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

IEEE J Biomed Health Inform. 2019 Nov;23(6):2398-2408. doi: 10.1109/JBHI.2018.2880097. Epub 2018 Nov 7.

Abstract

Unobtrusive monitoring of vital signs is relevant for both medical (patient monitoring) and non-medical applications (e.g., stress and fatigue monitoring). In this paper, we focus on the use of imaging photoplethysmography (iPPG). High frame rate videos were acquired by using a monochrome camera and an optical band-pass filter ([Formula: see text] 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 [Formula: see text] 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 intervals with or without ICA pre-processing. Smaller MAE values of frequency domain descriptors were observed when ICA pre-processing was 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms
  • Female
  • Heart Rate / physiology*
  • Humans
  • Male
  • Middle Aged
  • Photoplethysmography / methods*
  • Principal Component Analysis
  • Signal Processing, Computer-Assisted*
  • Video Recording / methods*
  • Young Adult