Machine Learning Framework for Noise Detection and Classification of Electrocardiogram (ECG)

This thesis aims to develop a knowledge-based filtering system for improving the quality of electrocardiogram (ECG) signals acquired in everyday situations. This system will enhance remote heart health monitoring using wearable devices, enabling early detection of various life-threatening cardiovascular issues.