Detection of obstructive sleep apnea by analysis of phase angle using the forced oscillation signal

Abstract

Pharyngeal collapse in patients with obstructive sleep apnea syndrome (OSAS) is linked to decreased upper airway muscle activity. We hypothesised that decreased muscle activity causes decreased stiffness of the upper airway wall and assumed that a decrease in wall stiffness would result in a change point (CP) of the morphology of phase angle time series φ(t) obtained by forced oscillation technique (FOT). We developed an algorithm to detect CPs in φ(t) and investigated φ(t) data measured in parallel to all-night polysomnography in seven patients. A total of 2724 CPs were detected by algorithm. The CPs were marked on the polysomnograms and compared with polysomnogram scoring performed jointly by three sleep expert physicians. A total of 791 (67%) of the 1172 handscored respiratory events showed a CP in φ(t) within a time interval of 8 sec before and 6 sec after the marked onset. A total of 672 (57%) respiratory events were detected at an earlier time by algorithm, and 119 (10%) were algorithmically detected later. The average detection time by the CP algorithm was 4.0±1.1 sec earlier than the manual scoring. We conjecture that a CP in φ(t) indicates a change in upper airway collapsibility and that φ(t) might be a potentially useful parameter for detection of impending upper airway obstruction.