Paper Info
Title
Investigating properties of the cardiovascular system using innovative analysis algorithms based on ensemble empirical mode decomposition.
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.
Year
DOI
Venue
2012
10.1155/2012/943431
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
Keywords
Field
DocType
algorithms,arterial pressure,cardiovascular system,monte carlo method,blood pressure,computer simulation
Artery,Clamping,Signal processing,Oscillation,Nonlinear system,Computer science,Algorithm,Arterial stiffness,Blood pressure,Hilbert–Huang transform
Journal
Volume
ISSN
Citations 
2012
1748-670X
2
PageRank 
References 
Authors
0.51
4
6
Name
Order
Citations
PageRank
Jia-Rong Yeh1685.99
Tzu-Yu Lin2353.84
Yun Chen3156.17
Wei-Zen Sun485.51
Maysam F. Abbod522428.14
Jiann Shing Shieh622428.44