SynthesisFrontiers in neurology
Gait analysis in cerebral palsy (2005-2025): a bibliometric mapping of research trends, collaboration networks, and emerging technologies.
Synthesis in Frontiers in neurology. 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
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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
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Gait dysfunction is a hallmark of cerebral palsy (CP) limiting mobility and quality of life. Despite growing research, a systematic synthesis of the scientific landscape of CP gait analysis is lacking. Methods: We systematically searched the Web of Science Core Collection (2005-2025) following PRISMA guidelines. VOSviewer and CiteSpace were used for co-authorship, co-occurrence, clustering, burst detection, and dual-map overlay analyses. To verify the robustness of our findings, a secondary validation analysis was performed using Scopus (Elsevier) with an equivalent search strategy. Results: 1,404 publications were identified; annual output grew from 26 to 112. The USA was most productive (376 papers, h-index 45). Gait & Posture published the most articles (207). Keyword clustering identified 10 clusters, with "crouch gait," "reliability," and "gross motor function" as persistent themes. Recent bursts include "wearable sensors," "musculoskeletal modeling," and "artificial intelligence." Notably, intervention studies linking gait analysis to patient-centered outcomes remain underrepresented. Conclusion: This bibliometric analysis reveals a maturing field with growing research interest in technology-assisted rehabilitation, as suggested by recent keyword bursts. Emerging technologies (wearables, AI, musculoskeletal modeling) warrant prioritization in future clinical research, although their current adoption remains limited. The persistent evidence gap between gait measurement and clinical decision-making calls for multi-center validation and real-world implementation studies. Systematic review registration: Open Science Framework (OSF) (DOI: 10.17605/OSF.IO/CT27P).
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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.