This work investigates the estimation biases of remote photoplethysmography (rPPG) methods for pulse rate measurement across diverse demographics. Advances in photoplethysmography (PPG) and rPPG methods have enabled the development of contact and noncontact approaches for continuous monitoring and collection of patient health data. The contagious nature of viruses such as COVID-19 warrants noncontact methods for physiological signal estimation. However, these approaches are subject to estimation biases due to variations in environmental conditions and subject demographics. The performance of contact-based wearable sensors has been evaluated, using off-the-shelf devices across demographics. However, the measurement uncertainty of rPPG methods that estimate pulse rate has not been sufficiently tested across diverse demographic populations or environments. Quantifying the efficacy of rPPG methods in real-world conditions is critical in determining their potential viability as health monitoring solutions. Currently, publicly available face datasets accompanied by physiological measurements are typically captured in controlled laboratory settings, lacking diversity in subject skin tones, age, and cultural artifacts (e.g, bindi worn by Indian women). In this study, we collect pulse rate and facial video data from human subjects in India and Sierra Leone, in order to quantify the uncertainty in noncontact pulse rate estimation methods. The video data are used to estimate pulse rate using state-of-the-art rPPG camera-based methods, and compared against ground truth measurements captured using an FDA-approved contact-based pulse rate measurement device. Our study reveals that rPPG methods exhibit similar biases when compared with a contact-based device across demographic groups and environmental conditions. The mean difference between pulse rates measured by rPPG methods and the ground truth is found to be ~2% (1 beats per minute (b.p.m.)), signifying agreement of rPPG methods with the ground truth. We also find that rPPG methods show pulse rate variability of ~15% (11 b.p.m.), as compared to the ground truth. We investigate factors impacting rPPG methods and discuss solutions aimed at mitigating variance.

这项工作调查了远程光电容积描记 (rPPG) 方法在不同人口统计数据中用于脉率测量的估计偏差。光电容积脉搏波 (PPG) 和 rPPG 方法的进步使接触式和非接触式方法的发展成为可能，以连续监测和收集患者健康数据。COVID-19 等病毒的传染性保证了生理信号估计的非接触方法。然而，由于环境条件和受试者人口统计的变化，这些方法会受到估计偏差的影响。已经使用跨人口统计的现成设备评估了基于接触的可穿戴传感器的性能。然而，估计脉率的 rPPG 方法的测量不确定性尚未在不同的人口群体或环境中得到充分测试。量化 rPPG 方法在现实条件下的功效对于确定其作为健康监测解决方案的潜在可行性至关重要。目前，伴随着生理测量的公开可用的面部数据集通常是在受控实验室环境中捕获的，缺乏主题肤色、年龄和文化产物（例如，印度妇女穿的宾迪）的多样性。在这项研究中，我们从印度和塞拉利昂的人类受试者中收集脉搏率和面部视频数据，以量化非接触式脉搏率估计方法的不确定性。视频数据用于使用最先进的基于 rPPG 相机的方法来估计脉搏率，并与使用 FDA 批准的基于接触的脉搏率测量设备捕获的地面实况测量值进行比较。我们的研究表明，与跨人口群体和环境条件的基于接触的设备相比，rPPG 方法表现出类似的偏差。发现通过 rPPG 方法测量的脉搏率与地面实况之间的平均差异为 ~2%（每分钟 1 次跳动 (bpm)），表明 rPPG 方法与地面实况一致。我们还发现，与地面实况相比，rPPG 方法显示出约 15% (11 bpm) 的脉率变异性。我们调查了影响 rPPG 方法的因素并讨论了旨在减少差异的解决方案。我们的研究表明，与跨人口群体和环境条件的基于接触的设备相比，rPPG 方法表现出类似的偏差。发现通过 rPPG 方法测量的脉搏率与地面实况之间的平均差异约为 2%（每分钟 1 次跳动 (bpm)），表明 rPPG 方法与地面实况一致。我们还发现，与真实情况相比，rPPG 方法显示出约 15% (11 bpm) 的脉率变异性。我们调查了影响 rPPG 方法的因素并讨论了旨在减少差异的解决方案。我们的研究表明，与跨人口群体和环境条件的基于接触的设备相比，rPPG 方法表现出类似的偏差。发现通过 rPPG 方法测量的脉搏率与地面实况之间的平均差异为 ~2%（每分钟 1 次跳动 (bpm)），表明 rPPG 方法与地面实况一致。我们还发现，与地面实况相比，rPPG 方法显示出约 15% (11 bpm) 的脉率变异性。我们调查了影响 rPPG 方法的因素并讨论了旨在减少差异的解决方案。我们还发现，与地面实况相比，rPPG 方法显示出约 15% (11 bpm) 的脉率变异性。我们调查了影响 rPPG 方法的因素并讨论了旨在减少差异的解决方案。我们还发现，与地面实况相比，rPPG 方法显示出约 15% (11 bpm) 的脉率变异性。我们调查了影响 rPPG 方法的因素并讨论了旨在减少差异的解决方案。