Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Internet of Things-based Health Monitoring Systems, Artificial Intelligence-driven Diagnostic Algorithms, and Body Area Sensor Networks in COVID-19 Prevention, Screening, and Treatment

Internet of Things-based Health Monitoring Systems, Artificial Intelligence-driven Diagnostic... Despite the relevance of Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks in COVID-19 prevention, screening, and treatment, only limited research has been conducted on this topic. In this article, I cumulate previous research findings indicating that wearable Internet of Medical Things technologies can accurately assess COVID-19 symptoms. I contribute to the literature on smart sensor-based Internet of Medical Things and healthcare-integrated technologies by showing that machine learning algorithms and deep learning techniques can assist in COVID-19 prognosis. Throughout January 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “COVID-19” + “Internet of Things-based health monitoring systems,” “artificial intelligence-driven diagnostic algorithms,” and “body area sensor networks.” As I inspected research published between 2020 and 2022, only 152 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 28, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT. Keywords: Internet of Medical Things; COVID-19; body area sensor network http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Medical Research Addleton Academic Publishers

Internet of Things-based Health Monitoring Systems, Artificial Intelligence-driven Diagnostic Algorithms, and Body Area Sensor Networks in COVID-19 Prevention, Screening, and Treatment

Peter Bowles
American Journal of Medical Research , Volume 9 (1): 16 – Jan 1, 2022
Download PDF
16 pages

Loading next page...
 
/lp/addleton-academic-publishers/internet-of-things-based-health-monitoring-systems-artificial-G90Zo441RM
Publisher
Addleton Academic Publishers
Copyright
© 2009 Addleton Academic Publishers
ISSN
2334-4814
eISSN
2376-4481
Publisher site
See Article on Publisher Site

Abstract

Despite the relevance of Internet of Things-based health monitoring systems, artificial intelligence-driven diagnostic algorithms, and body area sensor networks in COVID-19 prevention, screening, and treatment, only limited research has been conducted on this topic. In this article, I cumulate previous research findings indicating that wearable Internet of Medical Things technologies can accurately assess COVID-19 symptoms. I contribute to the literature on smart sensor-based Internet of Medical Things and healthcare-integrated technologies by showing that machine learning algorithms and deep learning techniques can assist in COVID-19 prognosis. Throughout January 2022, I performed a quantitative literature review of the Web of Science, Scopus, and ProQuest databases, with search terms including “COVID-19” + “Internet of Things-based health monitoring systems,” “artificial intelligence-driven diagnostic algorithms,” and “body area sensor networks.” As I inspected research published between 2020 and 2022, only 152 articles satisfied the eligibility criteria. By eliminating controversial findings, outcomes unsubstantiated by replication, too imprecise material, or having similar titles, I decided upon 28, generally empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Dedoose, Distiller SR, and MMAT. Keywords: Internet of Medical Things; COVID-19; body area sensor network

Journal

American Journal of Medical Research – Addleton Academic Publishers

Published: Jan 1, 2022

There are no references for this article.