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Automatická klasifikace spánkových fází z polysomnografických dat / Automatic sleep scoring using polysomnographic data

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.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:316853
Date January 2017
CreatorsKříženecká, Tereza
ContributorsPotočňák, Tomáš, Ronzhina, Marina
PublisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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