Laboratorio Nacional Of Computacao Centifica

Brazil

Laboratorio Nacional Of Computacao Centifica

Brazil

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Trenhago P.R.,Laboratorio Nacional Of Computacao Centifica | Fernandes L.G.,Federal Rural University of Rio de Janeiro | Muller L.O.,Laboratorio Nacional Of Computacao Centifica | Blanco P.J.,Laboratorio Nacional Of Computacao Centifica | Feijoo R.A.,Laboratorio Nacional Of Computacao Centifica
International Journal for Numerical Methods in Biomedical Engineering | Year: 2016

This study presents a lumped model for the human cardiorespiratory system. Specifically, we incorporate a sophisticated gas dissociation and transport system to a fully integrated cardiovascular and pulmonary model. The model provides physiologically consistent predictions in terms of hemodynamic variables such as pressure, flow rate, gas partial pressures, and pH. We perform numerical simulations to evaluate the behavior of the partial pressures of oxygen and carbon dioxide in different vascular and pulmonary compartments. For this, we design the rest condition with low oxygen requirements and carbon dioxide production and exercise conditions with high oxygen demand and carbon dioxide production. Furthermore, model sensitivity to more relevant model parameters is studied. © 2016 John Wiley & Sons, Ltd.


PubMed | Federal Rural University of Rio de Janeiro and Laboratorio Nacional Of Computacao Centifica
Type: Journal Article | Journal: International journal for numerical methods in biomedical engineering | Year: 2016

This study presents a lumped model for the human cardiorespiratory system. Specifically, we incorporate a sophisticated gas dissociation and transport system to a fully integrated cardiovascular and pulmonary model. The model provides physiologically consistent predictions in terms of hemodynamic variables such as pressure, flow rate, gas partial pressures, and pH. We perform numerical simulations to evaluate the behavior of the partial pressures of oxygen and carbon dioxide in different vascular and pulmonary compartments. For this, we design the rest condition with low oxygen requirements and carbon dioxide production and exercise conditions with high oxygen demand and carbon dioxide production. Furthermore, model sensitivity to more relevant model parameters is studied. Copyright 2015 John Wiley & Sons, Ltd.

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