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Validation of the Inverse Dynamic Analysis of Human Gait Using a Forward Dynamics Approach

[+] Author Affiliations
Rosa Pàmies-Vilà, Josep M. Font-Llagunes

Universitat Politècnica de Catalunya, Barcelona, Catalunya, Spain

Paper No. DETC2013-13023, pp. V07AT10A006; 10 pages
doi:10.1115/DETC2013-13023
From:
  • ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 7A: 9th International Conference on Multibody Systems, Nonlinear Dynamics, and Control
  • Portland, Oregon, USA, August 4–7, 2013
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5596-6
  • Copyright © 2013 by ASME

abstract

One of the aims of the dynamic analysis of human gait is to know the joint forces and torques that the musculoskeletal system produces during the motion. For this purpose, an 18 segment 3D model with 57 degrees of freedom is implemented. The analysis of a captured motion can be addressed by means of forward or inverse dynamic analyses. In this work, both analyses are computed using multibody dynamics techniques. The forward dynamic analysis is carried out with the aim of simulating the movement of the multibody system using the results of the inverse problem as input data. Since the inverse analysis is solved using a dynamically consistent methodology, the forward dynamic analysis allows us to simulate up to the 90% of the gait cycle without any controller. After that, a proportional derivative (PD) controller is implemented to stabilize the system, which gets to simulate the complete captured motion. Moreover, the dynamic contribution of the controller is really low and the simulated motion is extremely close to the original one. The methodology presented allows us to validate the correctness of the inverse dynamics analysis and it is an intermediate step towards the prediction problem: it requires dynamical consistency too, but the uncertainties involved in the problem are lower than in a predictive approach.

Copyright © 2013 by ASME

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