ESTIMATION OF MUCUS CLEARANCE IN PULMONARY AIRWAYS BY MEANS OF A REGRESSION MODEL

In this study, a multivariate regression analysis was performed on a dataset obtained from experimental tracheal model for mucus clearance in pulmonary airways. Several simulations have been done to verify the validity of the generated regression model. In general, the clearance of mucus in the airways is achieved by the beating action of cilia inside the serous layer which is the primary means of removing inhaled particulates and airway debris from airways in healthy people. In this study, two types of mucus simulants are used in the experimental setup. Clearance distances of a teardrop shape simulant are measured for different velocities, slope angles and surfaces properties. On the obtained data by applying several genuine transformations we developed a multiple regression model that is able to predict clearance up to 86% accuracy. Simulations revealed several important data like direct relation between velocity and clearance and indirect relation between angle and clearance.