Since nobody wants to reply, you can at least redirect me to some material that can clarify the concepts related to the Wavelet transorm and how to use it to correct the baseline
ECG signal baseline drift correction
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I'm at the start of learning signal processing.
I'm trying to denoising this ECG signal using Wavelet Trasform to correct the baseline drift. This is my attempt, but I am very doubtful about it. I do not know if my attempt is correct or not (the signal does not seems so). I need an advice from someone more experienced than me, so in this way I can understand better and improve my work.
%--Load Real signal--%
load ('100m.mat');
RealECG = val/200;
Fs = 360; % Hz
L = length(RealECG); % Signal Length
TimeInterval = 10; % sec
T = linspace(0,TimeInterval,L); % time axis
%--Plot--%
figure (1); plot(T, RealECG); grid on;
title('ECG Signal'); xlabel('time (sec)'); ylabel('voltage (mV)');
%% Correction of the wandering baseline of the ecg signal
wv = 'db9';
[c,l] = wavedec(RealECG,8,wv);
nc = wthcoef('a',c,l);
rec = waverec(nc,l,wv);
figure(2); plot(T,rec); grid on;
title('WT Baseline Correction');
xlabel('time (sec)'); ylabel('voltage (mV)');
Answers (1)
Mathieu NOE
on 7 Jun 2022
hello
a simple high pass filter suffices
%--Load Real signal--%
load ('100m.mat');
RealECG = val/200;
Fs = 360; % Hz
L = length(RealECG); % Signal Length
TimeInterval = 10; % sec
T = linspace(0,TimeInterval,L); % time axis
%--Plot--%
figure (1); plot(T, RealECG); grid on;
title('ECG Signal'); xlabel('time (sec)'); ylabel('voltage (mV)');
%% Correction of the wandering baseline of the ecg signal
% wv = 'db9';
% [c,l] = wavedec(RealECG,8,wv);
% nc = wthcoef('a',c,l);
% rec = waverec(nc,l,wv);
% some high pass filtering % baseline correction
N = 2;
fc = 1; % Hz
[B,A] = butter(N,2*fc/Fs,'high');
rec = filtfilt(B,A,RealECG);
figure(2); plot(T,rec); grid on;
title('WT Baseline Correction');
xlabel('time (sec)'); ylabel('voltage (mV)');
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