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Feature Extraction and Selection for Emotions Detection from EEG Signals Using Python
Češková, Simona ; Hussain, Yasir (oponent) ; Jawed, Soyiba (vedoucí práce)
This work deals with the extraction and selection of features of EEG signals for emotion detection. Processing these signals included steps such as signal pre–processing, extraction of its features and subsequent selection of features. For verification of the correct implementation, the extraction and selection results were evaluated by a machine learning algorithm. This work works with the already measured DREAMER dataset.

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