@article {10.3844/ajbbsp.2020.103.111,
article_type = {journal},
title = {ECG Energy Change Study Based on Variational Mode Decomposition},
author = {Dong, Kai and Sun, Lin and Xiong, Hongjun and Wang, Wenbo},
volume = {16},
number = {1},
year = {2020},
month = {Mar},
pages = {103-111},
doi = {10.3844/ajbbsp.2020.103.111},
url = {https://thescipub.com/abstract/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.},
journal = {American Journal of Biochemistry and Biotechnology},
publisher = {Science Publications}
}