Jorge, Cláudio José Marques2026-02-242026-02-242025http://hdl.handle.net/10400.5/117278Tese de Mestrado, Engenharia Biomédica e Biofísica, 2025, Universidade de Lisboa, Faculdade de CiênciasPreterm labor remains a major public health challenge and one of the leading causes of neonatal morbidity and mortality. The electrohysterogram (EHG), a non-invasive recording of uterine electrical activity, is considered a promising biomarker for predicting labor and preterm birth. However, the scarcity of robust and user-friendly software tools for multichannel EHG analysis has limited its wider adoption in both research and clinical practice. This dissertation presents the development of UterineExplorerPLUS (UExPLUS), a MATLAB-based platform designed to process, analyze, and visualize EHG signals. Migrating from the outdated GUIDE system to AppDesigner, UExPLUS introduces a modular and sustainable structure that integrates a wide range of methods within a unified environment. These include spectral and time-frequency analyses (Welch, Continuous Wavelet Transform, Empirical Mode Decomposition), nonlinear complexity measures (Approximate Entropy, Sample Entropy, Fuzzy Entropy, Conditional Entropy), clustering algorithms, and adaptive filtering. A key contribution is the implementation of a robust Alvarez wave detector, based on strict spectral criteria and concatenation of waves less than three seconds apart, while filtering maternal respiration artefacts. Other innovations include improved pacemaker estimation, intrauterine pressure (IUP) analysis, and maternal respiration processing. UExPLUS also enables multichannel visualization through scalograms and spectrograms, supporting the estimation of instantaneous frequency, bandwidth, and energy distributions. Validation with public datasets, such as the Icelandic 16-channel database, confirmed the reliability and versatility of the platform. Results demonstrate that UExPLUS provides accurate computation, clear visualization, and reproducible storage of multiple uterine activity parameters. This work contributes to computational obstetrics by offering an integrated and extensible toolbox for EHG analysis, paving the way for future clinical translation and supporting the early detection of labor complications, particularly preterm birth.application/pdfengElectrohysterographyUterine ElectromyographyPreterm laborPregnancy MonitoringComputational Obstetricsmaster thesis204174619