Detection of upper airway narrowing via classification of LPC coefficients: Implications for obstructive sleep apnea diagnosis

The similarities between unvoiced speech sounds and turbulent breath sounds were used to detect change in sound characteristics caused by narrowing of the upper airway (UA), similar to that occurring in obstructive sleep apnea (OSA). In 18 awake subjects, UA resistance (RAU), an index of UA narrowing, was measured simultaneously with breath sounds recording. Linear Prediction Coding was applied on turbulent inspiratory sounds drawn from low and high RAU conditions and K-means was used to cluster the resulting coefficients. The resulting 2 clusters were tested for agreement with the underlying RAU status. Distinct clusters were formed when RUA increased relatively high but not in cases with lower rise in RUA (P<;0.01 for all indicators.) This is the first work to show the utility of LPC in breath sounds analysis confirmed by an objective indicator or UA narrowing.