  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.
