Stage 2: Who Are the Best Candidates for Robotic Gait Training Rehabilitation in Hemiparetic Stroke?

We aimed to compare the effects of robotic-assisted gait training (RAGT) in patients with FAC < 2 (low initial functional ambulation category [LFAC]) and FAC >= 2 (high initial functional ambulation category [HFAC]) on sensorimotor and spasticity, balance and trunk stability, the number of steps and walking distance in subacute hemiparetic stroke. Fifty-seven patients with subacute hemiparetic stroke (mean age, 63.86 +/- 12.72 years; 23 women) were assigned to two groups. All patients received a 30-min Walkbot-assisted gait training session, 3 times/week, for 6 weeks. Clinical outcomes included scores obtained on the Fugl-Meyer Assessment (FMA) scale, Modified Ashworth Scale (MAS), Berg Balance Scale (BBS), trunk impairment scale (TIS), and the number of walking steps and walking distance. Analysis of covariance and analysis of variance were conducted at p < 0.05. Significant main effects of time in both groups on number of walking steps and distance (p < 0.05) were observed, but not in MAS (p > 0.05). Significant changes in FMA, BBS, and TIS scores between groups (p < 0.05) were observed. Significant main effects of time on BBS and TIS were demonstrated (p < 0.05). Our study shows that RAGT can maximize improvement in the functional score of FMA, BBS, TIS, steps, and distance during neurorehabilitation of subacute stroke patients regardless of their FAC level.

Automated summary

The study demonstrates that robotic-assisted gait training can improve sensorimotor function, balance, trunk stability, and walking distance in subacute stroke patients. Regardless of initial functional ambulation category, RAGT maximizes improvements in FMA, BBS, TIS, and other functional scores during neurorehabilitation.