Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Inverse optimization: functional and physiological considerations related to the force-sharing problem

D Tsirakos1, V Baltzopoulos, R Bartlett

  • 1Manchester Metropolitan University, Crewe and Alsager Faculty, Department of Exercise and Sport Science, England.

Critical Reviews in Biomedical Engineering
|January 1, 1997
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The effects of a sleeve knee brace during stair negotiation in patients with symptomatic patellofemoral osteoarthritis.

Clinical biomechanics (Bristol, Avon)·2023
Same author

Determining concentric and eccentric force-velocity profiles during squatting.

European journal of applied physiology·2022
Same author

Cochlear implantation in Malawi: report of the first four cases.

The Journal of laryngology and otology·2017
Same author

SU-E-J-124: Assessment of Intrafraction and Interfraction Motion in Cranial SRT Using Tomotherapy.

Medical physics·2017
Same author

Anterior knee pain: the need for objective measurement.

Clinical biomechanics (Bristol, Avon)·2013
Same author

Development of a computer system for real-time display and analysis of isokinetic data.

Clinical biomechanics (Bristol, Avon)·2013

This review explores optimization techniques for biomechanical force sharing, distributing joint moments to muscles and ligaments. Nonlinear and multiobjective methods offer more realistic muscle force predictions than linear approaches.

Area of Science:

  • Biomechanics
  • Computational Biology
  • Human Movement Science

Background:

  • The force-sharing problem involves distributing net joint moments to active biological structures like muscles and ligaments.
  • Optimization techniques are crucial for solving this problem by minimizing/maximizing objective functions subject to physiological constraints.
  • Understanding muscle force distribution is fundamental to analyzing human and animal movement.

Purpose of the Study:

  • To review and compare various optimization techniques for solving the force-sharing problem in biomechanics.
  • To evaluate the effectiveness of linear, nonlinear, and multiobjective optimization methods in predicting muscle forces.
  • To discuss methods for validating predicted muscle forces against experimental and analytical data.

Main Methods:

Related Experiment Videos

  • Review of optimization techniques including linear, nonlinear, and multiobjective approaches.
  • Analysis of objective functions and constraints related to physiological properties (e.g., muscle stress, activation levels).
  • Discussion of validation methods: direct force measurement, EMG patterns, forward dynamics, and analytical solutions.

Main Results:

  • Linear optimization offers limited capabilities but can yield acceptable results with appropriate constraints.
  • Nonlinear optimization provides more physiologically realistic predictions, especially when considering movement dynamics.
  • Multiobjective optimization is likely to yield the most realistic results for complex dynamic activities.

Conclusions:

  • Nonlinear and multiobjective optimization techniques are superior to linear methods for accurate muscle force prediction in biomechanics.
  • The choice of objective function (global vs. local) significantly impacts the realism of predicted muscle forces.
  • Further research and validation are needed to refine optimization strategies for complex biological movements.