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2017 | OriginalPaper | Chapter

Adaptive Arm Weight Support Using a Cable-Driven Robotic System

Authors : Sven Knuth, Arne Passon, Frank Dähne, Andreas Niedeggen, Ingo Schmehl, Thomas Schauer

Published in: Converging Clinical and Engineering Research on Neurorehabilitation II

Publisher: Springer International Publishing

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Abstract

Many stroke and spinal cord injured (SCI) patients suffer from a paretic arm movement, which can be characterized by a limited shoulder flexion. We consider a possibility to assist the patient in slow arbitrary arm flexions within a large range of motion. To address this issue, we propose a shoulder flexion dependent weight support during robot-assisted therapy of the upper limb. Inverse static models of the cable-driven robotics and the passive human arm are used to estimate the required forces at the ropes to flex the upper arm in order to compensate a given percentage of the arm weight. Our results show that conventional constant rope forces during a therapy may produce an over- or undercompensated weight support, whereas the proposed adaptive approach achieves a desired larger range of motion.

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Literature
1.
go back to reference L. Marchal-Crespo, D.J. Reinkensmeyer, Review of control strategies for robotic movement training after neurologic injury. J. NeuroEng. Rehabil. 6(1), 20+ (2009) L. Marchal-Crespo, D.J. Reinkensmeyer, Review of control strategies for robotic movement training after neurologic injury. J. NeuroEng. Rehabil. 6(1), 20+ (2009)
2.
go back to reference G. Rosati, P. Gallina, S. Masiero, Design, implementation and clinical tests of a wire-based robot for neurorehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. Publ. IEEE Eng. Med. Biol. Soc. 15(4), 560–569 (2007)CrossRef G. Rosati, P. Gallina, S. Masiero, Design, implementation and clinical tests of a wire-based robot for neurorehabilitation. IEEE Trans. Neural Syst. Rehabil. Eng. Publ. IEEE Eng. Med. Biol. Soc. 15(4), 560–569 (2007)CrossRef
Metadata
Title
Adaptive Arm Weight Support Using a Cable-Driven Robotic System
Authors
Sven Knuth
Arne Passon
Frank Dähne
Andreas Niedeggen
Ingo Schmehl
Thomas Schauer
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-46669-9_215