A neuromuscular elbow model for analysis of force and movement variability in slow movements.
Identifieur interne : 001D90 ( Ncbi/Merge ); précédent : 001D89; suivant : 001D91A neuromuscular elbow model for analysis of force and movement variability in slow movements.
Auteurs : Ozkan Celik [États-Unis] ; Marcia K. OrmalleySource :
- Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference [ 1557-170X ] ; 2011.
English descriptors
- KwdEn :
- MESH :
Abstract
In this paper, we present a neuromuscular elbow model with both motor unit pool recruitment and Hill-based contraction dynamics. The model builds upon various models reported in the literature and provides a way to quantify force and movement variability in both isometric and non-isometric contractions. The model's accuracy in estimating muscle force variability at low force levels (at less than 20% maximum voluntary contraction) is evaluated in isometric contraction case and compared with experimental results from the literature. This comparison suggests that the model is accurate in estimating force variability within the low force range and can be used to explore effects of muscle force variability in increased kinematic variability during slow movements.
DOI: 10.1109/IEMBS.2011.6092038
PubMed: 22256262
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pubmed:22256262Le document en format XML
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<front><div type="abstract" xml:lang="en">In this paper, we present a neuromuscular elbow model with both motor unit pool recruitment and Hill-based contraction dynamics. The model builds upon various models reported in the literature and provides a way to quantify force and movement variability in both isometric and non-isometric contractions. The model's accuracy in estimating muscle force variability at low force levels (at less than 20% maximum voluntary contraction) is evaluated in isometric contraction case and compared with experimental results from the literature. This comparison suggests that the model is accurate in estimating force variability within the low force range and can be used to explore effects of muscle force variability in increased kinematic variability during slow movements.</div>
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