基于特征的检测和分类的睡眠呼吸暂停和睡眠暂停使用多光谱成像
IEEE journal of biomedical and health informatics
|March 3, 2025
概括
一种新的非接触式方法使用多光谱成像来高精度地检测和分类睡眠呼吸暂停 (SAS) 事件. 这种方法为诊断与睡眠相关的呼吸障碍提供了传统的多睡眠学 (PSG) 的有希望的替代方案.
科学领域:
- 生物医学工程 生物医学工程
- 医疗成像医学成像
- 睡眠医学 睡眠医学
背景情况:
- 睡眠呼吸暂停综合征 (SAS) 是一种带有严重健康后果的睡眠障碍.
- 目前通过多睡眠学 (PSG) 进行诊断,使用不舒服的接触传感器.
- 需要非接触式诊断方法来提高患者的舒适性和数据准确性.
研究的目的:
- 开发一种新的无接触方法来检测和分类呼吸暂停事件.
- 在近红外 (NIR) 和远红外 (FIR) 光谱中利用多光谱成像用于SAS诊断.
- 与传统的PSG相比,评估该方法的准确性.
主要方法:
- 从多光谱图像 (NIR和FIR) 中提取特征.
- 多种数据模式的融合,包括图像,患者数据和时间序列分析.
- 呼吸事件 (正常,低呼吸,呼吸暂停) 和呼吸暂停类型 (阻塞性,中心) 的分类.
主要成果:
- 在分类正常呼吸,低呼吸和呼吸暂停时达到99.5%的准确性.
- 在区分阻塞性与中心性呼吸暂停症时,达到98.8%的准确性.
- 高皮尔森相关性 (0.9981-0.9989) 对于呼吸暂停-呼吸暂停指数估计.
结论:
- 拟议的多光谱成像方法在睡眠呼吸暂停检测和分类方面具有很高的准确性.
- 这种非接触式方法是多睡眠学 (PSG) 的可行替代方案.
- 该方法有可能改善与睡眠相关的呼吸障碍的诊断.
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