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Podněty svalové činnosti při chůzi a běhu na pevném povrchu a chodícím pásu
Čurda, Josef ; Šťastný, Jan (referee) ; Korvas, Pavel (advisor)
This term paper deals with the difference in the electrical activity of muscles when walking and running on a solid surface and when walking and running on a treadmill. The measurements are performed using a Cometa Wave plus multichannel electromyograph. Software evaluation is performed using EMGandMotionToolsv software from © 2018 Logemas Pty Ltd. Results are processed in MATLAB software from MathWorks (R2021a). The theoretical section describes the physiological processes occurring in the neuromuscular system, muscle structure and an explanation of the concept of EMG. The practical part includes methodology, measurement protocol, research questions, stated objectives and results of the work evaluated in the conclusion.
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Analysis of differences in biomechanical parameters during training of football players on natural or artificial grass
Malata, Mirek ; Korvas, Pavel (referee) ; Pavelka, Jan (advisor)
The aim of this bachelor thesis is to compare sprint speed and rapid change of direction on natural and artificial turf in soccer players and to verify whether higher speed is associated with a greater risk of injury. The theoretical part describes the historika development of football with its rules, the training process, the biomechanics of running, and its variation in sprinting and agility. It also focuses on describing and exploring the connections associated with natural and artificial turf in football. In the practical part, two standardized tests, the 30-meter sprint and the 5-0-5 agility test, are used to determine on which surface an athlete is faster.
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Analýza tlaku chodidla na podložku při různých rychlostech běhu
Pevná, Barbora ; Pavelka, Jan (referee) ; Korvas, Pavel (advisor)
The bachelor thesis deals with the analysis of foot pressure with increasing running speed. The Medilogic WLAN insole system was used to record foot pressure over time. The thesis describes running biomechanics, running technique, stride technique and devices used for running analysis. One part of the thesis deals with the anatomy of the lower limbs. Two groups of runners were measured during the research. The first group consisted of 10 orienteering runners and the second group consisted of 10 middle and long distance runners. All runners completed eighteen 50 metre sections at gradually increasing running speeds. The data collection and processing are described in the methodological part of the thesis. From the measured data it was found that athletes and orienteers run with different techniques. Differences between the groups were found in pressure values, load ranges and power values. Athletes use the swing running technique earlier and use more forefoot than orienteers as running speed increases. The final section of the thesis includes a discussion that evaluates the benefits and limitations of the work.
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The Study of Conditions for Sport in Chosen Enviroment
Votoupal, Tomáš ; Chlíbková, Daniela (referee) ; Korvas, Pavel (advisor)
This thesis deals with conditions for sport and physical activity in Trebic. The most important tools for processing the status quo analysis, comparison of data primarily from municipal budgets, and finally carried out a survey on the conditions of physical activity. Carried out the research, I found that the city of Trebic has on its size and population, good conditions for sport and physical activity, it can be judged from the number of sports facilities and based on increasing amounts on sport and investment in sports facilities. The quality conditions and also reflects 86% positive opinions on the conditions for physical activity that emerged from the survey.
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Validity of predictive equations for determining resting energy expenditure
Fabián, Patrik ; Korvas, Pavel (referee) ; Chlíbková, Daniela (advisor)
This bachelor thesis deals with the validation of predictive equations to determine resting metabolic rate. The objective of this bachelor thesis was to compare individual predictive equations for determining resting metabolic rate with self-measurement using indirect caloriemetry and to establish a own procedure for predicting resting metabolic rate. The evaluation of each predictive equation was based on statistical analyses. Based on statistical analyses, it was found that the available predictive equations underestimate resting metabolism by an average of 20 % of kilocalories per day compared to the value measured by indirect calorimetry. Machine learning was used to determine the actual procedure for predicting resting metabolic rate, which was then presented using the user interface. The following testing showed that the neural network for predicting resting metabolic rate provides more accurate results compared to the available predictive equations.
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