Guidali, Marco; Duschau-Wicke, Alexander; Broggi, Simon; Klamroth-Marganska, Verena; Nef, Tobias; Riener, Robert (2011). A robotic system to train activities of daily living in a virtual environment. Medical & biological engineering & computing, 49(10), pp. 1213-1223. Heidelberg: Springer 10.1007/s11517-011-0809-0
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In the past decade, several arm rehabilitation robots have been developed to assist neurological patients during therapy. Early devices were limited in their number of degrees of freedom and range of motion, whereas newer robots such as the ARMin robot can support the entire arm. Often, these devices are combined with virtual environments to integrate motivating game-like scenarios. Several studies have shown a positive effect of game-playing on therapy outcome by increasing motivation. In addition, we assume that practicing highly functional movements can further enhance therapy outcome by facilitating the transfer of motor abilities acquired in therapy to daily life. Therefore, we present a rehabilitation system that enables the training of activities of daily living (ADL) with the support of an assistive robot. Important ADL tasks have been identified and implemented in a virtual environment. A patient-cooperative control strategy with adaptable freedom in timing and space was developed to assist the patient during the task. The technical feasibility and usability of the system was evaluated with seven healthy subjects and three chronic stroke patients.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurology |
UniBE Contributor: |
Nef, Tobias |
ISSN: |
0140-0118 |
Publisher: |
Springer |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 14:14 |
Last Modified: |
05 Dec 2022 14:02 |
Publisher DOI: |
10.1007/s11517-011-0809-0 |
PubMed ID: |
21796422 |
Web of Science ID: |
000296694200012 |
BORIS DOI: |
10.48350/3376 |
URI: |
https://boris.unibe.ch/id/eprint/3376 (FactScience: 207048) |