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ORIGINAL ARTICLE Free access
European Journal of Physical and Rehabilitation Medicine 2019 August;55(4):456-62
DOI: 10.23736/S1973-9087.18.05368-6
Copyright © 2018 EDIZIONI MINERVA MEDICA
language: English
Self-selected speed gait training in Parkinson’s disease: robot-assisted gait training with virtual reality versus gait training on the ground
Cira FUNDARÒ 1 ✉, Roberto MAESTRI 2, Giorgio FERRIERO 3, Pierluigi CHIMENTO 1, Giovanni TAVEGGIA 4, 5, 6, Roberto CASALE 4, 5, 6
1 Unit of Neuropathophysiology, Maugeri Scientific Institutes for Research and Care, Pavia, Italy; 2 Department of Biomedical Engineering, Maugeri Scientific Institutes for Research and Care, Pavia, Italy; 3 Unit of Neurorehabilitation, Maugeri Scientific Institutes for Research and Care, Pavia, Italy; 4 Unit of Neurorehabilitation, Habilita Care and Research Rehabilitation Hospitals, Zingonia di Ciserano, Bergamo, Italy; 5 Department of Advanced Technology Rehabilitation, Habilita Care and Research Rehabilitation Hospitals, Zingonia di Ciserano, Bergamo, Italy; 6 Unit of Pain Rehabilitation, Habilita Care and Research Rehabilitation Hospitals, Zingonia di Ciserano, Bergamo, Italy
BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative disorder causing progressive gait disability. Although robot-assisted gait training (RAGT) using the Lokomat device has been demonstrated to improve gait in PD, it is not clear what the best training settings are, in particular if a self-selected treadmill speed can give better results.
AIM: The aims of this study were: 1) to evaluate if self-selected speed training using Lokomat plus virtual reality (VR) can give better results compared to self-selected speed overground training; 2) to assess the possible influence of VR on patients’ gait speed in the Lokomat group.
DESIGN: Retrospective analysis.
POPULATION: Patients with idiopathic PD (N.=20), aged 18-90 years, Hoehn & Yahr 2-3, Mini Mental State Examination (MMSE) ≥24, unchanged therapy, and without freezing episodes, dyskinesia, and neurological, orthopedic, cardiac, respiratory or severe visual impairments, who underwent four weeks of gait training (five 30-minute sessions/week): ten with Lokomat (Group 1) and ten without (Group 2).
SETTING: Rehabilitation hospital; inpatients.
METHODS: Group 1: Lokomat parameters: body weight support fixed at 30%, guidance force set at 80% bilaterally. Treadmill speed was self-selected by each patient, and subsequently modified on patient request. VR scenery was applied. Group 2: self-selected speed gait training on the ground. Both groups were assessed pre- and post-training with the Unified Parkinson’s Disease Rating Scale (UPDRS), Functional Independence Measure (FIM) scale, and the 10-metre walking test (10-MWT). For group 1, a VR score was evaluated.
RESULTS: All patients showed significant post-training improvement in UPDRS and FIM scores, with a significantly better improvement in Group 1 for total UPDRS (P=0.037). Velocity at 10-MWT significantly improved after rehabilitation in Group 2 (P=0.002). Lokomat treadmill speed and VR score both improved significantly after rehabilitation, but without any association (P=0.48), while a significant inverse relationship (P=0.014) was observed between the changes in 10-MWT and in treadmill speed.
CONCLUSIONS: Self-selected speed Lokomat training in PD patients can provide clinical enhancements but is not superior to self-selected speed overground gait training; the influence of VR on motor performance seems to be related to non-motor aspects.
CLINICAL REHABILITATION IMPACT: Regarding self-selected speed gait training, there seems to be no difference between RAGT and conventional overground gait training. Other parameter settings for RAGT need to be carefully investigated for a tailored use of RAGT in PD.
KEY WORDS: Parkinson disease; Walking speed; Neurologic gait disorders; Virtual reality