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首页> 外文期刊>Biomedical signal processing and control >PQR signal quality indexes: A method for real-time photoplethysmogram signal quality estimation based on noise interferences
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PQR signal quality indexes: A method for real-time photoplethysmogram signal quality estimation based on noise interferences

机译：PQR信号质量指标：一种基于噪声干扰的实时光体积描记图信号质量估计方法

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摘要

The photoplethysmograph (PPG) acquired from pulse oximeters has been extensively used to estimate the heart rate and blood oxygen saturation. However, how to improve the accuracy of these parameters is always a challenging work as PPG is susceptible to be contaminated by noises especially motion artifacts (MAs). This study presents an algorithm called PQR to calculate three indexes (P/QJR) for estimation the signal quality based on noise interferences and rSQl index for comparison of any two signals. P/Q/R indicates the influencing degree of high-frequency noise, baseline wandering and motion artifacts on PPG respectively. And a relative signal quality estimation index rSQI is designed to compare the quality of any two signals. When the value of rSQI is greater than zero, it illustrates that the quality of the former signal is better than the latter, and vice versa. Lower P/Q/R scores could be obtained from the algorithm if PPG is contaminated by strong artifacts or with an irregular signal morphology. The algorithm put a complete successive signal into consideration instead of signal segmentation beat by beat. Experiment results using MIMIC (Multi-parameter Intelligent Monitoring for Intensive care) database indicates the availability of PQR algorithm. And the real-time PPG signal quality estimation system could be realized to help estimating heart rate online by applying PQR algorithm to the dataset of IEEE Signal Processing Society. Moreover, the experiments using our lab hardware platform show the corresponding preliminary results of application on the comparison of different signal processing methods. The novel PQR algorithm generates significantly lower rSQI values with the comparison of reference signal when PPG signals are contaminated by strong noise. The chosen threshold could be established once an application has been defined derived from the collected data. The PQR algorithm maybe could help to guide the choice of PPG signal in real-time for the physical information extraction such as heart rate. (C) 2018 Elsevier Ltd. All rights reserved.
机译：从脉搏血氧仪获得的光电容积描记器（PPG）已被广泛用于估算心率和血氧饱和度。但是，如何提高这些参数的精度始终是一项具有挑战性的工作，因为PPG容易受到噪声特别是运动伪影（MA）的污染。这项研究提出了一种称为PQR的算法，该算法可基于噪声干扰计算三个指数（P / QJR）来估计信号质量，并比较rSQl指数来比较任意两个信号。 P / Q / R分别表示PPG上高频噪声，基线漂移和运动伪影的影响程度。设计了相对信号质量估计指标rSQI来比较任意两个信号的质量。当rSQI的值大于零时，说明前者的信号质量优于后者，反之亦然。如果PPG被强伪影或不规则信号形态污染，则可以从算法中获得较低的P / Q / R分数。该算法将完整的连续信号考虑在内，而不是逐节拍地进行信号分段。使用MIMIC（重症监护多参数智能监控）数据库的实验结果表明了PQR算法的可用性。通过将PQR算法应用于IEEE Signal Processing Society的数据集，可以实现实时PPG信号质量估计系统，以帮助在线估计心率。此外，使用我们实验室硬件平台进行的实验通过比较不同的信号处理方法，显示了相应的初步应用结果。当PPG信号被强噪声污染时，与参考信号相比，新颖的PQR算法生成的rSQI值要低得多。一旦定义了从收集的数据派生的应用程序，就可以建立所选的阈值。 PQR算法可能有助于指导PPG信号的实时选择，以进行诸如心率之类的物理信息提取。 （C）2018 Elsevier Ltd.保留所有权利。

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