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Robot-assisted distal training improves upper limb dexterity and function after stroke: a systematic review and meta-regression

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Stroke is one of the top 10 causes of death worldwide, and more than half of stroke patients face distal upper extremity dysfunction. Considering that robot-assisted training may be effective… Click to show full abstract

Stroke is one of the top 10 causes of death worldwide, and more than half of stroke patients face distal upper extremity dysfunction. Considering that robot-assisted training may be effective in improving distal upper extremity function, the review evaluated the effect of robot-assisted distal training on motor function, hand dexterity, and spasticity after stroke. Eleven databases were systematically searched for randomised controlled trials (RCTs) from inception until Aug 28, 2021. Meta-analysis and meta-regression were performed to investigate the overall effect and source of heterogeneity, respectively. Twenty-two trials involving 758 participants were included in this systematic review. The overall effect of robot-assisted distal training on the motor function of the wrists and hands was significant improvement (MD = 3.92; 95% CI, 3.04–4.80; P < 0.001). The robot-assisted training had a significantly beneficial effect on other motor functions (MD = 2.84; 95% CI, 1.54–4.14; P < 0.001); dexterity (MD = 9.01; 95% CI, -12.07–-5.95; P < 0.001), spasticity, upper extremity strength (SMD = 0.42; 95% CI, 0.07–0.78; P = 0.02) and activities of daily living (SMD = 0.70; 95% CI, 0.29–1.23; P < 0.001). A series of subgroup analyses showed preferable design and effective regime of training. Meta-regression indicated the statistically significant effect of the year of trial, country, and duration on the effectiveness of training. Robot-assisted distal training has a significant effect on motor function, dexterity and spasticity of the upper extremity, compared to conventional therapy.

Keywords: function; robot assisted; assisted distal; distal training; training

Journal Title: Neurological Sciences
Year Published: 2022

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