Vital Sign Estimation from Passive Thermal Video

Abstract

Conventional wired detection of vital signs limits the
use of these important physiological parameters by many
applications, such as airport health screening, elder care,
and workplace preventive care. In this paper, we explore
contact-free heart rate and respiratory rate detection
through measuring infrared light modulation emitted near
superficial blood vessels or a nasal area respectively. To
deal with complications caused by subjects’ movements,
facial expressions, and partial occlusions of the skin, we
propose a novel algorithm based on contour segmentation
and tracking, clustering of informative pixels, and dominant
frequency component estimation. The proposed method
achieves robust subject regions-of-interest alignment and
motion compensation in infrared video with low SNR. It relaxes
some strong assumptions used in previous work and
substantially improves on previously reported performance.
Preliminary experiments on heart rate estimation for 20
subjects and respiratory rate estimation for 8 subjects exhibit promising results.