Currently submitted to: JMIR Rehabilitation and Assistive Technologies
Date Submitted: Apr 6, 2026
Open Peer Review Period: Apr 17, 2026 - Jun 12, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Mapping the Global Landscape of Wearable Devices in Healthcare: A Dual-Database Bibliometric Analysis (2016–2025)
ABSTRACT
Background:
The rising burden of chronic diseases demands a shift toward proactive, personalized health management. Wearable devices are central to this transition, yet a comprehensive quantitative overview of the field's evolution remains lacking. This study systematically visualizes the knowledge structure and developmental trends in wearable healthcare technology over the past decade.
Objective:
This study aims to systematically visualize the knowledge structure, spatiotemporal distribution, and developmental trends of wearable device applications in healthcare over the past decade.
Methods:
A bibliometric analysis was conducted on 16,807 articles from Web of Science and Scopus (2016–2025) using CiteSpace and VOSviewer for network analysis, co-citation clustering, and keyword burst detection.
Results:
Analysis of 16,807 eligible articles identified China and the United States as leading contributors. Eight primary research clusters emerged: (1) COVID-19 pandemic, (2) the Medical Internet of Things (IoMT), (3) chronic disease, (4) cancer survivors, (5) human activity recognition, (6) breast milk, (7) PM2.5, and (8) chronic wounds. Burst detection further highlighted an escalating shift toward telemedicine integration, cost-efficiency, and quality-of-life-focused rehabilitation.
Conclusions:
This dual-database synthesis delineates the evolving landscape of wearable health technology, offering strategic insights to guide innovation and policy in personalized digital health. Clinical Trial: This study is a non-interventional study and does not require clinical trial registration.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.