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Optimal determination of respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system.

Li H, Haddad WM - Comput Math Methods Med (2012)

Bottom Line: We develop optimal respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system.Specifically, we use classical calculus of variations minimization techniques to derive an optimal airflow pattern for inspiratory and expiratory breathing cycles.Finally, we numerically integrate the resulting nonlinear two-point boundary value problems to determine the optimal airflow patterns over the inspiratory and expiratory breathing cycles.

View Article: PubMed Central - PubMed

Affiliation: School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA.

ABSTRACT
We develop optimal respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system. Specifically, we use classical calculus of variations minimization techniques to derive an optimal airflow pattern for inspiratory and expiratory breathing cycles. The physiological interpretation of the optimality criteria used involves the minimization of work of breathing and lung volume acceleration for the inspiratory phase, and the minimization of the elastic potential energy and rapid airflow rate changes for the expiratory phase. Finally, we numerically integrate the resulting nonlinear two-point boundary value problems to determine the optimal airflow patterns over the inspiratory and expiratory breathing cycles.

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Optimal volume x*(t) versus time for a four-compartmental model.
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Related In: Results  -  Collection


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fig11: Optimal volume x*(t) versus time for a four-compartmental model.

Mentions: Finally, Figure 11 shows the optimal air volume trajectories for a four-compartment model with each air volume trajectory satisfying the boundary conditions given in (18), (19), (28), and (29). For this simulation, the compliance parameters are taken to be identical to those used for the two-compartment model with i = 1,2, 3,4, and the values for airway resistances are generated using the results of [30].


Optimal determination of respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system.

Li H, Haddad WM - Comput Math Methods Med (2012)

Optimal volume x*(t) versus time for a four-compartmental model.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3376482&req=5

fig11: Optimal volume x*(t) versus time for a four-compartmental model.
Mentions: Finally, Figure 11 shows the optimal air volume trajectories for a four-compartment model with each air volume trajectory satisfying the boundary conditions given in (18), (19), (28), and (29). For this simulation, the compliance parameters are taken to be identical to those used for the two-compartment model with i = 1,2, 3,4, and the values for airway resistances are generated using the results of [30].

Bottom Line: We develop optimal respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system.Specifically, we use classical calculus of variations minimization techniques to derive an optimal airflow pattern for inspiratory and expiratory breathing cycles.Finally, we numerically integrate the resulting nonlinear two-point boundary value problems to determine the optimal airflow patterns over the inspiratory and expiratory breathing cycles.

View Article: PubMed Central - PubMed

Affiliation: School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0150, USA.

ABSTRACT
We develop optimal respiratory airflow patterns using a nonlinear multicompartment model for a lung mechanics system. Specifically, we use classical calculus of variations minimization techniques to derive an optimal airflow pattern for inspiratory and expiratory breathing cycles. The physiological interpretation of the optimality criteria used involves the minimization of work of breathing and lung volume acceleration for the inspiratory phase, and the minimization of the elastic potential energy and rapid airflow rate changes for the expiratory phase. Finally, we numerically integrate the resulting nonlinear two-point boundary value problems to determine the optimal airflow patterns over the inspiratory and expiratory breathing cycles.

Show MeSH