使用智能子进行峰值独立的无袖血压监测:时间滞后模型在基于脚的PPG中的作用
Hamed Abdollahzadeh1, Elisa Montaldi1, Riccardo Olivieri1
1Department of Industrial and Information Engineering and Economics, University of L'Aquila, 67100 L'Aquila, Italy.
Sensors (Basel, Switzerland)
|February 27, 2026
概括
这项研究引入了一种智能子,用于使用光聚聚光学 (PPG) 测量无袖血压 (BP). 该系统在校准后提供准确,连续的BP监测,克服传统方法的局限性.
科学领域:
- 生物医学工程 生物医学工程
- 可穿戴技术可穿戴技术
- 心血管监测 心血管监测
背景情况:
- 持续的血压 (BP) 监测对于医疗保健至关重要,但在当前的袖口式设备中具有挑战性.
- 可穿戴系统需要非侵入性,长期的血压监测解决方案.
研究的目的:
- 开发一种使用智能子平台和光电显微镜 (PPG) 的无袖血压估计方法.
- 探索峰值独立特征和时间建模,以加强BP监测.
主要方法:
- 利用来自60名参与者的单站PPG信号,在30s窗口中处理.
- 提取了统计和信息理论特征,包括衍生品,并应用了时间滞后建模 (5-15秒).
- 采用多重回归模型与泄漏安全交叉验证用于BP估计.
主要成果:
- 独立于对象的估计实现了8.60 mmHg (心缩) 和6.42 mmHg (腹缩) 的误差.
- 校准后的监测带来了显著的改善,平均绝对误差为1.3-1.7mmHg,R2>0.90.
- 证明了峰值独立特征和时间上下文建模的有效性.
结论:
- 基于脚的PPG,结合先进的特征工程和时间建模,使得准确的连续个性化BP监测后校准.
- 独立于对象的BP估计仍然是一个重大挑战.
- 智能子平台为长期BP管理提供了舒适有效的替代方案.
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