Predictive modelling of human walking over a complete gait cycle

Ren, L; Jones, RK; Howard, D

Abstract

An inverse dynamics multi-segment model of the body was combined with optimisation techniques to simulate normal walking in the sagittal plane on level ground. Walking is formulated as an optimal motor task subject to multiple constraints with minimisation of mechanical energy expenditure over a complete gait cycle being the performance criterion. All segmental motions and ground reactions were predicted from only three simple gait descriptors (inputs): walking velocity, cycle period and double stance duration. Quantitative comparisons of the model predictions with gait measurements show that the model reproduced the significant characteristics of normal gait in the sagittal plane. The simulation results suggest that minimising energy expenditure is a primary control objective in normal walking. However, there is also some evidence for the existence of multiple concurrent performance objectives.

Keywords: Gait prediction; Inverse dynamics; Optimisation; Optimal motor task

Citation

Ren, L., Jones, R., & Howard, D. (2007). Predictive modelling of human walking over a complete gait cycle. Journal of Biomechanics, 40(7), 1567-1574. https://doi.org/10.1016/j.jbiomech.2006.07.017

• Journal Article Type: Article
• Publication Date: May 1, 2007
• Deposit Date: Aug 9, 2007
• Publicly Available Date: Apr 5, 2016
• Journal: Journal of Biomechanics
• Print ISSN: 0021-9290
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 40
• Issue: 7
• Pages: 1567-1574
• DOI: https://doi.org/10.1016/j.jbiomech.2006.07.017
• Keywords: Gait prediction, inverse dynamics, optimisation, optimal motor task
• Publisher URL: http://dx.doi.org/10.1016/j.jbiomech.2006.07.017