Literature DB >> 7806555

In vivo determination of the anatomical axes of the ankle joint complex: an optimization approach.

A J van den Bogert1, G D Smith, B M Nigg.   

Abstract

This study investigates the feasibility of a subject-specific three-dimensional model of the ankle joint complex for kinematic and dynamic analysis of movement. The ankle joint complex was modelled as a three-segment system, connected by two ideal hinge joints: the talocrural and the subtalar joint. A mathematical formulation was developed to express the three-dimensional translation and rotation between the foot and shank segments as a function of the two joint angles, and 12 model parameters describing the locations of the joint axes. An optimization method was used to fit the model parameters to three-dimensional kinematic data of foot and shank markers, obtained during test movements throughout the entire physiological range of motion of the ankle joint. The movement of the talus segment, which cannot be measured non-invasively, is not necessary for the analysis. This optimization method was used to determine the position and orientation of the joint axes in 14 normal subjects. After optimization, the discrepancy between the best fitting model and actual marker kinematics was between 1 and 3 mm for all subjects. The predicted inclination of the subtalar joint axis from the horizontal plane was 37.4 +/- 2.7 degrees, and the medial deviation was 18.0 +/- 16.2 degrees. The lateral side of the talucrural axis was directed slightly posteriorly (6.8 +/- 8.1 degrees), and inclined downward by 7.0 +/- 5.4 degrees. These results are similar to previously reported typical results from anatomical, in vitro studies. Reproducibility was evaluated by repeated testing of one subject, which resulted in variations of about one-fifth of the standard deviation within the group, the inclination of the subtalar joint axis was significantly correlated to the arch height and a radiographic 'tarsal index'. It is concluded that this optimization method provides the opportunity to incorporate inter-individual anatomical differences into kinematic and dynamic analysis of the ankle joint complex. This allows a more functional interpretation of kinematic data, and more realistic estimates of internal forces.

Entities:  

Mesh:

Year:  1994        PMID: 7806555     DOI: 10.1016/0021-9290(94)90197-x

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  28 in total

Review 1.  Imaging-based estimates of moment arm length in intact human muscle-tendons.

Authors:  Constantinos N Maganaris
Journal:  Eur J Appl Physiol       Date:  2003-12-18       Impact factor: 3.078

2.  Evaluating foot kinematics using magnetic resonance imaging: from maximum plantar flexion, inversion, and internal rotation to maximum dorsiflexion, eversion, and external rotation.

Authors:  Michael J Fassbind; Eric S Rohr; Yangqiu Hu; David R Haynor; Sorin Siegler; Bruce J Sangeorzan; William R Ledoux
Journal:  J Biomech Eng       Date:  2011-10       Impact factor: 2.097

3.  Subject-Specific Axes of Rotation Based on Talar Morphology Do Not Improve Predictions of Tibiotalar and Subtalar Joint Kinematics.

Authors:  Jennifer A Nichols; Koren E Roach; Niccolo M Fiorentino; Andrew E Anderson
Journal:  Ann Biomed Eng       Date:  2017-06-21       Impact factor: 3.934

4.  Multibody dynamic simulation of knee contact mechanics.

Authors:  Yanhong Bei; Benjamin J Fregly
Journal:  Med Eng Phys       Date:  2004-11       Impact factor: 2.242

5.  Modelling and simulation of the intervertebral movements of the lumbar spine using an inverse kinematic algorithm.

Authors:  L W Sun; R Y W Lee; W Lu; K D K Luk
Journal:  Med Biol Eng Comput       Date:  2004-11       Impact factor: 2.602

6.  Evaluation of parallel decomposition methods for biomechanical optimizations.

Authors:  Byung Il Koh; Jeffrey A Reinbolt; Benjamin J Fregly; Alan D George
Journal:  Comput Methods Biomech Biomed Engin       Date:  2004-08       Impact factor: 1.763

7.  3D inverse dynamics in non-orthonormal segment coordinate system.

Authors:  R Dumas; L Chèze
Journal:  Med Biol Eng Comput       Date:  2007-01-25       Impact factor: 2.602

8.  Are patient-specific joint and inertial parameters necessary for accurate inverse dynamics analyses of gait?

Authors:  Jeffrey A Reinbolt; Raphael T Haftka; Terese L Chmielewski; Benjamin J Fregly
Journal:  IEEE Trans Biomed Eng       Date:  2007-05       Impact factor: 4.538

9.  Parallel global optimization with the particle swarm algorithm.

Authors:  J F Schutte; J A Reinbolt; B J Fregly; R T Haftka; A D George
Journal:  Int J Numer Methods Eng       Date:  2004-12-07       Impact factor: 3.477

10.  Evaluation of a particle swarm algorithm for biomechanical optimization.

Authors:  Jaco F Schutte; Byung-Il Koh; Jeffrey A Reinbolt; Raphael T Haftka; Alan D George; Benjamin J Fregly
Journal:  J Biomech Eng       Date:  2005-06       Impact factor: 2.097

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.