ECG Feature Analysis by Continuous Wavelet based Second-order Synchrosqueezing Transform

Abstract

Continuous wavelet based second-order synchrosqueezing transform (WSST2nd) decomposes the signal into some intrinsic mode type functions (IMTFs) according with second-order instantaneous frequency and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signals. Energy of ECG signals 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 WSST2nd, 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. The comparing results show that heart disease could cause high-frequency components of the WSST2nd energy vector to drop significantly, especially the energy of IMTF1 component varies greatly; this drop trend has a good discrimination and can be used as a reference for heart disease diagnosis. It can be seen according to the experimental results that the decomposition results of WSST2nd are dependent on the ECG signal itself, and can better reflect the impacts of age and disease on ECG energy distribution.