Abstract
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.
Highlights
Exoskeletal robotic-assisted gait training (RAGT) has rapidly gained popularity as a powerful and promising therapeutic modality to improve gait function in hemiparetic stroke; the best time to intervene and initial locomotor motor function level of patients for RAGT is unknown [1]
We believe that the Walkbot interactive guidance mode can assist in mobilizing the ankle-knee-hip joint to facilitate the reciprocal interlimb-coordinated locomotor pattern for stroke patients with functional ambulatory category (FAC) < 2, while progressive resistance force mode strengthens weak ankle-knee-hip muscles for stroke patients with FAC ≥ 2. As these claims remain to be validated, the purpose of the present study was to determine the effects of Walkbot RAGT on sensorimotor recovery using the following outcomes: Fugl–Meyer Assessment (FMA) scale scores, spasticity based on the Modified Ashworth Scale (MAS), balance based on the Berg Balance Scale (BBS), and trunk stability based on the Trunk Impairment Scale (TIS), as well as the number of steps and walking distance in subacute stroke patients with FAC < 2 and FAC ≥ 2
There were no significant differences in baseline age, height, weight, type of stroke, and side of hemiplegia distribution variables between the LFAC and HFAC groups (Table 1)
Summary
Exoskeletal robotic-assisted gait training (RAGT) has rapidly gained popularity as a powerful and promising therapeutic modality to improve gait function in hemiparetic stroke; the best time to intervene and initial locomotor motor function level of patients for RAGT is unknown [1]. A report from the National Rehabilitation Center recently emphasized the need to assess the characteristics leading to the best effectiveness and optimal timing, intensity, and duration of post-stroke RAGT rehabilitation interventions [2]. Determining the patient’s initial ambulation level at which robot gait training is most effective remains problematic [3]. There is a need to determine the best functional ambulatory category (FAC) for more effective and sustainable RAGT intervention outcomes in stroke patients. Exoskeletal RAGT types, including the Lokomat (Hocoma, Zurich, Switzerland) and Walkbot (P&S Mechanics, Seoul, Korea), were suggested to be more effective in stroke patients with FAC < 2 (weight supporting group), whereas overground walking training was recommended for patients with FAC ≥ 2 (non-weight supporting group) [4]
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