ECG Energy Change Study Based on Variational Mode Decomposition

Kai Dong,Hongjun Xiong,Lin Sun,Wenbo Wang

doi:10.3844/ajbbsp.2020.103.111

Abstract

Variational Mode Decomposition (VMD) decomposes the signal into a series of Intrinsic Mode Type Functions (IMTFs) according with variational model and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signal. Energy of ECG signal has certain distribution rules, but which could be affected by diseases; therefore, the study of ECG energy distribution change is of great importance to the research and clinical diagnosis of heart diseases. In this paper, firstly, ECG signals are decomposed into a series IMTFs with VMD and the fluctuating characteristics and physical meanings of ECG signals on different time scale are analyzed by observing the fluctuation rule of IMTFs. Then, the energy vectors of ECG signals are obtained by calculating the energy of each IMTF and a comparative analysis of energy vectors is conducted between healthy people and three kinds of heart disease patients. It can be seen according to the experimental results that heart disease could cause high-frequency components of the VMD energy vector to drop significantly and the VMD energy vector can well reflect the impacts of age and disease on ECG energy distribution, which can be used as a reference for heart disease diagnosis.

Highlights

As the comprehensive reflection of the heart electrical activity on the surface of the body, Electrocardiogram (ECG) can serve as an important reference in the study of basic heart functions and disease diagnoses (Rakshit and Das, 2018)
The ECG signals are decomposed into a group Intrinsic Mode Type Functions (IMTFs) by the Variational Mode Decomposition (VMD)
By applying the IMTFS energy vectors method to study ECG signals, the effects of age and heart diseases on the distribution of the VMD energy vector have been discovered: The energies of highfrequency IMTFs gradually decrease with age and disease and the decrease degree is positively correlated with disease severity

Summary

Introduction

As the comprehensive reflection of the heart electrical activity on the surface of the body, Electrocardiogram (ECG) can serve as an important reference in the study of basic heart functions and disease diagnoses (Rakshit and Das, 2018). Frequency analysis and Time-Frequency analysis are the main methods for studying variation of ECG energy distribution. The time-frequency analysis methods can reflect the time and frequency feature of ECG signal, which have obtained very good analysis results in QRS wave group detection, ECG identification and classification, disease diagnosis, etc (Banerjee and Mitra 2014; Nguyen et al, 2017; Peng et al, 2014; Kai-Yu et al, 2012). The experimental results show that, the ECG energy vectors based on VMD method can provided an effective reference for the research and diagnosis of heart disease

Analysis Method of VMD Energy Vector

Conclusion and Perspectives

Findings

Conflict of Interest