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Review Article Open Access
Volume 6 | Issue 1 | DOI: https://doi.org/10.33696/Neurol.6.105

Upper-limb Robots after Stroke: How to Get beyond the Hype?

  • 1Servizio di Analisi del movimento e della Funzione Locomotoria - SAFLo, IRCCS Santa Maria Nascente, Fondazione Don Gnocchi, Milano, Italy
  • 2Department of Rehabilitation Medicine, Amsterdam UMC, VU Amsterdam, Amsterdam Movement Sciences, Amsterdam Neuroscience Research Institute, Research Program NeuroVascular Disorders, Amsterdam, The Netherlands
  • 3Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, North-Western University, Chicago, IL, USA
+ Affiliations - Affiliations

Corresponding Author

Gert Kwakkel, g.kwakkel@amsterdamumc.nl

Received Date: September 12, 2024

Accepted Date: November 23, 2024

Abstract

Introduction: Upper limb (UL) rehabilitation is driven by intensive, task-specific training. In this article we further elaborate on the results of a systematic review and meta-analysis on the effectiveness of UL-robots (UL-RTs) to recovery of UL-motor impairment, UL-capacity, and basic-ADLs post-stroke when compared to any non-UL-RT. Our second aim was to identify patient, trial, robot and other intervention variables that are associated with found effect sizes (ESs).

Material and Methods: Relevant randomized controlled trials (RCTs) were identified in electronic searches until August 1, 2022. Meta-analyses were performed for measures of UL muscle synergism, muscle power, muscle tone, UL-capacity, performance, and basic ADLs. Methodological quality was assessed with a risk of bias tool. Sensitivity and meta-regression analyses were applied to identify factors potentially associated with found trial-ESs.

Results: Ninety RCTs (N=4.311) were included. Meta-analyses of 86 trials (N=4.240) showed small, significant improvements in UL-muscle synergism (Fugl-Meyer Assessment of the UL [FM-UL]) (mean difference [MD] 2.23[1.11–3.35]), muscle power (standardized mean difference [SMD] 0.39[0.16–0.61]), motor performance (SMD 0.11[0.00–0.21]), and basic ADLs (SMD 0.28[0.10–0.45]). No overall effects were found for muscle tone (SMD −0.10[−0.26 to 0.07]) or UL-capacity (SMD 0.04[−0.10 to 0.18]), except with exoskeletons (SMD 0.27[0.10–0.43]). Meta-regressions showed a significant positive association between baseline mean FM-UL and ESs for UL-capacity (r=0.339; p=0.03). No other significant subgroup differences or associations were found in our sensitivity analyses and meta-regression.

Conclusions: The present research synthesis shows a small (~3%), but significant homogeneous effects in favor of UL-RTs of motor impairment. However, this favorable effect did not generalize to clinically meaningful improvements at level of UL-capacity. The robustness and consistency of our findings suggest that a better mechanistic understanding is required about the assumed interaction effects between motor control and motor learning during recovery of UL-capacity when designing UL-RTs for subjects with a stroke. To achieve this, longitudinal studies are needed that investigate recovery of quality of movement in terms of behavioral restitution and compensation post stroke.

Keywords

Stroke, Robotics, Upper limb, Review, Meta-analysis, Motor recovery, Motor learning, Motor control, Neurorehabilitation

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