A Computational Study of Flow-Induced Plate Flutter as Potential Markers for Sleep Apnea

Abstract

Collapse of airway during sleep (sleep apnea) is a disorder that requires expensive and cumbersome sleep tests for its diagnosis, making it unattractive for large-scale detection in the mass population. Acoustic signals from snoring has become an attractive research area for developing inexpensive and non-invasive test for diagnosing sleep apnea. In this article, potential for an alternative apnea detection from snoring acoustic signals is investigated by examining effect of airway obstruction on onset of soft palate snoring or flutter. To that end, this study is concerned with flow-induced vibrations of a cantilever plate inside a two-dimensional, viscous, obstructed channel flow that represents the human pharynx associated with snoring and obstructive sleep apnea syndrome. The soft palate vibrations are examined by coupling a full Navier-Stokes flow solver in an Arbitrary Lagrangian-Eulerian (ALE) description to a thin plate equation of motion. A threshold velocity for initiation of unstable plate vibration was determined for each different occlusion depth, and correlating the two, showed that the critical velocity decreased with increasing occlusion depth. By relating the critical velocity to a breathing cycle, the time for initiation of snoring could help estimate the degree of localized airway occlusion and justify further study for potential non-invasive diagnosis of obstructive airway.