Real-Time Heartbeat Sensing with Face Video using a Webcam and OpenCV

People's heart rates can be measured for a variety of purposes, including telemedicine, the Internet of Things (IoT), sports, security, etc. The traditional method of monitoring HR can, however, be challenging at times or it may not scale. This study offers a solution that can simultaneously assess the heart rates of various persons using live video broadcasts. By recording the color changes brought on by blood circulation in facial skin, heart rate can be measured. An indicator that correlates to heart rate is represented by the typical hue in the area of interest (ROI) selected on the face. A pulse frequency is frequently retrieved from this signal using signal processing. This method is reasonably accurate and stable. A webcam is used to simultaneously detect the faces of persons and measure their heart rates, yielding a Heart rate slip rate of 3–5 percent. Our solution uses object tracking along with face detection, which requires less computing resources and enables greater scaling.