Perspectives and Challenges in Robotic Neurorehabilitation

Author:  Iandolo, Riccardo; Marini, Francesca; Semprini, Marianna; Laffranchi, Matteo; Mugnosso, Maddalena; Cherif, Amel; De Michieli, Lorenzo; Chiappalone, Michela; Zenzeri, Jacopo. 2019.

Publication:  Applied Sciences 2019, Vol. 9, Page 3183

CITE.CC academic search helps you expand the influence of your papers.

Tags:     IT

Abstract

The development of robotic devices for rehabilitation is a fast-growing field. Nowadays, thanks to novel technologies that have improved robots&rsquo capabilities and offered more cost-effective solutions, robotic devices are increasingly being employed during clinical practice, with the goal of boosting patients&rsquo 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.

Cite this article

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. Applied Sciences. 2019; 9(15):3183.https://doi.org/10.3390/app9153183

View full text

>> Full Text:   Perspectives and Challenges in Robotic Neurorehabilitation

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

AUV Adaptive Sampling Methods: A Review