Investigation of the Effects of Statistically Significant Features on the Classification of EEG-Based Motor Imagery Tasks

Murside Degirmenci

Motor imagery (MI) task classification is highly prevalent in Electroencephalography (EEG)-based Brain-Computer Interface (BCI) research area. Extremity movement task classification and finger movement classification studies are presented in this thesis. In extremity movement classification, binary-class (right hand and left hand) and multi-class (right hand, left hand, right hand, and left hand) classifications are performed using 4 different feature extraction approaches and statistically significance-based feature selection (the independent t-test, one-way ANOVA test). Firstly, time- ...Daha fazlası

Doktora Tezi 2024 Yalçın İşler İzmir Katip Çelebi Üniversitesi Fen Bilimleri Enstitüsü 4 Görüntülenme Ambargo Kalkış : 19.07.2024