Background and Objectives

Measurement of arterial compliance is recognized as important for clinical use and for enabling better understanding of circulatory system regulation mechanisms. Estimation of arterial compliance involves either a direct measure of the ratio between arterial volume and pressure changes or an inference from the pulse wave velocity (PWV). In this study we demonstrate an approach to assess arterial compliance by fusion of these two information sources. The approach is based on combining oscillometry as used for blood pressure inference and PWV measurements based on ECG/PPG. Enabling reliable arterial compliance measurements will contribute to the understanding of regulation mechanisms of the arterial tree, possibly establishing arterial compliance as a key measure relevant in hemodynamic monitoring.

Methods

A measurement strategy, a physiological model, and a framework based on Bayesian principles are developed for measuring changes in arterial compliance based on combining oscillometry and PWV data. A simulation framework is used to study and validate the algorithm and measurement principle in detail, motivated by previous experimental findings.

Results

Simulations demonstrate the possibility of inferring arterial compliance via fusion of simultaneously acquired volume/pressure relationships and PWV data. In addition, the simulation framework demonstrates how Bayesian principles can be used to handle low signal – to – noise ratio and partial information loss.

Conclusions

The developed simulation framework shows the feasibility of the proposed approach for assessment of arterial compliance by combining multiple data sources. This represents a first step towards integration of arterial compliance measurements in hemodynamic monitoring using existing clinical technology. The Bayesian approach is of particular relevance for such patient monitoring settings, where measurements are repeated frequently, context is relevant, and data is affected by artefacts. In addition, the simulation framework is necessary for future clinical-study design, in order to determine device specifications and the extent to which noise affects the inference process.

中文翻译：

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通过融合示波法和脉搏波速度信息评估动脉顺应性的建模框架。

背景和目标

动脉顺应性的测量被认为对于临床使用和使人们更好地了解循环系统调节机制很重要。动脉顺应性的估计包括直接测量动脉体积与压力变化之间的比率，或从脉搏波速度（PWV）推论得出。在这项研究中，我们展示了一种通过融合这两种信息源来评估动脉顺应性的方法。该方法基于将用于血压推断的示波法和基于ECG / PPG的PWV测量相结合。启用可靠的动脉顺应性测量将有助于理解动脉树的调节机制，可能将动脉顺应性确定为与血流动力学监测相关的关键措施。

方法

开发了一种基于贝叶斯原理的测量策略，生理模型和框架，用于通过结合示波法和PWV数据来测量动脉顺应性变化。在之前的实验结果的推动下，使用了一个仿真框架来详细研究和验证算法和测量原理。

结果

模拟表明通过同时获取的体积/压力关系和PWV数据融合来推断动脉顺应性的可能性。此外，仿真框架演示了如何使用贝叶斯原理来处理低信噪比和部分信息丢失。

结论

所开发的模拟框架通过组合多个数据源显示了所提出方法用于评估动脉顺应性的可行性。这代表了使用现有临床技术将动脉顺应性测量结果整合到血液动力学监测中的第一步。对于这样的患者监测设置，贝叶斯方法尤其重要，在这种情况下，测量经常被重复，上下文是相关的，并且数据受伪影影响。此外，仿真框架对于将来的临床研究设计是必需的，以便确定设备规格以及噪声影响推理过程的程度。