Observer-Based Deconvolution of Deterministic Input in Coprime Multichannel Systems With Its Application to Noninvasive Central Blood Pressure Monitoring.
Observer-Based Deconvolution of Deterministic Input in Coprime Multichannel Systems With Its Application to Noninvasive Central Blood Pressure Monitoring.
复制标题
DOI：
10.1115/1.4047060
复制
发表时间：
2020-05
期刊：
影响因子：
--
通讯作者：
Z. Ghasemi;Woongsun Jeon;Chang-Sei Kim;Anuj Gupta;R. Rajamani;J. Hahn
中科院分区：
文献类型：
--
作者：
Z. Ghasemi;Woongsun Jeon;Chang-Sei Kim;Anuj Gupta;R. Rajamani;J. Hahn
估计中心主动脉血压（BP）对于心血管（CV）健康和风险预测目的是重要的。CV系统是一个多通道动力学系统，在不同的身体部位产生多个BP，以响应中央主动脉BP。本文涉及的发展和分析的一个基于卷积的方法去卷积未知的输入在一类互质多通道系统适用于无创估计的中央主动脉血压。多通道系统响应于公共输入而产生多个输出。因此，任何两个输出之间的关系构成了一个假设的输入输出系统，其中嵌入了作为状态的未知输入。我们的方法的核心思想是通过为假设的输入输出系统设计一个观测器来获得未知的输入。针对互质多通道系统的输入反卷积问题，提出了一种未知输入观测器（UIO）。我们提供了一个通用的设计算法，以及有意义的物理见解和固有的性能限制与算法。我们的方法的有效性和潜力进行了说明使用的案例研究，估计中心主动脉BP波形从两个非侵入性采集的外周动脉脉搏波形。与传统的逆滤波（IF）和外周动脉脉搏缩放技术相比，UIO可以将与中心主动脉BP相关的均方根误差（RMSE）降低高达27.5%和28.8%。
Estimating central aortic blood pressure (BP) is important for cardiovascular (CV) health and risk prediction purposes. CV system is a multichannel dynamical system that yields multiple BPs at various body sites in response to central aortic BP. This paper concerns the development and analysis of an observer-based approach to deconvolution of unknown input in a class of coprime multichannel systems applicable to noninvasive estimation of central aortic BP. A multichannel system yields multiple outputs in response to a common input. Hence, the relationship between any pair of two outputs constitutes a hypothetical input-output system with unknown input embedded as a state. The central idea underlying our approach is to derive the unknown input by designing an observer for the hypothetical input-output system. In this paper, we developed an unknown input observer (UIO) for input deconvolution in coprime multichannel systems. We provided a universal design algorithm as well as meaningful physical insights and inherent performance limitations associated with the algorithm. The validity and potential of our approach were illustrated using a case study of estimating central aortic BP waveform from two noninvasively acquired peripheral arterial pulse waveforms. The UIO could reduce the root-mean-squared error (RMSE) associated with the central aortic BP by up to 27.5% and 28.8% against conventional inverse filtering (IF) and peripheral arterial pulse scaling techniques.