With a surge in online medical advising remote monitoring of patient vitals is required. This can be facilitated with the Remote Photoplethysmography (rPPG) techniques that compute vital signs from facial videos. It involves processing video frames to obtain skin pixels, extracting the cardiac data from it and applying signal processing filters to extract the Blood Volume Pulse (BVP) signal. Different algorithms are applied to the BVP signal to estimate the various vital signs. We implemented a web application framework to measure a person's Heart Rate (HR), Heart Rate Variability (HRV), Oxygen Saturation (SpO2), Respiration Rate (RR), Blood Pressure (BP), and stress from the face video. The rPPG technique is highly sensitive to illumination and motion variation. The web application guides the users to reduce the noise due to these variations and thereby yield a cleaner BVP signal. The accuracy and robustness of the framework was validated with the help of volunteers.

翻译：需要通过在线医疗咨询对病人生命迹象进行远程监测,这可以通过远程光谱截图(rPPG)技术得到促进,该技术从面部视频中计算生命迹象,涉及处理视频框架以获取皮肤像素,从中提取心脏数据,并应用信号处理过滤器提取血液卷脉冲信号。对BVP信号应用不同的算法以估计各种生命迹象。我们实施了网络应用框架以测量一个人的心率(HR)、心率挥发性(HRV)、氧饱和性(SpO2)、呼吸率(RRR)、血液压力(BP)和面部视频的压力。RPPG技术对照明和运动变异非常敏感。网络应用指导用户减少这些变异造成的噪音,从而产生更清洁的BVP信号。框架的准确性和稳健性在志愿者的帮助下得到了验证。