Remote imaging photoplethysmography (RIPPG) is able to access human vital signs without physical contact. However most of the conventional RIPPG approaches are susceptive to motions of subjects or camera. Overcoming motion artifacts presents one of the most challenging problems. Focusing on the motion artifacts problem, the effects of motion artifacts on RIPPG signals were analyzed. In order to suppress motion artifacts for RIPPG, region of interest (ROI) is stabilized by using face tracking based on feature points tracking. And adaptive bandpass filter is further used to suppress the residual motion artifacts.
With the addition of motion artifacts, the sorting of independent component analysis (ICA) outputs becomes more important, hence reference sine signals are generated to be correlated with ICA output components, and the cardiac pulse wave is automatically picked up from ICA output components, with the largest correlation coefficient.Fourteen subjects were enrolled to test the robustness with large motion artifacts for the proposed RIPPG method. Experimental results show that the proposed method could obtain a much better performance in accessing pulse rates for moving subjects, compared to the state-of-the-art method. The effectiveness of our method in motion artifacts suppression was verified by comparison with a commercial oximeter using Bland-Altman analysis and Pearson’s correlation. With the efficient motion artifact suppression, RIPPG method has good potential in broadening the application of vital signs accesses.