Computational and Mathematical Methods in Medicine
Volume 2012 (2012), Article ID 943431, 11 pages
http://dx.doi.org/10.1155/2012/943431
Research Article
Investigating Properties of the Cardiovascular System Using Innovative Analysis Algorithms Based on Ensemble Empirical Mode Decomposition
1Research Center for Adaptive Data Analysis & Center for Dynamical Biomarkers and Translational Medicine,
National Central University, Jhongli 3200, Taiwan
2Department of Mechanical Engineering, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li, Taoyuan 320, Taiwan
3Department of Anesthesiology, Far Eastern Memorial Hospital, Taipei 220, Taiwan
4Department of Surgery, Far Eastern Memorial Hospital, Taipei 22060, Taiwan
5Department of Chemical Engineering & Materials Science, Yuan Ze University, Taoyuan 320, Taiwan
6Department of Anesthesiology, College of Medicine, National Taiwan University, Taipei 100, Taiwan
7School of Engineering and Design, Brunel University, London UB83PH, UK
Received 3 March 2012; Revised 31 May 2012; Accepted 15 June 2012
Academic Editor: Amaury Lendasse
Copyright © 2012 Jia-Rong Yeh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Cardiovascular system is known to be nonlinear and nonstationary. Traditional linear assessments algorithms of arterial stiffness and systemic resistance of cardiac system accompany the problem of nonstationary or inconvenience in practical applications. In this pilot study, two new assessment methods were developed: the first is ensemble empirical mode decomposition based reflection index (EEMD-RI) while the second is based on the phase shift between ECG and BP on cardiac oscillation. Both methods utilise the EEMD algorithm which is suitable for nonlinear and nonstationary systems. These methods were used to investigate the properties of arterial stiffness and systemic resistance for a pig’s cardiovascular system via ECG and blood pressure (BP). This experiment simulated a sequence of continuous changes of blood pressure arising from steady condition to high blood pressure by clamping the artery and an inverse by relaxing the artery. As a hypothesis, the arterial stiffness and systemic resistance should vary with the blood pressure due to clamping and relaxing the artery. The results show statistically significant correlations between BP, EEMD-based RI, and the phase shift between ECG and BP on cardiac oscillation. The two assessments results demonstrate the merits of the EEMD for signal analysis.