# How to upsample an ECG signal and its associated data?

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Mibang am 23 Jun. 2024
Bearbeitet: Star Strider am 24 Jun. 2024
I have an ECG signal which has a sampling frequency of 250 Hz and I want to upsample it to 360 Hz.
The signal has peaks and the indexes of the peaks are also given as "peaks.mat".
The given data is described as follows:
sig.mat: ECG signal whose size is 273010X1, which has 633 peaks as specified in "peaks.mat".
peaks.mat: the sample index where the peaks occur in "sig.mat" and the size is 633X1
So, besides upsampling the signal, how to adjust the indexes of the peaks accordingly?
Thank you,
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### Antworten (2)

Catalytic am 23 Jun. 2024
Use interp1 to sample the signals where you want.
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Star Strider am 23 Jun. 2024
Use the resample function to upsample it, since this function is specifically designed for signal processing, and contains an anti-aliasing filter to prevernt spurious frequencies from appearing in the resampled signal.
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Mibang am 24 Jun. 2024
Bearbeitet: Mibang am 24 Jun. 2024
Thank you, but your approach is not what I want.
I think I got your helpl enough. Thank you.
Star Strider am 24 Jun. 2024
Bearbeitet: Star Strider am 24 Jun. 2024
My pleasure!
What do you want, then?
I’m still not clear on that.
peaks = LD.peaks
peaks = 2273x1
77 370 662 946 1231 1515 1809 2044 2402 2706
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sig = LD.sig;
tm = LD.tm;
Ts = mean(diff(tm))
Ts = 0.0028
% Tsd = std(diff(tm))
Fs = 1/Ts
Fs = 360.0000
[myPks,myLocs] = findpeaks(sig, 'MinPeakProminence',0.5)
myPks = 2274x1
0.8400 0.9400 0.9600 0.8600 0.8200 0.8850 0.9450 0.8750 0.8850 0.8900
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myLocs = 2274x1
78 371 664 948 1232 1516 1810 2046 2404 2707
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figure
plot(tm, sig)
hold on
plot(tm(peaks), sig(peaks), 'vr')
plot(tm(myLocs), myPks, '^g')
hold off
grid
xlim([0 25])
sig_filt = highpass(sig, 1.5, Fs, 'ImpulseResponse','iir'); % Filter Out Baseline Variation
[myPks_filt,myLocs_filt] = findpeaks(sig_filt, 'MinPeakProminence',0.5);
figure
plot(tm, sig_filt)
hold on
plot(tm(peaks), sig_filt(peaks), 'vr')
plot(tm(myLocs_filt), myPks_filt, '^g')
hold off
grid
xlim([0 25])
[sig450,t450] = resample(sig_filt,tm,450)
sig450 = 812500x1
0.0093 0.0105 0.0107 0.0116 0.0128 0.0133 0.0134 0.0169 0.0125 0.0213
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t450 = 812500x1
0 0.0022 0.0044 0.0067 0.0089 0.0111 0.0133 0.0156 0.0178 0.0200
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format shortG
myLocs450 = resample(myLocs, 360,450)
myLocs450 = 1820x1
1.0e+00 * 84.705 441.23 809.46 1155.2 1523.7 1858.6 2219.1 2640.5 2994 3354.2
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myLocs450 = round(myLocs450)
myLocs450 = 1820x1
85 441 809 1155 1524 1859 2219 2640 2994 3354
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[MyPks450,MyLocs450] = findpeaks(sig450, 'MinPeakProminence',0.5)
MyPks450 = 2275x1
1.0691 1.2059 1.2364 1.1561 1.1356 1.1777 1.2228 1.1528 1.2006 1.184
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MyLocs450 = 2275x1
97 464 830 1185 1540 1895 2263 2557 3005 3384
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figure
plot(t450, sig450)
hold on
plot(t450(myLocs450),sig450(myLocs450), 'sr')
plot(t450(MyLocs450),sig450(MyLocs450), 'sg')
hold off
xlim([0 25])
It is simply not possible to resample the location indices as well as the signal, and have the location indices ‘make sense’ in any real way. As I mentioned earlier, find the peaks and locations of the resampled signal after resampl;ing it. Interpolating the data from the original signal to the resampled signal will simply not work. Just use findpeaks on the resampled signal and be done with it.
Notice the difference between the peak locations of the actual resampled signal and the resampled locations of the original signal. That approach just doesn’t work.
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