一种估计脉压变异的新方法。

A novel approach to pulse pressure variation estimation.

作者信息

Austin Daniel, Staats Christian, Aboy Mateo

机构信息

Electronics Engineering Technology, Oregon Institute of Technology, Portland, OR 97006, USA.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1391-3. doi: 10.1109/IEMBS.2006.260039.

DOI:10.1109/IEMBS.2006.260039

PMID:17946043

Abstract

We describe a novel algorithm to estimate the pulse pressure variation index (PPV) from arterial blood pressure signals (ABP). PPV has been shown to be one of the best predictors of fluid responsiveness in mechanically ventilated subjects. Our PPV algorithm uses a non-linear technique for envelope estimation, eliminating the need for automatic beat detection. Additionally, the algorithm makes use of nonparametric spectral techniques to extract the respiratory rate, and a median filter for artifact removal. The algorithm was validated against the continuous PPV output obtained from the commercially available PiCCOreg system and gold standard expert PPV manual annotations. The data consists of ABP taken from subjects who experienced rapid changes in hemodynamics. This data comprised over six hours of continuous ABP monitoring.

摘要

我们描述了一种从动脉血压信号（ABP）估计脉压变异指数（PPV）的新算法。PPV已被证明是机械通气患者液体反应性的最佳预测指标之一。我们的PPV算法使用非线性技术进行包络估计，无需自动搏动检测。此外，该算法利用非参数谱技术提取呼吸频率，并使用中值滤波器去除伪迹。该算法与从市售PiCCOreg系统获得的连续PPV输出以及金标准专家PPV手动注释进行了验证。数据包括从血流动力学快速变化的受试者获取的ABP。这些数据包括超过六小时的连续ABP监测。