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Erschienen in: Medical & Biological Engineering & Computing 10/2017

20.03.2017 | Original Article

Resistance training using a novel robotic walker for over-ground gait rehabilitation: a preliminary study on healthy subjects

verfasst von: Kyung-Ryoul Mun, Brandon Bao Sheng Yeo, Zhao Guo, Soon Cheol Chung, Haoyong Yu

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 10/2017

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Abstract

Strength training is an aspect of gait rehabilitation, which complements balance control and weight-bearing training. However, conventional strength training does not show positive gait outcomes, due to lack of task specificity. Therefore, the aims of this study were to investigate the effects of a resistance force applied at the center of mass (CoM) and to investigate whether this exercise can be used for effective task-specific gait training. Using a novel robotic walker, a consistent resistive force was applied to the CoM of subjects in the posterior direction. Eleven healthy subjects were instructed to walk under five walking conditions with increasing forces, based on each subject’s body weight (BW), at 0, 2.5, 5, 7.5, and 10% BW. Joint kinematics and mean amplitude and frequency of electromyography signals from nine major muscles were measured. The application of resistance resulted in significantly increased flexion angles at ankle, knee, and hip joints. A large amount of motor unit activation with lower firing rates was found at knee and hip joints, indicating that this type of resistance training can improve muscular strength and endurance in a task-specific manner. The long-term effects of the resistance training on neurologically challenged patients will be investigated in the future.

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Metadaten
Titel
Resistance training using a novel robotic walker for over-ground gait rehabilitation: a preliminary study on healthy subjects
verfasst von
Kyung-Ryoul Mun
Brandon Bao Sheng Yeo
Zhao Guo
Soon Cheol Chung
Haoyong Yu
Publikationsdatum
20.03.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 10/2017
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-017-1634-x

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