Classification of Motor Imagery in Electroencephalogram Signal Based on Spatio-temporal Feature selection Using Elastic Net, M.Sc. Thesis Sharif University of Technology ; Jahed, Mehran (Supervisor)
Abstract
Motor imagery causes Event related Synchronization/Desynchronization (ERS/ERD) in Electroencephalogram (EEG) signal. These potentials can be used as an input for a Brain Computer Interface (BCI) system. To do so, it is necessary for these inputs to be correctly classified. The quality of classification is severely affected by the features extracted. Common Spatial Patterns (CSP) algorithm is often used for this task. Some of this method disadvantages are neglecting non-stationary properties of EEG signal and its proneness to overfitting. Additionally, its success is highly dependent on the frequency band that the algorithm is performed in. The most suitable sub band is interchangeable...
Cataloging briefClassification of Motor Imagery in Electroencephalogram Signal Based on Spatio-temporal Feature selection Using Elastic Net, M.Sc. Thesis Sharif University of Technology ; Jahed, Mehran (Supervisor)
Abstract
Motor imagery causes Event related Synchronization/Desynchronization (ERS/ERD) in Electroencephalogram (EEG) signal. These potentials can be used as an input for a Brain Computer Interface (BCI) system. To do so, it is necessary for these inputs to be correctly classified. The quality of classification is severely affected by the features extracted. Common Spatial Patterns (CSP) algorithm is often used for this task. Some of this method disadvantages are neglecting non-stationary properties of EEG signal and its proneness to overfitting. Additionally, its success is highly dependent on the frequency band that the algorithm is performed in. The most suitable sub band is interchangeable...
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