Classification of Nonlinear Features of Uterine Electromyogram Signal Towards the Prediction of Preterm Birth

Abstract

Early detection of preterm labor is important to avoid neonatal death and mortality. Uterine electromyography (UEMG) or electrohysterography is a non-invasive method of extracting electrical activity signal from the abdominal part during pregnancy, which helps in early detection. This signal can be used to classify term and preterm labors. Herein, the performances of four classifiers have been evaluated using seven nonlinear features extracted from UEMG signals. They were then compared with four features analyzed from different literature. The results show that with the Elman neural network classifier, the bi-spectrum feature, which has phase information, outperforms other features with 99.8875% accuracy, 100% sensitivity, and 99.77% specificity.

KEYWORDS:

• Bi-spectrum analysis
• Detrended fluctuation analysis
• Electrohysterography
• Elman neural network
• Energy entropy
• Higuchi fractal dimension
• Median frequency
• Peak frequency
• Root mean square
• Sample entropy
• Teager energy
• Teager energy entropy
• Uterine electromyography

Additional information

Notes on contributors

P. Shaniba Asmi

P Shaniba Asmi is currently pursuing her PhD degree in electronics and communication engineering at Karpagam Academy of Higher Education, Coimbatore, India, and working as associate professor in MES College of Engineering, Kuttippuram, India. Her research interest is in biomedical signal processing.

Kamalraj Subramaniam

Kamalraj Subramaniam received his PhD degree in mechatronic engineering, University Malaysia Perlis, Perlis, Malaysia in 2014. Currently, he is an associate professor & deputy head (Human Machine Interface Cluster) Karpagam Academy of Higher Education, Coimbatore, India. Hiş research interests include biomedical signal processing, artificial neural networks, VLSI design. Email: [email protected]

Nisheena V. Iqbal

Nisheena V Iqbal is currently pursuing her PhD degree in electronics and communication engineering at Karpagam Academy of Higher Education, Coimbatore, India, and working as associate professor in MES college of Engineering, Kuttippuram, India. Her research interest is in biomedical signal processing. Email: [email protected]