Nonlinear Wave Propagation Analysis using Experimental Data for the Estimation of Central Aortic Blood Pressure using Peripheral Circulatory Signals

中心主动脉血压比常用的肱动脉血压更能预测心血管风险。然而，由于它很难测量，因此在临床实践中没有广泛使用。本计画系关于数学模型之基础研究，以使能从两个非侵入性周边循环波形来估测中央主动脉血压。如果成功，该项目将推动个性化医疗保健和医疗器械行业的发展。特别是，它将通过其低成本和非侵入性方法改善心血管疾病患者的治疗方式，从而更好地评估心血管健康并及时检测其损伤。它还可以刺激医疗器械行业，进而刺激开发具有成本效益的可部署心血管健康监测医疗器械，从而促进整体经济，最终改善治疗和治疗。该项目还将对教育和知识传播产生广泛影响，弥合工程学、系统生物学和医学之间的差距，吸引妇女和代表性不足的学生从事多学科研究，并通过一个专门的网站广泛传播从该项目中获得的知识。该项目的目的是测试中心主动脉血压可以从两个非-通过基于模型的系统识别的侵入性外周循环波形。为了实现这一目标，心血管系统被视为一个非线性的动态波传播系统的未知输入。本计画将针对一类非线性波传播系统，进行系统辨识与输入反褶积方法的理论研究，并将其应用于由两个非侵入性的外周循环波形来估测中央主动脉血压波形的问题，以验证方法的有效性。本计画将借由解决一类非线性动态系统之系统辨识问题，以促进动态系统与控制之发展。由于所考虑的系统类别属于心血管健康监测应用，因此它将推进系统生理学举措。特别是，本项目将有利于生理系统和神经科学的基于数据的建模方法的发展，如心血管血流动力学的状态监测和评估的心脏调节功能。最终，该项目可能为普及和个性化医疗的技术进步开辟新的机会，最终可以改善人类的生活质量。

Central aortic blood pressure significantly better predicts cardiovascular risk than commonly used brachial artery blood pressure. However, it is not widely used in clinical practice since it is very difficult to measure. This project concerns fundamental research on mathematical modeling to enable estimation of central aortic blood pressure from as few as two non-invasive peripheral circulatory waveforms. If successful, this project will advance personalized healthcare and medical device industry sectors. In particular, it will improve the way patients with cardiovascular disease are treated via its low-cost and non-invasive method that allows better assessment of cardiovascular health and prompt detection of its impairment. It may also stimulate the medical device industry and in turn the overall economy by stimulating the development of cost-effective, deployable medical devices for cardiovascular health monitoring, which will ultimately lead to improved therapy and treatment. This project will also have broad impact on education and knowledge dissemination, by bridging the gap between engineering, systems biology and medicine, attracting women and underrepresented students to multi-disciplinary research, and broadly disseminating the knowledge gained from this project through a dedicated website.The objective of this project is to test the hypothesis that central aortic blood pressure can be estimated from as few as two non-invasive peripheral circulatory waveforms via model-based system identification. To fulfill this objective, cardiovascular system is viewed as a nonlinear dynamic wave propagation system with unknown input. In this project, a theoretical study to develop system identification and input de-convolution methods for a class of nonlinear wave propagation systems will be conducted, and then the validity of the methods will be examined by applying them to the problem of estimating central aortic blood pressure waveform from two non-invasive peripheral circulatory waveforms. This project will contribute to advance dynamic systems and control by solving a system identification problem for a class of nonlinear dynamic systems. Since the class of systems considered belongs to cardiovascular health monitoring applications, it will advance systems physiology initiatives. Especially, this project will benefit the development of data-based modeling methods for physiologic systems and neuroscience, such as condition monitoring of cardiovascular hemodynamics and assessment of autonomic-cardiac regulation function. Ultimately, this project may open up new opportunities for technological advances in pervasive and personalized medicine, which can ultimately improve the quality of life of human beings.