Classification of 4-class motor imagery EEG data with Common Sparse Spectral Spatial Pattern method

Brain computer interface aims to provide a communication system with external media via thoughts. For this purpose, brain signals are acquired from the scalp by EEG device and processed for characterization. In this work, the classification of movement imagery EEG data has been studied for left hand, right hand, foot and tongue movement imagination cases. common spatial patterns (CSP) method and temporal filters have been used in classification and common sparse spectral spatial patterns (CSSSP) method has been tried on 4-class motor imagery data in order to improve the accuracy for classification.