns in stationary intervals of abdominal uterine electromyograms during gestation

Lookup NU author(s): Luigi Di Marco, Costanzo Di Maria, Dr Wing Tong, Professor Michael TaggartORCiD, Professor Steve RobsonORCiD, Dr Philip Langley


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Abdominal uterine electromyograms (uEMG) studies have focused on uterine contractions to describe the evolution of uterine activity and preterm birth (PTB) prediction. Stationary, non-contracting uEMG has not been studied. The aim of the study was to investigate the recurring patterns in stationary uEMG, their relationship with gestation age and PTB, and PTB predictivity. A public database of 300 (38 PTB) three-channel (S1-S3) uEMG recordings of 30 min, collected between 22 and 35 weeks' gestation, was used. Motion and labour contraction-free intervals in uEMG were identified as 5-min weak-sense stationarity intervals in 268 (34 PTB) recordings. Sample entropy (SampEn), percentage recurrence (PR), percentage determinism (PD), entropy (ER), and maximum length (L (MAX)) of recurrence were calculated and analysed according to the time to delivery and PTB. Random time series were generated by random shuffle (RS) of actual data. Recurrence was present in actual data (p < 0.001) but not RS. In S3, PR (p < 0.005), PD (p < 0.01), ER (p < 0.005), and L (MAX) (p < 0.05) were higher, and SampEn lower (p < 0.005) in PTB. Recurrence indices increased (all p < 0.001) and SampEn decreased (p < 0.01) with decreasing time to delivery, suggesting increasingly regular and recurring patterns with gestation progression. All indices predicted PTB with AUC a parts per thousand yen0.62 (p < 0.05). Recurring patterns in stationary non-contracting uEMG were associated with time to delivery but were relatively poor predictors of PTB.

Publication metadata

Author(s): Di Marco LY, Di Maria C, Tong WC, Taggart MJ, Robson SC, Langley P

Publication type: Article

Publication status: Published

Journal: Medical & Biological Engineering & Computing

Year: 2014

Volume: 52

Issue: 8

Pages: 707-716

Print publication date: 10/07/2014

ISSN (print): 0140-0118

ISSN (electronic): 1741-0444

Publisher: Springer


DOI: 10.1007/s11517-014-1174-6


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Funder referenceFunder name
Newcastle upon Tyne NHS Foundation Trust
National Institute for Health Research Newcastle Biomedical Research Centre based at Newcastle Hospitals Foundation Trust and Newcastle University
G902091Medical Research Council Bioinformatics Training Fellowship