Literature DB >> 34461365

Experimental recommendations for estimating lower extremity loading based on joint and activity.

Todd J Hullfish1, John F Drazan1, Josh R Baxter2.   

Abstract

Researchers often estimate joint loading using musculoskeletal models to solve the inverse dynamics problem. This approach is powerful because it can be done non-invasively, however, it relies on assumptions and physical measurements that are prone to measurement error. The purpose of this study was to determine the impact of these errors - specifically, segment mass and shear ground reaction force - have on analyzing joint loads during activities of daily living. We performed traditional marker-based motion capture analysis on 8 healthy adults while they completed a battery of exercises on 6 degree of freedom force plates. We then scaled the mass of each segment as well as the shear component of the ground reaction force in 5% increments between 0 and 200% and iteratively performed inverse dynamics calculations, resulting in 1681 mass-shear combinations per activity. We compared the peak joint moments of the ankle, knee, and hip at each mass-shear combination to the 100% mass and 100% shear combination to determine the percent error. We found that the ankle was most resistant to changes in both mass and shear and the knee was resistant to changes in mass while the hip was sensitive to changes in both mass and shear. These results can help guide researchers who are pursuing lower-cost or more convenient data collection setups.
Copyright © 2021. Published by Elsevier Ltd.

Entities:  

Keywords:  Biomechanics; Inverse dynamics; Low-cost data collection; Run; Sensitivity analysis; Walk

Mesh:

Year:  2021        PMID: 34461365      PMCID: PMC8643134          DOI: 10.1016/j.jbiomech.2021.110688

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.789


  24 in total

1.  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

2.  An efficient probabilistic methodology for incorporating uncertainty in body segment parameters and anatomical landmarks in joint loadings estimated from inverse dynamics.

Authors:  Joseph E Langenderfer; Peter J Laz; Anthony J Petrella; Paul J Rullkoetter
Journal:  J Biomech Eng       Date:  2008-02       Impact factor: 2.097

3.  Estimating subject-specific body segment parameters using a 3-dimensional modeller program.

Authors:  Peter L Davidson; Suzanne J Wilson; Barry D Wilson; David J Chalmers
Journal:  J Biomech       Date:  2008-11-07       Impact factor: 2.712

4.  OpenSim: open-source software to create and analyze dynamic simulations of movement.

Authors:  Scott L Delp; Frank C Anderson; Allison S Arnold; Peter Loan; Ayman Habib; Chand T John; Eran Guendelman; Darryl G Thelen
Journal:  IEEE Trans Biomed Eng       Date:  2007-11       Impact factor: 4.538

5.  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

6.  nmsBuilder: Freeware to create subject-specific musculoskeletal models for OpenSim.

Authors:  Giordano Valente; Gianluigi Crimi; Nicola Vanella; Enrico Schileo; Fulvia Taddei
Journal:  Comput Methods Programs Biomed       Date:  2017-09-18       Impact factor: 5.428

7.  A simple instrumented insole algorithm to estimate plantar flexion moments.

Authors:  Todd J Hullfish; Josh R Baxter
Journal:  Gait Posture       Date:  2020-04-21       Impact factor: 2.840

8.  Instrumented immobilizing boot paradigm quantifies reduced Achilles tendon loading during gait.

Authors:  Todd J Hullfish; Kathryn M O'Connor; Josh R Baxter
Journal:  J Biomech       Date:  2020-07-01       Impact factor: 2.712

9.  Moving outside the lab: Markerless motion capture accurately quantifies sagittal plane kinematics during the vertical jump.

Authors:  John F Drazan; William T Phillips; Nidhi Seethapathi; Todd J Hullfish; Josh R Baxter
Journal:  J Biomech       Date:  2021-06-13       Impact factor: 2.789

10.  Standardized loads acting in knee implants.

Authors:  Georg Bergmann; Alwina Bender; Friedmar Graichen; Jörn Dymke; Antonius Rohlmann; Adam Trepczynski; Markus O Heller; Ines Kutzner
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

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