Literature DB >> 21959315

A model-experiment comparison of system dynamics for human walking and running.

Susanne W Lipfert1, Michael Günther, Daniel Renjewski, Sten Grimmer, Andre Seyfarth.   

Abstract

The human musculo-skeletal system comprises high complexity which makes it difficult to identify underlying basic principles of bipedal locomotion. To tackle this challenge, a common approach is to strip away complexity and formulate a reductive model. With utter simplicity a bipedal spring-mass model gives good predictions of the human gait dynamics, however, it has not been fully investigated whether center of mass motion over time of walking and running is comparable between the model and the human body over a wide range of speed. To test the model's ability in this respect, we compare sagittal center of mass trajectories of model and human data for speeds ranging from 0.5 m/s to 4 m/s. For simulations, system parameters and initial conditions are extracted from experimental observations of 28 subjects. The leg parameters stiffness and length are extracted from functional fitting to the subjects' leg force-length curves. With small variations of the touch-down angle of the leg and the vertical position of the center of mass at apex, we find successful spring-mass simulations for moderate walking and medium running speeds. Predictions of the sagittal center of mass trajectories and ground reaction forces are good, but their amplitudes are overestimated, while contact time is underestimated. At faster walking speeds and slower running speeds we do not find successful model locomotion with the extent of allowed parameter variation. We conclude that the existing limitations may be improved by adding complexity to the model.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21959315     DOI: 10.1016/j.jtbi.2011.09.021

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  11 in total

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3.  The rotary component of leg force during walking and running.

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4.  Force direction patterns promote whole body stability even in hip-flexed walking, but not upper body stability in human upright walking.

Authors:  Roy Müller; Christian Rode; Soran Aminiaghdam; Johanna Vielemeyer; Reinhard Blickhan
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5.  A neural circuitry that emphasizes spinal feedback generates diverse behaviours of human locomotion.

Authors:  Seungmoon Song; Hartmut Geyer
Journal:  J Physiol       Date:  2015-06-23       Impact factor: 5.182

Review 6.  Stiffness as a Risk Factor for Achilles Tendon Injury in Running Athletes.

Authors:  Anna V Lorimer; Patria A Hume
Journal:  Sports Med       Date:  2016-12       Impact factor: 11.136

7.  Walking in circles: a modelling approach.

Authors:  Horst-Moritz Maus; Andre Seyfarth
Journal:  J R Soc Interface       Date:  2014-10-06       Impact factor: 4.118

8.  Golden Gait: An Optimization Theory Perspective on Human and Humanoid Walking.

Authors:  Marco Iosa; Giovanni Morone; Stefano Paolucci
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9.  Neuromusculoskeletal model that walks and runs across a speed range with a few motor control parameter changes based on the muscle synergy hypothesis.

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Journal:  Sci Rep       Date:  2019-01-23       Impact factor: 4.379

Review 10.  Linking Gait Dynamics to Mechanical Cost of Legged Locomotion.

Authors:  David V Lee; Sarah L Harris
Journal:  Front Robot AI       Date:  2018-10-17
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