BP-diff:使用U-Net进行无袖连续BP波形估计的条件扩散模型
Yinsong Liu1, Junsheng Yu1,2,3, Hanlin Mou4
1Department of School of Electronic Engineering, Beijing University of Posts and Telecommunication, Beijing 100876, People's Republic of China.
Physiological measurement
|September 25, 2024
概括
一种新的无袖式血压 (BP) 监测方法,BP-Diff,使用光电显微镜 (PPG) 信号进行准确,连续的BP估计. 这种非侵入性技术符合医疗标准,非常适合可穿戴设备.
科学领域:
- 生物医学工程 生物医学工程
- 医疗器械 医疗器械
- 信号处理 信号处理
背景情况:
- 持续监测血压 (BP) 对医疗保健至关重要.
- 侵入性血压测量方法是准确的,但不适合日常使用.
- 摄影透视图 (PPG) 为BP估计提供了一种有前途的非侵入性方法.
研究的目的:
- 开发一种新的无袖方法,使用PPG信号进行准确的连续BP估计.
- 介绍BP-Diff,这是一个端到端的深度学习模型,用于BP波形估计.
主要方法:
- 使用了与U-Net架构集成的条件扩散概率模型.
- 使用PPG信号及其衍生品作为BP波形估计的条件.
- 使用未校准和校准的方案与参考BP测量对该方法进行了评估.
主要成果:
- BP-Diff准确地跟踪了BP动态,包括峰值和山谷位置和时间.
- 校准的BP-Diff实现了高精度的BP估计,平均绝对误差较低 (例如,对透气BP的2.6 mmHg).
- 该方法符合AAMI标准,并获得了英国高血压协会的A级,证明了高可靠性.
结论:
- BP-Diff提供了一种优越的,非侵入性的,无袖的方法,用于持续的血压监测.
- 该技术适合整合到日常医疗保健应用的可穿戴设备中.
- 这一进步为持续的BP管理提供了切实可行的解决方案.
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