A system identification approach to baroreflex sensitivity estimation

The body contains a bewildering array of regulatory systems which maintain homeostasis. There is considerable difficulty in isolating a single control loop for analysis, due to the interactions with other systems/loops. One important such regulatory loop is the baroreflex, and baroreflex sensitivity is a characteristic open-loop parameter which can help us to assess the health of the baroreflex. A diverse range of methods have been proposed to determine baroreflex sensitivity from experimental data. Unfortunately, there appears to be little consistency of result among the different methods and some explanation can be found in the nature of the problem: In most cases, an attempt is being made to determine open-loop measures from a system operating in closed-loop, subject to poor excitation. In this paper we propose a strict procedure, based on a rigourous mathematical framework, from which reliable estimates of baroreflex sensitivity can be obtained. A comparison with other methods for baroreflex sensitivity estimation, using the EuroBaVar data set, is performed

A system identication approach to baroreflex sensitivity estimation

The body contains a bewildering array of regulatory systems which maintain homeostasis. There is considerable dificulty in isolating a single control loop for analysis, due to the interactions with other systems/loops. One important such regulatory loop is the baroreflex, and baroreflex sensitivity is a characteristic open-loop parameter which can help us to assess the health of the baroreflex. A diverse range of methods have been proposed to determine baroreflex sensitivity from experimental data. Unfortunately, there appears to be little consistency of result among the different methods and some explanation can be found in the nature of the problem: In most cases, an attempt is being made to determine open-loop measures from a system operating in closed-loop, subject to poor excitation. In this paper we propose a strict procedure, based on a rigourous mathematical framework, from which reliable estimates of baroreflex sensitivity can be obtained. A comparison with other methods for baroreflex sensitivity estimation, using the EuroBaVar data set, is performed

A 5-component model for salt-induced hypertension

Salt-induced hypertension has been widely studied in rats, monkeys, chimpanzees and humans. Until recently, the multiple phases of this blood pressure increase to high salt intake had not been closely studied. This work builds upon a recent study, which developed a grey-box multicomponent model of salt-induced hypertension in the Dahl-S rat. The previous 3-component model has been extended here to include additional model dynamics to improve the model fit and add new important elements to the model response. The model was optimised using numerical techniques with experimental data from 4 different protocols with Dahl-S and hybrid rats. Results show a marked improvement over the previous model and confirm the merit of the 5-component model structure

A 5-component mathematical model for salt-induced hypertension in Dahl-S and Dahl-R rats

Salt-induced hypertension has been demonstrated in a variety of species including rats, monkeys, chimpanzees and humans. Until recently, the multiple phases of this blood pressure increase due to high salt intake had not been closely studied. This work builds upon a recent study, which developed a grey-boxmulti-component model of salt-induced hypertension in the Dahl-S rat. The previous 3-component model has been extended here to include additional model dynamics to improve the model fit and add new important elements to the model response. The model was optimised using numerical techniques with experimental data from 4 different protocols with Dahl-S, Dahl-R and FF2 hybrid rats. Results show a marked improvement over the previous model and confirm the merit of the 5-component model structure. A comparison between the model dynamics for different rat strains has also been include

A multi-component model of the dynamics of salt-induced hypertension in Dahl-S rats

