Robot-assisted gait training (RAGT) is a promising technique aimed at improving motor function in PD. However, its effectiveness remains debated. This review aims to evaluate RAGT’s clinical effectiveness in PD.

A comprehensive search was conducted across PubMed, Embase, Web of Science, and Cochrane Library up to May 2024. Pooled outcomes were presented as mean difference (MD) with 95% confidence intervals (CI) using the random-effects model. The I² and X² statistics were employed to evaluate interstudy heterogeneity. All the calculations were performed using RevMan 5.4 and R Studio (v4.3.3). 

A total of 21 RCTs involving 793 patients from 65 to 78 years of age; having Hoehn and Yahr score ranging between 1 and 4, were included in this review. Lokomat and Gait-Trainer GT1 were the main robotic devices used in the multi-session rehabilitation programs. RAGT significantly improved UPDRS-III (MD -3.34, 95% CI -5.02 to -1.66,  P<0.0001, I²=69%), 10-MWT  (MD 0.07, CI 0.03 to 0.11, P=0.001, I²=16% ), 6-MWT  (MD 18.10, CI 2.89 to 33.32, P=0.02, I²=90%), BBS (MD 2.95, CI = 1.75 to 4.14, P<0.00001, I²=63%), walking speed  (MD 3.20, CI 1.81 to 4.59, P<0.00001, I²=0%), stride length (MD 5.26, CI 3.29 to7.23, p<0.00001, I²=0%) and ABC (MD7.18, CI 4.45 to 9.91, P<0.00001, I²=11%). No significant differences for TUG (MD -0.58, CI -1.17 to 0.02, P=0.06, I²=7%), step length (MD 4.54, CI -1.08 to 10.17, P=0.11, I²=60%), and cadence (MD 4.00, CI -3.19 to 11.19; P=0.28, I²=70%) were observed.

RAGT shows statistical efficacy, but lacks clinical efficacy. More high-quality studies are needed.