ABSTRACT. The aim of this systematic review is to synthesize and analyze immersive virtual reality technologies, wearable health monitoring sensors, and machine learning-based automated diagnostic systems. With increasing evidence of healthcare diagnosis and treatment in the metaverse, there is an essential demand for comprehending whether Internet of Things-based smart healthcare systems integrate physiological and behavioral sensors as regards 3D virtual avatars in the management of chronic conditions. In this research, prior findings were cumulated indicating that body sensor networks, cloud-based personalized healthcare systems, and holographic simulation techniques further immersive 3D experiences in virtual diagnostic environments. I carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout June 2022, with search terms including “metaverse healthcare data” + “smart wearable sensing systems,” “immersive 3D experiences,” and “virtual diagnostic environments.” As I analyzed research published in 2022, only 138 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 33, 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.

Keywords: metaverse; healthcare; wearable; sensor; virtual; diagnostic

How to cite: Pera, A. (2022). “Metaverse Healthcare Data, Smart Wearable Sensing Systems, and Immersive 3D Experiences in Virtual Diagnostic Environments,” American Journal of Medical Research 9(2): 25–40. doi: 10.22381/ajmr9220222.

Received 22 July 2022 • Received in revised form 23 October 2022
Accepted 26 October 2022 • Available online 30 October 2022

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