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Filtering EEG signals
Pohludka, Aleš ; Ronzhina, Marina (referee) ; Potočňák, Tomáš (advisor)
This work describes basics of electroencephalography, measuring methods of electroencephalographic signals, their processing and especially their filtration. The most basic normalised international system for measuring EEG from the scalp is described. The end of theoretical part is dedicated to the most frequent artifacts. The practical part deals with testing two methods based on adaptive filtration of reference EOG signals using the LMS algorithm. Further in the paper are presented tests of before mentioned methods and their verification in practice on gathered signals from volunteers. At the conclusion there is an evaluation of the methods used.
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Brain wakefullness detection using frequency and time-frequency EEG signal analysis
Pohludka, Aleš ; Ronzhina, Marina (referee) ; Potočňák, Tomáš (advisor)
This work describes basics of electroencephalography, measuring methods of electroen- cephalographic signals, their processing and especially the interpretation of EEG signal in frequency and time-frequency domains for mental fatigue detection purposes. Mental fatigue, its sources, consequences and connection with sensory-cognitive system and link to memory is discussed. The most basic normalized international system for measuring EEG from the scalp as well as some of the experiments that ultimately lead to mental fatigue are described. With this knowledge in mind, an experiment was prepared for inducing such a state. Ten subjects participated in the test which was conducted in la- boratory with EEG machine GES 410MR by EGI. The data were analyzed mainly with S-transform and Hilbert-Huang transform. These two transforms represent two distinct state of the art time-frequency methods of spectral analysis. The result of this work lies in evaluating the relationship between mental fatigue, errors accumulated during the task and with time.
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Brain wakefullness detection using frequency and time-frequency EEG signal analysis
Pohludka, Aleš ; Ronzhina, Marina (referee) ; Potočňák, Tomáš (advisor)
This work describes basics of electroencephalography, measuring methods of electroen- cephalographic signals, their processing and especially the interpretation of EEG signal in frequency and time-frequency domains for mental fatigue detection purposes. Mental fatigue, its sources, consequences and connection with sensory-cognitive system and link to memory is discussed. The most basic normalized international system for measuring EEG from the scalp as well as some of the experiments that ultimately lead to mental fatigue are described. With this knowledge in mind, an experiment was prepared for inducing such a state. Ten subjects participated in the test which was conducted in la- boratory with EEG machine GES 410MR by EGI. The data were analyzed mainly with S-transform and Hilbert-Huang transform. These two transforms represent two distinct state of the art time-frequency methods of spectral analysis. The result of this work lies in evaluating the relationship between mental fatigue, errors accumulated during the task and with time.
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Filtering EEG signals
Pohludka, Aleš ; Ronzhina, Marina (referee) ; Potočňák, Tomáš (advisor)
This work describes basics of electroencephalography, measuring methods of electroencephalographic signals, their processing and especially their filtration. The most basic normalised international system for measuring EEG from the scalp is described. The end of theoretical part is dedicated to the most frequent artifacts. The practical part deals with testing two methods based on adaptive filtration of reference EOG signals using the LMS algorithm. Further in the paper are presented tests of before mentioned methods and their verification in practice on gathered signals from volunteers. At the conclusion there is an evaluation of the methods used.
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