Key result
Object-oriented electrical modeling aligns with clinical data for predicting exercise cardiorespiratory interactions.
Why the study?
Modelling the human cardiorespiratory system with computer simulation tools can help physicians comprehend the causes and development of cardiorespiratory diseases.
An object-oriented computer simulation model using electrical analogies provides a valuable tool for predicting cardiorespiratory interactions during exercise without complex mathematical models.
Modelling the human cardiorespiratory system using computer simulation tools can serve to help physicians to comprehend the causes and development of cardiorespiratory diseases. The objective of this paper is to develop an integrated model of the cardiovascular and respiratory systems, along with their intrinsic control mechanisms, by combining analogous hydraulic-electric and diffusion-electric circuits, respectively. This modelling task is performed in object-oriented language in SIMSCAPE using the physical interconnected components to define the underlying dynamic equations. Simulation steady state results under rest and under variable physical exercise conditions, as well as under limiting conditions show a high qualitative agreement with clinical observations reported in literature. This object-oriented modelling approach, based on the combined use of electrical analogies, proves to be avaluable tool as a test bench for different strategies aimed to qualitative prediction of the effects of cardiorespiratory interactions during exercise, thus avoiding the formulation of complex mathematical models.
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Cañete et al. (2021) studied Cardiorespiratory diseases. Integrated model of the cardiovascular and respiratory systems using analogous hydraulic-electric and diffusion-electric circuits was evaluated on Simulation steady state results under rest and variable physical exercise conditions. An object-oriented modelling approach using combined electrical analogies showed high qualitative agreement with clinical observations for predicting cardiorespiratory interactions during exercise.
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