Skip to the content

Predictive modelling of human walking over a complete gait cycle

Ren, L, Jones, RK and Howard, D 2007, 'Predictive modelling of human walking over a complete gait cycle' , Journal of Biomechanics, 40 (7) , pp. 1567-1574.

PDF - Accepted Version
Download (615kB) | Preview
[img] PDF - Published Version
Restricted to Repository staff only

Download (545kB)


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

Item Type: Article
Uncontrolled Keywords: Gait prediction, inverse dynamics, optimisation, optimal motor task
Themes: Subjects / Themes > R Medicine > R Medicine (General)
Health and Wellbeing
Schools: Schools > School of Health Sciences > Centre for Health Sciences Research
Schools > School of Environment and Life Sciences
Schools > School of Health Sciences
Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre (SIRC)
Journal or Publication Title: Journal of Biomechanics
Publisher: Elsevier
Refereed: Yes
ISSN: 00219290
Depositing User: H Kenna
Date Deposited: 09 Aug 2007 12:08
Last Modified: 30 Nov 2015 23:59

Actions (login required)

Edit record (repository staff only) Edit record (repository staff only)


Downloads per month over past year