Respiratory Mechanics, Gas Transport and Perfusion during exercise

Abstract Several mathematical models of the respiratory system and gas transport have been proposed in order to explain the behavior of this complex system. These potential tools can help clinicians to understand pathophysiological processes as well as to improve medical therapies, especially under the clinical point of view. In this paper, a nonlinear dynamic mathematical model able to represent the relationship between lungs, blood and tissues is proposed. The aim of this system is to analyse the mechanics of breathing, gas transport and perfusion under different circumstances: resting, exercise and recovery. In this paper four principal components of this physiological system are highly focused: lungs, pulmonary capillaries, lungs and systemic capillaries. For the implementation, Dymola, an objected-oriented physical modelling language, was used. The results achieved show the ability of the implemented model to reproduce the main features of the system's response in terms of ventilation and gas exchange. Moreover, it also demonstrates the ability and feasibility to simulate the dynamics of pressures and concentrations of carbon dioxide (CO 2 ) and oxygen (O 2 ) in the pulmonary and systemic circulation. In order to validate the results, they are compared with data from other papers. To sum up, by implementing this sophisticated model the multifactorial interactions between changes in ventilation, perfusion and diffusion before, during and after exercise can be studied.

[1]  Y Miyamoto,et al.  Dynamics of cardiac, respiratory, and metabolic function in men in response to step work load. , 1982, Journal of applied physiology: respiratory, environmental and exercise physiology.

[2]  G. Grimby,et al.  Respiration in Exercise , 1969 .

[3]  G. Grimby,et al.  Respiratory muscle action inferred from rib cage and abdominal V-P partitioning. , 1976, Journal of applied physiology.

[4]  R. W. Jones,et al.  Respiratory responses to CO2 inhalation; a theoretical study of a nonlinear biological regulator. , 1954, Journal of applied physiology.

[5]  Steen Andreassen,et al.  A model of perfusion of the healthy human lung , 2011, Comput. Methods Programs Biomed..

[6]  Keith Stokes,et al.  Physiological effects of exercise , 2004 .

[7]  Fleur T. Tehrani,et al.  Function of brainstem neurons in optimal control of respiratory mechanics , 2003, Biological Cybernetics.

[8]  D M Rapoport,et al.  CO2 homeostasis during periodic breathing: predictions from a computer model. , 1993, Journal of applied physiology.

[9]  P. Robbins,et al.  A mathematical model of the human ventilatory response to isocapnic hypoxia. , 1993, Journal of applied physiology.

[10]  John E. Remmers,et al.  A Computational Model of the Human Respiratory Control System: Responses to Hypoxia and Hypercapnia , 2004, Annals of Biomedical Engineering.

[11]  F. Grodins,et al.  MATHEMATICAL MODELS OF RESPIRATORY REGULATION * , 1963, Annals of the New York Academy of Sciences.

[12]  H. Thamrin,et al.  Modelling the respiratory control system in human subjects for excercise conditions , 2008 .

[13]  S J Connellan,et al.  The effects of nebulized salbutamol on lung function and exercise tolerance in patients with severe airflow obstruction. , 1982, British journal of diseases of the chest.

[14]  H. Milhorn,et al.  A MATHEMATICAL MODEL OF THE HUMAN RESPIRATORY CONTROL SYSTEM. , 1965, Biophysical journal.

[15]  A. Jackson,et al.  Digital computer simulation of respiratory mechanics. , 1973, Computers and biomedical research, an international journal.

[16]  Steen Andreassen,et al.  A model of ventilation of the healthy human lung , 2011, Comput. Methods Programs Biomed..

[17]  J. S. Gray,et al.  The Multiple Factor Theory of the Control of Respiratory Ventilation. , 1946, Science.

[18]  E R Carson,et al.  A breathing model of the respiratory system; the controlled system. , 1980, Journal of theoretical biology.

[19]  A. J. Bart,et al.  Mathematical analysis and digital simulation of the respiratory control system. , 1967, Journal of applied physiology.