A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait. Issue 8 (11th June 2018)

• Record Type: Journal Article
• Authors: Koelewijn, Anne D.; Dorschky, Eva; van den Bogert, Antonie J.
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 21:Issue 8(2018)
• Page Start: 521
• Page End: 531
• Publication Date: 2018-06-11
• Subjects: Metabolic energy -- minimization -- predictive simulation -- gait; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2018.1490954
• Languages: English
• ISSNs: 1025-5842

Abstract

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.