阻塞性睡眠呼吸暂停查通过关节和信号分析和PPG衍生脉率振荡
IEEE journal of biomedical and health informatics
|November 10, 2023
概括
可穿戴传感器可以使用脉冲氧计和心率数据选阻塞性睡眠呼吸暂停 (OSA). 一个新的指数,CVHRI,与氧和相结合,准确地识别了家庭诊断的OSA严重程度.
科学领域:
- 生物医学工程 生物医学工程
- 心血管生理学心血管生理学
- 睡眠医学 睡眠医学
背景情况:
- 阻塞性睡眠呼吸暂停 (OSA) 是很常见的,而且往往没有被诊断出来.
- 多人睡眠学是黄金标准,但对广泛的查有局限性.
- 可穿戴技术为可访问的OSA查提供了潜力.
研究的目的:
- 评价从光电脉冲图 (PPG) 来用于OSA诊断的外周氧和脉冲间隔 (PPI) 的使用.
- 开发和验证一个新的指数 (CVHRI) 用于OSA严重性评估.
- 探索这些方法在家庭OSA查中的实用性.
主要方法:
- 来自PPG的外周氧和和PPI系列被用作OSA诊断模型的输入.
- 训练了二进制和多类分类模型以识别正常,呼吸暂停和呼吸暂停的呼吸段.
- 一个新的指数,心率指数 (CVHRI) 的周期变化,是从PPI频谱分析中得出的.
主要成果:
- 模型实现了86.27%的二进制准确度和73.07%的多类细分类别分类.
- CVHRI显示与呼吸暂停-呼吸暂停指数 (AHI) (r=0.94和r=0.91) 有很强的相关性.
- 基于CVHRI的分层实现了AHI值为5和15的77.27%和79.55%的准确性.
结论:
- 将氧和和 PPI 分析与 CVHRI 结合起来,为家庭 OSA 查提供了一个低成本,易于穿戴的工具.
- 这种方法可以有效地对OSA严重程度进行患者分层.
- 拟议的方法有望改善OSA诊断的可访问性.
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