Analysis of nonlinear dynamic respiratory system mechanics: An improvement of the adaptive SLICE Method

Abstract

The estimation of nonlinear dynamic respiratory system mechanics may be useful for guiding the ventilator settings. The newly developed Adaptive SLICE Method (ASM) was proven to be efficient and precise in analysis of dynamic respiratory system compliance (Crs) and resistance (Rrs). In the present study, we improved the ASM by predicting the estimates with different confidence levels that cover the whole tidal volume range. The respiratory signals under volume control ventilation mode (airway flow, pressure and volume) were simulated with an exponential decreasing Crs. White noise and colored noise were added to the simulated respiratory data. The original ASM was applied to calculated the dynamic Crs for the volume range that reliable estimates can be determined (based on confidence interval). Outside the reliable volume range, Crs values with lowest weighted confidence interval and slice width were used. These estimates would be marked differently as the estimates calculated in the original ASM. Three different weighted combinations of confidence interval and slice width were tested. Combination in favor of confidence interval delivered the best estimates with lowest relative error. The result indicates that the enhanced- ASM visualizes intratidal nonlinear dynamic lung mechanics, which may help the intensivists to understand the patient's status rapidly. © 2013 Springer-Verlag.