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Parametric dynamic analysis of walking within a cable-based gait trainer

Published online by Cambridge University Press:  15 August 2018

Houssein Lamine Open the ORCID record for Houssein Lamine [Opens in a new window] ,
Lotfi Romdhane  and
Sami Bennour
Houssein Lamine*
Affiliation:
Mechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, Tunisia E-mail: [email protected], [email protected]
Lotfi Romdhane
Affiliation:
Mechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, Tunisia E-mail: [email protected], [email protected] Mechanical Engineering Department, American University of Sharjah, PO Box 26666, Sharjah, United Arab Emirates
Sami Bennour
Affiliation:
Mechanical Laboratory of Sousse (LMS), National Engineering School of Sousse, University of Sousse, Sousse 4000, Tunisia E-mail: [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

In this paper, a parametric analysis of the inverse dynamics of an upright partially unloaded walking is performed. This motion is produced through a gait-training machine emulating the over-ground walking using a body weight support mechanism and a cable-driven robot. The input motion is the kinematics of a normal gait, and the ultimate output result is the required tensions to be generated by the cable robot in order to drive the lower limb. The dynamic analysis is carried out based on the Newton–Euler approach. A Matlab Simscape model is also built to validate the analytical results. The obtained dynamic model is used to investigate the effect of the variation of the gait simulation parameters on the actuation wrench and the cable tensions. The obtained results could be used to determine the optimal design of the gait trainer actuators and they are useful in estimating optimal gait training parameters.

Keywords

gait analysiscable-driven robotsgait trainingpartial unloaded walkingNewton–EulerMatlab Simscape
Type
Articles
Information
Robotica , Volume 37 , Special Issue 7: Computational Kinematics Conference, CK 2017 , July 2019 , pp. 1225 - 1239
Copyright
© Cambridge University Press 2018 

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