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Classification of Motor Imagery Using Combination of Feature Extraction and Reduction Methods for Brain-Computer Interface
2019
Information Technology and Control
The motor imagery (MI) based brain-computer interface systems (BCIs) can help with new communication ways. A typical electroencephalography (EEG)-based BCI system consists of several components including signal acquisition, signal pre-processing, feature extraction and feature classification. This paper focuses on the feature extraction step and proposes to use a combination of different feature extraction and feature reduction methods. The research presented in the paper explores the methods
doi:10.5755/j01.itc.48.2.23091
fatcat:e4zzqljpmje6dfszbq3exsxerm