Research Hotspots and Trends of Virtual Reality Intervention for Stroke: Bibliometric Analysis
Bibliographic record
Abstract
Background: Virtual reality (VR) is a rapidly developing technology that has gained significant traction in the treatment and rehabilitation of individuals with stroke. Research on VR-based stroke treatment has garnered increasing attention. Objective: The aim of this study is to present a bibliometric analysis of VR for stroke studies to identify the application status, research hotspots, and emerging trends and guide future scientific research. Methods: We included studies and reviews on the topic of VR-based stroke treatment and rehabilitation from 1999 to 2023 were retrieved from Web of Science Core Collection database. Citespace 6.3.1 and VOSviewer 1.6.20 software was used for the visual analysis of publications, institutions, authors, journals, citations, and Scimago Graphica software was used for the geographic visualization of published countries or regions. Results: Our study analyzed 1171 papers on VR-based stroke rehabilitation published between 1999 and 2023, revealing a gradual increase in annual publications over the past 2 decades, peaking at 154 in 2022. North America and Western Europe were identified as major contributors, with significant input from their institutions, researchers, and publications. The Journal of NeuroEngineering and Rehabilitation emerged as the leading journal in this field, while Calabrò Rocco Salvatore was recognized as the most prolific author, focusing on the neurophysiological impacts of VR on patients with stroke. Keywords with notable citation bursts, such as "environment," "trial," "arm," and "motor learning," highlighted the core research themes in this domain. Conclusions: Our study provides valuable insights into the current research hotspots and emerging trends in VR-based stroke treatment and rehabilitation. Current research primarily focuses on evaluating the effectiveness of VR in improving upper limb function and balance in patients with stroke. Future directions are shifting towards integrating VR with rehabilitation techniques, such as physiotherapy and occupational therapy, while advancements in VR technology continue to garner increasing attention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.072 | 0.068 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".