连续无袖血压估计 基于分数顺序导数 通过格拉米安角场 仅使用光电血压图
Jiaqi Li1, Bingo Wing-Kuen Ling1
1Faculty of Information Engineering, Guangdong University of Technology, Guangzhou, China.
IET systems biology
|August 11, 2025
概括
这项研究引入了一种新型的无袖血压 (BP) 估计方法,该方法使用光斑血图 (PPG) 的分数顺序导数 (FOD). 新技术通过捕捉复杂的生理动态来提高BP估计的准确性,优于传统方法.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 持续监测血压 (BP) 对于预防中风等关键事件至关重要.
- 传统的手式BP设备无法提供连续的估计.
- 现有的无袖方法采用光聚体图 (PPG) 的整数顺序导数,由于生理非线性,其精度受到限制.
研究的目的:
- 开发一种先进的无袖BP估计方法,利用PPG信号的分数顺序导数 (FOD).
- 通过解决血流的非线性特征,提高连续血压估计的准确性.
- 将拟议的FOD-based方法与传统的整数顺序导数方法的性能进行比较.
主要方法:
- 用单一光谱分析 (SSA) 预处理光谱图 (PPG).
- 预处理PPG的分数顺序衍生品 (FOD) 被计算出来.
- 多通道格拉米安角场 (GAF) 图像编码应用于整数和分数顺序导数,生成多通道图像.
- 从编码图像中使用ResNet-18和U-Net架构进行BP估计.
主要成果:
- 与现有方法相比,基于FOD的拟议方法显示了较低的估计误差和更高的相关系数.
- 多通道GAF编码方法比单通道方法提高了性能.
- 在BP估计准确度方面,FOD方法显著优于传统的基于整数顺序导数的技术.
结论:
- 分数顺序衍生品为PPG信号提供了一个更有效的特征提取方法,用于无袖式BP估计.
- 拟议的方法为准确和持续的非侵入性血压监测提供了有希望的进步.
- 这种方法有可能通过更精确的血压跟踪来改善心血管健康管理.
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