Heart Rate and Heart Rate Variability from Single-Channel Video and ICA Integration of Multiple Signals

Unobtrusive monitoring of vital signs is relevant for both medical (patient monitoring) and non-medical applications (e.g. stress and fatigue monitoring). In this work, we focus on the use of imaging photoplethysmography (iPPG). High frame rate videos were acquired by using a monochrome camera and an op- tical band-pass filter (560 ± 20 nm). To enhance iPPG signal, we investigated the use of Independent Component Analysis (ICA) pre-processing applied to iPPG signal from different regions of the face. Methodology was tested on 30 healthy volunteers. Heart rate (HR) and standard time and frequency domain descriptors of heart rate variability (HRV), simultaneously extracted from videos and ECG data, were compared. A mean absolute error (MAE) about 3.812 ms was observed for normal-to-normal in- tervals with or without ICA pre-processing. Smaller MAE values of frequency domain descriptors were observed when ICA pre- processing is used. The impact of both video frame rate and video signal interval were also analyzed. All the results support the conclusion that proposed ICA pre-processing can effectively improve the HR and HRV assessment from iPPG.