A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait

Abstract

Whether humans minimize metabolic energy in gait is unknown. Gradient-based optimization could be used to predict gait without using walking data but requires a twice differentiable metabolic energy model. Therefore, the metabolic energy model of Umberger et al. (2003) was adapted to be twice differentiable. Predictive simulations of a reaching task and gait were solved using this continuous model and by minimizing effort. The reaching task simulation showed that energy minimization predicts unrealistic movements when compared to effort minimization. The predictive gait simulations showed that objectives other than metabolic energy are also important in gait.

Keywords:

• Metabolic energy
• minimization
• predictive simulation
• gait

Acknowledgements

The authors would like to thank Ross Miller for his suggested adaptations to the metabolic energy model.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the National Science Foundation under Grant No. [1344954] and by a Graduate Scholarship from the Parker-Hannifin Corporation and Division of Information and Intelligent Systems.