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Biofeedback and its practical use
Dvořák, Jiří ; Hrozek, Jan (referee) ; Čmiel, Vratislav (advisor)
The aim of this work is describe common methods of biological feedback therapy that is used to treat some psychosomatic diseases. Subsequently, the description is focused on minimal brain dysfunction treatment by the help of EEG biofeedback. Properties and technical requirements for this therapy are concretized. The last part of this thesis is dedicated to the design and realization of practical software tool for EEG biofeedback therapy which is made in LabView 7.1. The M535 acquisition unit and NI USB-6221 measuring device are used for hardware solution.
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Processing of heart sounds signals
Němcová, Simona ; Matějková, Magdaléna (referee) ; Vondra, Vlastimil (advisor)
This bachelor thesis is focused on the heart sound signal. It describes the principles of hear sound formation, measurement methods and especially the analysis of the measured phonocardiography signal. In the practical part of this thesis, the algorithm for detecting the first and the second heart sounds is designed by using MATLAB software. Its principle is realized in finding maximum or center of gravity in the filtered phonocardiography signal.
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A Method to Supress Interferences in Wigner-Ville Distribution
Pikula, Stanislav ; Pazdera, Luboš (referee) ; Hájek, Karel (referee) ; Beneš, Petr (advisor)
The doctoral thesis focuses on signal representation in the time-frequency domain with constant resolution. In theoretical introduction the possibilities of displaying a signal in time and frequency are summarized. Attention is concentrated on comparison of short-time Fourier Transform (STFT) and Wigner-Ville Distribution (WVD). The latter achieves a significantly better resolution, especially for a linearly modulated signal. The disadvantage of WVD, which is the presence of interferences resulting from the calculation of the instantaneous autocorrelation function, is described in detail. These interferences are due to the presence of multiple components in the signal or its non-linear modulation. Subsequently, several methods are discussed, which can suppress these interferences, but at the cost of resolution loss. One of the interference suppression methods is smoothed pseudo Wigner-Ville distribution. It is further used in this thesis for the analysis of interference suppression when various filtrations in the time-frequency plane are applied. Several signals with multiple components or various non-linear modulations are used. Based on the analysis, a method using a set of variously smoothed pseudo Wigner-Ville distributions is designed to estimate the time-frequency representation with high resolution and minimal interferences. To compare the results to other methods, the quantitative metrics used in the literature are compared. To select the appropriate one a new metric is suggested. It is applicable to simulated signals and uses mean square error. Based on the comparison, the Stankovi\'{c} measure is selected as the most appropriate for comparing results. The selected metric is used to determine the appropriate minimal number of differently smoothed pseudo Wigner-Ville distributions. Using the selected metric, the proposed method is compared with other methods. These are STFT with optimized window length, S-method with optimized parameter and optimization method using radial Gaussian kernel (RGK). These methods are compared based on the set of signals previously used for interference suppression analysis. In addition, noises are added to the signals. Finally, the methods are also compared based on the real bat echo signal. In conclusion, the proposed method outperforms the compared methods in suppressing interference and resolution.
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Time-frequency analysis of electrograms
Doležal, Petr ; Ronzhina, Marina (referee) ; Kolářová, Jana (advisor)
This thesis deals with time-frequency analysis of electrograms measured on isolated guinea pig hearts perfused according to Langendorff. Time-frequency analysis is based on algorithms Matching Pursuit and Wigner-Ville Distribution. The theoretical part describes the basics of electrocardiography, measurement on isolated hearts, the theory of approximation method Matching Pursuit and its combination with the Wigner-Ville distribution spectrum showing the energy density of the signal. Also other common approaches of time-frequency analysis are presented including the theory of continuous wavelet transform. The presented algorithms were tested on a set of electrograms, on which were induced ischemia within measurement followed by reperfusion. The proposed method allows for the fast detection of ischemia without any a priori knowledge of the signal, and also serves as a tool for measurement of EG important points and intervals. In the conclusion efficacy of the method was presented and its possible uses has been discussed.
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Comparison of success rate of multi-channel methods of speech signal separation
Přikryl, Petr ; Zezula, Radek (referee) ; Míča, Ivan (advisor)
The separation of independent sources from mixed observed data is a fundamental problem in many practical situations. A typical example is speech recordings made in an acoustic environment in the presence of background noise or other speakers. Problems of signal separation are explored by a group of methods called Blind Source Separation. Blind Source Separation (BSS) consists on estimating a set of N unknown sources from P observations resulting from the mixture of these sources and unknown background. Some existing solutions for instantaneous mixtures are reviewed and in Matlab implemented , i.e Independent Componnent Analysis (ICA) and Time-Frequency Analysis (TF). The acoustic signals recorded in real environment are not instantaneous, but convolutive mixtures. In this case, an ICA algorithm for separation of convolutive mixtures in frequency domain is introduced and in Matlab implemented. This diploma thesis examines the useability and comparisn of proposed separation algorithms.
