Example #2 showing the basic usage of wICA algorithm

For details see TestExample1. Data provided by: Yaseen Gerhold

Author: Valeri A. Makarov

e-mail: vmakarov@mat.ucm.es

http://www.mat.ucm.es/~vmakarov/index.html

Oct. 2012

Contents

Reset environment

clear all
close all

Load and plot data

load('./Data/Test_Data_wICA.set', '-mat')
Fs = EEG.srate;
nChns = EEG.nbchan;
Data = floatread('./Data/Test_Data_wICA.fdt',[nChns,Inf]);
figure('color','w')
PlotEEG(Data, Fs, [], 150, 'raw EEG data')

ICA of EEG

[icaEEG, A, W] = fastica(Data,'stabilization','off','verbose','off');
figure('color','w');
PlotEEG(icaEEG, Fs, [], 12, 'Independent Components');
xlabel('Time (s)')

wICA algorithm

nICs = 1:size(icaEEG,1);
Kthr = 1.1;
ArtefThreshold = 7;
verbose = 'off';

icaEEG2 = RemoveStrongArtifacts(icaEEG, nICs, Kthr, ArtefThreshold, Fs, verbose);
figure('color','w');
PlotEEG(icaEEG2, Fs, [], 12, 'wavelet filtered ICs');

Data_wICA = A*icaEEG2;
figure('color','w');
PlotEEG(Data_wICA, Fs, [], 150, 'wICA cleanned EEG');