Remote photoplethysmography (rPPG) in the wild: Remote heart rate imaging via online webcams

Remote photoplethysmography (rPPG) is a low-cost technique to measure physiological parameters such as heart rate by analyzing videos of a person. There has been growing attention to this technique due to the increased possibilities and demand for running psychological experiments on online platforms. Technological advancements in commercially available cameras and video processing algorithms have led to significant progress in this field. However, despite these advancements, past research indicates that suboptimal video recording conditions can severely compromise the accuracy of rPPG. In this study, we aimed to develop an open-source rPPG methodology and test its performance on videos collected via an online platform, without control of the hardware of the participants and the contextual variables, such as illumination, distance, and motion. Across two experiments, we compared the results of the rPPG extraction methodology to a validated dataset used for rPPG testing. Furthermore, we then collected 231 online video recordings and compared the results of the rPPG extraction to finger pulse oximeter data acquired with a validated mobile heart rate application. Results indicated that the rPPG algorithm was highly accurate, showing a significant degree of convergence with both datasets thus providing an improved tool for recording and analyzing heart rate in online experiments.