@inproceedings{8268e0d0a75b4a469cf2e75462522539,
title = "Respiration and Cardiac Activity Sensing Using 3-D Cameras",
abstract = "Remote vital sign monitoring at home with commercially viable hardware extends care from hospital wards to personal settings without overwhelming health care providers and resources. In this paper, we explore usage of Azure Kinect (Microsoft) to monitor respiration and cardiac activity of a subject. We propose a fusion sensing technique that ensures immunity to ambient lighting conditions and movements of the subject, two key limitations while employing cameras or radars respectively. The functionality of this process is enabled by the phenomenon of Photoplethysmography (PPG) and availability of commercial sensors that can leverage it. We investigate robustness of the proposed technique by conducting experiments in variable lighting conditions while the subject is in motion. A comparison is drawn to an RGB camera and the results are validated using a pulse oximeter, a contact PPG sensor.",
keywords = "Depth Sensor, Near Infrared (NIR), Remote Photoplethysmography (rPPG), RGB Cameras",
author = "Yu Rongt and Sharanya Srinivas and Huiwen Chu and Hanguang Yu and Kailing Liu and Bliss, {Daniel W.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020 ; Conference date: 01-11-2020 Through 05-11-2020",
year = "2020",
month = nov,
day = "1",
doi = "10.1109/IEEECONF51394.2020.9443331",
language = "English (US)",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
publisher = "IEEE Computer Society",
pages = "955--959",
editor = "Matthews, {Michael B.}",
booktitle = "Conference Record of the 54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020",
}