Effects of gait training with a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), on quality of life in patients with neuromuscular disease, able to walk independently with aids

Autor: Eiichi Tsuda, Yuki Saito, Kazutomo Miura, Kazushi Maeda, Ikue Ito, Masakazu Kogawa, Yasuyuki Ishibashi, Kosuke Kuzuhara, Natsuka Masuno, Hiroaki Ishiyama, Kazutaka Urita, Rui Henmi, Hiroko Yokoyama
Rok vydání: 2021
Předmět:
Zdroj: Journal of Clinical Neuroscience. 89:211-215
ISSN: 0967-5868
Popis: Robot-assisted gait training using a voluntary-driven wearable cyborg, Hybrid Assistive Limb (HAL), has been shown to improve the mobility of patients with neurological disorders; however, its effect on the quality of life (QOL) of patients is not clear. The aim of this study was to assess the effects of HAL-assisted gait training on QOL and mobility in patients with neuromuscular diseases (NMDs). Ten patients with NMDs (seven men and three women, mean age: 57 ± 11 years), with impairment in mobility but could walk alone with aids underwent two courses of gait training with HAL over 6 months, and the single course consisted of nine sessions of training for 4 weeks. We compared the findings of the 2 min walk test, 10 m walk test, the Short Form-36 (SF-36) questionnaire, and the Hospital Anxiety and Depression Scale at baseline, after the 1st training, before the 2nd training, and after the 2nd training using the Friedman test. A significant improvement was observed in the 2 min walking distance from baseline (93 ± 50 m) to after the 2nd training (115 ± 48 m, P = 0.034), as well as in the domains of vitality (P = 0.019) and mental component summary score (P = 0.019) of SF-36. The improvement in 10 m walking speed was significantly correlated with that in the physical functioning (R = 0.831, P = 0.003) and role physical (R = 0.697, P = 0.025) domains in the SF-36. Our findings suggest that HAL-assisted gait training is effective in improving QOL associated with mental health as well as gait ability in selected patients with NMDs.
Databáze: OpenAIRE