Discriminative ocular artifact correction for feature learning in EEG analysis
© 2016 IEEE. Electrooculogram (EOG) artifact contamination is a common critical issue in general electroencephalogram (EEG) studies as well as in brain-computer interface (BCI) research. It is especially challenging when dedicated EOG channels are unavailable or when there are very few EEG channels...
| Main Authors: | Li, X., Guan, Cuntai, Zhang, H., Ang, K. |
|---|---|
| Format: | Journal Article |
| Published: |
IEEE
2017
|
| Online Access: | http://hdl.handle.net/20.500.11937/72511 |
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