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Perspectives and Challenges in Robotic Neurorehabilitation

1
Rehab Technologies, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
2
Robotics, Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Via Melen 83, 16152 Genova, Italy
3
Department of Informatics, Bioengineering, Robotics and System Engineering, University of Genova, Viale Causa 13, 16145 Genova, Italy
*
Author to whom correspondence should be addressed.
Equal second author.
Equal last author.
Appl. Sci. 2019, 9(15), 3183; https://doi.org/10.3390/app9153183
Received: 31 May 2019 / Revised: 25 July 2019 / Accepted: 31 July 2019 / Published: 5 August 2019
The development of robotic devices for rehabilitation is a fast-growing field. Nowadays, thanks to novel technologies that have improved robots’ capabilities and offered more cost-effective solutions, robotic devices are increasingly being employed during clinical practice, with the goal of boosting patients’ recovery. Robotic rehabilitation is also widely used in the context of neurological disorders, where it is often provided in a variety of different fashions, depending on the specific function to be restored. Indeed, the effect of robot-aided neurorehabilitation can be maximized when used in combination with a proper training regimen (based on motor control paradigms) or with non-invasive brain machine interfaces. Therapy-induced changes in neural activity and behavioral performance, which may suggest underlying changes in neural plasticity, can be quantified by multimodal assessments of both sensorimotor performance and brain/muscular activity pre/post or during intervention. Here, we provide an overview of the most common robotic devices for upper and lower limb rehabilitation and we describe the aforementioned neurorehabilitation scenarios. We also review assessment techniques for the evaluation of robotic therapy. Additional exploitation of these research areas will highlight the crucial contribution of rehabilitation robotics for promoting recovery and answering questions about reorganization of brain functions in response to disease. View Full-Text
Keywords: electrophysiological recordings; end-effector robot; exoskeleton; neuroimaging; robotic rehabilitation; sensorimotor assessment electrophysiological recordings; end-effector robot; exoskeleton; neuroimaging; robotic rehabilitation; sensorimotor assessment
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Iandolo, R.; Marini, F.; Semprini, M.; Laffranchi, M.; Mugnosso, M.; Cherif, A.; De Michieli, L.; Chiappalone, M.; Zenzeri, J. Perspectives and Challenges in Robotic Neurorehabilitation. Appl. Sci. 2019, 9, 3183.

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