用最优信号质量指数增强远程PPG和心率估计

Jiyang Li, K. Vatanparvar, Li Zhu, Jilong Kuang, A. Gao
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引用次数: 2

摘要

随着无创生命体征检测的普及,远程光容积脉搏波描记术(rPPG)越来越受到社会的关注。远程PPG或rPPG信号以非接触方式提取,比可穿戴传感器收集的PPG信号更容易产生伪影。为了开发一种鲁棒和准确的从rPPG信号估计心率(HR)的管道,我们提出了一种新的实时动态ROI跟踪算法,该算法适用于轻微的运动和光线变化。此外,我们开发并包含了一个信号质量指数(SQI)来提高HR估计的精度。研究已经探索了PPG信号的最佳sqi,但没有针对远程PPG信号。在本文中,我们选择并测试了来自30名戴口罩的参与者的124次rPPG会话的6个SQIs:灌注、峰度、偏度、过零、熵和信噪比(SNR)。基于HR估计的平均绝对误差(MAE),选择最优SQI,并通过Mann-Whitney U检验(MWU)进行验证。最后,我们表明,在去除由最优SQI决定的异常值后,HR估计精度提高了29%,最佳结果达到2.308 bpm的MAE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhancement of Remote PPG and Heart Rate Estimation with Optimal Signal Quality Index
With the popularity of non-invasive vital signs detection, remote photoplethysmography (rPPG) is drawing attention in the community. Remote PPG or rPPG signals are extracted in a contactless manner that is more prone to artifacts than PPG signals collected by wearable sensors. To develop a robust and accurate pipeline to estimate heart rate (HR) from rPPG signals, we propose a novel real-time dynamic ROI tracking algorithm that applies to slight motions and light changes. Furthermore, we develop and include a signal quality index (SQI) to improve the HR estimation accuracy. Studies have explored optimal SQIs for PPG signals, but not for remote PPG signals. In this paper, we select and test six SQIs: Perfusion, Kurtosis, Skewness, Zero-crossing, Entropy, and signal-to-noise ratio (SNR) on 124 rPPG sessions from 30 participants wearing masks. Based on the mean absolute error (MAE) of HR estimation, the optimal SQI is selected and validated by Mann–Whitney U test (MWU). Lastly, we show that the HR estimation accuracy is improved by 29% after removing outliers decided by the optimal SQI, and the best result achieves the MAE of 2.308 bpm.
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