Systematic review and meta-analysis of effectiveness of robotic therapy in the recovery of motor functions after stroke
Amirbekova M. Kispayeva T. Adomaviciene A. Eszhanova L. Bolshakova I. Ospanova Z.
2025Frontiers Media SA
Frontiers in Human Neuroscience
2025#19
Background: Stroke is a leading cause of adult disability worldwide, often resulting in persistent motor impairments. While conventional rehabilitation approaches often yield modest results, robotic-assisted therapy has emerged as a promising solution to enhance motor recovery. However, the impact of stroke phase (acute, subacute, chronic) and other clinical modifiers on the effectiveness of robotic rehabilitation remains underexplored. Methods: The protocol for this systematic review and meta-analysis was registered in PROSPERO under the registration number CRD420251038754. A systematic review and meta-analysis were conducted in accordance with PRISMA guidelines. The literature search was conducted using MEDLINE, PubMed, Cochrane Library, Scopus, Web of Science, and EMBASE. Risk of bias was assessed using the RoB 2.0. Primary outcomes included motor recovery, gait speed, and balance. A random-effects model (DerSimonian-Laird) was applied to calculate pooled standardized mean differences (SMD), and subgroup analyses and meta-regression were used to assess the influence of stroke phase, age, therapy duration, and combined interventions (e.g., virtual reality, mirror therapy). Results: Thirteen randomized controlled trials (RCTs) published between 2015 and 2025 were included, with a total of 424 post-stroke patients. Robotic therapy showed a moderate but statistically significant effect over conventional rehabilitation (SMD = 0.59, 95% CI: [0.33; 0.84], p < 0.001), with low-to-moderate heterogeneity (I2 = 30.5%). Subgroup analysis revealed the strongest effects during the subacute phase (SMD = 0.74) and acute phase (SMD = 0.75), while the chronic phase yielded limited improvement (SMD = 0.23). Younger age and a intervention duration of more than 6 weeks were associated with enhanced outcomes. Meta-regression indicated a trend toward reduced effectiveness with prolonged intervention duration (β = −0.134), although not statistically significant (p = 0.102). No publication bias was detected (Egger’s p = 0.56). Conclusion: Robotic-assisted therapy provides clinically meaningful improvements in post-stroke motor recovery. The findings support early stratification and personalization of rehabilitation programs based on stroke timing, age, and intervention intensity. Integration of robotic systems with virtual and cognitive components may further enhance neuroplasticity, leading to improved functional outcomes. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251038754. Copyright
meta-analysis , motor functions , neurorehabilitation , robotic therapy , stroke recovery
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Institute of Life Sciences, Karaganda Medical University, Karaganda, Kazakhstan
School of Nursing Education, Karaganda Medical University, Karaganda, Kazakhstan
Rehabilitation Center “Neuron”, Karaganda, Kazakhstan
Department of Rehabilitation, Institute of Medical Sciences, Physical and Sports Medicine, Vilnius University, Vilnius, Lithuania
Department of Neurology, Medical University of Astana, Astana, Kazakhstan
Department of History of Kazakhstan and Socio-Political Disciplines, Karaganda Medical University, Karaganda, Kazakhstan
Institute of Life Sciences
School of Nursing Education
Rehabilitation Center “Neuron”
Department of Rehabilitation
Department of Neurology
Department of History of Kazakhstan and Socio-Political Disciplines
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