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rawaa mejri vor etwa 10 Stunden
Kommentiert: Star Strider vor etwa 3 Stunden
Dear Matlab Community,
I am currently in the process of planning data organization for an ECG analysis using the PTB-XL dataset, and I would like to seek your advice and expertise on a specific question.
When it comes to data organization, is it recommended to use each lead separately (12 leads --> 12 columns)? Or would it be preferable to adopt an approach where each row represents a distinct ECG signal?
I would greatly appreciate insights and recommendations from those who have experience in this area.
Thank you very much for your valuable contribution.
Best regards,
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Star Strider vor etwa 7 Stunden
I am not certain what you want to do, or what question you are asking. In general, EKG data are analysed column-wise, with a time vector (generally beginning at zero with regular sampling intervals and a sampling frequency at least 256 Hz and 1 kHz if possible) for the first column, and each lead being successive columns, ordered characteristically as 
. This also is the way MATLAB data matrices in general are organised.
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rawaa mejri vor etwa 7 Stunden
Direkter Link zu diesem Kommentar
https://de.mathworks.com/matlabcentral/answers/2122541-data-organization-in-ecg-analysis-separate-leads-or-individual-signals#comment_3171671
Thank you for your response @Star Strider ,
To clarify, Do we use a single temporal vector for all (one column only), or do we create a temporal vector for each lead? For instance, for lead I, do we have a column called time_I (12 leads -> 12 temporal vectors)? Is that correct? Or do we have a single temporal vector (one column only) for all 12 leads (12 columns)?
Star Strider vor etwa 6 Stunden
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My pleasure!
I’m not sure what you mean by ‘temporal vector’. There is characteristically one time vector in the first column, and each corresponding EKG lead in columns 2-13 (2-14 if 
is included). All the leads are collected and recorded at the same times, those times given in the first-column time vector.
Collectting them serially is not appropriate, because natural variations in heart rate in a normal, healthy heart make the serial records ininterpretable when aggregated. They must all be collected and recorded at the same times.
rawaa mejri vor etwa 6 Stunden
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Thanks a lot for your help !
I understand! Just one last question: in the PTB-XL dataset, I have a .dat file and a .hea file. I suppose I should use the .hea file to extract the leads. Regarding the time vector, should I generate it based on the sampling frequency provided?
Star Strider vor etwa 6 Stunden
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In MATLAB Online öffnen
My pleasure!
I am not familiar with that dataset. If you do not already have a time vector provided with it, you can create one using the linspace function —
EKG = rand(10,12); % EKG Data
Fs = 256; % Sampling Frequency
Time = linspace(0, size(EKG,1)-1, size(EKG,1)).'/Fs; % Synthetic Time Vector
EKG_Matrix = [Time EKG]
EKG_Matrix = 10x13
0 0.4856 0.4760 0.7745 0.4151 0.9988 0.3865 0.1495 0.0096 0.3425 0.5348 0.8598 0.7829 0.0039 0.2463 0.4456 0.8281 0.5107 0.2525 0.9103 0.6471 0.9814 0.8694 0.4492 0.7721 0.6395 0.0078 0.0309 0.3216 0.8742 0.5227 0.1697 0.0887 0.3554 0.8075 0.9444 0.6633 0.4132 0.8197 0.0117 0.8595 0.4542 0.1945 0.4590 0.8822 0.3897 0.8010 0.4530 0.7423 0.4072 0.3338 0.5004 0.0156 0.6430 0.4124 0.0590 0.6767 0.2136 0.2213 0.6985 0.4550 0.9520 0.1370 0.3643 0.0842 0.0195 0.2821 0.6850 0.2601 0.8432 0.0871 0.4847 0.4177 0.0077 0.2032 0.9331 0.3941 0.1442 0.0234 0.8091 0.6667 0.7804 0.9966 0.2299 0.6895 0.8777 0.4294 0.6993 0.5283 0.4722 0.7945 0.0273 0.3704 0.8445 0.5042 0.5735 0.3571 0.5817 0.5753 0.2384 0.2834 0.7878 0.5440 0.5434 0.0312 0.7034 0.0919 0.8106 0.9310 0.7157 0.6494 0.4306 0.1360 0.6325 0.9629 0.2411 0.9952 0.0352 0.4809 0.0332 0.9774 0.0175 0.4227 0.0604 0.3911 0.7998 0.9508 0.4208 0.3304 0.4006
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figure
plot(EKG_Matrix(:,1), EKG_Matrix(:,2:end)+[1:size(EKG_Matrix,2)-1]*2)
grid
ylim('padded')
xlabel('Time')
legend(compose('Lead %s',["I","II","III","aV_R","aV_L","aV_F","V_1","V_2","V_3","V_4","V_5","V_6"]), 'Location','eastoutside')
.
