A Framework for Information Processing in the Diagnosis of Sleep Apnea

TL;DRAbstract

Obstructive sleep apnea (OSA) is one of the most common sleep disorders. It is characterized by repetitive obstruction of the upper airways during sleep. The frequency of such events can range up to hundreds of events per sleep-hour. Full closure of the airways is termed apnea, and a partial closure is known as hypopnea. The number of apnea/hypopnea events per hour is known as the AHI-index, and is used by clinical community as a measure of the severity of OSA. OSA, when untreated, presents as a major public health concern throughout the world. OSA patients use health facilities at twice the average rate (Delaive, Roos, Manfreda, & Kryger, 1998), causing huge pressures on national healthcare systems. OSA is associated with serious complications such as cardiovascular disease, stroke, (Barber & Quan, 2002; Kryger, 2000,), and sexual impotence. It also causes cognitive deficiencies, low IQ in children, fatigue, and accidents. Australian Sleep Association reported (ASA, 1999) that

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