Plotted ECG signals are not around Amplitude 0 line

Question

For my project I have to have few datasets of ECG signals and I did get them from Physionet website.

What I Got

So I downloaded few ECG signals and plotted them in Matlab. Below shows one plot (I lead) I got.

As you can see, this signal is not in the Amplitude 0 line. But all the ECG recordings I have seen and saw in research papers are horizontal. Like in below image.

My Question

I'm new to ECG signal processing. So I'm curious to know,

1)Whether datasets having this kind of abnormal behavior of ECG are wrong?

2)Is there any Matlab function which can convert such data to view like in 2nd image I attached?

UPDATE

To download the dataset,

https://www.physionet.org/cgi-bin/atm/ATM

Go to the above link and select "PTB Diagnosed ECG database" as the Database and select a patient record (E.g: s0010_re).

Answer 1

I have tried the BEADS technique we have developed for the separation of

• sparse signals, possibly positive, with sparse derivatives,
• a trend (low frequency),
• random noise.

I have played with one signal for about two minutes, and here is one outcome:

It is called BEADS, for "Baseline Estimation And Denoising with Sparsity". The Matlab BEADS code is at MatlabCentral, the paper is Chromatogram baseline estimation and denoising using sparsity (BEADS). It was initially meant for chromatographic signals, but is also used for EEG/ECG and several other spectral signal, see the BEADS page .

One nice feature is that you directly see the noise (and how uncorrelated it can be) and the shape of the trend, then tweak the parameters. Mine (probably not optimal) are:

addpath('C:\Users\duvall\Documents\MATLAB\toolbox\2014_BEADS_Baseline\');
% load('s0010_rem.mat')
 data = val(1,:)';
% Filter parameters
fc = 0.004;     % fc : cut-off frequency (cycles/sample)
d = 1;          % d : filter order parameter (d = 1 or 2)
% Positivity bias (peaks are mostly symmetric)
r = 1;          % r : asymmetry parameter
% Regularization parameters
amp = 0.8;
lam0 = 0.5*amp;
lam1 = 5*amp;
lam2 = 4*amp;

[x1, f1, cost] = beads(data, d, fc, r, lam0, lam1, lam2);
figure(2);
subplot(4,1,1)
h=plot([data]);axis tight;grid on;set(h,'LineWidth',2);
subplot(4,1,2)
h=plot([x1]);axis tight;grid on;set(h,'LineWidth',2);
subplot(4,1,3)
h=plot([f1]);axis tight;grid on;set(h,'LineWidth',2);
subplot(4,1,4)
h=plot([data-x1-f1]);axis tight;grid on;set(h,'LineWidth',2);

Basically, it took me 10-times more to download and load the signal than to tune the parameters (90 seconds approximately), but I know the code :)

Answer 2

Adding to the comments: As people have already said, this is a phenomenom called baseline drift and can be handled in different ways depending on how your signal looks.

For sinusoidal signals where the frequency spectrum is known to you, it is possible to just apply bandpassfilters to remove the unwanted drift.

For your example I would probably just subtract the envelope (generated from the peaks) of the signal. This works for nonlinear shifts as well. Attached bellow is a matlab example to illustrate the technique. TAKE NOTICE: I selected a bad example intentionally, to highlight a limitation in getting perfect signal structure back between RR-intervals.

load('nonuniformdata.mat','ecgsig','t2')

[yupper,ylower] = envelope(ecgsig,700,'peak'); %% use the findpeak function to find suitable peak distance

figure; plot(t2,ecgsig)
hold on; plot(t2,ylower,'Linewidth',2)
hold on; plot(t2,yupper,'Linewidth',2)
title('ECG signal with non linear baseline variation')
xlabel('time [s]')
ylabel('Amplitude [A.U]')

figure; plot(t2,ecgsig-ylower)

figure; plot(t2,ecgsig-yupper)
title('ECG signal with upper envelope subtracted')
xlabel('time [s]')
ylabel('Amplitude [A.U]')