ArticlePloS one2025
Computer-assisted rehabilitation system in the use of motor function recovery: A protocol for scoping review.
Article in PloS one, 2025. 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundsMotor dysfunction, a prevalent sequela of neurological disorders such as stroke, Parkinson's disease, and cerebral palsy, profoundly compromises patients' capacity to perform daily activities and participate in social interactions. To address this challenge, computer-assisted rehabilitation systems (CARS) have emerged as innovative tools for facilitating motor function recovery. However, the rapid proliferation of diverse CARS modalities-encompassing novel technical approaches, interdisciplinary integrations, and heterogeneous clinical applications-has resulted in a fragmented and poorly delineated research landscape. This scoping review protocol aims to systematically map the current evidence, clarify conceptual boundaries, identify key research themes, and highlight critical knowledge gaps within the CARS field.
methodsFollowing PRISMA-ScR guidelines, a comprehensive search across English (PubMed, Embase, Web of Science) and Chinese (CNKI, Wanfang, VIP, SinoMed) databases (inception to May 2025) will retrieve peer-reviewed studies using controlled vocabulary (MeSH: Rehabilitation/methods) and keywords ("computer-assisted rehabilitation system*"). After deduplication (EndNote X9) and manual verification, two reviewers will independently screen titles/abstracts and full texts, resolving discrepancies via third-party arbitration. Data extraction will categorize studies into study characteristics (design, population), technical specifications (sensors, AI), and clinical contexts (outcome measures, motor domains). Quantitative synthesis will map publication trends, geographic distributions, and methodological profiles using PRISMA diagrams and heatmaps. Thematic analysis will identify dominant research clusters (e.g., robotics, VR) and interdisciplinary linkages. Results will be disseminated via interactive evidence maps and narrative summaries emphasizing clinical translation. Any protocol deviations will be explicitly documented to ensure methodological transparency. DISCUSSION: This review will synthesize the heterogeneous CARS field into a structured framework, guiding future research prioritization and clinical implementation. By delineating technical innovations, clinical efficacy, and knowledge gaps, findings aim to optimize rehabilitation strategies for neurological populations. Detail of this review project can be found in Open Science Framework: https://doi.org/10.17605/OSF.IO/HXDT8.
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.