Literature DB >> 24347565

Sensitivity of joint kinematics and kinetics to different pose estimation algorithms and joint constraints in the elderly.

Vera Moniz-Pereira1, Silvia Cabral, Filomena Carnide, António P Veloso.   

Abstract

The purpose of this research was to study the sensitivity of lower limb joint kinematics and kinetics, calculated during different functional tasks (walking, stair descent and stair ascent) in a sample of older adults, to different pose estimation algorithms and models' joint constraints. Three models were developed and optimized differently: in one model, each segment had 6 degrees of freedom (segment optimization, SO), while in the other two, global optimization (GO) was used, with different joint constraints: (1) GO, allowing all joint rotations; (2) GOR, allowing three rotations at the hip, one at the knee (flexion/extension) and two at the ankle (dorsi/plantar flexion and eversion/inversion). The results showed that joint angles are more sensitive to the model's constraints than joint moments and, the more restrictive the model, the higher the differences between models, especially for the frontal and transverse planes (max. RMS difference during gait: 11.7 degrees (64%) vs 0.12 N·m/kg (35.4%). In addition, except for knee abduction/adduction angle, differences between SO and GO models were relatively low. Since GO avoids the nonanatomical dislocations sometimes observed in SO, choosing this model seems to be reasonable for future studies with a similar sample and study design.

Mesh:

Year:  2013        PMID: 24347565     DOI: 10.1123/jab.2013-0105

Source DB:  PubMed          Journal:  J Appl Biomech        ISSN: 1065-8483            Impact factor:   1.833


  4 in total

1.  Prediction of In Vivo Knee Joint Loads Using a Global Probabilistic Analysis.

Authors:  Alessandro Navacchia; Casey A Myers; Paul J Rullkoetter; Kevin B Shelburne
Journal:  J Biomech Eng       Date:  2016-03       Impact factor: 2.097

2.  Global sensitivity analysis of the joint kinematics during gait to the parameters of a lower limb multi-body model.

Authors:  Aimad El Habachi; Florent Moissenet; Sonia Duprey; Laurence Cheze; Raphaël Dumas
Journal:  Med Biol Eng Comput       Date:  2015-03-18       Impact factor: 2.602

Review 3.  Methodological factors affecting joint moments estimation in clinical gait analysis: a systematic review.

Authors:  Valentina Camomilla; Andrea Cereatti; Andrea Giovanni Cutti; Silvia Fantozzi; Rita Stagni; Giuseppe Vannozzi
Journal:  Biomed Eng Online       Date:  2017-08-18       Impact factor: 2.819

4.  Knee Kinematics Estimation Using Multi-Body Optimisation Embedding a Knee Joint Stiffness Matrix: A Feasibility Study.

Authors:  Vincent Richard; Giuliano Lamberto; Tung-Wu Lu; Aurelio Cappozzo; Raphaël Dumas
Journal:  PLoS One       Date:  2016-06-17       Impact factor: 3.240

  4 in total

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