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Polysomnographic data analysis
Jagošová, Petra ; Králík, Martin (referee) ; Ronzhina, Marina (advisor)
The bachelor´s thesis is focused on analysis of polysomnographic signals based on various parameters in time and frequency domain. The parameters are acquired from 30 seconds long segments of EEG, EOG and EMG signals recorded during different sleep stages. The parameters useful for automatic detection of sleep stages are selected according to both visual analysis of boxplots and statistical analysis via comparison tests. EOG parameters selected in the time domain were mobility, skewness and kurtosis. Among EEG parameters, aktivity, 75. percentile, kurtosis and mobility were selected. Among EMG parameters, 75. percentile and complexity were selected. Finally, the parameters selected in the frequency domain were relative power spectra in alpha, delta and beta bands.
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Sleep EEG analysis
Vávrová, Eva ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
The bachelor´s thesis is focused on analysis of sleep electroencephalograms based on extraction of chosen parameters in time and frequency domain. The parameters are acquired from segments of EEG signals coincident with sleep stages. The parameters used for automatic detection of sleep stages are selected according to statistical analysis. The program with a graphical user interface for selection, display and analysis EEG was created using Matlab.
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Polysomnographic data analysis
Jagošová, Petra ; Králík, Martin (referee) ; Ronzhina, Marina (advisor)
The bachelor´s thesis is focused on analysis of polysomnographic signals based on various parameters in time and frequency domain. The parameters are acquired from 30 seconds long segments of EEG, EOG and EMG signals recorded during different sleep stages. The parameters useful for automatic detection of sleep stages are selected according to both visual analysis of boxplots and statistical analysis via comparison tests. EOG parameters selected in the time domain were mobility, skewness and kurtosis. Among EEG parameters, aktivity, 75. percentile, kurtosis and mobility were selected. Among EMG parameters, 75. percentile and complexity were selected. Finally, the parameters selected in the frequency domain were relative power spectra in alpha, delta and beta bands.
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|
|
Sleep EEG analysis
Vávrová, Eva ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
The bachelor´s thesis is focused on analysis of sleep electroencephalograms based on extraction of chosen parameters in time and frequency domain. The parameters are acquired from segments of EEG signals coincident with sleep stages. The parameters used for automatic detection of sleep stages are selected according to statistical analysis. The program with a graphical user interface for selection, display and analysis EEG was created using Matlab.
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