MATLAB: How to do segmentation on ECG signal for feature extraction

ecgsegmentation

I have a 1-minute ECG signal. How do I segment it into 10s? The Fs is 250Hz

thank you in advanced!

Best Answer

Use the Signal Processing Toolbox buffer function.

Calculating ‘n’ is straightforward:

n = 10 * 250

producing:

n =
        2500

So 10 seconds of a signal sampled at 250 Hz is 2500 samples.

Related Solutions

MATLAB: How to find Q and S point in QRS complex of ECG signal

The first trace doesn’t have any S-waves, so don’t look for them. The EKG morphology is dependent on the lead placement and heart health. The second one is a very sick heart, with a left bundle-branch block pattern. It also has an RSR' pattern, so you have to be careful to not detect the first R-deflection.

My code:

q = load('Explorer 16265m');
EKG1 = q.val(1,:);
EKG2 = q.val(2,:);
Fs   = 128;
t    = [0:size(EKG1,2)-1]/Fs;
[R1,TR1]  = findpeaks( EKG1, t, 'MinPeakHeight',200);
[Q1,TQ1]  = findpeaks(-EKG1, t, 'MinPeakHeight',100);              % NOTE: No ‘S’ Waves In EKG1
[R2,TR2]   = findpeaks( EKG2, t, 'MinPeakHeight', 50);
[QS2,TQS2] = findpeaks(-EKG2, t, 'MinPeakHeight', 75);
figure(1)
subplot(2,1,1)
plot(t, EKG1)
hold on
plot(TR1, R1, '^r')
plot(TQ1, -Q1, 'vg')
hold off
grid
axis([0  2    ylim])
legend('EKG', 'R', 'Q')
subplot(2,1,2)
plot(t, EKG2)
hold on
plot(TR2, R2, '^r')
plot(TQS2(1:2:end), -QS2(1:2:end), 'vg')
plot(TQS2(2:2:end), -QS2(2:2:end), 'vb')
hold off
grid
axis([0  2    ylim])
legend('EKG', 'R', 'Q', 'S')

My plot:

MATLAB: QRS complex detection in ventricular tachycardia ECG

If this is a homework problem, you will not be able to use this code. If it is for research, you can likely adapt it to other problems.

The Code —

D = load('cu01m.mat');
EKG = D.val;
figure
plot(EKG)
grid
xlim([0 1000])
Fs = 250;                                                       % Estimate Sampling Frequency
Fn = Fs/2;                                                      % Nyquist Frequency
Ts = 1/Fs;                                                      % Estimate Sampling Interval
t = linspace(0, numel(EKG), numel(EKG))/Fs;
Wp = [2  90]/Fn;                                                % Normalised Passband (Passband = 46 Hz To 54 Hz)
Ws = [1 100]/Fn;                                                % Normalised Stopband (Passband = 49 Hz To 51 Hz)
Rp =  1;                                                        % Passband Ripple/Attenuation
Rs = 50;                                                        % Stopband Ripple/Attenuation
[n,Wp] = ellipord(Wp, Ws, Rp, Rs);                              % Calculate Elliptic Filter Optimum Order
[z,p,k] = ellip(n, Rp, Rs, Wp,'bandpass');                      % Elliptic Filter
[sos,g] = zp2sos(z,p,k);                                        % Convert To Second-Order-Sections For Stability
figure
freqz(sos,2^16,Fs)
filtered_EKG = filtfilt(sos,g,EKG);
[lmn,npr] = islocalmin(filtered_EKG, 'MinProminence',100);      % Detect: Q & S
lnix = find(lmn);
prqs = npr(lnix);
[lmx,xpr] = islocalmax(filtered_EKG, 'MinProminence',500);      % Detect: R
lxix = find(lmx);
prr = xpr(lxix);
figure
plot(t, EKG)
grid
xlim([0 5])
figure
plot(t, filtered_EKG)
grid
xlim([0 5])
figure
plot(t, filtered_EKG)
hold on
plot(t(lxix), filtered_EKG(lxix), 'r^')
plot(t(lnix), filtered_EKG(lnix), 'gv')
hold off
grid
xlim([0 5])
figure
plot(t, EKG)
hold on
plot(t(lxix), EKG(lxix), 'r^')
plot(t(lnix), EKG(lnix), 'gv')
hold off
grid
legend('EKG', 'R', 'Q S')
xlim([0 5])

Use the correct time vector, and make the appropriate changes to the filter design if necesary.

Best Answer

Related Solutions

MATLAB: How to find Q and S point in QRS complex of ECG signal

MATLAB: QRS complex detection in ventricular tachycardia ECG

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