4.3 Article

Is intensive gait training feasible and effective at old age? A retrospective case-control study on the use of Lokomat Free-D in patients with chronic stroke

Journal

JOURNAL OF CLINICAL NEUROSCIENCE
Volume 92, Issue -, Pages 159-164

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jocn.2021.08.013

Keywords

Robotic rehabilitation; Neurorehabilitation; Virtual reality; Elderly; Neurological disease

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This study aimed to evaluate the effects of robotic rehabilitation in elderly patients, finding that high-intensity robotic neurorehabilitation may improve gait, balance, and mood in the elderly.
Background: In the last decade, the number of people over 60 has increased, leading to various healthcare problems. The aim of this retrospective study is to evaluate the effects of robotic rehabilitation in elderly patients as well as their perception of usability and adaptation to intensive robotic neurorehabilitation. Methods: This is a retrospective case-control study. Eighty elderly stroke patients were included in the analysis using an electronic data retrieval system. The enrolled patients were divided into two groups: the experimental group (EG) underwent rehabilitation training with Lokomat FreeD, equipped with a VR screen, while the control group (CG) performed traditional rehabilitation training. The two groups matched for age, sex, education, brain injury, stroke interval. The rehabilitation protocol included a total of 40 training sessions. Results: Both types of rehabilitation led to an improvement in the perceived level of disability (FIM) and in the performance in gait and balance (TT), highlighting a significant improvement especially in the EG. However, only in the EG, Lokomat training had induced an increase in the distance covered in 10 min (10 m walk test), and a significant improvement in mood (HRS-D). Moreover, Lokomat-FreeD was well tolerated by patients with high levels of usability. Conclusions: Our results suggest that elderly patients may benefit from high-intensity robotic neurorehabilitation using the Lokomat-Pro FreeD. (c) 2021 Elsevier Ltd. All rights reserved.

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