SuperTrial: Super Trial

In LauraMasiero/RiemannR: RiemannR - EEG-based BCI analysis with Riemannian geometry

Description

This function creates a super trial (Barachant and Congedo, 2014) to use in ERP signal analysis for BCI.

Usage

SuperTrial(list, n=16, length_epochs=129, tidy=F, col=17)

Arguments

list	a list of matrices with a specific construction. See Details below.
n	number of channels used to record the EEG signal.
length_epochs	number of time points of the registered signal (its length).
tidy	option to remove specific channels. If tidy=TRUE no channels will be removed to construct the Super trial, if tidy=FALSE then the columns of the channels to be removed have to be specified with the option col.
col	columns to be removed (when tidy=FALSE).

Details

The initial list must have a specific construction: every list element has to be a list itself with two main elements, $epochs and $labels. $epochs contains tensors with dimensions [n,c,t], where n are the number of epochs, c are the number of channels and t is the recording (epoch) length. $labels contains the class of the epochs considered (i.e. target or non target).

Value

It returns a list:

mean_epoch	a matrix that is the signal mean of every channel considered.
super_trial	a list with the super trials constructed from the initial list.

Author(s)

Laura Masiero, email: [e-mail]

References

Barachant, Alexandre e Marco Congedo (2014). “A Plug&Play P300 BCI Using Information Geometry”. url: http://arxiv.org/abs/1409.0107.

LauraMasiero/RiemannR documentation built on Sept. 29, 2020, 9:51 p.m.