Internet of Medical Things-driven Remote Monitoring Systems, Big Healthcare Data Analytics, and Wireless Body Area Networks in COVID-19 Detection and Diagnosis
Internet of Medical Things-driven Remote Monitoring Systems, Big Healthcare Data Analytics, and Wireless Body Area Networks in COVID-19 Detection and Diagnosis

Summary/Abstract: The aim of this systematic review is to synthesize and analyze Internet of Medical Things-driven remote monitoring systems, big healthcare data analytics, and wireless body area networks in COVID-19 detection and diagnosis. With increasing evidence of COVID-19 diagnostic applications, there is an essential demand for comprehending whether remote rapid monitoring and diagnosis of suspected COVID-19 individuals can be enabled by interconnected Internet of Medical Things infrastructure and healthcare equipment. In this research, prior findings were cumulated indicating that Internet of Medical Things can be leveraged in contact tracing during the COVID-19 pandemic. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout January 2022, with search terms including “COVID-19” + “Internet of Medical Things-driven remote monitoring systems,” “big healthcare data analytics,” and “wireless body area networks.” As I analyzed research published between 2020 and 2022, only 148 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, I decided on 29, chiefly empirical, sources. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, Distiller SR, ROBIS, and SRDR.

• Details
• Contents