期刊
SIMULATION MODELLING PRACTICE AND THEORY
卷 16, 期 8, 页码 988-997出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.simpat.2008.04.016
关键词
cardiac output; arterial stiffness; embedded simulation; differential equations; neural networks
The aim of the presented work has been the development of an algorithm for a non-invasive, portable, easy-to-use, and affordable device for measuring systemic cardiovascular parameters such as cardiac output and peripheral resistance. The data acquisition is based on a common oscillometric measurement using an occlusive blood pressure cuff, and no additional calibration is necessary. The novel algorithm introduced here combines several simulation techniques like neural networks or differential equations, which will be explained briefly. The determination of the hemodynamical parameters is based on the idea that the ejection work of the left ventricle is subject to an optimization principle. This kind of model needs no additional external calibration and opens therefore good perspectives for non-expert use in cardiovascular risk stratification and hypertension therapy optimization. To verify the approach we present some clinical results and a relevant discussion on it, followed by a view of future work. (C) 2008 Elsevier B.V. All rights reserved.
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