Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.

Journal: Physiological measurement
Published Date:

Abstract

UNLABELLED: Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospital ward, the main challenges in the development of continuous and robust non-contact monitoring techniques are the identification of time periods and the segmentation of skin regions of interest (ROIs) from which vital signs can be estimated. We propose a deep learning framework to tackle these challenges.

Authors

  • Sitthichok Chaichulee
    Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, United Kingdom. Author to whom any correspndence should be addressed.
  • Mauricio Villarroel
  • João Jorge
  • Carlos Arteta
  • Kenny McCormick
  • Andrew Zisserman
    Department of Engineering Science, University of Oxford, Oxford, UK.
  • Lionel Tarassenko
    Department of Engineering Science, University of Oxford, Oxford, UK.