Modelling of Long and Short Term Blood Pressure Control Systems

Blood pressure levels are tightly controlled in the body by a variety of interconnected mechanisms at the short-, medium- and long-term scale. In pathophysiological conditions, blood pressure may be chronically elevated above normal levels, which can lead to the development of cardiovascular disease and increased mortality. Building a complete picture of the mechanisms involved in blood pressure control is vital for the development of a better understanding of the processes that may lead to hypertension. Mathematical models of physiological systems can greatly aid in our understanding of the systems under study, and can also be used in teaching and research tools. This thesis develops a range of mathematical models of various blood pressure control systems and present a diverse set of generic modelling tools, which can be applied to other aspects of human physiology also. A set of nonlinear grey-box models of varying complexities are developed in this thesis to model the process of salt-induced hypertension in Dahl rats. The models successfully replicate the multiphasal response of blood pressure to high salt intake and provide information on the magnitudes and time scales of the various response components. The renal vasculature response to sympathetic nerve activity is also modelled by a nonlinear grey-box model. The model represents the renal blood ow response to electrical renal nerve stimulation, under the condition of renal denervation, which can aid in the development of an overall model of the neural control of blood pressure. In contrast, a linear black-box modelling approach is taken in this thesis to represent the arterial barore ex, since barore ex impairment has been associated with a number of conditions such as hypertension, myocardial infarction and heart failure. A measure of the gain of the barore ex, the barore ex sensitivity index, can be a useful diagnostic and prognostic tool in cardiology. This thesis develops a rigorous system identifcation approach to barore ex sensitivity estimation, based on a linear black-box model of the barore ex. Finally, this thesis presents a novel visual, hierarchical, implementation of Arthur Guyton's famous integrative physiology model (Guyton et al., 1972b), in a modelling and simulation environment, which could potentially facilitate its use and further development