Includes abstract. / Includes bibliographical references. / Several methods have been used to quantify the internal training load of a bout of exercise. However, arecent novel approach to quantify the internal training load has been to investigate the dynamic returntowards resting homeostasis at the cessation of exercise. Objective and non-invasive methods ofmonitoring the return towards resting homeostasis include measures of heart rate recovery (HRR) andexcess post-exercise oxygen consumption (EPOC). However, the relative potential of autonomic- vs. metabolic-type recovery measurements to represent the internal training load or homeostatic stress of the preceding exercise bout has not been established. Therefore, the broad aim of this thesis was to investigate the magnitude of EPOC (EPOCMAG), the time constant of the EPOC recovery curve (EPOCτ),HRR within the first minute post-exercise (HRR60s) and the time constant of the HRR curve (HRRτ) as measures which might reflect the homeostatic stress of an exercise bout. It was hypothesized that a measure representing the homeostatic stress of an exercise bout could have the following possible applications; - to identify inter-individual variation in the homeostatic stress of a standardized exercise bout - to detect intra-individual variation in the homeostatic stress of different exercise bouts- to detect intra-individual variation in “readiness to train”, based on the response to a standardized exercise bout. Therefore, the investigations of this thesis aimed to assess the relative potential of EPOCMAG, EPOCτ,HRR60s and HRRτ in these different roles. The experimental work was divided into 4 studies.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/3264 |
| Date | January 2013 |
| Creators | Mann, Theresa Naomin Carol |
| Contributors | Lambert, Michael, Lamberts, Robert P |
| Publisher | University of Cape Town, Faculty of Health Sciences, Department of Human Biology |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, Doctoral, PhD |
| Format | application/pdf |
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