On indirect assessment of heart rate in video
This work provides a baseline for photoplethysmography in video, though it is incremental and not directly applicable in medicine.
The paper tackled the problem of indirectly assessing heart rate from video by examining adaptive baseline methods, such as regression models using age and motion intensity, which achieved a top-quarter position in the Remote Physiological Signal Sensing challenge leaderboard.
Problem of indirect assessment of heart rate in video is addressed. Several methods of indirect evaluations (adaptive baselines) were examined on Remote Physiological Signal Sensing challenge. Particularly, regression models of dependency of heart rate on estimated age and motion intensity were obtained on challenge's train set. Accounting both motion and age in regression model led to top-quarter position in the leaderboard. Practical value of such adaptive baseline approaches is discussed. Although such approaches are considered as non-applicable in medicine, they are valuable as baseline for the photoplethysmography problem.