how can I get cardioid graph from ecg QRS complex?

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Neal 2016-10-5

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评论： Star Strider 2016-12-11

采纳的回答： Star Strider

HI, CAN ANYONE SHOW ME HOW SHOULD I GET CARDIOD GRAPH FROM QRS COMPLEX?

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Answer 1

Star Strider 2016-10-5

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The plot you want is called a vectorcardiogram. You need an EKG record that is noise-free and has baseline offset and baseline variation removed. Use Lead I and Lead aVF records to plot it. See Detecting QRS complex in ECG signal for details. My ‘EKG_Explore.m’ function (attached to my initial Answer) should provide you with guidance on how to program it.

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Star Strider 2016-11-9

在 MATLAB Online 中打开

That EKG demonstrates atrial fibrillation with multifocal junctional and ventricular PVCs. There are no normal P-QRS-T complexes that I can identify. Please see if you can find a normal sinus rhythm 6- or 12-lead EKG.

The code I used to filter and display Lead I is:

D = load('sourav I18m.mat');
EKG = D.val;
Fs = 256;                                                           % Sampling Frequency (Guess)
Fn = Fs/2;                                                          % Nyquist Frequency
Ts = 1/Fs;                                                          % Sampling Interval
t = linspace(0, 1, size(EKG,2))*Ts;                                 % Time Vector
Wp = [2  40]/Fn;                                                    % Passband
Ws = [1  50]/Fn;                                                    % Stopband
Rp =  5;                                                            % Passband Ripple
Rs = 20;                                                            % Stopband Ripple
[n,Wn] = buttord(Wp,Ws,Rp,Rs);                                      % Butterworth Filter Order
[b,a] = butter(n,Wn);                                               % Butterworth Filter Transfer Function Coefficients
[SOS,G] = tf2sos(b,a);                                              % Convert to Second-Order-Section For Stability
figure(1)
freqz(SOS, 4096, Fs)                                                % Assess Filter
EKGf = filtfilt(SOS,G,EKG')';                                       % Filter EKGs
figure(2)
plot(t, EKGf(1,:))
grid
axis([[0  0.001]+0.0025    ylim])

Star Strider 2016-11-10

在 MATLAB Online 中打开

EKG_0319214B-1559-4B14-8252-6659E91A480Dm.mat

Unfortunately, no. To plot a complete vectorcardiogram, you have to have at least one normal identifiable P-QRS-T complex. I searched the database and managed to find a normal EKG record (attached). It reads, filters, and plots the scalar and vector EKG.

The Code â€”

D = load('EKG_0319214B-1559-4B14-8252-6659E91A480Dm.mat');
EKG = D.val;
Fs = 1000;                                                          % Sampling Frequency (Guess)
Fn = Fs/2;                                                          % Nyquist Frequency
Ts = 1/Fs;                                                          % Sampling Interval
t = linspace(0, 1, size(EKG,2))*Ts;                                 % Time Vector
Wp = [2  40]/Fn;                                                    % Passband
Ws = [1  60]/Fn;                                                    % Stopband
Rp =  5;                                                            % Passband Ripple
Rs = 20;                                                            % Stopband Ripple
[n,Wn] = buttord(Wp,Ws,Rp,Rs);                                      % Butterworth Filter Order
[b,a] = butter(n,Wn);                                               % Butterworth Filter Transfer Function Coefficients
[SOS,G] = tf2sos(b,a);                                              % Convert to Second-Order-Section For Stability
figure(1)
freqz(SOS, 4096, Fs)                                                % Assess Filter
EKGf = filtfilt(SOS,G,EKG')';                                       % Filter EKGs
figure(2)
for k1 = 1:size(EKGf,1)                                             % Plot All Records
    subplot(size(EKGf,1), 1, k1)
    plot(t, EKGf(k1,:))
    grid
    axis([[0  2E-4]+0.0    ylim])
end
idx0 = find(t <= 0.40E-4, 1, 'last');                               % Define Segments By Index
idx1 = find(t <= 0.55E-4, 1, 'last');
idx2 = find(t <= 0.70E-4, 1, 'last');
idx3 = find(t <= 1.20E-4, 1, 'last');
figure(3)                                                           % Plot Loops
plot(EKGf(2,idx0:idx1), EKGf(7,idx0:idx1))
hold on
plot(EKGf(2,idx1:idx2), EKGf(7,idx1:idx2))
plot(EKGf(2,idx2:idx3), EKGf(7,idx2:idx3))
hold off
axis equal
legend('P', 'QRS', 'T', 'Location','NE')
title('Frontal Vectorcardiogram - Segment Loops')
u = -gradient(EKGf(2,:));
v = -gradient(EKGf(7,:));
figure(4)                                                           % Plot Direction Vectors
quiver(EKGf(2,idx0:idx1), EKGf(7,idx0:idx1), u(idx0:idx1), v(idx0:idx1))
hold on
quiver(EKGf(2,idx1:idx2), EKGf(7,idx1:idx2), u(idx1:idx2), v(idx1:idx2))
quiver(EKGf(2,idx2:idx3), EKGf(7,idx2:idx3), u(idx2:idx3), v(idx2:idx3))
hold off
axis equal
legend('P', 'QRS', 'T', 'Location','NE')
title('Frontal Vectorcardiogram - Direction of Action Propagation')

-----------------------------------------------------------

figure(4) â€”

Star Strider 2016-11-17

First, a bit about electrocardiography and the cardiac excitation cycle. Briefly, it begins with the sinoatrial node initiating the P-wave (atrial depolarization) that then goes to the Bundle of His before it is transmitted to ventricles to create the QRS complex (ventricular depolarization), then the ventricular myocardium re-polarizes, creating the T-wave.

