PURPOSE: There is growing interest in the use of both variable and pressure-controlled ventilation (PCV). The combination of these approaches as "noisy PCV" requires adaptation of the mechanical ventilator to the respiratory system mechanics. Thus, we developed and evaluated a new control system based on the least-mean-squares adaptive approach, which automatically and continuously adjusts the driving pressure during PCV to achieve the desired variability pattern of tidal volume (V (T)). METHODS: The controller was tested during numerical simulations and with a physical model reproducing the mechanical properties of the respiratory system. We applied step changes in respiratory system mechanics and mechanical ventilation settings. The time needed to converge to the desired V (T) variability pattern after each change (t (c)) and the difference in minute ventilation between the measured and target pattern of V (T) (DeltaMV) were determined. RESULTS: During numerical simulations, the control system for noisy PCV achieved the desired variable V (T) pattern in less than 30 respiratory cycles, with limited influence of the dynamic elastance (E*) on t (c), except when E* was underestimated by >25%. We also found that, during tests in the physical model, the control system converged in <60 respiratory cycles and was not influenced by airways resistance. In all measurements, the absolute value of DeltaMV was <25%. CONCLUSION: The new control system for noisy PCV can prove useful for controlled mechanical ventilation in the intensive care unit.
A novel adaptive control system for noisy pressure-controlled ventilation: a numerical simulation and bench test study.
PELOSI, PAOLO PASQUALINO;
2010-01-01
Abstract
PURPOSE: There is growing interest in the use of both variable and pressure-controlled ventilation (PCV). The combination of these approaches as "noisy PCV" requires adaptation of the mechanical ventilator to the respiratory system mechanics. Thus, we developed and evaluated a new control system based on the least-mean-squares adaptive approach, which automatically and continuously adjusts the driving pressure during PCV to achieve the desired variability pattern of tidal volume (V (T)). METHODS: The controller was tested during numerical simulations and with a physical model reproducing the mechanical properties of the respiratory system. We applied step changes in respiratory system mechanics and mechanical ventilation settings. The time needed to converge to the desired V (T) variability pattern after each change (t (c)) and the difference in minute ventilation between the measured and target pattern of V (T) (DeltaMV) were determined. RESULTS: During numerical simulations, the control system for noisy PCV achieved the desired variable V (T) pattern in less than 30 respiratory cycles, with limited influence of the dynamic elastance (E*) on t (c), except when E* was underestimated by >25%. We also found that, during tests in the physical model, the control system converged in <60 respiratory cycles and was not influenced by airways resistance. In all measurements, the absolute value of DeltaMV was <25%. CONCLUSION: The new control system for noisy PCV can prove useful for controlled mechanical ventilation in the intensive care unit.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.