AI-based classification of single-trial EEG data
This paper studies the potential of six artificial intelligence (AI)-based approaches for classification of non-averaged EEG data that is on important issue for the building of a brain-computer interface (BCI). The effectiveness of the methods in terms of classification accuracy, stability and speed is reported.