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Breathing sounds spectral and higher order statistics changes from wakefulness to sleep in apneic and non-apneic people

机译:呼吸暂停和非呼吸暂停的人的呼吸声频谱和高阶统计量从清醒到睡眠发生变化

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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.
机译:呼吸音分析可传达有关睡眠和清醒期间阻塞性睡眠呼吸暂停(OSA)的有价值的信息。在这项研究中,我们调查了呼吸是否从清醒到睡眠都发生了频谱频谱变化和高阶统计特征(HOS)变化,更重要的是,这种变化是否与OSA的严重程度有关。在这项研究中,使用了6名重度OSA个体和6名非OSA个体在清醒和睡眠第2阶段时均处于仰卧位的气管呼吸声。声音与完整的通宵多导睡眠图(PSG)评估同时记录。首先,为每个研究对象手动提取5个无噪音呼吸周期的声音并将其隔离为吸气和呼气阶段段。将每个声音片段归一化为其能量后,便会计算出频谱和HOS特征。研究发现,包括中位双频谱频率(MBF),频谱带宽(BW)和双频谱谐波均值(HM)在内的几个特征,从醒觉到入睡,在统计学上均具有统计学上的显着变化,而在严重OSA组中变化不大。 MBF观察到两组OSA和非OSA之间最显着,最一致的变化。它从清醒转变为两组的睡眠方式相反。该观察结果与OSA人群中上呼吸道非均质性增加的假设是一致的。

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