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A framework for the analysis and synthesis of 3D dynamic human gait.

Authors :
Firmani, Flavio
Park, Edward J.
Source :
Robotica; Jan2012, Vol. 30 Issue 1, p145-157, 13p
Publication Year :
2012

Abstract

A comprehensive framework for the analysis and synthesis of 3D human gait is presented. The framework consists of a realistic morphological representation of the human body involving 40 degrees of freedom and 17 body segments. Through the analysis of human gait, the joint reaction forces/moments can be estimated and parameters associated with postural stability can be quantified. The synthesis of 3D human gait is a complicated problem due to the synchronisation of a large number of joint variables. Herein, the framework is employed to reconstruct a dynamically balanced gait cycle and develop sets of reference trajectories that can be used for either the assessment of human mobility or the control of mechanical ambulatory systems. The gait cycle is divided into eight postural configurations based on particular gait events. Gait kinematic data is used to provide natural human movements. The balance stability analysis is performed with various ground reference points. The proposed reconstruction of the gait cycle requires two optimisation steps that minimise the error distance between evaluated and desired gait and balance constraints. The first step (quasi-static motion) is used to approximate the postural configurations to a region close to the second optimisation step target while preserving the natural movements of human gait. The second step (dynamic motion) considers a normal speed gait cycle and is solved using the spacetime constraint method and a global optimisation algorithm. An experimental validation of the generated reference trajectories is carried out by comparing the paths followed by 19 optical markers of a motion tracking system with the paths of the corresponding node points on the model. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
02635747
Volume :
30
Issue :
1
Database :
Complementary Index
Journal :
Robotica
Publication Type :
Academic Journal
Accession number :
67669395
Full Text :
https://doi.org/10.1017/S0263574711000440