基于3D面部特征与头偏角的rPPG区域选择方法，提升急诊室心率检测精度。
R2I-rPPG: A Robust Region of Interest Selection Method for Remote Photoplethysmography to Extract Heart Rate
- 利用3D人脸关键点和头偏角动态定位最优采集区域
- 在急诊室环境下实现90%以上的心率估计准确率
- 适合临床远程监测与移动健康设备应用
新冠疫情凸显了低成本、可扩展的无接触生命体征测量需求，适用于医疗机构初筛或远程问诊。远距离光体积描记（rPPG）在光照良好、受试者静止的实验室环境中能准确估算心率（HR），但其在真实医疗场景中的应用受限。主要障碍在于感兴趣区域（ROI）的精准定位。临床或远程就诊常面临光照不足、运动伪影、相机角度变化及距离不一等问题。本文提出一种基于3D面部地标与患者头部偏转角的rPPG ROI选择方法，并验证其与平面正交于皮肤（POS）rPPG方法结合，在急诊科呼吸系统症状患者视频上的鲁棒性。结果表明，该方法显著提升了复杂临床环境下的rPPG准确性与稳定性。
原文摘要 · Abstract (English)
The COVID-19 pandemic has underscored the need for low-cost, scalable approaches to measuring contactless vital signs, either during initial triage at a healthcare facility or virtual telemedicine visits. Remote photoplethysmography (rPPG) can accurately estimate heart rate (HR) when applied to close-up videos of healthy volunteers in well-lit laboratory settings. However, results from such highly optimized laboratory studies may not be readily translated to healthcare settings. One significant barrier to the practical application of rPPG in health care is the accurate localization of the region of interest (ROI). Clinical or telemedicine visits may involve sub-optimal lighting, movement artifacts, variable camera angle, and subject distance. This paper presents an rPPG ROI selection method based on 3D facial landmarks and patient head yaw angle. We then demonstrate the robustness of this ROI selection method when coupled to the Plane-Orthogonal-to-Skin (POS) rPPG method when applied to videos of patients presenting to an Emergency Department for respiratory complaints. Our results demonstrate the effectiveness of our proposed approach in improving the accuracy and robustness of rPPG in a challenging clinical environment.
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