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Appl. Sci. 2019, 9(4), 626;

Modular Design and Decentralized Control of the Recupera Exoskeleton for Stroke Rehabilitation

Robotics Innovation Center, German Research Center for Artificial Intelligence (DFKI GmbH), 28359 Bremen, Germany
AG Robotik, Department of Mathematics and Computer Science, University of Bremen, 28359 Bremen, Germany
Authors to whom correspondence should be addressed.
The two authors contribute equally to the work.
Received: 21 December 2018 / Revised: 1 February 2019 / Accepted: 8 February 2019 / Published: 13 February 2019
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Robot-assisted therapy has become increasingly popular and useful in post-stroke neurorehabilitation. This paper presents an overview of the design and control of the dual-arm Recupera exoskeleton to provide intense therapist-guided as well as self training for sensorimotor rehabilitation of the upper body. The exoskeleton features a lightweight design, high level of modularity, decentralized computing, and various levels of safety implementation. Due to its modularity, the system can be used as a wheel-chair mounted system or as a full-body system. Both systems enable a wide range of therapies while efficiently grounding the weight of the system and without compromising the patient’s mobility. Furthermore, two rehabilitation therapies implemented on the exoskeleton system, namely teach & replay therapy and mirror therapy, are presented along with experimental results. View Full-Text
Keywords: prosthetics and exoskeletons; rehabilitation robotics; mechanical design prosthetics and exoskeletons; rehabilitation robotics; mechanical design

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Kumar, S.; Wöhrle, H.; Trampler, M.; Simnofske, M.; Peters, H.; Mallwitz, M.; Kirchner, E.A.; Kirchner, F. Modular Design and Decentralized Control of the Recupera Exoskeleton for Stroke Rehabilitation. Appl. Sci. 2019, 9, 626.

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