Literature DB >> 21169022

Predicted knee kinematics and kinetics during functional activities using motion capture and musculoskeletal modelling in healthy older people.

Peter Worsley1, Maria Stokes, Mark Taylor.   

Abstract

Knowledge of joint forces and moments is essential for comparisons between healthy people and those with pathological conditions, with observed changes at joints providing basis for a particular intervention. Currently the literature analysing both kinematics and kinetics at the knee has been limited to small samples, typically of young subjects or those who have undergone joint arthroplasty. In this study, we examined tibiofemoral joint (TFJ) kinematics and kinetics during gait, sit-stand-sit, and step-descent in 20 healthy older subjects (aged 53-79 years) using motion capture data and inverse dynamic musculoskeletal models. Mean peak distal-proximal force in the TFJ were 3.1, 1.6, and 3.5 times body weight (N/BW) for gait, sit-stand, and step-descent respectively. There were also significant posterior-anterior forces, with sit-stand activity peaking at 1.6 N/BW. Moments about the TFJ peaked at a mean of 0.07 Nm/BW during the sit-stand activity. One of the most important findings of this study was variability found across the subjects, who spanned a wide age range, showing large standard deviations in all of the activities for both kinematics and kinetics. These data have provided an initial prediction for assessing kinematics and kinetics in the older population. Larger studies are needed to refine the database, in particular to reduce the variability in the results by studying sub-populations, to enable more robust comparisons between healthy and pathological TFJ kinematics and kinetics.
Copyright © 2010 Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Year:  2010        PMID: 21169022     DOI: 10.1016/j.gaitpost.2010.11.018

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  4 in total

1.  Chondrocyte deformations as a function of tibiofemoral joint loading predicted by a generalized high-throughput pipeline of multi-scale simulations.

Authors:  Scott C Sibole; Ahmet Erdemir
Journal:  PLoS One       Date:  2012-05-23       Impact factor: 3.240

2.  A new graphical method to display data sets representing biomechanical knee behaviour.

Authors:  Silvia Pianigiani; Jos Vander Sloten; Walter Pascale; Luc Labey; Bernardo Innocenti
Journal:  J Exp Orthop       Date:  2015-08-28

3.  Statistical Modeling of Lower Limb Kinetics During Deep Squat and Forward Lunge.

Authors:  Joris De Roeck; J Van Houcke; D Almeida; P Galibarov; L De Roeck; Emmanuel A Audenaert
Journal:  Front Bioeng Biotechnol       Date:  2020-04-02

4.  Uncertainty in Muscle-Tendon Parameters can Greatly Influence the Accuracy of Knee Contact Force Estimates of Musculoskeletal Models.

Authors:  Seyyed Hamed Hosseini Nasab; Colin R Smith; Allan Maas; Alexandra Vollenweider; Jörn Dymke; Pascal Schütz; Philipp Damm; Adam Trepczynski; William R Taylor
Journal:  Front Bioeng Biotechnol       Date:  2022-06-03
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.