Effect of robot-assisted training on cognitive function in post-stroke patients: a meta-analysis

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Authors: Juan Wang, Man Ding, Chao Weng, Hui Cai
Cited by: 0
References: 53

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: = 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. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier (CRD42024568846).

Fields of Study & Subjects

Stroke Rehabilitation and Recovery Dementia and Cognitive Impairment Research Cognitive Functions and Memory

Publication details

Journal / source
Frontiers in Neurology
Volume
17
Pages
1725457–1725457
Publication date
3 March 2026
Language
EN