ESTIMATION OF CARDIAC OUTPUT AND PERIPHERAL RESISTANCE USING SQUARE-WAVE-APPROXIMATED AORTIC FLOW SIGNAL

摘要

This paper presents a model-based approach to the estimation of cardiac output (CO) and total peripheral resistance (TPR). The cardiovascular system (CVS) model is characterized by fitting its response to the measurements of systolic, diastolic, and mean blood pressures (BP). In contrast to the standard windkessel-model-based approach to CO and TPR estimation (which approximates the aortic flow signal as a train of impulses), the proposed approach uses the aortic flow signal that is approximated as a train of square waves to yield more realistic BP waveforms. It is shown that the proposed method encompasses its standard counterpart as a limiting case. It is also suggested that the proposed method may outperform the standard method by treating systolic, diastolic, and mean BP as independent features, rather than solely resorting to a single feature (i.e. the pulse pressure) as in the case of the standard method. Experimental results from in-vivo animal study illustrated that the proposed approach could achieve 17% and 12% reduction in CO and TPR errors compared with the standard approach.