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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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Application for HRV analysis
Podbrežný, Viliam ; Šíma, Jan (referee) ; Němcová, Andrea (advisor)
This bachelor’s thesis deals with the investigation of heart rate variability (HRV). It describes in detail the physiological principles of HRV, its clinical significance and methods of its analysis. It deals with Poincaré’s map in more detail. The work also includes the implementation of an algorithm for rendering a real-time Poincere map with a resolution of the age of points. The algorithm is then part of the application, enabling a complex analysis of the HRV signal, obtained either from the chest belt or by various methods of offline acquisition.
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Preprocessing of R-R interval tachogram
Had, Filip ; Kozumplík, Jiří (referee) ; Kubičková, Alena (advisor)
Heart rate variability (HRV) is a parameter, which monitors variability of the time intervals between consecutive heart beats. Signal HRV contains artefacts and trends, which is necessary to remove before further processing. This work contains a brief information about the HRV and ECG signal processing. Further on the most frequently methods of heart rate variability preprocessing are described. The work includes a brief assessment of each method. Further on, several of the mentioned preprocessing algorithms are realized and described in this work. The last part is testing an evaluating of programmed algorithms on generated data and then demonstration on real data.
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Use of HRV analysis for automatic detection of ischemia in animal isolated heart
Vykoupil, Pavel ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This paper deals with HRV analysis, creating segments for this analysis, calculating HRV parameters and their classification for automatic detection of ischemia. First part of the work is dedicated to theoretical describtion of heart anatomy, ECG reading, its processing and methods of HRV analysis. Next part of this work outline the principle of creating segments used for calculation of HRV parameters. Last part of the work indtroduces classification of said parameters with the help of multilayered neural networks and finding their best possible setup based on least classification error and computing time achieved. Calculation of HRV parameters and classification was realized using software Matlab.
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LabView and biosignal analysis
Kutílek, Miloš ; Harabiš, Vratislav (referee) ; Kolář, Radim (advisor)
This bachelor’s thesis deals with the analysis of biological signals in LabView environment. Mainly it focuses on the analysis of ECG signals. The thesis also describes the theory of electrocardiogram and occupies by several programs which consider various approaches to digital filtering of ECG signals, programs for detection R wave by different ways and simple cardiology monitor.
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Software for manual delineation of ECG signals
Jež, Radek ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
This thesis deals with evaluation EKG in terms of classification rhythm and analysis HRV. In theoretic part of work are described basics of heart physiology and its usual pathology, basics of electrocardiography, evaluation EKG and standard methods of HRV evaluation. In practical part are described algorithms used in created application. Mainly describes technique of rhythm evaluation, ectopic rhythms and delineation error elimination, data preparing for HRV evaluation, drift removal from DES and HRV evaluation methods. Created program was tested on CSE and MIT- BIH database records. For lack of suitable data and absence of tested data, it wasn’t possible to test all the classification rules of used algorithms. Tested part of program appears reliable and functional.
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Modeling of RR intervals
Jach, Daniel ; Kozumplík, Jiří (referee) ; Kubičková, Alena (advisor)
This thesis is focused on modelling RR intervals. Different models are created illustrating the function of cardiovascular system in order to test various methods for expressing, removing trend and analyzing heart rate variability signals. In this thesis the IPFM model as well as the McSharry model are described and realized.
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Mobil system for monitoring of sports activity
Maleňák, Filip ; Čížek, Martin (referee) ; Rozman, Jiří (advisor)
The aim of this master’s thesis is to analyse methods that are used for monitoring athlete’s activities and a description of current technical solutions with a focus on heart rate and respiratory rate monitoring. The presented solution shows the possibilities of using available open source SW and HW technologies and their implementation in the design of an integrated tool for monitoring sports activities with the iOS operating system.
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