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Microstates analysis in EEG data of sleep-deprived subjects
Křápková, Monika ; Koudelka, Vlastimil (referee) ; Lamoš, Martin (advisor)
This bachelor’s thesis deals with the processing and analysis of EEG data in sleep deprived subjects. In the theoretical part, the electroencephalography method is presented first. Further, there are possibilities of preprocessing and analysis of EEG data, introduction to statistics, and the last one is a research on the influence of sleep deprivation on human electrophysiology. The practical part consists of the preprocessing of EEG data, EEG microstates analysis and statistical evaluation of the results from the study of sleep deprivation. Finally, the results of this part are discussed in a separate chapter.
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Analysis of EEG signal using principal component analysis (PCA)
Walczysko, Martin ; Vítek, Martin (referee) ; Rychtárik, Milan (advisor)
In the beginning of the bachelor’s thesis is dealt with the measurement of EEG signals in the laboratory of Department of Biomedical Engineering at FEEC BRNO and following processing in programming environment Matlab. The aim of the thesis tries to demonstrate the analysis of EEG dates using the principal components analysis. There are shown the using possibilities for reducing the dimension of input’s dates. It is considered the lay-out of electrodes, the duration of recording or existing artifact. There is also conducted a study of highlighting the abnormalities contained in EEG in order to easier detection. In the end are outlined the possibilities of using the ICA for analysis of EEG and eventually for removing unwanted artifacts.
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Microstates analysis in EEG data of sleep-deprived subjects
Křápková, Monika ; Koudelka, Vlastimil (referee) ; Lamoš, Martin (advisor)
This bachelor’s thesis deals with the processing and analysis of EEG data in sleep deprived subjects. In the theoretical part, the electroencephalography method is presented first. Further, there are possibilities of preprocessing and analysis of EEG data, introduction to statistics, and the last one is a research on the influence of sleep deprivation on human electrophysiology. The practical part consists of the preprocessing of EEG data, EEG microstates analysis and statistical evaluation of the results from the study of sleep deprivation. Finally, the results of this part are discussed in a separate chapter.
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|
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Analysis of EEG signal using principal component analysis (PCA)
Walczysko, Martin ; Vítek, Martin (referee) ; Rychtárik, Milan (advisor)
In the beginning of the bachelor’s thesis is dealt with the measurement of EEG signals in the laboratory of Department of Biomedical Engineering at FEEC BRNO and following processing in programming environment Matlab. The aim of the thesis tries to demonstrate the analysis of EEG dates using the principal components analysis. There are shown the using possibilities for reducing the dimension of input’s dates. It is considered the lay-out of electrodes, the duration of recording or existing artifact. There is also conducted a study of highlighting the abnormalities contained in EEG in order to easier detection. In the end are outlined the possibilities of using the ICA for analysis of EEG and eventually for removing unwanted artifacts.
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