Impact Factor

Original Research ARTICLE

Front. Physiol., 25 July 2012 | http://dx.doi.org/10.3389/fphys.2012.00298

Estimation of cardiac output and peripheral resistance using square-wave-approximated aortic flow signal

  • Department of Mechanical Engineering, University of Alberta, Edmonton, AB, Canada

This paper presents a model-based approach to estimation of cardiac output (CO) and total peripheral resistance (TPR). In the proposed approach, the response of cardiovascular system (CVS), described by the windkessel model, is tuned to the measurements of systolic, diastolic and mean arterial blood pressures (BP) so as to yield optimal individual- and time-specific system time constant that is used to estimate CO and TPR. Unique aspects of the proposed approach are that it approximates the aortic flow as a train of square waves and that it also assumes pressure-dependent arterial compliance, as opposed to the traditional windkessel model in which aortic flow is approximated as a train of impulses and constant arterial compliance is assumed. It was shown that the proposed model encompasses the standard windkessel model as a limiting case, and that it also yields more realistic BP waveform response than the standard windkessel model. The proposed approach has potential to outperform its standard counterpart by treating systolic, diastolic, and mean BP as independent features in estimating CO and TPR, rather than solely resorting to pulse pressure as in the case of the standard windkessel model. Experimental results from in-vivo data collected from a number of animal subjects supports the viability of the proposed approach in that it could achieve approximately 29% and 24% reduction in CO and TPR errors when compared with its standard counterpart.

Keywords: cardiovascular system, cardiac output, peripheral resistance, windkessel model, pressure-dependent arterial compliance

Citation: Fazeli N and Hahn J-O (2012) Estimation of cardiac output and peripheral resistance using square-wave-approximated aortic flow signal. Front. Physio. 3:298. doi: 10.3389/fphys.2012.00298

Received: 16 May 2012; Accepted: 10 July 2012;
Published online: 25 July 2012.

Edited by:

Zhe Chen, Massachusetts Institute of Technology, USA

Reviewed by:

Lucy T. Zhang, Rensselaer Polytechnic Institute, USA
Marek Matejak, Charles University, Czech Republic

Copyright © 2012 Fazeli and Hahn. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

*Correspondence: Jin-Oh Hahn, Department of Mechanical Engineering, University of Alberta, 4-9 Mechanical Engineering Building, Edmonton, AB T6G 2G8, Canada. e-mail: jinoh.hahn@alum.mit.edu