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Toward a noninvasive subject-specific estimation of abdominal aortic pressure

机译:寻求非侵入性的受试者特定的腹主动脉压

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First published July 11, 2008; doi:10.1152/ajpheart.01154.2007.-A method for estimation of central arterial pressure based on linear one-dimensional wave propagation theory is presented in this paper. The equations are applied to a distributed model of the arterial tree, truncated by three-element windkessels. To reflect individual differences in the properties of the arterial trees, we pose a minimization problem from which individual parameters are identified. The idea is to take a measured waveform in a peripheral artery and use it as input to the model. The model subsequently predicts the corresponding waveform in another peripheral artery in which a measurement has also been made, and the arterial tree model is then calibrated in such a way that the computed waveform matches its measured counterpart. For the purpose of validation, invasively recorded abdominal aortic, brachial, and femoral pressures in nine healthy subjects are used. The results show that the proposed method estimates the abdominal aortic pressure wave with good accuracy. The root mean square error (RMSE) of the estimated waveforms was 1.61 +- 0.73 mmHg, whereas the errors in systolic and pulse pressure were 2.32 +- 1.74 and 3.73 +- 2.04 mmHg, respectively. These results are compared with another recently prbposed method based on a signal processing technique, and it is shown that our method yields a significantly (P < 0.01) lower RMSE. With more extensive validation, the method may eventually be used in clinical practice to provide detailed, almost individual, specific information as a valuable basis for decision making.
机译:首次发布于2008年7月11日; doi:10.1152 / ajpheart.01154.2007.-本文提出了一种基于线性一维波传播理论的中心动脉压估计方法。这些方程式被应用于动脉树的分布式模型,该模型被三元素风帆截短。为了反映动脉树属性的个体差异,我们提出了一个最小化问题,可以从中识别出各个参数。想法是在外周动脉中获取测量的波形,并将其用作模型的输入。该模型随后预测另一条周围动脉中也进行了测量的相应波形,然后以计算出的波形与其测量到的对应波形相匹配的方式校准动脉树模型。为了进行验证,使用了9位健康受试者的侵入性记录的腹主动脉,肱和股骨压。结果表明,该方法能够较好地估计腹主动脉压力波。估计波形的均方根误差(RMSE)为1.61±0.73 mmHg,而收缩压和脉压的误差分别为2.32±1.74和3.73±2.04 mmHg。将这些结果与最近基于信号处理技术的另一种方法进行了比较,结果表明我们的方法产生的RMSE显着降低(P <0.01)。经过更广泛的验证,该方法最终可用于临床实践,以提供详细的,几乎个别的,特定的信息,作为决策的有价值的基础。

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