https://nova.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:10948 Sat 24 Mar 2018 08:14:16 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:20916 Sat 24 Mar 2018 08:06:12 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:18358 Sat 24 Mar 2018 07:52:40 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:26747 2max 4.1 ± 0.7 L/min, training experience 2.7 ± 1.2 y) and to establish the relationship between physiological variables (VO_2max, VO₂ kinetics, muscleoxygen kinetics, paddling efficiency) and sprint kayak performance. VO_2max, power at VO_2max, power:weight ratio, paddling efficiency, VO₂ at lactate threshold, and whole-body and muscle oxygen kinetics were determined on a kayak ergometer in the laboratory. Separately, on-water time trials (TT) were completed over 200 m and 1000 m. Large to nearly perfect (-.5 to-.9) inverse relationships were found between the physiological variables and on-water TT performance across both distances. Paddling efficiency and lactate threshold shared moderate to very large correlations (-.4 to-.7) with 200- and 1000-m performance. In addition, trivial to large correlations (-.11 to-.5) were observed between muscle-oxygenation parameters, muscle and whole-body oxygen kinetics, and performance. Multiple regression showed that 88% of the unadjusted variance for the 200-m TT performance was explained by VO_2max, peripheral muscle deoxygenation, and maximal aerobic power (P < .001), whereas 85% of the unadjusted variance in 1000-m TT performance was explained by VO_2max and deoxyhemoglobin (P < .001). The current findings show that well-trained junior sprint kayak athletes possess a high level of relative aerobic fitness and highlight the importance of the peripheral muscle metabolism for sprint kayak performance, particularly in 200-m races, where finalists and nonfinalists are separated by very small margins. Such data highlight the relative aerobic-fitness variables that can be used as benchmarks for talent-identification programs or monitoring longitudinal athlete development. However, such approaches need further investigation.]]> Sat 24 Mar 2018 07:24:48 AEDT ]]> https://nova.newcastle.edu.au/vital/access/ /manager/Repository/uon:32764 IO₂] = 21%) and moderate-level hypoxia (MH; F_IO₂ = 16%). Exercise comprised 3 sets of 10 repetitions of squats and deadlifts at 60% of 1 repetition maximum, with 60-second interset rest. Blood lactate (BLa⁻) was quantified after each exercise, whereas arterial oxygen saturation and heart rate (HR) were assessed after each set. Thigh circumference was measured before and after exercise. Muscle activation and oxygenation were monitored by surface electromyography (EMG) and near-infrared spectroscopy, respectively. Relative BLa⁻ concentrations were significantly higher following squats (p = 0.041) and deadlifts (p = 0.002) in MH than NORM. Arterial oxygen saturation was lower after each set in MH compared with NORM (p , 0.001), although HR and thigh circumference were not different between conditions. Integrated EMG was higher in MH than in NORM for the squat during several repetitions (p ≤ 0.032). Measures of muscle oxygen status were not significantly different between conditions (p ≥ 0.247). The main findings from this study suggest that hypoxia during moderate-load resistance exercise augments metabolite accumulation and muscle activation. However, a significant hypoxic dose was not measured at the muscle, possibly because of the moderate level of hypoxia used. The current data support previous hypotheses that have suggested hypoxia can augment some physiological responses that are important for muscular development, and may therefore provide benefit over the equivalent training in normoxia.]]> Mon 23 Jul 2018 12:49:19 AEST ]]>