THE DETECTION AND ESTIMATION OF THE AIR LEAKAGE IN NONINVASIVE VENTILaTION: PLATFORM STUDY

Abstract

Although noninvasive ventilation has been increasingly used in clinics and homes to treat respiratory diseases, the problem of air leaks should not be neglected because they may affect the performance of the ventilation and even pose a threat to life. The detection and estimation of the leakage are required to implement auto-compensation, which is important in the development of intelligent ventilation. In this study, the methods of detection and estimation of the leakage were established and validated. Ventilation experiments were performed based on the established experimental platform. The air flow and pressure were detected at different locations of the airway to determine the relationship between the leakage and the other variables. The leakage was estimated using linear predictor models. The curves describing the relationships among pressure, flow and volume changed regularly with the leakage. For pressure-controlled ventilation, the leakage could be estimated by the detected peak flow and by the ventilation volume of one breathing cycle. The methods for the leakage estimation were validated. Volume-controlled ventilation was also studied. Although the leakage could be estimated using the detected peak pressure, the limitation of volume-controlled ventilation was obvious for noninvasive ventilation (NIV). Leaks could be detected and estimated using a linear predictor model via the flow/pressure curve. The use of this model is a potential method for the auto-compensation of noninvasive ventilation.