Abstract
Photoplethysmography (PPG) is a method for contactless heart rate estimation through the analysis of slight variations of skin color. Skin color variation caused by changes in the blood volume in vessels and registered by a camera is called color signal. Recent studies proved that some PPG methods could be used to produce accurate heart rate estimations on videodata recorded by common web-cameras that makes them potentially applicable for longterm health monitoring in home or office conditions. In this work, we study novel Approximation-based transformation method of signal processing and evaluate its combination with common preprocessing and postprocessing algorithms. Approximation-based transformation is the procedure of computing an approximation signal that consists of leading coefficients of the local quadratic approximation of the color signal.
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