4 papers
Empirical mode decomposition and interpretable machine learning for preterm birth classification from electrohysterography
Umesha Tilakarathna, Senith Jayakody, Kalana Jayasooriya +4
Preterm birth (PTB) remains a major global health problem, and reliable non-invasive risk assessment remains difficult. Electrohysterography (EHG) records uterine electrical activi…
Spectrotemporal Feature Extraction in EHG Signals and Tocograms for Enhanced Preterm Birth Prediction
Senith Jayakody, Kalana Jayasooriya, Sashini Liyanage +3
Preterm birth (PTB), defined as delivery before 37 weeks of gestation, is a leading cause of neonatal mortality and long term health complications. Early detection is essential for…
Comprehensive Study on Denoising of Medical Images Utilizing Neural Network Based Auto-Encoder
Thoshara Nawarathne, Thanushi Withanage, Samitha Gunarathne +7
Fetal motion discernment utilizing spectral images extracted from accelerometric data incident on pregnant mothers abdomen has gained substantial attention in the state-of-the-art…
Novel Non-Invasive In-house Fabricated Wearable System with a Hybrid Algorithm for Fetal Movement Recognition
Upekha Delay, Thoshara Nawarathne, Sajan Dissanayake +6
Fetal movement count monitoring is one of the most commonly used methods of assessing fetal well-being. While few methods are available to monitor fetal movements, they consist of…