时间复杂性在光电解剖学及其对血压的影响
Xiaoman Xing1,2, Rui Huang2,3, Liling Hao4
1School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou, China.
Frontiers in physiology
|September 25, 2023
概括
摄影复合图 (PPG) 信号的时间复杂性是估计血压 (BP) 的关键. 基于模型的模拟揭示了PPG模式如何反映血液动力学变化,有助于算法开发.
科学领域:
- 生物医学工程 生物医学工程
- 生理学 生理学 生理学
- 信号处理 信号处理
背景情况:
- 光电显微镜 (PPG) 信号包含与血压 (BP) 相关的复杂时间信息.
- 解释随机PPG模式对于增强BP估计算法至关重要.
研究的目的:
- 通过基于模型的模拟方法来解释静态光聚体图形 (PPG) 图案.
- 通过理解PPG的时间复杂性来优化血压 (BP) 估计算法.
主要方法:
- 针对PPG模拟,调整了一个具有BP依赖性合规性的四要素风模型.
- 使用脉冲和连续刺激生成PPG反应以模仿血液动力学变化.
- 使用Higuchi碎形维度 (HFD) 和自相关函数 (ACF) 量化PPG时间复杂性.
- 经过验证的模拟结果,连续记录了40名健康受试者的BP,PPG和中风体积.
主要成果:
- 血管合规性,外周阻力和心脏输出影响PPG响应特征 (时间延迟,振幅,相位转移).
- PPG复杂性来自随机刺激,其自相关性模式调节.
- 模型预测PPG复杂性-血液动力学关系与实验数据保持一致.
- 与形态特征不同的是,HFD和ACF表现出对BP估计的稳定贡献,即使有心脏输出波动.
结论:
- 单位PPG中的时间复杂性模式对于准确的BP估计至关重要.
- 了解这些模式的生理基础有助于开发可解释和优化的BP估计算法.
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