Recent trends in robot-assisted therapy environments to improve real-life functional performance after stroke
Identifieur interne : 000A43 ( Ncbi/Curation ); précédent : 000A42; suivant : 000A44Recent trends in robot-assisted therapy environments to improve real-life functional performance after stroke
Auteurs : Michelle J. Johnson [États-Unis]Source :
- Journal of NeuroEngineering and Rehabilitation [ 1743-0003 ] ; 2006.
Abstract
Upper and lower limb robotic tools for neuro-rehabilitation are effective in reducing motor impairment but they are limited in their ability to improve real world function. There is a need to improve functional outcomes after robot-assisted therapy. Improvements in the effectiveness of these environments may be achieved by incorporating into their design and control strategies important elements key to inducing motor learning and cerebral plasticity such as mass-practice, feedback, task-engagement, and complex problem solving.
This special issue presents nine articles. Novel strategies covered in this issue encourage more natural movements through the use of virtual reality and real objects and faster motor learning through the use of error feedback to guide acquisition of natural movements that are salient to real activities. In addition, several articles describe novel systems and techniques that use of custom and commercial games combined with new low-cost robot systems and a humanoid robot to embody the " supervisory presence" of the therapy as possible solutions to exercise compliance in under-supervised environments such as the home.
Url:
DOI: 10.1186/1743-0003-3-29
PubMed: 17176474
PubMed Central: 1764881
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PMC:1764881Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Upper and lower limb robotic tools for neuro-rehabilitation are effective in reducing motor impairment but they are limited in their ability to improve real world function. There is a need to improve functional outcomes after robot-assisted therapy. Improvements in the effectiveness of these environments may be achieved by incorporating into their design and control strategies important elements key to inducing motor learning and cerebral plasticity such as mass-practice, feedback, task-engagement, and complex problem solving.</p>
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