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EEG Analysis During Anaesthesia
Hodulíková, Tereza ; Kolářová, Jana (referee) ; Sadovský, Petr (advisor)
This master's thesis deals with the method of functional examination of brain electric activity. In the first part is description of central nervous system, method of electroencephalography and possible connections. Furthermor the project involves characteristic of EEG signal and its artifacts. It also includes signal processing and list of symptoms, which will be used for an analysis of the EEG during anesthesia. The second part of thesis involves development of application, which allow viewing and proccesing of EEG signal. In conclusion of thesis is carried out unequal segmentation and statistical processing.
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Presentation of selected themes of BSIS in PPT-environment
Havlín, Radomil ; Šebesta, Vladimír (referee) ; Sigmund, Milan (advisor)
The bachelors thesis occupy by topics of the course BSIS, which can be presented by the multimedia and animation techniques in the presentation. In the introduction, these topics are given a different method of processing. In most cases, provides a modular solution by demonstration and argued spectrum signal. The chapters describe the operation with one, two signals at the time, the properties of Fourier transform with illustrative demonstration, the correlation with convolution, kvaziperiodické signals and the last chapter the spectrum of selective signals.
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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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Analysis of connections between simultaneous EEG and fMRI data
Labounek, René ; Kremláček,, Jan (referee) ; Lamoš, Martin (advisor)
Electroencephalography and functional magnetic resonance are two different methods for measuring of neural activity. EEG signals have excellent time resolution, fMRI scans capture records of brain activity in excellent spatial resolution. It is assumed that the joint analysis can take advantage of both methods simultaneously. Statistical Parametric Mapping (SPM8) is freely available software which serves to automatic analysis of fMRI data estimated with general linear model. It is not possible to estimate automatic EEG–fMRI analysis with it. Therefore software EEG Regressor Builder was created during master thesis. It preprocesses EEG signals into EEG regressors which are loaded with program SPM8 where joint EEG–fMRI analysis is estimated in general linear model. EEG regressors consist of vectors of temporal changes in absolute or relative power values of EEG signal in the specified frequency bands from selected electrodes due to periods of fMRI acquisition of individual images. The software is tested on the simultaneous EEG-fMRI data of a visual oddball experiment. EEG regressors are calculated for temporal changes in absolute and relative EEG power values in three frequency bands of interest ( 8-12Hz, 12-20Hz a 20-30Hz) from the occipital electrodes (O1, O2 and Oz). Three types of test analyzes is performed. Data from three individuals is examined in the first. Accuracy of results is evaluated due to the possibilities of setting of calculation method of regressor. Group analysis of data from twenty-two healthy patients is performed in the second. Group EEG regressors analysis is realized in the third through the correlation matrix due to the specified type of power and frequency band outside of the general linear model.
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Analysis of EEG signals
Bartošovský, Petr ; Dlouhý, Jiří (referee) ; Rozman, Jiří (advisor)
BARTOŠOVSKÝ, P. Analysis of EEG signals. Brno: Brno university of technology, Faculty of electrical engineering and communication, 2008. 35 p. Supervisor of bachelor’s thesis doc. Ing. Jiří Rozman, CSc. This thesis deals with EEG signal analysis and methods of their digital processing. So-called artifacts can distort data measured during brain activity. These data were basis for comparison of two methods: The Principal Component Analysis and The Independent Component Analysis for Artifact elimination. Both methods were compared and results evaluated.
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Sleep stage classification based on Hjorth descriptors of EEG signals
Kupková, Kristýna ; Ronzhina, Marina (referee) ; Kozumplík, Jiří (advisor)
This bachelor thesis is focused on the distinction between sleep stages from EEG signals. In its first part the classical method of visual classification of sleep stages is introduced, the second part introduces an automated method for sleep stage scoring. It is a method that uses the three parameters of Hjorth to create a vector space, in which, on the basis of similarity of formed shapes, different stages of sleep could be distinguished. Parameters of Hjorth are calculated from the whole EEG signal, and also from its bands. In the next section of this thesis a principle component analysis is performed. The principle components are placed into a vector space analogously with parameters of Hjorth and the character of formed objects is observed.
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Electrical Activity Brain Mapping
Dobeš, Petr ; Drahanský, Martin (referee) ; Kupková, Karolína (advisor)
Electrical activity of human brain is one of the most significant signals of biological origin. In order to understand and interpret electroencephalogram (EEG signal) correctly, it is often necessary to perform its visualization. This bachelor thesis deals with EEG signal and its visualization using topographic mapping. The work includes the basics of theory and processing of EEG signal. Moreover, this work consists of design proposal and implementation of an application for topographic mapping of EEG signal obtained using Emotiv Epoc Headset device. Visualization is performed in real time (at the time of measurement). Visualized quantities are amplitude and frequency domain with the possibility to select frequency bands. Implemented application represents an alternative to the procedure when EEG signal has to be recorded and stored in order to perform its visualization.
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Inverse values of EEG signal power in joint EEG-fMRI analysis
Sanetrníková, Dominika ; Kolář, Radim (referee) ; Labounek, René (advisor)
The first part of this thesis summarizes the basic theory of brain activity measurement using the BOLD signal and scalp EEG, the effect of noise phenomena in the data and its suppression, the merger of the fusion of the measured data using the general linear model and the current implementation of computational algorithms in the software library EEG Regressor Builder 1.0. Within the own solution of this thesis, the changes of the software library to version 1.1 were realized according to the requirements of the bachelor thesis. The hypothesis that temporal changes of the EEG relative band power (20 - 40Hz) has the same spatial correlates with the BOLD signal as the inverse power in the frequency range 0-12Hz. The hypothesis was rejected based on the calculation of similarity criterions between 3D activation maps for different parameter settings of the joint analysis calculations. As an appropriate criterions were chosen the correlation coefficient and the cosine criterion. The Euclidean distance was proved to be unfit. Also it was proved the inverse power value of EEG signal in the given frequency band brings to the common EEG-fMRI analysis an anti-correlated signal to the normal absolute power in the same frequency band. Furthermore the influence of regressors describing motion artifacts reduces the number of supra-thresholded voxels.
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Study of the influence of acoustic stimuli on man
Schwanzer, Miroslav ; Kolář, Radim (referee) ; Ronzhina, Marina (advisor)
The thesis deals with EEG signals, their description, methods of quantitative analysis and the processes in time-frequency domains, or power spectrums. The relationsheep between brain electrical activity and acustic stimuli (Mozart´s “Sonata K448”) was studied using EEG analysis in relation to sound impulses from replayed extracts of. The proposed experiment protocol included recording of EEG of volunteers. In order to visualize and analyze the data, the software with the graphic user interface was created, which enables topological mapping of brain activity and its vizualization in the time-frequency domain.
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Study of the influence of acoustic stimuli on man
Schwanzer, Miroslav ; Kolář, Radim (referee) ; Ronzhina, Marina (advisor)
The thesis deals with EEG signals, their description, methods of quantitative analysis and the processes in time-frequency domains, or power spectrums. The relationsheep between brain electrical activity and acustic stimuli (Mozart´s “Sonata K448”) was studied using EEG analysis in relation to sound impulses from replayed extracts of. The proposed experiment protocol included recording of EEG of volunteers. In order to visualize and analyze the data, the software with the graphic user interface was created, which enables topological mapping of brain activity and its vizualization in the time-frequency domain.
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