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DOI Prefix: 10.47001/IRJIET

Quantitative Analysis of Electrohysterogram Features for Pregnancy Monitoring

Sandeep GuptaCollege of Engineering and Management, Punjabi University Neighbourhood Campus, Punjab, IndiaVibha AggarwalUniversity College, Barnala, Punjab, IndiaManjeet Singh PatterhDepartment of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, IndiaLovepreet SinghUniversity College, Barnala, Punjab, India

Vol 9 No 4 (2025): Volume 9, Issue 4, April 2025 | Pages: 12-15

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 07-04-2025

doi Logo doi.org/10.47001/IRJIET/2025.904002

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Abstract

Electrohysterogram (EHG) signals have emerged as a valuable tool for analyzing uterine activity and predicting pregnancy outcomes. This study investigates key statistical features extracted from EHG signals and examines their significance in differentiating pregnancy cases. A comprehensive statistical analysis, including analysis of variance (ANOVA) and Tukey's post-hoc test, was conducted on twelve extracted features. Results indicate that six features—standard deviation, root mean square (RMS), entropy, spectral entropy, Higuchi fractal dimension (HFD), and approximate entropy (ApEn)—exhibited significant differences among the cases. These findings highlight the potential of these features in distinguishing pregnancy conditions and improving predictive models for preterm birth risk.

Keywords

Electrohysterogram (EHG), analysis of variance (ANOVA), Higuchi fractal dimension (HFD), approximate entropy (ApEn)


Citation of this Article

Sandeep Gupta, Vibha Aggarwal, Manjeet Singh Patterh, & Lovepreet Singh. (2025). Quantitative Analysis of Electrohysterogram Features for Pregnancy Monitoring. International Research Journal of Innovations in Engineering and Technology - IRJIET, 9(4), 12-15. Article DOI https://doi.org/10.47001/IRJIET/2025.904002

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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