Paper Info
Title
PulseGAN: Learning to generate realistic pulse waveforms in remote photoplethysmography
Abstract
Remote photoplethysmography (rPPG) is a non-contact technique for measuring cardiac signals from facial videos. High-quality rPPG pulse signals are urgently demanded in many fields, such as health monitoring and emotion recognition. However, most of the existing rPPG methods can only be used to get average heart rate (HR) values due to the limitation of inaccurate pulse signals. In this paper, a n...
Year
DOI
Venue
2021
10.1109/JBHI.2021.3051176
IEEE Journal of Biomedical and Health Informatics
Keywords
DocType
Volume
Generative adversarial networks,Feature extraction,Skin,Heart rate variability,Videos,Heart rate,Gallium nitride
Journal
25
Issue
ISSN
Citations 
5
2168-2194
2
PageRank 
References 
Authors
0.37
0
6
Name
Order
Citations
PageRank
Rencheng Song1156.03
Chen Huan220.37
Juan Cheng36211.53
chang li428219.50
Yu Liu549230.80
Xun Chen645852.73