Automatic Selection of Webcam Photoplethysmographic Pixels Based on Lightness Criteria
We propose, in this study, an original method that was developed to remotely measure the instantaneous pulse rate using photoplethysmographic signals that were recorded from a low-cost webcam. The method is based on a prior selection of pixels of interest using a custom segmentation that used the face lightness distribution to define different sub-regions. The most relevant sub-regions are automatically selected and combined by evaluating their respective signal to noise ratio. Performances of the proposed technique were evaluated using an approved contact sensor on a set of seven healthy subjects. Different experiments while reading, with motion or while performing common tasks on a computer were conducted in the laboratory. The proposed segmentation technique was compared with other benchmark methods that were already introduced in the scientific literature. The results exhibit high degrees of correlation and low pulse rate absolute errors, demonstrating that the segmentation we propose in this study outperform available region-of-interest selection methods.