Smartphone photoplethysmography is a newly developed technique that can detect several physiological parameters from the photoplethysmographic signal obtained by the built-in camera of a smartphone. It is simple, low-cost, and easy-to-use, with a great potential to be used in remote medicine and home healthcare service. However, the determination of the optimal region of interest (ROI), which is an important issue for extracting photoplethysmographic signals from the camera video, has not been well studied. We herein proposed five algorithms for ROI selection: variance (VAR), spectral energy ratio (SER), template matching (TM), temporal difference (TD), and gradient (GRAD). Their performances were evaluated by a 50-subject experiment comparing the heart rates measured from the electrocardiogram and those from the smartphone using the five algorithms. The results revealed that the TM and the TD algorithms outperformed the other three as they had less standard error of estimate (<1.5 bpm) and smaller limits of agreement (<3 bpm). The TD algorithm was slightly better than the TM algorithm and more suitable for smartphone applications. These results may be helpful to improve the accuracy of the physiological parameters measurement and to make the smartphone photoplethysmography technique more practical.
Investigation of Five Algorithms for Selection of the Optimal Region of Interest in Smartphone Photoplethysmography