@article{c90d1069e0cf46cb819c111dc3bcce97,
title = "Wearable sensing and telehealth technology with potential applications in the coronavirus pandemic",
abstract = "Coronavirus disease 2019 (COVID-19) has emerged as a pandemic with serious clinical manifestations including death. A pandemic at the large-scale like COVID-19 places extraordinary demands on the world's health systems, dramatically devastates vulnerable populations, and critically threatens the global communities in an unprecedented way. While tremendous efforts at the frontline are placed on detecting the virus, providing treatments and developing vaccines, it is also critically important to examine the technologies and systems for tackling disease emergence, arresting its spread and especially the strategy for diseases prevention. The objective of this article is to review enabling technologies and systems with various application scenarios for handling the COVID-19 crisis. The article will focus specifically on 1) wearable devices suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals; 2) unobtrusive sensing systems for detecting the disease and for monitoring patients with relatively mild symptoms whose clinical situation could suddenly worsen in improvised hospitals; and 3) telehealth technologies for the remote monitoring and diagnosis of COVID-19 and related diseases. Finally, further challenges and opportunities for future directions of development are highlighted.",
keywords = "Wearable sensor, unobtrusive monitoring, telehealth, COVID-19, point clouds, roadside LiDAR, detection, intelligent transportation system, Humans, Wearable Electronic Devices, SARS-CoV-2/pathogenicity, COVID-19/diagnosis, Telemedicine/methods, Pandemics/prevention & control, Delivery of Health Care/methods, Technology/methods",
author = "Xiao-Rong Ding and David Clifton and Nan Ji and Lovell, {Nigel H.} and Paolo Bonato and Wei Chen and Xinge Yu and Zhong Xue and Ting Xiang and Xi Long and Ke Xu and Xinyu Jiang and Qi Wang and B. Yin and Guodong Feng and Yuan-Ting Zhang",
year = "2021",
doi = "10.1109/RBME.2020.2992838",
language = "English",
volume = "14",
pages = "48--70",
journal = "IEEE Reviews in Biomedical Engineering",
issn = "1937-3333",
publisher = "Institute of Electrical and Electronics Engineers",
}