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dc.contributor.advisorJacobs, Robert A.
dc.contributor.authorBatterson, Philip M.
dc.contributor.committeememberSubudhi, Andrew
dc.contributor.committeememberPearson, James
dc.contributor.committeememberLindsay, Keston
dc.date.accessioned2019-05-10T17:52:03Z
dc.date.available2019-05-10T17:52:03Z
dc.date.submitted2019-05
dc.descriptionIncludes bibliographical references.
dc.description.abstractTraditional exercise physiology dogma presents endurance capacity as a biological construct primarily determined through a combination of one’s maximal rate of whole-body oxygen consumption (V ̇O2max), measure(s) of performance or fatigue threshold(s), and efficiency during exercise. Although all collective assumptions implicit in this traditional tenet have never been empirically verified directly, the aggregate literature examining human integrative physiology supports this premise. A slightly divergent interpretation of the relationship between these exact biological characteristics and endurance performance advocates that optimal endurance performance requires a robust and efficient capacity to transfer and utilize oxygen from the environment to mitochondria in working skeletal muscle. The aim of the current thesis is to empirically validate both postulates regarding the predictive physiology of competitive endurance performance. First, a review of the concept and use of canonical physiologic measures of human endurance performance, their physiologic determinants, relationship to mitochondria, and role in fatigue resistance is completed. Then the discussion turns to the rise of new technologies used to measure mitochondrial function and the use of near-infrared spectroscopy to monitor the balance of oxygen delivery and utilization in skeletal muscle. Finally, the function of these technologies is described and their potential for prediction of endurance performance is discussed. Second, a study validating that the traditional exercise physiology variables of V ̇O2max, fatigue thresholds, and exercise economy are indeed highly predictive of 25 km cycling endurance performance was completed. Traditional variables were able to explain 87.9% of the variance in time trial performance. It was also shown that variables reflecting working skeletal muscle’s ability to deliver and utilize oxygen are also highly predictive of endurance performance, collectively, accounting for 86.7% of the variation in TT25. This is the first time that a combination of non-invasive measures of skeletal muscle oxygenation along with HR have been shown to strongly predict endurance performance, warranting further research to explore the extent that near-infrared spectroscopy-derived variables can be used to predict performance and possibly improve the precision of individual exercise training.
dc.identifierBatterson_uccs_0892N_10443.pdf
dc.identifier.urihttps://hdl.handle.net/10976/167091
dc.languageEnglish
dc.publisherUniversity of Colorado Colorado Springs. Kraemer Family Library
dc.relation.ispartofTheses
dc.rightsCopyright of the original work is retained by the author.
dc.subjectMaximal oxygen consumption
dc.subjectPerformance
dc.subjectEfficiency
dc.subjectThreshold
dc.subjectMitochondria
dc.titleNear-Infrared Spectroscopy: Shining Light on Endurance Performance
dc.typeText
dcterms.cdm.subcollectionBiology
thesis.degree.disciplineCollege of Letters, Arts, and Sciences-Biology
thesis.degree.grantorUniversity of Colorado Colorado Springs
thesis.degree.levelMasters


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