Wavelet permutation entropy analysis of Ventricular Fibrillation and Sudden Cardiac Death ECG signals

DOI

10.2991/iiicec-15.2015.51How to use a DOI?

Keywords

Ventricular Fibrillation Signals; Sudden Cardiac Death Signals; Wavelet Analysis; Reconstruction; Permutation Entropy

Abstract

In this paper, we applied wavelet permutation entropy to analyze the Ventricular Fibrillation (VF) signals and Sudden Cardiac Death (SCD) signals for making an effective distinction from normal sinus rhythm (NSR) signals. Firstly, three different ECG signals are decomposed by wavelet and reconstructed in each single layer. Then highly discriminated frequency band will be chosen as our target band. Furthermore, under the circumstances of different series length, embedding dimension and delay time, the main work is to distinguish the three ECG signals in different frequency bands based on the permutation entropy (PE). The results show that permutation entropy method can make a distinction between normal and abnormal ECG signals which aren’t decomposed, but the effect of decomposing with wavelets is better more. And the highest discriminated frequency band is from 15.625 Hz to 31.25 Hz .From the point of different data length, embedding dimension and delay time, it was found that permutation entropy method have different effects and the findings may assist cardiac clinical diagnosis.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lei Yang
AU  - Fengzhen Hou
AU  - Jun Wang
PY  - 2015/03
DA  - 2015/03
TI  - Wavelet permutation entropy analysis of Ventricular Fibrillation and Sudden Cardiac Death ECG signals
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 216
EP  - 219
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.51
DO  - 10.2991/iiicec-15.2015.51
ID  - Yang2015/03
ER  -