Abstract
Imaging photoplethysmography (iPPG) is a promising technology for contactless heart rate (HR) monitoring. However iPPG signals are easily deteriorated by subject movements and illumination changes. The purpose of this study was to develop a signal quality index (SQI) for realtime HR monitoring applications and to assess its performance on a challenging dataset composed of videos of moving subjects. HR was estimated using a multi-input adaptive frequency tracking scheme, in which the iPPG signals derived with different methods and their corresponding SQIs were provided as inputs. Using the proposed SQI, the average absolute error was reduced by 42%/45% when the forehead/entire face region was used to derive iPPG signals, respectively.
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