Control Strategies for Robot-Assisted Training - Literature Review and Experimental Impressions

Marchal Crespo, Laura (2013). Control Strategies for Robot-Assisted Training - Literature Review and Experimental Impressions. In: Pons, José L; Torricelli, Diego; Pajaro, Marta (eds.) Converging Clinical and Engineering Research on Neurorehabilitation. Biosystems & Biorobotics: Vol. 1 (pp. 115-120). Berlin, Heidelberg: Springer 10.1007/978-3-642-34546-3_19

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Much of the recent work on motor learning and rehabilitation robotics has focused on developing sophisticated, many degrees-of-freedom robotic mechanisms to support movement training of complex movements using fixed haptic guidance. Robotic haptic guidance is a motor-training strategy in which a machine physically interacts with the subject’s limbs during movement training. Although rehabilitation therapists commonly use haptic guidance in rehabilitation exercises, there is little evidence that robotic guidance is beneficial for human motor learning beyond enhancing safety. In fact, a long-standing hypothesis in motor learning asserts that providing too much assistance during training will impair learning. If this hypothesis stands, the field of rehabilitation robotics would end at a deadlock: a large number of developed rehabilitation robotic devices would be proved ineffective to improve rehabilitation outcomes and motor learning. Here we review the current state of the art robotic controllers that aim to improve motor learning and rehabilitation outcomes.

Item Type:	Book Section (Review Article)
Division/Institute:	10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Motor Learning and Neurorehabilitation 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Gerontechnology and Rehabilitation
UniBE Contributor:	Marchal Crespo, Laura
Subjects:	600 Technology > 610 Medicine & health 600 Technology > 620 Engineering
ISSN:	2195-3562
ISBN:	978-3-642-34545-6
Series:	Biosystems & Biorobotics
Publisher:	Springer
Language:	English
Submitter:	Angela Amira Botros
Date Deposited:	19 Jun 2018 15:54
Last Modified:	05 Dec 2022 15:14
Publisher DOI:	10.1007/978-3-642-34546-3_19
URI:	https://boris.unibe.ch/id/eprint/117124