Soltanzadeh R, Moussavi Z
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:4228-31. doi: 10.1109/EMBC.2014.6944557.
Breathing sounds analysis conveys valuable information in relation to obstructive sleep apnea (OSA) during both sleep and wakefulness. In this study, we investigated whether the breathings sounds spectral and higher order statistics characteristics (HOS) change from wakefulness to sleep, and more importantly whether this change is associated with severity of OSA. Tracheal breathing sounds of 6 individuals with severe OSA and 6 non-OSA individuals during wakefulness and stage 2 of sleep, both in supine position, were used in this study. The sounds were recorded simultaneously with full overnight polysomnography (PSG) assessment. First, the sounds of 5 noise-free breathing cycles were extracted and sequestered into inspiratory and expiratory phase segments manually for each study subject. After normalizing each sound segment to its energy, spectral and HOS features were calculated. Several features including the median bispectral frequency (MBF), spectral bandwidth (BW) and bispectrum Harmonic Mean (HM) were found to change statistically significantly from wakefulness to sleep mostly in severe OSA group but not as much in non-OSA group. The most prominent and consistent change between the two groups of OSA and non-OSA was observed in MBF; it changed from wakefulness to sleep in the two groups in an opposite manner; this observation is congruent with the hypothesis that the upper airway in OSA population has an increased non-homogeneity.
呼吸音分析在睡眠和清醒状态下都能传达有关阻塞性睡眠呼吸暂停（OSA）的有价值信息。在本研究中，我们调查了呼吸音频谱和高阶统计特征（HOS）从清醒到睡眠是否发生变化，更重要的是这种变化是否与OSA的严重程度相关。本研究使用了6名重度OSA患者和6名非OSA患者在清醒和睡眠第二阶段仰卧位时的气管呼吸音。这些声音与整夜多导睡眠图（PSG）评估同时记录。首先，为每个研究对象手动提取5个无噪声呼吸周期的声音，并将其隔离为吸气和呼气阶段片段。在将每个声音片段的能量归一化后，计算频谱和HOS特征。发现包括中值双谱频率（MBF）、频谱带宽（BW）和双谱调和均值（HM）在内的几个特征从清醒到睡眠在统计学上有显著变化，主要在重度OSA组中，但在非OSA组中变化不大。在MBF中观察到OSA组和非OSA组之间最显著和一致的变化；两组从清醒到睡眠的变化方式相反；这一观察结果与OSA人群上呼吸道非均匀性增加的假设一致。
