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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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Spatial-temporal analysis of HD-EEG data in pacients with nerodegenerative disease
Jordánek, Tomáš ; Kozumplík, Jiří (referee) ; Lamoš, Martin (advisor)
This master’s thesis deals with diagnostics of prodromal stage of Lewy body disease using microstate analysis. First part of the thesis includes theoretical background which is needed for understanding discussed topics and presented results. This part consists of description of the disease, diagnostic options, electroencephalography, pre-processing of the EEG record and the microstate analysis process. Theoretical background is followed by a practical part of the thesis. In the beginning, there is a chapter about a dataset, used EEG device, and own solution of the pre-processing. Microstate analysis is discussed next, its output parameters were compared between groups with statistical methods. Comparison of the subjects in prodromal stage of Lewy body disease and healthy controls brought significant differences in three parameters of microstates, in rate of unlabelled time frames and also for some counts of transitions between each map or unlabelled sections. Comparison of the subjects in prodromal stage of Lewy body disease and healthy controls brought significant differences in three parameters of microstates, in rate of unlabelled time frames and also for some counts of transitions between each map or unlabelled sections.
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Spatial-temporal analysis of HD-EEG data in pacients with nerodegenerative disease
Jordánek, Tomáš ; Kozumplík, Jiří (referee) ; Lamoš, Martin (advisor)
This master’s thesis deals with diagnostics of prodromal stage of Lewy body disease using microstate analysis. First part of the thesis includes theoretical background which is needed for understanding discussed topics and presented results. This part consists of description of the disease, diagnostic options, electroencephalography, pre-processing of the EEG record and the microstate analysis process. Theoretical background is followed by a practical part of the thesis. In the beginning, there is a chapter about a dataset, used EEG device, and own solution of the pre-processing. Microstate analysis is discussed next, its output parameters were compared between groups with statistical methods. Comparison of the subjects in prodromal stage of Lewy body disease and healthy controls brought significant differences in three parameters of microstates, in rate of unlabelled time frames and also for some counts of transitions between each map or unlabelled sections. Comparison of the subjects in prodromal stage of Lewy body disease and healthy controls brought significant differences in three parameters of microstates, in rate of unlabelled time frames and also for some counts of transitions between each map or unlabelled sections.
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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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