A Development of Enhanced Contactless Bio Signal Estimation Algorithm and System for COVID19 Prevention

In recent days, many wearable biological data measuring devices have been developed. Despite many advantages, these devices have a few shortcomings such as tissue allergies, motion artifact, and signal noise problem. User identification for the remote monitoring center is another issue. Most of these problems are caused by the sensor contact measurement method. Due to these problems, many studies have been conducted to find ways that simplify the measurement process and cause less discomfort to the users. Many existing studies measured heart rate and respiratory rate by extracting photo plethysmography (PPG) signals from the user’s face with cameras and proper lighting. In this study, the face recognition experiment, we conducted face recognition in various situations. The recognition rate of this system exhibited 96.0% accuracy when trying to recognize the front, and exhibited 86.0% accuracy from the sides of the face. The average heart rate estimation accuracy was 99.1%, compared to the gold standard method.