Abstract
One of the limitations of photoplethysmography (PPG) using a contact sensor to estimate the heart rate is that the sensor must be attached directly to the patient's body. rPPG (remote-Photoplethysmography) can remotely monitor a patient's heart ratebased on an image. However, rPPG has limitations in instances where this technology is directly affected by the lighting conditions and direction of the observed subject. This study used rPPG based on the Green Channel and HSV (Hue, Saturation, and Value) color model to estimate heart rate under different lighting conditions. Analysis, computational methods,and image transformation functions are used for data selection, denoising, colormodel conversion, spectral analysis, and visualization to extract biomedical signals from inputs. The estimatedheart rate was then derivedusing spectral analysis on videostaken from an area of interest on the forehead. Compared to the ground truth, theaverage percentage error from the facial lighting tests conducted at 260 lux, 19 lux, and 11 lux for the Green Channel color modelis 0.038, 0.118, and 0.229, which is less than the HSV's error of 0.095, 0.212, and 0.247.
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