Abstract
Nowadays wearable rehabilitation exoskeletons are one of the most studied gait rehabilitation tool from a technological point of view. Current devices use prerecorded healthy gait patterns. This leads to potentially non-natural imposed gait patterns, and to solve this issue, we propose the use of regression-based methods to reconstruct speed dependent angular trajectories. Results suggest that the proposed method can lead to a more natural gait. Consequently, a naive user may more easily learn to walk under the presence of a robot guidance.
G. Asín-Prieto— This study has been funded by grant from the European Commission, within the Seventh Framework Programme (IFP7-ICT-2013-10-611695: BioMot - Smart Wearable Robots with Bioinspired Sensory-Motor Skills).
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Asín-Prieto, G. et al. (2015). Testing the Generation of Speed-Dependent Gait Trajectories to Control a 6DoF Overground Exoskeleton. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2015. Lecture Notes in Computer Science(), vol 9245. Springer, Cham. https://doi.org/10.1007/978-3-319-22876-1_42
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DOI: https://doi.org/10.1007/978-3-319-22876-1_42
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