Removal of Baseline Wander from ECG signal using Cascaded Empirical Mode Decomposition and Morphological Functions

The ECG is a record of the electrical activities of the heart. It is used for the diagnosis of a number of cardiac defects such as arrhythmias, AF etc. Quite often they get corrupted by various kinds of artifacts, thus in order to obtain proper information from them they must first be denoised. Baseline wander artifact is one of the most common artifact of ECG. This paper presents a novel approach for the filtering of low frequency baseline wander artifact of ECG signals by using a combination of Empirical Mode Decomposition (EMD) and morphological functions. By using this novel approach for denoising of baseline wander artifact, it is ensured that morphological information from the ECG signal remain preserved.