SYSTEMATIC REVIEW article

Front. Neurol.

Sec. Neurorehabilitation

Effect of Robot-assisted Training on Cognitive Function in Post-stroke Patients: A Meta-analysis

  • Neurology, Renmin Hospital of Wuhan University, Wuhan, China

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Abstract

Background: About 1/3 of stroke patients worldwide experience post-stroke cognitive impairment (PSCI). The management of cognitive function (CF) after stroke is an important issue that needs to be addressed. In recent years, robot-assisted training (RAT) has been widely used in the rehabilitation of CF, its intervention effect is still controversial. Therefore, this study was aimed at reporting the latest meta-analysis (MA) and evidence updates to compare the effects of RAT with traditional training (TT) on CF in post-stroke (PS) patients. Methods: Databases (PubMed, Embase, Cochrane Library and Web of Science) were retrieved to include randomized controlled trial articles that met the criteria. The intervention group used RAT, and the control group used TT. Outcome measures mainly included the Montreal Cognitive Assessment score (MoCA), and so on. Study screening, quality assessment, and data extraction were done separately by two investigators. The stability of results and potential sources of heterogeneity were explored by sensitivity and subgroup analyses. Data were pooled by RevMan 5.4 and STATA 15.0. Results: A total of 13 studies with 488 patients were included. The MA results showed that in PS patients, RAT significantly improved the MoCA score (SMD=0.43, 95% CI (0.04-0.81), P=0.03). The sensitivity analysis showed significant instability in the changes in MoCA score and change in Frontal Assessment Battery (FAB) score. Therefore, the effect of RAT on CF in PS patients should be interpreted with caution. Conclusion: RAT improved CF in PS patients to some extent. However, evidence for this conclusion was of low quality. Therefore, further studies are still required for confirmation.

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Keywords

Cognitive Function, Meta-analysis, rct, Robot-assisted training, Stroke

Received

12 November 2025

Accepted

10 February 2026

Copyright

© 2026 Wang, Ding, Weng and Cai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Juan Wang

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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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