rawaa mejri vor etwa 5 Stunden
Direkter Link zu diesem Kommentar
https://de.mathworks.com/matlabcentral/answers/2122541-data-organization-in-ecg-analysis-separate-leads-or-individual-signals#comment_3171741
Thank you again for your invaluable assistance. Following your recommendations, I have selected the first example and tried it out. Here are the signals; based on your experience, are they correct? Here are the data in the file .hea:
00001_lr 12 100 1000
00001_lr.dat 16 1000.0(0)/mV 16 0 -119 1508 0 I
00001_lr.dat 16 1000.0(0)/mV 16 0 -55 723 0 II
00001_lr.dat 16 1000.0(0)/mV 16 0 64 64758 0 III
00001_lr.dat 16 1000.0(0)/mV 16 0 86 64423 0 AVR
00001_lr.dat 16 1000.0(0)/mV 16 0 -91 1211 0 AVL
00001_lr.dat 16 1000.0(0)/mV 16 0 4 7 0 AVF
00001_lr.dat 16 1000.0(0)/mV 16 0 -69 63827 0 V1
00001_lr.dat 16 1000.0(0)/mV 16 0 -31 6999 0 V2
00001_lr.dat 16 1000.0(0)/mV 16 0 0 63759 0 V3
00001_lr.dat 16 1000.0(0)/mV 16 0 -26 61447 0 V4
00001_lr.dat 16 1000.0(0)/mV 16 0 -39 64979 0 V5
00001_lr.dat 16 1000.0(0)/mV 16 0 -79 832 0 V6
here the first rows of data :
rawaa mejri vor etwa 5 Stunden
Direkter Link zu diesem Kommentar
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here are the ecg signal , leads :
rawaa mejri vor etwa 5 Stunden
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@Star Strider Thanks a lot
Star Strider vor etwa 4 Stunden
Direkter Link zu diesem Kommentar
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In MATLAB Online öffnen
My pleasure!
That appears to be correct, and the timing appears to be approppriate (about 66 bpm).
The only change I would make is the order of the plots. The most common arrangement is something like this —
EKG = rand(100,12); % EKG Data
Fs = 256; % Sampling Frequency
Time = linspace(0, size(EKG,1)-1, size(EKG,1)).'/Fs; % Synthetic Time Vector
EKG_Matrix = [Time EKG];
Leads = ["I","II","III","aV_R","aV_L","aV_F","V_1","V_2","V_3","V_4","V_5","V_6"];
figure
tiledlayout(6,2)
for k = 1:6
nexttile(2*k-1)
plot(EKG_Matrix(:,1), EKG_Matrix(:,k+1))
grid
title(Leads(k))
end
for k = 1:6
nexttile(2*k)
plot(EKG_Matrix(:,1), EKG_Matrix(:,k+6))
grid
title(Leads(k+6))
end
Another common format —
figure
tiledlayout(3,4)
for k = 1:3
nexttile(4*k-3)
plot(EKG_Matrix(:,1), EKG_Matrix(:,k+1))
grid
title(Leads(k))
end
for k = 1:3
nexttile(4*k-2)
plot(EKG_Matrix(:,1), EKG_Matrix(:,k+4))
grid
title(Leads(k+3))
end
for k = 1:3
nexttile(4*k-1)
plot(EKG_Matrix(:,1), EKG_Matrix(:,k+7))
grid
title(Leads(k+6))
end
for k = 1:3
nexttile(4*k)
plot(EKG_Matrix(:,1), EKG_Matrix(:,k+10))
grid
title(Leads(k+9))
end
That would actually look corect if I had your data to plot.
.
rawaa mejri vor etwa 3 Stunden
Direkter Link zu diesem Kommentar
https://de.mathworks.com/matlabcentral/answers/2122541-data-organization-in-ecg-analysis-separate-leads-or-individual-signals#comment_3171831
Thanks a lot for your help !
Star Strider vor etwa 3 Stunden
Direkter Link zu diesem Kommentar
https://de.mathworks.com/matlabcentral/answers/2122541-data-organization-in-ecg-analysis-separate-leads-or-individual-signals#comment_3171836
My pleasure!
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Siehe auch
Tags
- signal processing
- ptb-xl dataset
- data organization
- ecg
- leads
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