Detection of airway obstructions and sleep apnea by analyzing the phase relation of respiration movement signals

This paper presents a novel computer-aided diagnostic method of sleep apnea syndrome, a very common respiration disorder. Apnea diagnostics require long-term, multichannel vital signal recording called polysomnography. Although various methods already exist for the computer-aided analysis of the polysomnograms, only some of them can detect the type of apnea precisely enough (i.e., central versus obstructive episodes). The system introduced in this paper processes only the thoracic and abdominal excursion signals and can distinguish between obstructive and central episodes of apnea. The main novelty is that the phase difference between the two respiration signals is considered in order to determine the presence and grade of obstructive apnea. Central apnea is recognized if no or only very small respiration movements occur. Unlike many existing systems, the presented signal processing allows on-line implementation, which plays an important role in many clinical applications.