A feedback control approach to the estimation of patient airway and leak flow for Non-Invasive, Positive Pressure Ventilation (NPPV)

摘要

Estimation of patient airway flow by remote sensing is a practical alternative in critical care ventilation to direct measurement using a flow sensor at the patient connection which can present a number of issues including fouling by patient secretions. This paper describes a new algorithm that estimates patient airway and leak flow for Non-Invasive Positive Pressure Ventilation (NPPV). The estimator does not require any knowledge of the patient lung mechanics nor the use of measurement signal derivatives, but rather uses simple feedback control, measurements of the proximal pressure, ventilator inlet flow, and a nonlinear model of the connecting circuit. Unknown (disturbance) leaks occur during breath delivery, and these are further managed using a separate feedback controller that minimizes the averaged net flow for each breath. The combined controllers results in an effective integrated system that accurately tracks true airway flow with low noise and minimum bias, accurate accounting of patient leak, and improved patient data and breath triggering capability.