Eeg Ocular Artifact Removal through Armax Model System Identification Using Extended Least Squares

@inproceedings{Haas2003EegOA,
  title={Eeg Ocular Artifact Removal through Armax Model System Identification Using Extended Least Squares},
  author={Shane M. Haas and Mark G. Frei and Ivan Osorio and Bozenna Pasik-Duncan and Jeff Radel},
  year={2003}
}
The removal of ocular artifact from scalp electroencephalograms (EEGs) is of considerable importance for both the automated and visual analysis of underlying brainwave activity. Traditionally, subtraction techniques use linear regression to estimate the influence of eye movements on the electrodes of interest. These methods are based on the assumption that the underlying brainwave activity is uncorrelated when, in general, it is not. Furthermore, regression methods assume that the ocular… CONTINUE READING
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