Date of Award

2-2012

Document type

dissertation

Access Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Kinesiology

First Advisor

Jane A. Kent-Braun

Second Advisor

Edward P. Debold

Third Advisor

John Staudenmayer

Subject Categories

Kinesiology

Abstract

Repeated or prolonged activation of skeletal muscle results in an acute decline in the muscle's ability to produce force, which is typically referred to as fatigue. Muscle fatigue is likely related to the by-products of cellular metabolism, alterations in neural activation and diminished membrane excitability that have been shown to accompany repeated contractions. However, the complicated etiology of the fatigue process makes it difficult to understand the relative influence of these physiological responses. Computational modeling of the skeletal muscle response to repeated activation is an appealing means of gaining insight into the mechanisms of muscle fatigue. A reasonably comprehensive model would include components that represent motor neurons and populations of muscle fibers that reflect the range of metabolic and contractile characteristics known to exist in human skeletal muscle. Consideration of joint and connective tissue mechanical properties will add translational value by predicting whole joint segment behavior that can be validated by in vivo experimentation. The proposed dissertation project involved the development of a computational model incorporating multiple components meant to represent the function of the intact neuromuscular system. The complete model combines previously-validated models of neural activation and contractile behavior with a control function that attempts to match torque output to a pre-determined task. The model uses experimentally-derived functions describing metabolic cost and force inhibition to predict the loss of force generating capacity during repeated activation. Once tested using data from a group of adult men, the parameters of this model were altered to reflect age-related changes in the human neuromuscular system. The model's ability to predict the well-established phenomenon of age-related fatigue resistance during isometric contractions was then tested. The results from this series of studies support the utility of a computational approach to the investigation of muscle fatigue, and provide useful tools for future studies.

DOI

https://doi.org/10.7275/pxne-a233

Included in

Kinesiology Commons

COinS