In a progressively aging population, it is of utmost importance to develop reliable, noninvasive, and cost-effective tools to estimate biomarkers which can be indicative of cardiovascular risk. Various pathophysiological conditions are associated to changes in the total arterial compliance (C_T), and thus its estimation via an accurate and simple method is valuable.Direct noninvasive measurement of C_T is not feasible in the clinical practice. Previous methods exist for indirect estimation of C_T, which, however, require noninvasive, yet complex and expensive, recordings of the central pressure and flow. Here, we introduce a novel, noninvasive method for estimating C_T from a single carotid waveform measurement using regression analysis. Features were extracted from the carotid wave and are combined with demographic data. A prediction pipeline is adopted for estimating C_T using, firstly, a feature-based regression analysis and, secondly, the raw carotid pulse wave. The proposed methodology was appraised using the large human cohort (n=2256) of the Asklepios study. Accurate estimates of C_T were yielded for both prediction schemes; namely, r=0.83 and normalized-RMSE=9.58% for the feature-based model, and r=0.83 and normalized-RMSE=9.67% for the model which used the raw signal. The major advantage of this method pertains to the simplification of the technique offering easily applicable and convenient C_T monitoring. Such an approach could offer promising applications, ranging from fast and cost-efficient hemodynamical monitoring by the physician to integration in wearable technologies.

中文翻译：

---

从颈动脉压力波形评估动脉顺应性

在逐渐老龄化的人口中，开发可靠、无创且具有成本效益的工具来估计可指示心血管风险的生物标志物至关重要。各种病理生理条件与总动脉顺应性（C _T）的变化有关，因此通过准确和简单的方法对其进行估计是有价值的。直接无创测量C _T在临床实践中是不可行的。先前存在用于间接估计 C _{T 的}方法，然而，这些方法需要非侵入性的、复杂且昂贵的中心压力和流量记录。在这里，我们介绍了一种新的、非侵入性的方法来估计 C _T从使用回归分析的单个颈动脉波形测量。从颈动脉波中提取特征并与人口统计数据相结合。采用预测管道来估计 C _T，首先使用基于特征的回归分析，其次使用原始颈动脉脉搏波。使用 Asklepios 研究的大型人类队列 (n=2256) 对提议的方法进行了评估。两种预测方案都得到了C _{T 的}准确估计；即，对于基于特征的模型，r=0.83 和 normalized-RMSE=9.58%，对于使用原始信号的模型，r=0.83 和 normalized-RMSE=9.67%。这种方法的主要优点在于简化了技术，提供了易于应用和方便的 C _T监测。这种方法可以提供有前景的应用，从医生快速且经济高效的血流动力学监测到可穿戴技术的集成。