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Establishing Mutual Links among Brain Structures
Klimeš, Petr ; Hlinka,, Jaroslav (referee) ; Krajča,, Vladimír (referee) ; Halámek, Josef (advisor)
The Human brain consists of mutually connected neuronal populations that build anatomically and functionally separated structures. To understand human brain activity and connectivity, it is crucial to describe how these structures are connected and how information is spread. Commonly used methods often work with data from scalp EEG, with a limited number of contacts, and are incapable of observing dynamic changes during cognitive processes or different behavioural states. In addition, connectivity studies almost never analyse pathological parts of the brain, which can have a crucial impact on pathology research and treatment. The aim of this work is connectivity analysis and its evolution in time during cognitive tasks using data from intracranial EEG. Physiological processes in cognitive stimulation and the local connectivity of pathology in the epileptic brain during wake and sleep were analysed. The results provide new insight into human brain physiology research. This was achieved by an innovative approach which combines connectivity methods with EEG spectral power calculation. The second part of this work focuses on seizure onset zone (SOZ) connectivity in the epileptic brain. The results describe the functional isolation of the SOZ from the surrounding tissue, which may contribute to clinical research and epilepsy treatment.
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Time-frequency analysis
Tráge, David ; Hadinec, Michal (referee) ; Kubásek, Radek (advisor)
The aim of this bachelor`s thesis is to explore possibilities of solving time-, frequency analysis a their combination time-frequency analysis by different methods for example Fourier transform a Wavelet transform. Going through this project we will get know each transformation and we will make clear procedure of their solving and first of all their advantages and disadvantages in view of accuracy of frequention`s mark in time.
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Classification of microsleep by means of analysis EEG signal
Ronzhina, Marina ; Smital, Lukáš (referee) ; Čmiel, Vratislav (advisor)
This master thesis deals with detection of microsleep on the basis of the changes in power spectrum of EEG signal. The results of time-frequency analysis are input values for the classifikation. Proposed classification method uses fuzzy logic. Four classifiers were designed, which are based on a fuzzy inference systems, that are differ in rule base. The results of fuzzy clustering are used for the design of rule premises membership functions. The two classifiers microsleep detection use only alpha band of the EEG signal’s spectrogram then allows the detection of the relaxation state of a person. Unlike to first and second classifiers, the third classifier is supplemented with rules for the delta band, which makes it possible to distinguish the 3 states: vigilance, relaxation and somnolence. The fourth classifier inference system includes the rules for the whole spectrum band. The method was implemented by computer. The program with a graphical user interface was created.
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Identification of the parameters of an electroencephalographic recording system
Svozilová, Veronika ; Sekora, Jiří (referee) ; Mézl, Martin (advisor)
Elektroencefalografický záznamový systém slouží k vyšetření mozkové aktivity. Na základě tohoto vyšetření lze stanovit diagnózu některých nemocí, například epilepsie. Účelem této práce bylo zpracování signálu z toho systému a vytvoření modelového signálu, který bude s reálným signálem porovnán. Uměle vytvořený signál vychází z Jansenova matematického modelu, který byl dále implementován v prostředí MATLAB a rozšířen ze základního modelu na komplexnější zahrnující nelinearity a model rozhraní elektroda – elektrolyt. Dále bylo provedeno měření signálů na EEG fantomu a následná identifikace parametrů naměřených signálu. V první fázi byly testovány jednoduché signály. Identifikace parametrů těchto signálů sloužila k validaci daného EEG fantomu. V druhé fázi bylo přistoupeno k testování EEG signálů navržených podle matematického Jansenova modelu. Analýza veškerých signálů zahrnuje mimo jiné časově frekvenční analýzu či ověření platnosti principu superpozice.
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Analysis of stabilometric signals in frequency domain
Netopil, Ondřej ; Hejč, Jakub (referee) ; Kozumplík, Jiří (advisor)
This work deals with the metods frequency and time frequency analysis of stabilometric signal. In the introroduction is described theory about posturography and posturographic measurment. The work contains describtion of stabilometric parametrs in time domain (1D and 2D parametrs) and in frequency domain. The aim is create review of basic metods used to processing and preprocessing of stabilometric signals and comparing this methods . In work is realized ferquency analysis used Frourier transfrmation and Burg method and time-frequency analysis used Short time Frourier transformation and Wavelet transformation. One part of program is aimed on comparison of this methods.
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