STUDY ON THE EFFECTIVENESS OF WAVELETS FOR DENOISING ECG SIGNALS USING SUBBAND DEPENDENT THRESHOLD

Abstract

An electrocardiogram (ECG) is a bioelectrical signal which records the heart’s electrical activity versus time on the body surface via contact electrodes. The recorded ECG signal is often contaminated by noise and artifacts that can be within the frequency band of interest. This noise can hide some important features of the ECG signal. The focus of this thesis is the application of new modified versions of the Universal threshold to allow additional enhancements in the reduction of ECG noise. Despite the fact that there are many types of contaminating noises in ECG signals, only white noise and baseline wandering will be considered. This type of noise is undesirable and needs to be removed prior to any additional signal processing for proper analysis and display of the ECG signal.