Literature DB >> 18789445

A theoretical approach for modeling peripheral muscle fatigue and recovery.

Ting Xia1, Laura A Frey Law.   

Abstract

A three-compartment model is presented to describe muscle activation, fatigue, and recovery under a variety of loading conditions. Muscle is considered to be in one of three states: resting (M(R)), activated (M(A)), or fatigued (M(F)). A bounded proportional controller represents muscle activation-deactivation, the transfer between M(R) and M(A). The fatigue and recovery rates determine the transfer to/from M(F) state. The model qualitatively demonstrates empirically based fatigue behavior, known as Rohmert's curves, with isometric loading conditions. An expanded version of the model utilizes the properties of three muscle fiber types and a last-in-first-out stack mechanism to represent the known muscle recruitment hierarchy. Additionally, a novel yet practical approach is introduced to quantitatively evaluate task-related muscle fatigue for complex and/or dynamic movements at the joint level, encompassing the nonlinear influences of joint angle and velocity. This approach may have potential for digital human modeling, ergonomics, and other real-time applications due to its computational efficiency.

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Year:  2008        PMID: 18789445     DOI: 10.1016/j.jbiomech.2008.07.013

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


  12 in total

1.  A phenomenological model of the time course of maximal voluntary isometric contraction force for optimization of complex loading schemes.

Authors:  Johannes L Herold; Christian Kirches; Johannes P Schlöder
Journal:  Eur J Appl Physiol       Date:  2018-09-04       Impact factor: 3.078

2.  A soft-contact model for computing safety margins in human prehension.

Authors:  Tarkeshwar Singh; Satyajit Ambike
Journal:  Hum Mov Sci       Date:  2017-04-07       Impact factor: 2.161

3.  Modification of a three-compartment muscle fatigue model to predict peak torque decline during intermittent tasks.

Authors:  John M Looft; Nicole Herkert; Laura Frey-Law
Journal:  J Biomech       Date:  2018-06-18       Impact factor: 2.712

4.  Mechanisms of in vivo muscle fatigue in humans: investigating age-related fatigue resistance with a computational model.

Authors:  Damien M Callahan; Brian R Umberger; Jane A Kent
Journal:  J Physiol       Date:  2016-03-02       Impact factor: 5.182

5.  A three-compartment muscle fatigue model accurately predicts joint-specific maximum endurance times for sustained isometric tasks.

Authors:  Laura A Frey-Law; John M Looft; Jesse Heitsman
Journal:  J Biomech       Date:  2012-05-09       Impact factor: 2.712

6.  Predicting non-isometric fatigue induced by electrical stimulation pulse trains as a function of pulse duration.

Authors:  M Susan Marion; Anthony S Wexler; Maury L Hull
Journal:  J Neuroeng Rehabil       Date:  2013-02-02       Impact factor: 4.262

7.  A computational model of torque generation: neural, contractile, metabolic and musculoskeletal components.

Authors:  Damien M Callahan; Brian R Umberger; Jane A Kent-Braun
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

8.  Mathematical Models of Localized Muscle Fatigue: Sensitivity Analysis and Assessment of Two Occupationally-Relevant Models.

Authors:  Ehsan Rashedi; Maury A Nussbaum
Journal:  PLoS One       Date:  2015-12-14       Impact factor: 3.240

9.  A motor unit-based model of muscle fatigue.

Authors:  Jim R Potvin; Andrew J Fuglevand
Journal:  PLoS Comput Biol       Date:  2017-06-02       Impact factor: 4.475

10.  Adapting a fatigue model for shoulder flexion fatigue: Enhancing recovery rate during intermittent rest intervals.

Authors:  John M Looft; Laura A Frey-Law
Journal:  J Biomech       Date:  2020-04-28       Impact factor: 2.712

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