📄 testnoisegenerator.m
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%
% Test program for colored noise generation.
%
% Dependencies: The baseline wander toolbox of the Open Source ECG Toolbox
%
% Open Source ECG Toolbox, version 1.0, November 2006
% Released under the GNU General Public License
% Copyright (C) 2006 Reza Sameni
% Sharif University of Technology, Tehran, Iran -- LIS-INPG, Grenoble, France
% reza.sameni@gmail.com
% This program is free software; you can redistribute it and/or modify it
% under the terms of the GNU General Public License as published by the
% Free Software Foundation; either version 2 of the License, or (at your
% option) any later version.
% This program is distributed in the hope that it will be useful, but
% WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General
% Public License for more details. You should have received a copy of the
% GNU General Public License along with this program; if not, write to the
% Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston,
% MA 02110-1301, USA.
clc
clear all
close all;
% load('SampleECG1.mat');
load('SampleECG2.mat'); data = data(1:15000,6)';
fs = 1000;
N = length(data);
% baseline wander removal
bsline = LPFilter(data,.7/fs); % baseline wander removal (may be replaced by other approaches)
%bsline = BaseLineKF(data,.5/fs); % baseline wander removal (may be replaced by other approaches)
data = data-bsline;
t = [0:N-1]/fs;
% noise variance calculation
SNR = 5;
SignalPower = mean(data.^2);
NoisePower = SignalPower / 10^(SNR/10);
noisetype = 5;
beta = 1.5; % noise color (for noisetype = 1)
w_bw = 1; % weight of baseline wander noise in the generated noise (for noisetype = 5)
w_em = 1; % weight of electrode movement noise in the generated noise (for noisetype = 5)
w_ma = 1; % weight of muscle artifact noise in the generated noise (for noisetype = 5)
switch noisetype
case 0 % white noise
noise = sqrt(NoisePower)*randn(size(data));
case 1 % colored noise
noise = ColoredNoise(sqrt(NoisePower),N,fs,beta);
case 2 % real muscle artifacts
load('MA.mat');artifact = MA(:,2);
artifact = resample(artifact,fs,360);
artifact = artifact(1:N)';
noise = sqrt(NoisePower)*(artifact - mean(artifact))/std(artifact,1);
case 3 % real electrode movements
load('EM.mat');artifact = EM(:,3);
artifact = resample(artifact,fs,360);
artifact = artifact(1:N)';
noise = sqrt(NoisePower)*(artifact - mean(artifact))/std(artifact,1);
case 4 % real baseline wander
load('BW.mat');artifact = BW(:,3);
artifact = resample(artifact,fs,360);
artifact = artifact(1:N)';
noise = sqrt(NoisePower)*(artifact - mean(artifact))/std(artifact,1);
case 5 % mixture of real baseline wander, electrode movements, muscle artifacts
load('BW.mat'); bw = BW(:,3); bw = (bw-mean(bw))/std(bw);
load('EM.mat'); em = EM(:,3); em = (em-mean(em))/std(em);
load('MA.mat'); ma = MA(:,3); ma = (ma-mean(ma))/std(ma);
artifact = (w_bw*bw + w_em*em + w_ma*ma)/(w_bw + w_em + w_ma);
artifact = resample(artifact,fs,360);
artifact = artifact(1:N)';
noise = sqrt(NoisePower)*(artifact - mean(artifact))/std(artifact,1);
end
x = data + noise;
figure;
plot(t,noise);
grid;
figure;
plot(t,x,'r');
hold on
plot(t,data,'b');
grid;
xlabel('time (sec.)');
legend('Noisy ECG','Original ECG');
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