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Assessment of the energy cost of florball and flag football
Máchal, Tomáš ; Bunc, Václav (advisor) ; Jandová, Soňa (referee)
The thesis elaborates the difficulty of flag football compared to floorball using heart rate measurements. Measurements for each sport were taken with six players in the age range of 18- 37 years old for twenty minutes of the game. Players are active in these sports and were selected after consultation with coaches. The measured values were processed using statistical data analysis and presented through bar graphs. Five load zones were determined for data analysis, using Polar application. The first zone of 50% to 60% of maximum heart rate and each subsequent zone covered values ranging 10% higher. The measurements showed that floorball players reached a significantly higher average heart rate during the game, 153.1 ± 9.4 bpm, compared to the average heart rate of 131 ± 6.7 bpm achieved by flag football players. The floorball players also measured a higher average maximum heart rate, which was 190.5 ± 9.4 beats/min. In flag football players, this value averaged 173.8 ± 8.5 beats/min. Furthermore, the measurements showed that the flag football players spent significantly more time in the lower load zones during the game than the floorball players. Specifically, flag football players spent 25.2% of the time in the first zone, 32.8% of the time in the second zone, 28.5% of the time in the third zone,...
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Using of neural network for detection of heart rhythm disturbances from ECG data and accelerometer signal
Aleksandrenko, Borys ; Ředina, Richard (referee) ; Bulková, Veronika (advisor)
This bachelor's thesis addresses the issue of detecting heart rhythm disorders from EKG and accelerometer signals using machine learning. First, an analysis of the possibilities for detecting heart rhythm disorders from these signals was conducted through a theoretical review. In the next part, a methodology was proposed for detecting two rhythm disorders: inappropriate sinus tachycardia and chronotropic incompetence. The methodology was further supplemented with adaptive filtering of EKG signals using signals from the accelerometer. In the third part of the thesis, a database of samples was created for training machine learning models proposed in the methodology. The next section included the description and implementation of the models. In the fifth part of the thesis, an application for detecting heart rhythm disorders using the proposed methodology was developed in the Python programming language. Finally, a discussion and evaluation of the results were conducted.
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Heart Rate Estimation from the PPG Signals
Šimčák, Petr ; Králík, Martin (referee) ; Kozumplík, Jiří (advisor)
This bachelor thesis focuses on heart rate estimation from photoplethysmographic (PPG) signals. The work utilizes two databases: CapnoBase and BUT PPG. The aim is not only to provide an overview of heart rate estimation methods from PPG signals but also to design, implement, and test algorithms for reliable detection of systolic peaks and heart rate determination. The advantages and limitations of each method are also discussed.
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Use of Physiological Data to Analyze and Improve the User Experience
Štefeková, Nina ; Beran, Vítězslav (referee) ; Materna, Zdeněk (advisor)
This thesis is concerned with the research of the physiological symptoms of stress, the design and execution of an experiment that can induce short-term stress. Subsequently, the goal was to create a dataset from the experimentally obtained data and use it to train a machine learning model. Stress detection by such a model can be used to analyze the user experience. The proposed experiment uses a combination of stimuli, consisting of a relaxation part, a Stroop test and a web game that deliberately uses an unfriendly user interface. During it, data was recorded using an Empatica E4 device and then processed by an implemented application into the final dataset. A machine learning model that can detect short-term stress was then trained and evaluated. The KNN algorithm model evaluated by cross-validation achieves an accuracy of 84\% when the subject of the is known prior to the model. For an unknown subject, it is on average 78\%. The thesis provides this model and the resulting dataset, for further use. These results show that short-term stress detection is more challenging without prior knowledge of the subject.
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Detection of pilot body conditions by biometric sensors
Jakubec, Jakub ; Cigánek, Jan (referee) ; Chlebek, Jiří (advisor)
This master 's thesis deals with the detection of the state of the pilot using biometric sensors. The theoretical part describes various physiological states and types of sensors used for monitoring. Studies dealing with sleep detectioin and ways to detect drowsiness and sleep are presented here. The practical section focuses on gathering data from the actual aircraft environment and analyzing it. The results of the practical part show that the technology used has great potential and pilots are open to this technology. This technology would significantly improve flight safety.
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Complete implementation of pulse oximeter
Doležal, Lukáš ; Kaller, Ondřej (referee) ; Šotner, Roman (advisor)
This thesis deals with the design of a pulse oximeter. The resulting device allows to measure human blood oxygen saturation and heart rate in a non-invasive way. Easy portability is enabled by battery power supply and the used colour graphical display ensures clear display of the measured data. The paper describes in general terms the principle of pulse oximetry, a description of the chosen electronic components and the firmware developed to ensure the device's operation. Verification of correct operation was performed by comparing the measurements with similar devices available on the market.
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The effect of beta-alanine supplementation on aerobic exercise in adolescent athletes
BAHENSKÝ, Petr
Supplementation is generally increasingly popular at this time, so the aim of our bachelor thesis was to explore in more detail the effect of beta-alanine supplementation on aerobic load in adolescent athletes. We looked at how beta-alanine affects the performance and endurance of young athletes during physical activity. In total, 20 young athletes participated in the study, of whom 8 were boys and 12 were girls. They underwent two staged exercise tests over a four-week period. The athletes were randomly divided into two groups: the experimental group that supplemented beta-alanine and the control group that took placebo. The results showed that after four weeks of beta-alanine supplementation, there was a significant improvement in the overall time to exhaustion. Specifically, an increase of 7.4 % was observed. The running rate at the second ventilation threshold increased by 5.7 %. An important aspect was also the blood lactate value, which increased by 8.8 % three minutes after the end of the test. This increase in lactate suggests that beta-alanine supplementation resulted in greater exhaustion, resulting in increased lactate production. Next finding was that other parameters such as VO2max, maximum heart rate and final respiratory exchange rate did not change significantly. This indicates the specificity of the effects of beta-alanine under aerobic load in adolescent athletes. In conclusion, the results of this bachelor's thesis suggest a positive effect of beta-alanine supplementation on aerobic load in young athletes. This dietary supplement can be a useful tool for improving endurance performance and achieving better sports results in this specific group.
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Advanced scoring of sleep data
Jagošová, Petra ; Novotná, Petra (referee) ; Ronzhina, Marina (advisor)
The master´s thesis is focused on advanced scoring of sleep data, which was performed using deep neural network. Heart rate data and the movement information were used for scoring measured using an Apple Watch smartwatch. After appropriate pre-processing, this data serves as input parameters to the designed networks. The goal of the LSTM network was to classify data into either two groups for sleep and wake or into three groups for wake, Non-REM and REM. The best results were achieved by network doing classification of sleep vs. wake using the accelerometer. The statistical evaluation of this best-designed network reached the values of sensitivity 71,06 %, specificity 57,05 %, accuracy 70,01 % and F1 score 81,42 %.
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Cardiotachometer
Máca, Kamil ; Číž, Radim (referee) ; Chmelař, Milan (advisor)
This masters thesis describes possibilities of a heart rate measuring. Several methods of measuring will be discussed. The primary objective of this paper is to design battery powered cardiotachometr with a range of 30-240 beats/min and a low battery indication. Cardiotachometer uses the R waves detector to measure heart rate. This thesis is focused on creation of the block diagram, electrical circuit, printed circuit and calculation of electronic device used in cardiotachometers.
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