ar_eogreg: Remove EOG using regression

In neuroconductor/eegUtils: Utilities for Electroencephalographic (EEG) Analysis

Remove EOG using regression

Description

Calculates and removes the contribution of eye movements to the EEG signal using least-squares regression. Specifically, it generate regression weights based on EOG channels that are used to estimate how much activity eye movements are responsible for across all channels.

Usage

ar_eogreg(data, heog, veog, bipolarize = TRUE)

## S3 method for class 'eeg_data'
ar_eogreg(data, heog, veog, bipolarize = TRUE)

## S3 method for class 'eeg_epochs'
ar_eogreg(data, heog, veog, bipolarize = TRUE)

Arguments

data	Data to regress - eeg_data or eeg_epochs
heog	Horizontal EOG channel labels
veog	Vertical EOG channel labels
bipolarize	Bipolarize the EOG channels. Only works when four channels are supplied (2 HEOG and 2 VEOG).

Value

An eeg_data or eeg_epochs object with corrections applied.

Author(s)

Matt Craddock, [e-mail]

neuroconductor/eegUtils documentation built on Feb. 3, 2023, 5:33 p.m.