Robot-assisted vs. sensory integration training in treating gait and balance dysfunctions in patients with multiple sclerosis: a randomized controlled trial.

Frontiers in human neuroscience(2014)

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摘要
BACKGROUND:Extensive research on both healthy subjects and patients with central nervous damage has elucidated a crucial role of postural adjustment reactions and central sensory integration processes in generating and "shaping" locomotor function, respectively. Whether robotic-assisted gait devices might improve these functions in Multiple sclerosis (MS) patients is not fully investigated in literature. PURPOSE:The aim of this study was to compare the effectiveness of end-effector robot-assisted gait training (RAGT) and sensory integration balance training (SIBT) in improving walking and balance performance in patients with MS. METHODS:Twenty-two patients with MS (EDSS: 1.5-6.5) were randomly assigned to two groups. The RAGT group (n = 12) underwent end-effector system training. The SIBT group (n = 10) underwent specific balance exercises. Each patient received twelve 50-min treatment sessions (2 days/week). A blinded rater evaluated patients before and after treatment as well as 1 month post treatment. Primary outcomes were walking speed and Berg Balance Scale. Secondary outcomes were the Activities-specific Balance Confidence Scale, Sensory Organization Balance Test, Stabilometric Assessment, Fatigue Severity Scale, cadence, step length, single and double support time, Multiple Sclerosis Quality of Life-54. RESULTS:Between groups comparisons showed no significant differences on primary and secondary outcome measures over time. Within group comparisons showed significant improvements in both groups on the Berg Balance Scale (P = 0.001). Changes approaching significance were found on gait speed (P = 0.07) only in the RAGT group. Significant changes in balance task-related domains during standing and walking conditions were found in the SIBT group. CONCLUSION:Balance disorders in patients with MS may be ameliorated by RAGT and by SIBT.
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