ReviewDigital health
Mapping the global landscape of wearable devices in healthcare: A dual-database bibliometric analysis (2016-2026).
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.