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Online Removal of Baseline Shift with a Polynomial Function for Hemodynamic Monitoring Using Near-Infrared Spectroscopy

机译:使用多项式函数在线移除基线位移以使用近红外光谱进行血液动力学监测

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摘要

Near-infrared spectroscopy (NIRS) has become widely accepted as a valuable tool for noninvasively monitoring hemodynamics for clinical and diagnostic purposes. Baseline shift has attracted great attention in the field, but there has been little quantitative study on baseline removal. Here, we aimed to study the baseline characteristics of an in-house-built portable medical NIRS device over a long time (>3.5 h). We found that the measured baselines all formed perfect polynomial functions on phantom tests mimicking human bodies, which were identified by recent NIRS studies. More importantly, our study shows that the fourth-order polynomial function acted to distinguish performance with stable and low-computation-burden fitting calibration (R-square >0.99 for all probes) among second- to sixth-order polynomials, evaluated by the parameters R-square, sum of squares due to error, and residual. This study provides a straightforward, efficient, and quantitatively evaluated solution for online baseline removal for hemodynamic monitoring using NIRS devices.
机译:近红外光谱(NIRS)已被广泛接受为用于临床和诊断目的无创监测血液动力学的有价值的工具。基线偏移已在该领域引起了极大的关注,但很少有关于基线去除的定量研究。在这里,我们旨在研究长时间(> 3.5小时)内建的便携式医疗NIRS设备的基线特征。我们发现,在最近的NIRS研究中,所测得的基线在模仿人体的幻像测试中均形成了完美的多项式函数。更重要的是,我们的研究表明,通过参数评估,四阶多项式函数通过稳定且低计算负担的拟合校准(所有探头的R平方> 0.99)来区分性能。 R平方,由于误差引起的平方和以及残差。这项研究为使用NIRS设备进行血流动力学监测的在线基线去除提供了一种简单,有效且经过定量评估的解决方案。

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