Thoracic loads (i.e., a heavy backpack) commonly used in occupational and recreational settings significantly challenge human physiological systems and increase the work of breathing, which may promote respiratory muscle fatigue and negatively impacts whole body performance during physical tasks. Accordingly this thesis: (Chapter number: II) designed a laboratory based protocol that closely reflects occupational demands and (III) assessed the effect that load carriage (LC) has upon physiological and respiratory muscle function. Consequently the thesis addressed (IV) acute, (V) chronic and (VI) functional inspiratory muscle loading strategies to assess the limitations and trainability of the respiratory muscles to load carriage performance. The novel laboratory protocol, performed wearing a 25 kg backpack load, combined submaximal load carriage (LC; 60 min treadmill march at 6.5 km·h-1) and self-paced time trial exercise (LCTT; 2.4 km) to better reflect the physiological demands of occupational performance (between trials mean difference -0.34 ± 0.89 min, coefficient of variation 10.5%). Following LC, maximal inspiratory muscle pressure (PImax) and maximal expiratory muscle pressure (P¬Emax) were reduced by 11% and 13% respectively (P<0.05), and further by 5% and 6%, respectively (P< 0.05), after LCTT. Acute inspiratory loading (2 × 30 forced inspiratory efforts 40% PImax) following an active warm-up (10 min lactate turnpoint) failed to improve LCTT despite a transient increase in PImax of ~7% (P<0.05). Chronic inspiratory loading (6 wk, 50% PImax, 30 breaths twice daily) increased PImax (31%, p<0.05) reduced HR and perceptual responses post-LC, and improved LCTT (8%, P< 0.05) with no change in a placebo control. Combining IMT with functional core muscle exercises improved PImax and LCTT by 7% and 4% respectively (P< 0.05), which was greater than traditional IMT alone. Acute, chronic and functional inspiratory muscle loading strategies did not protect against respiratory muscle or locomotor muscle fatigue during LC and LCTT.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:683944 |
Date | January 2016 |
Creators | Faghy, Mark |
Publisher | University of Derby |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://hdl.handle.net/10545/604948 |
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