Ghaemmaghami H, Abeyratne U R, Hukins C
School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Brisbane, Australia.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:5551-4. doi: 10.1109/IEMBS.2009.5333733.
Obstructive Sleep Apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The standard method of OSA diagnosis is known as Polysomnography (PSG), which requires an overnight stay in a specifically equipped facility, connected to over 15 channels of measurements. PSG requires (i) contact instrumentation and, (ii) the expert human scoring of a vast amount of data based on subjective criteria. PSG is expensive, time consuming and is difficult to use in community screening or pediatric assessment. Snoring is the most common symptom of OSA. Despite the vast potential, however, it is not currently used in the clinical diagnosis of OSA. In this paper, we propose a novel method of snore signal analysis for the diagnosis of OSA. The method is based on a novel feature that quantifies the non-Gaussianity of individual episodes of snoring. The proposed method was evaluated using overnight clinical snore sound recordings of 86 subjects. The recordings were made concurrently with routine PSG, which was used to establish the ground truth via standard clinical diagnostic procedures. The results indicated that the developed method has a detectability accuracy of 97.34%.
阻塞性睡眠呼吸暂停（OSA）是一种高度流行的疾病，其特征是睡眠期间上呼吸道塌陷，会导致严重后果。OSA诊断的标准方法是多导睡眠图（PSG），这需要在专门配备的设施中过夜，连接超过15个测量通道。PSG需要（i）接触式仪器，以及（ii）基于主观标准对大量数据进行专家人工评分。PSG成本高、耗时，且难以用于社区筛查或儿科评估。打鼾是OSA最常见的症状。然而，尽管有巨大潜力，但目前它尚未用于OSA的临床诊断。在本文中，我们提出了一种用于OSA诊断的新型打鼾信号分析方法。该方法基于一种新颖的特征，该特征量化了单个打鼾发作的非高斯性。使用86名受试者的过夜临床打鼾声音记录对所提出的方法进行了评估。这些记录是与常规PSG同时进行的，常规PSG通过标准临床诊断程序用于确定基本事实。结果表明，所开发的方法具有97.34%的可检测准确率。
