基于可穿戴设备的呼吸复杂性分析,用于检测心力衰竭患者的肺堵塞:观察性探索性研究
Mengwei Li1,2, Yu Kang3, Shuanglin Zhao4
1Department of Medical Engineering, Beidaihe Rest and Recuperation Center of PLA, Qinhuangdao, China.
Journal of medical Internet research
|August 27, 2025
概括
可穿戴设备可以检测心力衰竭 (HF) 患者的呼吸变化. 通过识别与PC相关的特定呼吸模式, 这项技术有望为早期干预和减少住院患者提供帮助.
科学领域:
- 心脏病和呼吸系统医学
- 生物医学工程和可穿戴技术
- 数字健康和预测诊断
背景情况:
- 过度的肺堵塞 (PC) 显著导致心力衰竭 (HF) 的恶化,经常导致紧急住院治疗.
- 使用可穿戴设备及早检测PC相关的呼吸系统异常可以促进及时干预,减少住院患者数量.
- 需要进一步研究可穿戴设备在检测PC的特定呼吸系统生物标志物的可行性.
研究的目的:
- 评估使用可穿戴设备监测住院HF患者的呼吸数据的可行性.
- 为了确定可穿戴设备的呼吸信号是否能区分PC和无PC的HF患者.
主要方法:
- 一项观察性探索性研究,涉及62名住院HF患者 (44名患有PC),不包括患有严重肺病或需要重症监护的患者.
- 参与者在接受治疗后的24小时内佩戴设备,并对夜间呼吸模式进行呼吸周期,幅度和多尺度 (MSE) 的分析.
- 在24小时内进行了全面的临床评估,包括肺部超声波以确定PC.
主要成果:
- 与没有PC的患者相比,PC患者的平均呼吸时间 (TE) 和呼吸时间比率 (TE_ratio) 显著延长.
- 在PC组中观察到1-5 (面积_1_5) 和6-20 (面积_6_20) 的呼吸幅度的多尺度 (MSE) 值增加.
- 后勤回归确定TE_ratio,RA面积_1_5和RA面积_6_20为PC的显著预测指标;一个多变量模型实现了0. 91的AUC.
结论:
- 基于可穿戴设备的MSE分析有效区分了患有PC和没有PC的住院HF患者.
- 长时间的呼气阶段和增加的呼吸幅度复杂性是PC组的特征.
- 这些发现表明可穿戴设备有潜力进行非侵袭性监测和早期检测HF的肺堵塞.
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