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    Nonlinear modelling of renal vasoaction


    Mangourova, Violeta and Ringwood, John and Guild, Sarah-Jane and Malpas, Simon (2007) Nonlinear modelling of renal vasoaction. Biomedical Signal Processing and Control, 2 (2). pp. 258-266. ISSN 1746-8094

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    Abstract

    The control of blood pressure is a complex mixture of neural, hormonal and intrinsic interactions at the level of the heart, kidney and blood vessels. While experimental approaches to understanding these interactions are useful, it remains difficult to conduct experiments to quantify these interactions as the number of parameters increases. Thus, modelling of such physiological systems can offer considerable assistance. Typical mathematical models which describe the ability of the blood vessels to change their diameter (vasoconstriction) assume linearity of operation. However, due to the interaction of multiple vasocontrictive and vasodilative effectors, there is a significant nonlinear response to the influence of neural factors, particularly at higher levels of nerve activity (often seen in subjects with high blood pressure) which leads to low blood flow rates. This paper proposes a number of nonlinear mathematical models for the relationship between neural influences (sympathetic nerve activity (SNA)) and renal blood flow, using a feedback path to model the predominantly nonlinear effect of local vasoactive modulators such as nitric oxide, which oppose the action of SNA. The model structures are motivated by basic physiological principles, while the model parameters are determined using numerical optimisation techniques using open-loop data collected from rabbits. The models were verified by demonstrating correlation between experimental results and model outputs.

    Item Type: Article
    Keywords: Biomedical systems; Mathematical model; Blood flow; Nonlinear analysis; Numerical optimisation;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 6899
    Identification Number: https://doi.org/10.1016/j.bspc.2007.07.001
    Depositing User: Professor John Ringwood
    Date Deposited: 20 Jan 2016 17:42
    Journal or Publication Title: Biomedical Signal Processing and Control
    Publisher: Elsevier
    Refereed: Yes
    URI:

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