Background. In humans, salt intake has been suggested to influence blood pressure (BP) on a wide range of time scales ranging from several hours or days to many months or years. Detailed time course data collected in the Dahl salt-sensitive rat strain suggest that the development of salt-induced hypertension may consist of several distinct phases or components that differ in their timing and reversibility. To better understand these components, the present study sought to model the dynamics of salt-induced hypertension in the Dahl salt sensitive (Dahl-S) rat using 3 sets of time course data. Results. The first component of the model ("Acute-Reversible") consisted of a linear transfer function to account for the rapid and reversible effects of salt on BP (ie. acute salt sensitivity, corresponding with a depressed slope of the chronic pressure natriuresis relationship). For the second component ("Progressive-Irreversible"), an integrator function was used to represent the relatively slow, progressive, and irreversible effect of high salt intake on BP (corresponding with a progressive salt-induced shift of the chronic pressure natriuresis relationship to higher BP levels). A third component ("Progressive-Reversible") consisted of an effect of high salt intake to progressively increase the acute salt-sensitivity of BP (ie. reduce the slope of the chronic pressure natriuresis relationship), amounting to a slow and progressive, yet reversible, component of salt-induced hypertension. While the 3 component model was limited in its ability to follow the BP response to rapid and/or brief transitions in salt intake, it was able to accurately follow the slower steady state components of salt-induced BP changes. This model exhibited low values of mean absolute error (1.92 0.23, 2.13 0.37, 2.03 0.3 mmHg for data sets 1 - 3), and its overall performance was significantly improved over that of an initial model having only 2 components. The 3 component model performed well when applied to data from hybrids of Dahl salt sensitive and Dahl salt resistant rats in which salt sensitivity varied greatly in its extent and character (mean absolute error = 1.11 0.08 mmHg). Conclusion. Our results suggest that the slow process of development of salt-induced hypertension in Dahl-S rats over a period of many weeks can be well represented by a combination of three components that differ in their timing, reversibility, and their associated effect on the chronic pressure natriuresis relationship. These components are important to distinguish since each may represent a unique set of underlying mechanisms of salt-induced hypertension

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

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

A system identification approach to baroreflex sensitivity estimation

The body contains a bewildering array of regulatory systems which maintain homeostasis. There is considerable difficulty in isolating a single control loop for analysis, due to the interactions with other systems/loops. One important such regulatory loop is the baroreflex, and baroreflex sensitivity is a characteristic open-loop parameter which can help us to assess the health of the baroreflex. A diverse range of methods have been proposed to determine baroreflex sensitivity from experimental data. Unfortunately, there appears to be little consistency of result among the different methods and some explanation can be found in the nature of the problem: In most cases, an attempt is being made to determine open-loop measures from a system operating in closed-loop, subject to poor excitation. In this paper we propose a strict procedure, based on a rigourous mathematical framework, from which reliable estimates of baroreflex sensitivity can be obtained. A comparison with other methods for baroreflex sensitivity estimation, using the EuroBaVar data set, is performed

A system identication approach to baroreflex sensitivity estimation

The body contains a bewildering array of regulatory systems which maintain homeostasis. There is considerable dificulty in isolating a single control loop for analysis, due to the interactions with other systems/loops. One important such regulatory loop is the baroreflex, and baroreflex sensitivity is a characteristic open-loop parameter which can help us to assess the health of the baroreflex. A diverse range of methods have been proposed to determine baroreflex sensitivity from experimental data. Unfortunately, there appears to be little consistency of result among the different methods and some explanation can be found in the nature of the problem: In most cases, an attempt is being made to determine open-loop measures from a system operating in closed-loop, subject to poor excitation. In this paper we propose a strict procedure, based on a rigourous mathematical framework, from which reliable estimates of baroreflex sensitivity can be obtained. A comparison with other methods for baroreflex sensitivity estimation, using the EuroBaVar data set, is performed

A system identication approach to baroreflex sensitivity estimation

The body contains a bewildering array of regulatory systems which maintain homeostasis. There is considerable dificulty in isolating a single control loop for analysis, due to the interactions with other systems/loops. One important such regulatory loop is the baroreflex, and baroreflex sensitivity is a characteristic open-loop parameter which can help us to assess the health of the baroreflex. A diverse range of methods have been proposed to determine baroreflex sensitivity from experimental data. Unfortunately, there appears to be little consistency of result among the different methods and some explanation can be found in the nature of the problem: In most cases, an attempt is being made to determine open-loop measures from a system operating in closed-loop, subject to poor excitation. In this paper we propose a strict procedure, based on a rigourous mathematical framework, from which reliable estimates of baroreflex sensitivity can be obtained. A comparison with other methods for baroreflex sensitivity estimation, using the EuroBaVar data set, is performed