Application of Artificial Neural Networks Method in Mucus Clearance in Pulmonary Airways

Abstract

Clearance of mucus is investigated in this study. Clearance of mucus in the airways by the beating action of cilia
inside the serous layer is the primary means of removing inhaled particulates and airway debris from airways in healthy
people. One of the major causes of pulmonary airway disease is the weakened clearance mechanism in the airways. In this
study, solid and liquid like mucus simulant are used in a tracheal model. Clearance distances of a teardrop shape simulant are
measured for different velocities and slope angles. Artificial neural networks method is applied to the data obtained and
clearance for intermediate velocity and angle values are determined.