Çelebi, Beşir and Yalçın, Mustafa and Patoğlu, Volkan (2013) AssistOn-Knee: A self-aligning knee exoskeleton. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), Tokyo, Japan
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Official URL: http://dx.doi.org/10.1109/IROS.2013.6696472
Abstract
We present kinematics, actuation, detailed design, characterization results and initial user evaluations of AssistOn-Knee, a novel self-aligning active exoskeleton for robot-assisted knee rehabilitation. AssistOn-Knee can, not only assist flexion/extension movements of the knee joint but also accommodate its translational movements in the sagittal plane. Automatically aligning its joint axes, AssistOn-Knee enables an ideal match between human knee axis and the exoskeleton axis, guaranteeing ergonomy and comfort throughout the therapy. Self-aligning feature significantly shortens the setup time required to attach the patient to the exoskeleton, allowing more effective time spent on exercises. The proposed exoskeleton actively controls the rotational degree of freedom of the knee through a Bowden cable-driven series elastic actuator, while the translational movements of the knee joints are passively accommodated through use of a 3 degrees of freedom planar parallel mechanism. AssistOn-Knee possesses a lightweight and compact design with significantly low apparent inertia, thanks to its Bowden cable based transmission that allows remote location of the actuator and reduction unit. Furthermore, thanks to its series-elastic actuation, AssistOn-Knee enables high-fidelity force control and active backdrive-ability within its control bandwidth, while featuring passive elasticity for excitations above this bandwidth, ensuring safety and robustness throughout the whole frequency spectrum.
Item Type: | Papers in Conference Proceedings |
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Divisions: | Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics Faculty of Engineering and Natural Sciences |
Depositing User: | Volkan Patoğlu |
Date Deposited: | 07 Jan 2014 10:37 |
Last Modified: | 26 Apr 2022 09:14 |
URI: | https://research.sabanciuniv.edu/id/eprint/23784 |