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Sleep EEG analysis
Kříženecká, Tereza ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
This thesis deals with the analysis of EEG during various sleep stages, which is done by calculating the selected parameters from the time and frequency domain. These parameters are calculated from individual segments of EEG signals that correspond with various sleep stages. Based on the analysis it decides which EEG parameters are appropriate for the automatic detection of the phases and which method is more suitable for evaluation of data in hypnogram. The programme MATLAB was used for the analysis and also for the comparison of chosen data.
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Automatic sleep scoring using polysomnographic data
Kříženecká, Tereza ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
The thesis is focused on automatic classification of polysomnographic signals based on various parameters in time and frequency domain. The parameters are acquired from 30 seconds long segments of EEG, EMG and EOG signals recorded during different sleep stages. The parameters used for automatic classification of sleep stages are selected according to statistical analysis. Classification is performed using the SVM method and evaluation of the success of the classification is done using sensitivity, specificity and percentage success. Classification method was implemented using Matlab.
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Automatic sleep scoring using polysomnographic data
Kříženecká, Tereza ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
The thesis is focused on automatic classification of polysomnographic signals based on various parameters in time and frequency domain. The parameters are acquired from 30 seconds long segments of EEG, EMG and EOG signals recorded during different sleep stages. The parameters used for automatic classification of sleep stages are selected according to statistical analysis. Classification is performed using the SVM method and evaluation of the success of the classification is done using sensitivity, specificity and percentage success. Classification method was implemented using Matlab.
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Sleep EEG analysis
Kříženecká, Tereza ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
This thesis deals with the analysis of EEG during various sleep stages, which is done by calculating the selected parameters from the time and frequency domain. These parameters are calculated from individual segments of EEG signals that correspond with various sleep stages. Based on the analysis it decides which EEG parameters are appropriate for the automatic detection of the phases and which method is more suitable for evaluation of data in hypnogram. The programme MATLAB was used for the analysis and also for the comparison of chosen data.
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