کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
558869 | 875009 | 2013 | 8 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Pulse pressure variation tracking using sequential Monte Carlo methods Pulse pressure variation tracking using sequential Monte Carlo methods](/preview/png/558869.png)
The pulse pressure variation (PPV) is a measure of the respiratory effect on the variation of systemic arterial blood pressure (ABP) in patients receiving full mechanical ventilation. It is a promising predictor of increases in cardiac output due to an infusion of fluid. We describe a novel automatic algorithm to estimate the PPV of ABP signals recorded under full respiratory support. The algorithm utilizes our recently developed sequential Monte Carlo method (SMCM), which is called a maximum a-posteriori adaptive marginalized particle filter (MAM-PF). MAM-PF estimates the state-space model parameters of the ABP signal continuously and its upper and lower envelopes are derived as a combination of those parameter estimates. Then, the continuous PPV values can be easily obtained based on those estimated envelopes. We report the assessment results of the proposed algorithm on real ABP signals.
Journal: Biomedical Signal Processing and Control - Volume 8, Issue 4, July 2013, Pages 333–340