Snore based systems for the diagnosis of apnoea: a novel feature and its receiver operating characteristics for a full-night clinical database

Obstructive sleep apnoea (OSA) is a disease in which upper airways are collapsed during sleep, leading to serious consequences. The gold standard of diagnosis, called polysomnography (PSG), requires a full-night hospital stay connected to over 10 channels of measurements requiring physical contact with sensors. PSG is inconvenient, expensive and unsuited for community screening. Snoring is the earliest symptom of OSA, but its potential in clinical diagnosis is not fully recognized yet. In this paper, we show that snoring carries vital information to diagnose OSA, and propose a feature termed the ´intra-snore-pitch-jump´ (ISPJ) to diagnose OSA. Working on clinical data, we show that ISPJ delivers OSA detection sensitivity at 86-100% while holding specificity at 50-80%. These numbers indicate that snore sounds and the ISPJ are excellent candidates for a take-home device for OSA screening. Snore sounds have the significant advantage in that they can be conveniently acquired with low-cost non-contact equipment.