Biologically Inspired Modelling for the Control of Upper Limb Movements: From Concept Studies to Future Applications
Identifieur interne : 001339 ( Ncbi/Curation ); précédent : 001338; suivant : 001340Biologically Inspired Modelling for the Control of Upper Limb Movements: From Concept Studies to Future Applications
Auteurs : Silvia Conforto [Italie] ; Ivan Bernabucci [Italie] ; Giacomo Severini [Italie] ; Maurizio Schmid [Italie] ; Tommaso D'Alessio [Italie]Source :
- Frontiers in Neurorobotics [ 1662-5218 ] ; 2009.
Abstract
Modelling is continuously being deployed to gain knowledge on the mechanisms of motor control. Computational models, simulating the behaviour of complex systems, have often been used in combination with soft computing strategies, thus shifting the rationale of modelling from the description of a behaviour to the understanding of the mechanisms behind it. In this context, computational models are preferred to deterministic schemes because they deal better with complex systems. The literature offers some striking examples of biologically inspired modelling, which perform better than traditional approaches when dealing with both learning and adaptivity mechanisms. Can these theoretical studies be transferred into an application framework? That is, can biologically inspired models be used to implement rehabilitative devices? Some evidences, even if preliminary, are presented here, and support an affirmative answer to the previous question, thus opening new perspectives.
Url:
DOI: 10.3389/neuro.12.003.2009
PubMed: 19949450
PubMed Central: 2782791
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PMC:2782791Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Modelling is continuously being deployed to gain knowledge on the mechanisms of motor control. Computational models, simulating the behaviour of complex systems, have often been used in combination with soft computing strategies, thus shifting the rationale of modelling from the description of a behaviour to the understanding of the mechanisms behind it. In this context, computational models are preferred to deterministic schemes because they deal better with complex systems. The literature offers some striking examples of biologically inspired modelling, which perform better than traditional approaches when dealing with both learning and adaptivity mechanisms. Can these theoretical studies be transferred into an application framework? That is, can biologically inspired models be used to implement rehabilitative devices? Some evidences, even if preliminary, are presented here, and support an affirmative answer to the previous question, thus opening new perspectives.</p>
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