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血管衰老中动脉顺应性的分数阶建模:一种用于研究心血管动力学的计算生物力学方法

Fractional-Order Modeling of Arterial Compliance in Vascular Aging: A Computational Biomechanical Approach for Investigating Cardiovascular Dynamics.

作者信息

Bahloul Mohamed A, Aboelkassem Yasser, Belkhatir Zehor, Laleg-Kirati Taous-Meriem

机构信息

Electrical Engineering Department, College of EngineeringAlfaisal University Riyadh 11533 Saudi Arabia.

College of Innovation and TechnologyUniversity of Michigan Flint MI 48502 USA.

出版信息

IEEE Open J Eng Med Biol. 2023 Dec 14;5:650-660. doi: 10.1109/OJEMB.2023.3343083. eCollection 2024.

Abstract

The goal of this study is to investigate the application of fractional-order calculus in modeling arterial compliance in human vascular aging. A novel fractional-order modified arterial Windkessel model that incorporates a fractional-order capacitor (FOC) element is proposed to capture the complex and frequency-dependent properties of arterial compliance. The model's performance is evaluated by verifying it using data collected from three different human subjects, with a specific focus on aortic pressure and flow rates. The results show that the FOC model accurately captures the dynamics of arterial compliance, providing a flexible means to estimate central blood pressure distribution and arterial stiffness. This study demonstrates the potential of fractional-order calculus in advancing the modeling and characterization of arterial compliance in human vascular aging. The proposed FOC model can improve our understanding of the physiological changes in arterial compliance associated with aging and help to identify potential interventions for age-related cardiovascular diseases.

摘要

本研究的目的是探讨分数阶微积分在人类血管衰老过程中动脉顺应性建模中的应用。提出了一种新型的分数阶修正动脉Windkessel模型,该模型纳入了分数阶电容(FOC)元件,以捕捉动脉顺应性的复杂和频率依赖性特性。通过使用从三名不同人类受试者收集的数据对该模型进行验证来评估其性能,特别关注主动脉压力和流速。结果表明,FOC模型准确地捕捉了动脉顺应性的动态变化,为估计中心血压分布和动脉僵硬度提供了一种灵活的方法。本研究证明了分数阶微积分在推进人类血管衰老过程中动脉顺应性建模和表征方面的潜力。所提出的FOC模型可以增进我们对与衰老相关的动脉顺应性生理变化的理解,并有助于识别与年龄相关的心血管疾病的潜在干预措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b417/11342938/c95242d0f5df/bahlo1-3343083.jpg

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