MATLAB: Segmenting QRS complexes.

ecgdataqrs signal

Lately I have been trying to experiment with some ECG data and I am currently trying to perform synchronized averging on a noisy ECG signal.

Up till now I plotted the data, with the x-axis set as time in seconds and I determined a reference point for each realization of the signal, the peak of the QRS (R-wave) was deemed to be most obvious.

Now I want to manually segment 10 QRS complexes so that I may perform synchronized averging. I was thinking that maybe I should find the distance between two consecutive peaks and that would be one sample. Each sample would be set having the distance between peaks as their width. Then by using a loop I would add these 10 samples and find their mean. Any idea as to how I could implement it code-wise?

Best Answer

Do this in code instead. See Average of Wave from 10 waves in single graph for a relevant example.

Related Solutions

MATLAB: How to find the x&y co-ordinates of the highest peak and storing the data into a variable

If you just want the highest peak can't you just use

doc max

? with the 2 output syntax to get the index which you can then pass to your frequency vector e.g.

[~, idx] = max( sgf_sm );
peakfreq = Fv( idx );

MATLAB: Noise in FFT of acceleration after windowing

Your signal has broad-band noise, so no frequency-selective filter (of which windows are a subset as you are using them) will elimiinate it. You may be able to eliminate most of the noise using wavelets. The best you can likely do otherwise is to use a Savitsky-Golay filter (the sgolayfilt function).

This is how I implemented it:

D1 = load('acc.mat');
T = load(' time.mat');
acc = D1.acc;
time = T.time;
L = numel(time);
Ts = mean(diff(time));
Fs = 1/Ts;
Fn = Fs/2;
FTacc = fft(acc)/L;
Fv = linspace(0, 1, fix(L/2) + 1)*Fn;
Iv = 1:numel(Fv);
figure
plot(Fv, abs(FTacc(Iv))*2)
grid
xlim([0, 1E+5])
xlabel('Frequency')
ylabel('Amplitude')
title('Fourier Transform')
sgf = sgolayfilt(acc, 3, fix(L/750));
figure
plot(time, acc)
hold on
plot(time, sgf)
hold off
grid
xlim([0.022  0.027])                                % ‘Zoom’ To See Detail
xlabel('Time')
ylabel('Amplitude')
legend('Original Signal', 'Savitzky-Golay Filtered Signal', 'Location','NE')

Experiment with the third argument to sgolayfilt (framelength’) to get the result you want.

Best Answer

Related Solutions

MATLAB: How to find the x&y co-ordinates of the highest peak and storing the data into a variable

MATLAB: Noise in FFT of acceleration after windowing

Related Question