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Nonlinear methods of heart rate variability analysis in metabolic syndrome
Vaňková, Eliška ; Kozumplík, Jiří (referee) ; Kubičková, Alena (advisor)
This work deals with the problematic of heart rate variability of patients with metabolic syndrome. Includes the theory, which describes the heart rate variability and the methods for its analysing. Especially it specifies nonlinear methods, particularly Lyapunov exponent and its calculation in Matlab software. Algorithm of the calculation is applicated to already measured tachogram of the healthy people and patients with the metabolic syndrome. Further, this work deals with general valorization of the results using Lyapunov exponent and her eis also done the statistical evaluation.
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Sleep stage classification based on HRV signals
Schlorová, Hana ; Kubičková, Alena (referee) ; Kozumplík, Jiří (advisor)
The most common method for scoring of sleep stages is the evaluation by EEG. This work utilizes ECG signal to the comparable evaluation of sleep. It summarizes the methods of presentation and assessment of heart rate variability (HRV) and describes the whole algorithm of calculation and presentation of this signal using Lorenz plot. This work also focuses on evaluation of Lorentz plots and parametrs quantifying variability of samples in maps. It seeks to draw the conclusion of sleep stages from their waveform.
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Suppression of artifacts in electrocardiograms
Šafárová, Marcela ; Kubičková, Alena (referee) ; Janoušek, Oto (advisor)
The bachelor’s thesis on the subject removal of ECG noise introduces processing of ECG signal for possible better diagnostics. The first part of the work is focused on initiation and propagation of action potential and methods for measuring heart´s electrical activity. Further are referred main types of noise affecting the ECG signal and basic filtering methods. The work focuses on filtration using Lynn´s filters, IIR filters, interpolation, spectral lines editing and adaptive filters and evaluation of their effectivity.
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Detrending heart rate variability signal with empirical mode decomposition EMD
Foltová, Anežka ; Janoušek, Oto (referee) ; Kubičková, Alena (advisor)
HRV analysis is an important indicator of pathophysiological examination. R-R waves are used for detection and analysis of ECG interval. R-R intervals can be analyzed by various methods. During spectral analysis is an often phenomenon disturbing non-stationary trend, which needs to be removed. In this paper, which deals about detrending, is mainly introduced Empirical mode decomposition (EMD) which is popular in recent years. Subsequently, this method is being compared to the method of wavelet transformation and Smoothness prior apprach (SPA).
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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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Noise map
Lokaj, Jiří ; Kubičková, Alena (referee) ; Rozman, Jiří (advisor)
The aim of this paper is to introduce the measurement of noise and create a noise map in a geographic information system. The first part is focused on describing the physical properties of sound in space, atmospheric and physiological acoustics. It also deals with the physiological effects of noise on the human body and technology needed for measure and process noise. Other part describes the structure of a geographic information system and noise map. The last part is about the practical creation of noise maps, includes a description of the real measurement results and evaluation
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Removing baseline wander in ECG with empirical mode decomposition
Procházka, Petr ; Kolářová, Jana (referee) ; Kubičková, Alena (advisor)
In this semestral thesis, realizations of chosen linear filters for baseline wander are described. These filters are then used on artificial ECG signals from CSE database with added baseline wander. These methods are compared and results are evaluated. After that, literature search of Empirical mode decomposition method is utilized. Realization of designed filters in MATLAB programming language are described, then results are evaluated with respect to filtration success.
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Muscle noise filtering in ECG signals
Novotný, Jiří ; Kubičková, Alena (referee) ; Smital, Lukáš (advisor)
This master's thesis deals with the optimization of numerical coefficients of the Wiener filter for muscle noise filtering in ECG signals. The theoretical part deals with ECG signal characteristic and muscle interference. It also contains a summary of the wavelet transform, wavelet Wiener's filtration, methods for calculating of the threshold and thresholding. In the last theoretical part the characteristic optimization techniques, the exhausive search and Nelder-Mead simplex method are mentioned, which were implemented in the practical part of this thesis in MATLAB. The functional verification and Wiener's filter optimization were tested on the standard electrocardiograms database CSE. By using the methods of exhausive search, the initial estimate for the solution method Nelder-Mead was obtained. The optimization method Nelder-Mead gives better results in the orders of hundredths or tenths than the method of exhausive search. The practical part is finished by the comparison of results of implemented algorithm with optimum coefficients, implemented in this thesis, with the results of other methods for filtering muscle interference in ECG signals.
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