Laguerre-model blind system identification: Cardiovascular dynamics estimated from multiple peripheral circulatory signals
Laguerre-model blind system identification: Cardiovascular dynamics estimated from multiple peripheral circulatory signals
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DOI：
10.1109/tbme.2005.856260
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发表时间：
2005-11-01
影响因子：
4.6
通讯作者：
Asada, HH
中科院分区：
文献类型：
--
作者：
McCombie, DB;Reisner, AT;Asada, HH
本文提出了一种比较在不同位置测量的多个循环波形的方法，以改进从这些信号中估计心血管参数的方法。该方法识别形成每个波形信号的不同血管动力学，并估计它们共享的共同心脏How输入。该信号处理算法使用拉盖尔函数级数展开对各动脉分支的血流动力学建模，并利用多通道盲系统识别从外周波形中识别这些模型中的未知参数。提出了一种确定拉盖尔基极的有效方法，使拉盖尔展开捕获并快速收敛到两个循环信号中观察到的固有动脉动力学，此外，还提出了一种新的反卷积方法，以稳定地反演识别的动态模型，用于从外周压力波形估计心输出量（CO）波形。将该方法应用于实验猪数据。该模型与测量的周围压力波形的平均误差小于5%，并且估计的CO波形与金标准测量结果非常吻合。
This paper presents a method for comparing multiple circulatory waveforms measured at different locations to improve cardiovascular parameter estimation from these signals. The method identifies the distinct vascular dynamics that shape each waveform signal, and estimates the common cardiac How input shared by them. This signal-processing algorithm uses the Laguerre function series expansion for modeling the hemodynamics of each arterial branch, and identifies unknown parameters in these models from peripheral waveforms using multichannel blind system identification. An effective technique for determining the Laguerre base pole is developed, so that the Laguerre expansion captures and quickly converges to the intrinsic arterial dynamics observed in the two circulatory signals, Furthermore, a novel deconvolution method is developed in order to stably invert the identified dynamic models for estimating the cardiac output (CO) waveform from peripheral pressure waveforms. The method is applied to experimental swine data. A mean error of less than 5% with the measured peripheral pressure waveforms has been achieved using the models and excellent agreement between the estimated CO waveforms and the gold standard measurements have been obtained.