从干涉度信号中提取动脉脉冲波形的方法.
Marian Janek1, Ivan Martincek1, Gabriela Tarjanyiova1
1Physics Department, Faculty of Electrical Engineering and Information Technology, University of Zilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia.
Sensors (Basel, Switzerland)
|July 30, 2025
概括
研究人员开发了一个开源的Python管道,从Fabry-Perot干扰度中提取动脉脉冲波形. 这种方法为非侵入性心血管诊断提供了一种实用,具有成本效益的工具.
科学领域:
- 生物医学工程 生物医学工程
- 光学传感传感器是什么?
- 信号处理 信号处理
背景情况:
- 非侵入性心血管评估对于诊断至关重要.
- 费布里 - 佩罗特干涉测量为生理监测提供了潜在的可能性.
- 对于动脉脉冲波形提取现有的方法是有限的.
研究的目的:
- 通过Fabry-Perot干涉度来提取动脉脉冲波形信号的方法.
- 开发和发布一个完整的,开源的Python处理管道,用于信号调节.
- 为了使实际的,非侵入性心血管评估.
主要方法:
- 使用了Fabry-Perot干扰计测量方法.
- 开发了一个基于Python的处理管道,包括异常值删除,Butterworth高通过和min-max规范化.
- 根据变化速率指导的信号重建,使用希尔伯特变换包裹,并检测到极端.
主要成果:
- 成功重建了从干扰度测量中获得的动脉脉冲波形信号.
- 确定了与传感器带宽和插值相关的振幅变化和噪声源.
- 对三名受试者的同步心电图 (ECG) 记录验证了该方法.
结论:
- 开发的方法提供了关于动脉运动的宝贵见解.
- 费布里-佩罗传感器可用于经济高效的非侵入性心血管诊断.
- 开源管道促进了生物信号分析和临床翻译方面的进步.
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