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Methods for respiration estimates from ECG signal
Mitrengová, Jana ; Mézl, Martin (referee) ; Králík, Martin (advisor)
The thesis deals with the realization of methods for estimation of the respiratory curve from the ECG signal. The first part of the thesis deals with the anatomy and physiology of the respiratory and cardiovascular system. In this part of the thesis are also described ways of the breathing monitoring. The second part of the thesis is dedicated to the description of individual methods for the ECG derived respiration. The third part deals with the realization of selected methods, application of method algorithms on real data and comparison of resulting respiratory curves with the respiratory signals available from the PhysioNet database. In conclusion, the individual methods are compared with each other.
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ECG baseline wander correction based on the empirical mode decomposition
Šlancar, Matěj ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
The aim of this thesis is to introduce with principle of Empirical Mode Decomposition method and possibility use for correction of baseline wander in ECG signals. The thesis describes the main components of the ECG signal, a selection of possible types of signal noise, its property and principles of chosen methods for filtration of ECG signals. In conclusion the evaluation of the effectiveness of the EMD method for filtering a baseline wander and it comparing with effectiveness of the linear filtration. Functionality of used algorithms has been tested on signals of CSE standard library.
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Advanced analysis of signals from gait laboratory.
Húsková, Michaela ; Mézl, Martin (referee) ; Svozilová, Veronika (advisor)
The aim of the thesis is a realization of advanced analysis of signals from gait laboratory. The introductory part deals with the gait cycle and its relation to the joints kinematic is discussed. Additionally, the work is focused on the description of the gait laboratory and the definition of the indexes in order to quantify patient´s overall gait in kinematic analysis. In the practical part, kinematic data analysis was implemented in the MATLAB environment and the results of healthy individuals and patients with cerebral palsy were compared. Kinematic analysis included peak detection in specific kinematic variables. In the last part a graphical user interface for visualization was implemented.
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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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Using Hilbert Huang transformation for analysis of non-stationary signals from physical experiments
Tuleja, Peter ; Balík, Miroslav (referee) ; Rášo, Ondřej (advisor)
This paper discusses the possible use of Hilbert-Huang transform to analyze the data obtained from physical experiments. Specifically for the analysis of acoustic emission in the form of acoustic shock. The introductory section explains the concept of acoustic emission and its detection process. Subsequently are discussed methods for signal analysis in time-frequency domain. Specifically, short-term Fourier transform, Wavelet transform, Hilbert transform and Hilbert-Huang transform. The final part contains the proposed method for measuring the performance and accuracy of different approaches.
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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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Research of the new augmentation methods for online handwriting
Sigmund, Jan ; Burget, Radim (referee) ; Zvončák, Vojtěch (advisor)
Graphomotor difficulties of school-aged children are characterised by problems in handwriting and drawing and can lead to developmental dysgraphia. Timely clinical diagnosis is critical to provide preventive care. In practice however, it is not feasible on day-to-day basis due to the need for expert staff and the prevalence of difficulties up to 30\%. Machine learning models can serve as an accessible objective tool for evaluating graphomotor functioning. In most cases there is not enough data collected, which results in poor classification performance. Therefore, this thesis focuses on data augmentation of online handwriting. Generating artificial samples is based on recombination of intrinsic mode functions, obtained by empirical mode decomposition. IMFs of health controls, numbering 72, and with graphomotor difficulties, 94 children in total, are calculated. The decomposition is performed specifically on X and Y coordinate time series. IMFs of the same indices of different subjects are randomly interchanged, thus producing a new signal. Then, the graphomotor features of the original and artificial time series are extracted. Only the spatial ones related to the coordinates are selected. Finally, the correlations of the features of the two databases will be analyzed and compared.
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Advanced analysis of signals from gait laboratory.
Húsková, Michaela ; Mézl, Martin (referee) ; Svozilová, Veronika (advisor)
The aim of the thesis is a realization of advanced analysis of signals from gait laboratory. The introductory part deals with the gait cycle and its relation to the joints kinematic is discussed. Additionally, the work is focused on the description of the gait laboratory and the definition of the indexes in order to quantify patient´s overall gait in kinematic analysis. In the practical part, kinematic data analysis was implemented in the MATLAB environment and the results of healthy individuals and patients with cerebral palsy were compared. Kinematic analysis included peak detection in specific kinematic variables. In the last part a graphical user interface for visualization was implemented.
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