Summary
- Plugin name : EOG Denoising
- Version : 023
- Author : Joao-Pedro Berti-Ligabo
- Company : Inria
- Short description : EOG Denoising using Regression Analysis
- Documentation template generation date : Apr 11 2018
Description
Algorithm implementation as suggested in Schlogl's article of 2007
This box uses a denoising matrix 'b' calculated previously through the EOG_Denoising_Calibration for removing the EOG effects on EEG. The principle is based on regression analysis (see article 'A fully automated correction method of EOG artifacts in EEG recordings) where a matrix 'b' is estimated being:b = <'Nt N>-ยน<'N S> with N being the noise (EOG electrodes) and S the source (EEG electrodes). The signal output is the EEG_Corrected (free of EOG noise):O=S-b*N (EEG_Corrected = EEG - b*EOG)
Inputs
1. EEG
Make sure to select the same quantity of EEG channels as specified in your 'b' parameter matrix
- Type identifier : Signal (0x5ba36127, 0x195feae1)
2. EOG
Make sure to select the same quantity of EOG channels as specified in your 'b' parameter matrix
- Type identifier : Signal (0x5ba36127, 0x195feae1)
Outputs
1. EEG_Corrected
The output has the same structure as the EEG input
- Type identifier : Signal (0x5ba36127, 0x195feae1)
Settings
1. Filename b Matrix
Make sure to select the right file containing your 'b' matrix with the right coefficients
- Type identifier : Filename (0x330306dd, 0x74a95f98)
- Default value : [ b-Matrix-EEG.txt ]
Examples
You can apply these boxes in a set with a high density of blinking eyes and see the results before and after.
Miscellaneous
Generated on Tue Jun 26 2012 15:25:54 for Documentation by 1.7.4