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Physiologic-State-Adaptive Recovery of Aortic Blood Pressure and Flow Using Blind 2-Channel IIR Cardiovascular System Identification

机译:使用盲2通道IIR心血管系统识别的生理状态 - 适应性恢复主动脉血压和流量

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This paper presents the development and analysis of a method to identify a two-channel cardiovascular system using two distinct peripheral blood pressure signals. The method is able to characterize the upper- and lower-limb arterial path dynamics as well as the aortic root impedance, and recover the aortic blood pressure and flow signals fed to it. The blind system identification and input de-convolution algorithms for a class of two-channel infinite impulse response systems are developed and applied to a gray-box model of a two-channel cardiovascular system. Persistent excitation condition, model identifiability and asymptotic variance are analyzed to quantify the method's validity and reliability. Experimental results based on 83 data segments obtained from a swine subject show that the cardiovascular dynamics can be identified very accurately and reliably, and the aortic blood pressure and flow signals are stably recovered from two distinct peripheral blood pressure signals under diverse physiologic conditions. The benefit of the proposed method is demonstrated by comparing it to a predetermined transfer function describing the cardiovascular dynamics at nominal physiologic conditions.
机译:本文提出了一种以确定使用两个不同的末梢血压的信号的两通道心血管系统方法的开发和分析。该方法能够以表征大写和下肢动脉路径动力学以及主动脉根阻抗,并恢复主动脉血压和流馈送给它的信号。盲系统识别和输入去卷积算法的一类双通道无限脉冲响应系统的开发和应用到双通道心血管系统的灰盒模型。持续激励条件,模型识别性和渐近方差进行分析以量化方法的有效性和可靠性。实验结果基于从猪受试者显示,心血管动力学可以非常精确地和可靠地识别,和主动脉血压得到的83个数据段和流信号被稳定地从不同的生理条件下两个不同的末梢血压的信号恢复。所提出的方法的优点是,通过比较它与描述在标称生理条件下的心血管动力学一个预定的传递函数表现出。

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