Empirical mode decomposition vs. variational mode decomposition on ECG signal processing: A comparative study

Most of the non-stationary signals need adaptive processing technique for denoising, signal processing for feature extraction and analysis. In this regard, signal decomposition methods plays a vital role as selective reconstruction extracts the enhanced version of the signal buried in the noise. Decomposition mode based analysis also becomes popular especially in case of biosignals due to their highly non-stationary nature. Biosignals are better decomposed by a technique where basis function is derived from the signal itself. This data adaptive decomposition of biosignals into different frequency modes is very effective irrespective of multiple periodicities present in the signal or unknown sampling rate. This paper aims to study the performance of Empirical Mode Decomposition (EMD) and the Variational Mode Decomposition (VMD) technique over the popular ECG signal in terms of different periodicities during various cardiac abnormalities. The results highlight the main differences between the methods in range of signal decomposition levels as well as ability of extracting both low and high frequency from the signal.