使用语音评估清醒期间阻塞性睡眠呼吸暂停的严重程度:一篇综述
Behrad TaghiBeyglou1, Ivana Čuljak2, Fatemeh Bagheri3
1Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; KITE Research Institute, Toronto Rehabilitation Institute- University Health Network, Toronto, ON, Canada.
Computers in biology and medicine
|August 22, 2024
概括
语音分析为查阻塞性睡眠呼吸暂停 (OSA) - - 一种常见的睡眠呼吸障碍 - - 提供了一个有希望的,易于使用的替代方案. 本综述探讨了使用语音模式来估计OSA的严重程度,绕过了繁的多睡眠学 (PSG) 的需要.
科学领域:
- 生物医学工程 生物医学工程
- 耳鼻喉科 耳鼻喉科 耳鼻喉科
- 语音科学 语言科学
背景情况:
- 阻塞性睡眠呼吸暂停 (OSA) 影响北美10-30%的成年人,通过多睡眠学 (PSG) 诊断.
- PSG是不方便的,昂贵的,并且涉及长时间的等待列表,需要使用替代查方法.
- 语音产生涉及类似于OSA受影响的喉结构.
研究的目的:
- 综合审查关于使用语音分析来估计阻塞性睡眠呼吸暂停 (OSA) 严重性的研究.
- 探索OSA和语音生产之间的生理联系.
- 识别语音特征,选择方法和用于OSA严重性预测的模型.
主要方法:
- 在PubMed和Connected Papers的851篇论文中进行系统的文献搜索.
- 使用PRISMA指南进行严格的过,最终包括32篇论文.
- 分析的重点是语音特征提取,选择和OSA预测模型的方法.
主要成果:
- 28篇论文的重点是开发用于OSA的语音分析方法.
- 4篇论文研究了OSA和语音特征之间的临床关联.
- 研究了OSA和语音产生机制之间的生理相似之处.
结论:
- 语音分析提供了一个可行的,可访问的工具,用于查和潜在地估计OSA的严重程度.
- 需要进一步的研究来解决目前的局限性,并完善预测模型.
- 本综述强调了语音分析在OSA管理中的潜力.
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