@inbook{007e79f6d3484c1ba71446ea169da0b4,
title = "Tacit adaptability of a mechanically adjustable compliance and controllable equilibrium position actuator, a preliminary study",
abstract = "Current powered exoskeleton (exo) control algorithms for locomotion assistance and rehabilitation are based on assistive, resistive and error augmentation paradigms. Within the assistive controller{\textquoteright}s family, assist-as-needed consists in applying a corrective force proportional to the error (actual limb position versus reference pattern). Our final goal is to implement a fully adaptable control mechanism to allow a full lower limb exo to dynamically adapt the gait pattern to each patient. We propose to use a modified version of tacit learning algorithm in combination with a variable stiffness actuator to explore the improvement of the adaptability in comparison to stiff actuators. The preliminary results show that using this concept on a compliant actuator it is possible to modulate a fixed trajectory to adapt to the position limits that are induced by user{\textquoteright}s movement capabilities.",
author = "Guillermo As{\'i}n-Prieto and Shingo Shimoda and Jos{\'e} Gonz{\'a}lez and S{\'a}nchez-Villama{\~n}{\'a}n, {M. Carmen} and Pons, {Jose L} and Moreno, {Juan C.}",
note = "Funding Information: Acknowledgments 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).",
year = "2017",
doi = "10.1007/978-3-319-46532-6_44",
language = "English (US)",
series = "Biosystems and Biorobotics",
publisher = "Springer International Publishing",
pages = "267--271",
booktitle = "Biosystems and Biorobotics",
}