Kriboy M, Tarasiuk A, Zigel Y
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:4224-7. doi: 10.1109/EMBC.2014.6944556.
Obstructive sleep apnea (OSA) is a common sleep disorder. OSA is associated with several anatomical and functional abnormalities of the upper airway. It was shown that these abnormalities in the upper airway are also likely to be the reason for increased rate of apneic events in the supine position. Functional and structural changes in the vocal tract can affect the acoustic properties of speech. We hypothesize that acoustic properties of speech that are affected by body position may aid in distinguishing between OSA and non-OSA patients. We aimed to explore the possibility to differentiate OSA and non-OSA patients by analyzing the acoustic properties of their speech signal in upright sitting and supine positions. 35 awake patients were recorded while pronouncing sustained vowels in the upright sitting and supine positions. Using linear discriminant analysis (LDA) classifier, accuracy of 84.6%, sensitivity of 92.7%, and specificity of 80.0% were achieved. This study provides the proof of concept that it is possible to screen for OSA by analyzing and comparing speech properties acquired in upright sitting vs. supine positions. An acoustic-based screening system during wakefulness may address the growing needs for a reliable OSA screening tool; further studies are needed to support these findings.
阻塞性睡眠呼吸暂停（OSA）是一种常见的睡眠障碍。OSA与上气道的多种解剖和功能异常有关。研究表明，上气道的这些异常也可能是仰卧位呼吸暂停事件发生率增加的原因。声道的功能和结构变化会影响语音的声学特性。我们假设受身体姿势影响的语音声学特性可能有助于区分OSA患者和非OSA患者。我们旨在通过分析清醒患者在直立坐姿和仰卧位时语音信号的声学特性，探索区分OSA患者和非OSA患者的可能性。记录了35名清醒患者在直立坐姿和仰卧位时发长元音的情况。使用线性判别分析（LDA）分类器，准确率达到84.6%，灵敏度达到92.7%，特异性达到80.0%。本研究提供了概念验证，即通过分析和比较直立坐姿与仰卧位时获得的语音特性来筛查OSA是可行的。清醒时基于声学的筛查系统可能满足对可靠OSA筛查工具日益增长的需求；需要进一步的研究来支持这些发现。
