Ex01_testPCA.m

% Principal component analysis
%
% BMI500 Course
% Lecture:  An Introduction to Blind Source Separation and Independent Component Analysis
%           By: R. Sameni
%           Department of Biomedical Informatics, Emory University, Atlanta, GA, USA
%           Fall 2020
%
% Dependency: The open-source electrophysiological toolbox (OSET):
%       https://github.com/alphanumericslab/OSET.git
%   OR
%       https://gitlab.com/rsameni/OSET.git
%

clc
clear
close all

example = 1;
switch example
    case 1 % Load a sample EEG signal
        load EEGdata textdata data % A sample EEG from the OSET package
        fs = 250;
        x = data'; % make the data in (channels x samples) format
        % Check the channel names
        disp(textdata)
    case 2 % Load a sample ECG signal
        load SampleECG2 data % A sample ECG from the OSET package
        fs = 1000;
        x = data(:, 2:end)'; % make the data in (channels x samples) format
        x = x - LPFilter(x, 1.0/fs); % remove the lowpass baseline
    otherwise
        error('unknown example');
end

N = size(x, 1); % The number of channels
T = size(x, 2); % The number of samples per channel