(2025) Allam, Majdouline; García Galán, Sebastián; Muñoz Expósito, José Enrique; Universidad de Jaén. Ingeniería de Telecomunicación
[en] In clinical cardiology, the QT interval is an important marker for determining arrhythmia risk and has typically been assessed using electrocardiograms (ECGs). However, due to the expense and complexity of the technology, ECG monitoring may be prohibitive in some situations. This thesis investigates the feasibility of measuring the QT interval using phonocardiogram (PCG) data, which provides a more accessible and non-invasive alternative. The project evaluates a database of 409 simultaneous ECG and PCG recordings. PCG features including S1, S2, Systole, and Diastole durations are recovered using hand-corrected annotations as well as the Springer segmentation technique. The project develops two predictive models: a Bayesian-optimized support vector machine (SVM) regression model and an explicit multiple linear regression model
