ArticleInternational journal of environmental research and public health2022
A Bibliometric Analysis of Wearable Device Research Trends 2001-2022-A Study on the Reversal of Number of Publications and Research Trends in China and the USA.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- Continuous Temperature Monitoring via Wearable Devices for Fever or Infection Management in Acute Care Hospitals: Scoping Review of Clinical Implementation and Data Analytics.JMIR mHealth and uHealth · 2026Article
- A Decade of Research at the Intersection of Additive Manufacturing and Wearable Technology: A Bibliometric Analysis (2015-2025).Biosensors · 2026Review
- Article
- Cross-Analysis of mHealth Social Acceptance Among Youth: A Comparative Study Between Japan and China.Behavioral sciences (Basel, Switzerland) · 2025Article
- Are Wearables Effective in LMICs?Public health reviews · 2025Review
- SmartWear body sensors for neurological and neurosurgical patients: A review of current and future technologies.World neurosurgery: X · 2024Review
- Global trends and research hotspots on HACCP and modern quality management systems in the food industry.Heliyon · 2023Article
- Insights into Non-Exercise Physical Activity on Control of Body Mass: A Review with Practical Recommendations.Journal of functional morphology and kinesiology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, Wearable Devices have been used in a wide variety of applications and fields, but because they span so many different disciplines, it is difficult to ascertain the intellectual structure of this entire research domain. No review encompasses the whole research domain related to Wearable Devices. In this study, we collected articles on wearable devices from 2001 to 2022 and quantitatively organized them by bibliometric analysis to clarify the intellectual structure of this research domain as a whole. The cluster analysis, co-occurrence analysis, and network centrality analysis were conducted on articles collected from the Web of Science. As a result, we identified one cluster that represents applied research and two clusters that represent basic research in this research domain. Furthermore, focusing on the top two countries contributing to this research domain, China and the USA., it was confirmed that China is extremely inclined toward basic research and the USA. toward applied research, indicating that applied and basic research are in balance. The basic intellectual structure of this cross-sectional research domain was identified. The results summarize the current state of research related to Wearable Devices and provide insight into trends.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.