Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
378022 | Artificial Intelligence in Medicine | 2008 | 13 Pages |
Abstract
Compared to similar works on electroencephalogram-based (EEG-based) BCI datasets, in spite of being computationally simple, this new technique's performance is comparable to very complicated methods, like support vector machines. This research indicates that, using both spatial and temporal information content of EEG trials (from all electrodes or a subset of them), even under a non-complicated mathematical framework can yield an accurate and powerful classification.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Gholamreza Salimi-Khorshidi, Ali Motie Nasrabadi, Mohammadreza Hashemi Golpayegani,