基于语音或打声音的阻塞性睡眠呼吸暂停的自动检测:一个叙事审查
Shuang Cao1, Ivana Rosenzweig2,3, Federico Bilotta4
1Department of Anesthesiology, The Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Journal of thoracic disease
|May 13, 2024
概括
阻塞性睡眠呼吸暂停 (OSA) 可以通过语音和打声音来检测. 这种非侵入性,具有成本效益的方法显示了自动查的前景,克服了传统多重睡眠学的局限性.
科学领域:
- 生物医学工程 生物医学工程
- 人工智能的人工智能
- 睡眠医学 睡眠医学
背景情况:
- 阻塞性睡眠呼吸暂停 (obstructive sleep apnea,OSA) 是一种普遍的慢性疾病,由于上呼吸道阻塞而导致睡眠呼吸障碍.
- 多睡眠学 (PSG) 是OSA的诊断标准,是昂贵的,耗时的和侵入性的.
- 新兴研究正在探索使用语音和打声音进行OSA检测的成本效益高,非侵入性方法.
研究的目的:
- 提供关于使用语音或打声音用于自动OSA检测的当前研究的全面审查.
- 讨论这一新型诊断方法的挑战和未来方向.
主要方法:
- 在PubMed,IEEE Xplore和Web of Science进行了系统的文献审查.
- 分析了1989年至2022年间发表的专注于通过语音或打声音自动检测OSA的研究.
主要成果:
- 语音和打的声音包含了重要的信息,用于OSA检测.
- 与AI模型 (SVM,GMM,HMM) 相结合的formant,LPCC和MFCC等特征已被广泛研究,用于自动化OSA查.
- 人工智能模型可以通过分析提取的语音和打声音特征,自动选患者的OSA.
结论:
- 使用语音或打声音的自动OSA检测为PSG提供了一个有希望的,非侵入性的,低成本的,无接触的替代方案.
- 这种方法有可能显著提高OSA查的可访问性和效率.
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