Prediction of Obstructive Sleep Apnea Based on Respiratory Sounds Recorded Between Sleep Onset and Sleep Offset

Abstract

This study showed that our binary classifier predicted patients with AHI of ≥15 with sensitivity and specificity of >80% by using respiratory sounds during sleep. Since our prediction model included all sleep stage data, algorithms based on respiratory sounds may have a high value for prescreening OSA with mobile devices.