Abstract
We presented a systematic study of how subject head motion affects pulse rate estimation using photoplethysmography from the subject's face. We evaluated the performance at various steps in the process, including object tracking, skin blob detection, pulse signal extraction and pulse rate estimation. We demonstrated that the signal-to-noise ratio of the power spectrum is a good indicator of signal artifacts induced by subject motion, thus can be used as a quantitative metric in continuous pulse rate monitoring to reduce estimation errors.
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