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Automatic detection of graphoelements in sleep EEG
Balcarová, Anežka ; Ronzhina, Marina (referee) ; Kozumplík, Jiří (advisor)
This project is aimed at sleeping EEG signal, especially at searching of sleeping graphoelements and next at processing signal, witch this segmentation go before. Charakterization of sleeping graphoelements and problems with their classification are outlined here. Principle of two detection methods of k-komplex are explained and processed by Matlab with graphically representation of results. Results of automatic classification are compared with scoring of two experts.
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The adaptive EEG segmentation
Balcarová, Anežka ; Kozumplík, Jiří (referee) ; Kubicová, Vladimíra (advisor)
This project is aimed at EEG signal, especially at segmentation of signal and next at processing signal, witch this segmentation go before. Problem with signals stacionarity and stress importance of adaptive segmentation are outlined here. Principle of basic methods of adaptive segmentation are explained and two of them are processed by Matlab to segmentation channel. Parameters (limiting value and window length) influence segmentation. The limiting value is assessed with help of white noise.
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The adaptive EEG segmentation
Balcarová, Anežka ; Kozumplík, Jiří (referee) ; Kubicová, Vladimíra (advisor)
This project is aimed at EEG signal, especially at segmentation of signal and next at processing signal, witch this segmentation go before. Problem with signals stacionarity and stress importance of adaptive segmentation are outlined here. Principle of basic methods of adaptive segmentation are explained and two of them are processed by Matlab to segmentation channel. Parameters (limiting value and window length) influence segmentation. The limiting value is assessed with help of white noise.
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Automatic detection of graphoelements in sleep EEG
Balcarová, Anežka ; Ronzhina, Marina (referee) ; Kozumplík, Jiří (advisor)
This project is aimed at sleeping EEG signal, especially at searching of sleeping graphoelements and next at processing signal, witch this segmentation go before. Charakterization of sleeping graphoelements and problems with their classification are outlined here. Principle of two detection methods of k-komplex are explained and processed by Matlab with graphically representation of results. Results of automatic classification are compared with scoring of two experts.
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