Non-contact video-based pulse rate measurement on a mobile service robot

Non-contact image photoplethysmography has gained a lot of attention during the last 5 years. Starting with the work of Verkruysse et al. [1], various methods for estimation of the human pulse rate from video sequences of the face under ambient illumination have been presented. Applied on a mobile service robot aimed to motivate elderly users for physical exercises, the pulse rate can be a valuable information in order to adapt to the users conditions. For this paper, a typical processing pipeline was implemented on a mobile robot, and a detailed comparison of methods for face segmentation was conducted, which is the key factor for robust pulse rate extraction even, if the subject is moving. A benchmark data set is introduced focusing on the amount of motion of the head during the measurement.