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Mapping the global landscape of wearable devices in healthcare: A dual-database bibliometric analysis (2016–2026)

Feb 2026 · Digital Health · Vol 12 · 1 citation · 104 references
Medicine

TL;DR

This study systematically visualizes the knowledge structure, spatiotemporal distribution, and developmental trends of wearable healthcare technology over the past decade and provides evidence for researchers and policymakers to optimize resource allocation in digital health innovation.

Abstract

Background The escalating demand for proactive, personalized healthcare, heavily driven by the rising global burden of chronic diseases, necessitates a shift in modern medical management. While wearable devices are central to this transition, a comprehensive, multi-source quantitative mapping of the field’s evolutionary trajectory and application domains remains lacking. Objective This study systematically visualizes the knowledge structure, spatiotemporal distribution, and developmental trends of wearable healthcare technology over the past decade. Methods A bibliometric analysis was conducted using integrated data from Web of Science and Scopus (2016–2026). Utilizing CiteSpace and VOSviewer, we performed cooperation network analysis, co-citation clustering, and keyword burst detection to identify global collaboration patterns and research emerging trends. Results Analysis of 12,812 eligible articles identified China and the United States as leading contributors. Ten distinct research clusters emerged: (1) PM2.5; (2) breast milk; (3) chronic wounds; (4) COVID-19 pandemic; (5) Internet of medical things; (6) human activity recognition; (7) cancer survivors; (8) chronic disease; (9) water-soluble composite; (10) personalized health monitoring. Burst detection further highlighted an escalating shift toward telemedicine integration, cost-efficiency, and quality-of-life-focused rehabilitation. Conclusion This study presents a comprehensive bibliometric assessment of wearable health technology. By delineating established domains and emerging trajectories in telemedicine and personalized prevention, it provides evidence for researchers and policymakers to optimize resource allocation in digital health innovation.

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