I visually identified the three segments (P, QRS, T) in one complete cycle by time, and then used the find command to determine the indices (in idx0 through idx3) corresponding to those times. I used Lead I and Lead aVF to create the plot, row 2 of the EKG record being Lead I and row 7 being Lead aVF. I then just plotted the segments from those two leads against each other for each segment to create the three loops, since those two leads are perpendicular to each other in the frontal plane. (I could have plotted the entire cycle as one plot but chose to break it up into the three segments plotted in different colours for clarity.) I used the hold function to plot all three segments on the same axes. Using the axes equal function guaranteed that the units in the x-direction are the same as the units in the y-direction to avoid distortion in the plot. See the documentation on legend and title for descriptions of those functions.

In figure(4), I plotted the vectors as the direction of propagation of each part of the cycle, using the gradient function to create the direction vectors. (The arrows in the P and T waves are visible, but you have to zoom in to see them.) Note that the right ventricle depolarizes first, this is due to its having less muscle mass than the left ventricle. The two ventricles contract almost simultaneously as the result.

Note that this is a healthy heart from an antiarrhythmic drug trial. The EKG has a normal configuration and normal intervals.

Star Strider 2016-11-19

在 MATLAB Online 中打开

That is a distinctly abnormal EKG, and exhibits a left anterior fascicular block pattern. Without the time vector it’s not possible to determine the width of the QRS complex, but it demonstrates the characteristic notch R-wave in Lead V1, and the notched S-wave in Lead V6.

First, you need to see the accompanying ‘.info’ file to determine the sampling frequency and amplification scaling. Without those, you can go no further.

Second, you need to use the bandpass filter I designed to eliminate the baseline drift.

Third, it’s clean enough so that you can then use the findpeaks function to locate the P, R, and T waves. You will need to experiment with the name-value pairs in the findpeaks function, along with using thresholds and the set function setdiff and possibly others to correctly isolate the various components of the cardiac electrophysiologic cycle.

I wrote this code to display the unfiltered and unscaled EKG. When you filter it and scale it, you will have to change the axis x-axis limits in figure(1):

D = load('Neal ptb.mat');
EKG = D.val;
[EKGr,EKGc] = size(EKG);
Leads = {'I','II','III','aV_R','aV_L','aV_F','V_1','V_2','V_3','V_4','V_5','V_6'};
q2 = [];
figure(1)
k3 = 1;
for k1 = 0 : 2
    for k2 = [1 4 7 10]
        q2 = [q2 k1+k2];
        subplot(3, 4, k3)
        plot(EKG(k1+k2,:))
        grid
        axis([0  2000    ylim])
        title(Leads{k1+k2})
        k3 = k3+1;
    end
end
windw = 100 : 700;
figure(2)
plot(EKG(1,windw), EKG(6,windw))
grid
axis equal
title('Frontal Plane Vectorcardiogram')
u = -gradient(EKG(1,windw));
v = -gradient(EKG(7,windw));
w = -gradient(EKG(6,windw));
windw = 100 : 700;
figure(3)
quiver3(EKG(1,windw), EKG(7,windw), EKG(6,windw), u, v, w)
grid on
axis equal
title('3D Vectorcardiogram')

Compare figure(2) here with the previous plot to see the effects of a left anterior fascicular block on the ventricular depolarisation sequence. Note in figure(3) that the right ventricle depolarises normally, then the depolarisation sequence shifts to the intact left posterior fascicle, with the anterior of the left ventricle depolarising later.

(This is something of a digression, but I really get off on this stuff!)

Neal 2016-12-11

Thanks for the information. can you tell me how the cardiod(loop) has plotted mathemetically. I want to know the mathematical expression to plot cardiod graph).

Star Strider 2016-12-11

My pleasure.

My code explains the plot clearly. There are three essentially orthogonal leads — I, aV_F, and V_2. The first two define the ‘+x’- and ‘-z’ directions in the frontal plane, and the third in the ‘+y’ direction, providing 3D reference coordinates. Plotting the first two create the 2D frontal vectorcardiogram loop, and adding the third creates it in 3D. All EKG leads have a common centre reference that is created within the EKG recording system electronics. The common zero origin of the plots is defined anatomically as the sinoatrial node, where the ‘pacemaker’ signal originiates. I refer you to John Webster’s textbook on biomedical instrumentation (there are likely others as well) for a thorough discussion.

As far as plotting it, that is simply plotting the EKG leads at corresponding time points. The activation sequence to plot the arrows in the quiver plots require the negative of the gradient simply because the way the vectors are defined in the quiver plots.

So the vectorcardiogram is not defined mathematically beyond the description I provided here. It is defined by the heart, and the way MATLAB plots the data. Mathematical simulations of the P-QRS-T complex are far beyond the scope of anything I want to get into here. The separation of the full activation and depolarisation sequence into its components I did visually. The mathematics of that is the subject of myriad publications. Considering that algorithms to do that have to recognise normal as well as abnormal rhythms and activation sequences makes this an extremely difficult problem. It is often difficult to do manually in extreme deviations from a normal, healthy heart.

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how can I get cardioid graph from ecg QRS complex?

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how can I get cardioid graph from ecg QRS complex?

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