National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Utilization of the running power meter STRYD in determining the dynamic parameters of running footwear and their impact on the performance of an endurance runner
Shánělová, Štěpánka ; Kundera, Václav (referee) ; Pavelka, Jan (advisor)
The thesis is concerned with the findings of running performance in two different types of running shoes. The differences in performance generated by the runner in each type of shoe are observed. The theoretical part discusses the methodology of running training, the evolution of running shoes, the monitored running parameters with a focus on running power. The second part of the thesis is practical, where the methodology of data collection and data processing is explained. Furthermore, the results are interpreted.
Využití běžeckého wattmetru STRYD pro stanovení úrovně VO2max u vytrvalostních běžců
Bekr, Ondřej ; Kundera, Václav (referee) ; Pavelka, Jan (advisor)
Determining the limits of general endurance, critical power and maximal oxygen consumption is now a common part of the training process of professional athletes and their preparation to achieve the best possible sports results. Power is a very useful metric in cycling, but in recent years runners have also been trying to exploit its potential. Running power is only functional if it represents well the metabolic load of the organism. This thesis investigates the relationship between running power PO and oxygen consumption VO2, a representative of the metabolic load of the organism, in indoor and outdoor environments. Furthermore, thesis verifies the possibility of determining the VO2max level of runners using running power. The relationship between PO and VO2 is linear, for individual subjects the R2 is 0,95±0,07 in the indoor and 0,97±0,02 in the outdoor. For all subjects (TO) in the indoor the R2 takes the value of 0,67 and in the outdoor the value of 0,79. There was a difference of 1,2% (PO) and 3,7% (VO2max) between the values measured in the different environments. The model prediction from all TO in the indoor environment has an error of 3,5%.

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