Remove EOG artefacts using linear regression — correct_eog

For each EEG channel, fits a multiple linear regression on all EOG reference channels and subtracts the fitted EOG component, leaving the residual as the cleaned signal. This removes both transient blink artefacts and slow ocular drift without requiring blink event detection.

Usage

correct_eog_regression(
  psg,
  eog_channels = NULL,
  eeg_channels = NULL,
  verbose = TRUE
)

Arguments

psg: An mrpheus_psg object from prepare_psg().
eog_channels: Character vector. EOG channel labels to use as regressors. If NULL (default), all channels of type "EOG" in psg$channel_map are used.
eeg_channels: Character vector. EEG channel labels to clean. If NULL (default), all non-bad "EEG" channels are used.
verbose: Logical. Print progress messages. Default TRUE.

Value

A new mrpheus_psg with cleaned EEG signals and re-segmented epochs. EOG and other channels are unchanged.

Details

This is the pure-R equivalent of MNE's compute_proj_eog() / SSP projection pipeline. Both approaches project out the subspace spanned by the EOG channels; regression does so directly on the continuous signal.

Examples

if (FALSE) { # \dontrun{
rec   <- read_edf("psg.edf")
psg   <- prepare_psg(rec) |> preprocess_psg()
clean <- correct_eog_regression(psg)
} # }