2006
DOI: 10.1016/j.jbiomech.2004.11.034
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The relationship between two different mechanical cost functions and muscle oxygen consumption

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Cited by 117 publications
(120 citation statements)
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“…Since the model includes more muscles than degrees of freedom, a nonlinear constrained optimization routine is used to resolve these torques into individual muscle forces. The optimization aims to minimize muscle energy consumption, using a cost function proposed by Praagman et al [20]. This method showed good correspondence with experimental muscle activity approximated using surface EMG.…”
Section: Simulationsmentioning
confidence: 99%
“…Since the model includes more muscles than degrees of freedom, a nonlinear constrained optimization routine is used to resolve these torques into individual muscle forces. The optimization aims to minimize muscle energy consumption, using a cost function proposed by Praagman et al [20]. This method showed good correspondence with experimental muscle activity approximated using surface EMG.…”
Section: Simulationsmentioning
confidence: 99%
“…By means of inverse dynamic simulation, muscle forces required to satisfy both the mechanical force equilibrium and moment equilibrium were calculated. Two different load sharing criteria were applied: a stress cost function, i.e., minimization of summed squared muscle stresses, and a compound linear and quadratic energy cost function [19]. Based on the estimated muscle forces, the Principal Actions for the muscles in the DSEM were calculated (PA sim ) [3,4].…”
Section: Model Simulationsmentioning
confidence: 99%
“…Praagman et al [19] introduced a combination of a linear stress and a quadratic energy cost function, which turned out to fit best with non-linear in vivo obtained muscle energy expenditure around the elbow using near infrared spectroscopy. They stated that most cost functions are chosen rather arbitrary, mainly due to the fact that validation is difficult since muscle force cannot be measured accurately in vivo.…”
Section: Introductionmentioning
confidence: 99%
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“…Although the general opinion was that musculoskeletal modeling has taken a great flight and has been and will be of great importance for understanding and quantifying musculoskeletal function, it was also clear that two major issues prevent widespread clinical use. Firstly, the general models available now need to be more thoroughly validated and tested: results by Steenbrink et al [16] indicated that there is no perfect simulation-experiment match as yet, although new cost functions [15] appear to improve results. Secondly, and also influencing the validation issue, it is quite likely that for clinical purposes models need to be individualized.…”
Section: Introductionmentioning
confidence: 99%