ReviewJournal of neuroengineering and rehabilitation2026
Robotics and artificial intelligence applications in neurorehabilitation: a bibliometric analysis (2003-2025).
Review in Journal of neuroengineering and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- From Clinical Technique to Interprofessional Implementation and Intelligent Integration: A Bibliometric Analysis of the Interdisciplinary Expansion of Robot-Assisted Spine Surgery.The international journal of medical robotics + computer assisted surgery : MRCAS · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRobotic and artificial intelligence (AI)-assisted neurorehabilitation has emerged as a rapidly growing interdisciplinary field, integrating engineering innovations with clinical practice to enhance motor and cognitive recovery in neurological disorders. While research in this domain has expanded substantially over the last two decades, only a few bibliometric studies have examined related topics (e.g., new technologies in neurorehabilitation, rehabilitation robotics after stroke, AI in stroke care), and, to our knowledge, no study has provided a comprehensive bibliometric mapping specifically focused on robotics and artificial intelligence applications in neurorehabilitation. This study aimed to analyse the global trends, influential contributors, thematic evolution, and collaborative networks in robotic and AI-assisted neurorehabilitation.
methodsA bibliometric analysis was conducted using the Web of Science Core Collection. A comprehensive search covering 2003-2025 identified relevant articles using controlled terms for neurorehabilitation, robotics, and AI. Data were exported as plain text files (savedrecs.txt) from the Web of Science Core Collection and processed using the Bibliometrix R package via the Biblioshiny interface. Analyses included annual growth, citation performance, authorship patterns, journal impact, keyword co-occurrence, thematic mapping, and international collaboration networks.
resultsA total of 468 articles were retrieved from 191 sources, showing a rapid annual growth rate of 19.57%. The average citation per article was 24.22, with 17,792 references cited overall. Authorship analysis revealed contributions from 1,972 authors, with an average of 5.49 co-authors per paper and 32.05% international collaboration. The Journal of NeuroEngineering and Rehabilitation (h-index = 15, 1,740 citations) and Sensors (m-index = 1.714) were identified as the leading journals. The most prolific authors included Aiguo Song (8 publications) and Robert Riener (6 publications), while Marchal-Crespo L. and Reinkensmeyer D.J. were the most locally cited. Keyword analysis highlighted "stroke" (n = 93), "rehabilitation" (n = 82), "design" (n = 58), "recovery" (n = 53), and "exoskeleton" (n = 49) as dominant themes, with stroke rehabilitation and robotic exoskeletons representing core research foci. China (n = 697) and the USA (n = 251) emerged as the most productive countries, with strong collaborative ties.
conclusionRobotic and AI-assisted neurorehabilitation has demonstrated exponential growth, reflecting both technological innovation and clinical translation. Stroke rehabilitation and gait training remain central themes, while emerging areas such as AI-based assessment systems, wearable sensors, and tele-rehabilitation suggest future directions. To our knowledge, this study provides a comprehensive bibliometric overview specifically centred on robotics and artificial intelligence applications in neurorehabilitation, offering strategic insights for guiding future research and clinical integration.
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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.