Purpose: Stroke is one of the leading causes of acquired disability in adults in high-income countries. This study aims to determine the intervention effects of robot-assisted task-oriented training on enhancing the upper limb function and daily living skills of stroke patients.
Methods: A systematic search was conducted across PubMed, China National Knowledge Infrastructure, Web of Science, Cochrane Library, Embase, and Scopus databases through March 1, 2024. This process yielded 1,649 articles, from which 15 studies with 574 samples met the inclusion criteria for analysis. The quality of the included studies was evaluated using the Cochrane Risk of Bias tool. We performed meta-analyses, subgroup analyses, regression analyses, and sensitivity analyses using Review Manager 5.4 and Stata 17.0. Furthermore, publication bias was assessed using Begg's and Egger's tests. This study is registered with PROSPERO (No. CRD42024513483).
Results: A random effects model was utilized. The results indicated that robot-assisted task-oriented training significantly improved Fugl-Meyer Assessment-Upper Extremity scores compared to the control group [SMD = 1.01, 95% CI (0.57, 1.45)]. Similarly, robot-assisted task-oriented training demonstrated a significant effect on the Modified Barthel Index scores [SMD = 0.61, 95% CI (0.41, 0.82)]. Subgroup and regression analyses revealed that the use of combined interventions, the geographical region of the first author, and the age of the subjects did not appear to be sources of high heterogeneity. Publication bias tests using the FMA-UE as an outcome measure yielded Begg's test (p = 0.76) and Egger's test (p = 0.93), suggesting no significant publication bias. Sensitivity analyses confirmed the robustness of the study findings.
Conclusions: Robot-assisted task-oriented training significantly enhances the rehabilitation of upper limb function and the recovery of daily living skills in stroke patients.
Copyright: © 2025 Jin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.