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journal.pcbi.1005581.pdf
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Univ Arizona, Coll Med, Dept PhysiolIssue Date
2017-06-02
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A motor unit-based model of muscle fatigue 2017, 13 (6):e1005581 PLOS Computational BiologyJournal
PLOS Computational BiologyRights
© 2017 Potvin, Fuglevand. This is an open access article distributed under the terms of the Creative Commons Attribution License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Muscle fatigue is a temporary decline in the force and power capacity of skeletal muscle resulting from muscle activity. Because control of muscle is realized at the level of the motor unit (MU), it seems important to consider the physiological properties of motor units when attempting to understand and predict muscle fatigue. Therefore, we developed a phenomenological model of motor unit fatigue as a tractable means to predict muscle fatigue for a variety of tasks and to illustrate the individual contractile responses of MUs whose collective action determines the trajectory of changes in muscle force capacity during prolonged activity. An existing MU population model was used to simulate MU firing rates and isometric muscle forces and, to that model, we added fatigue-related changes in MU force, contraction time, and firing rate associated with sustained voluntary contractions. The model accurately estimated endurance times for sustained isometric contractions across a wide range of target levels. In addition, simulations were run for situations that have little experimental precedent to demonstrate the potential utility of the model to predict motor unit fatigue for more complicated, real-worldapplications. Moreover the model provided insight, into the complex orchestration of MU force contributions during fatigue, that would be unattainable with current experimental approachesNote
Open access journal.ISSN
1553-7358PubMed ID
28574981Version
Final published versionSponsors
Auto21 Network of Centres of Excellence [A506-AWH]; National Institutes of Health [R01NS079147]Additional Links
http://dx.plos.org/10.1371/journal.pcbi.1005581ae974a485f413a2113503eed53cd6c53
10.1371/journal.pcbi.1005581
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Except where otherwise noted, this item's license is described as © 2017 Potvin, Fuglevand. This is an open access article distributed under the terms of the Creative Commons Attribution License.
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