Average of Wave from 10 waves in single graph

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Lokeswara reddy pamulapate 2019-11-20

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评论： Star Strider 2020-2-19

Hello Everyone,

I have a doubt concerning the average of the wave from a set of waves from sinlge dataset. I need to get a single average curve from all the curves from the figure. I am new to matlab and can not figure it out and have not been able Screenshot (6) .png

to do so for a long time. I need you to help and it would be great for me. Thanks in advance.

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Jan 2019-11-20

Please calm down. Posting a question twice will confuse the ones who want to help you and maybe waste their time, when they type an answer, which has been given already. Therefore I have cleaned up your identical former question.

You cannot expect the voluntary helpers to post an answer in some minutes. Mentioning, that the problem is "urgent" is counterproductive. See: https://www.mathworks.com/matlabcentral/answers/29922-why-your-question-is-not-urgent-or-an-emergency

There is only one curve in the image, so asking for an average is not meaningful. I guess, you mean that te curve is almost periodic and you want an average period. Then please explain, what the inputs are. It is easier to suggest a matching code, if we do not guess tis detail.

Lokeswara reddy pamulapate 2019-11-20

I have the data attched to this. Actually it is the wave of radial artery bloop pressure wave. I want to take the average of all the data to get one average curve from those data.

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Answer 1

Star Strider 2019-11-20

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https://ww2.mathworks.cn/matlabcentral/answers/492182-average-of-wave-from-10-waves-in-single-graph#answer_402481

在 MATLAB Online 中打开

Try this:

D = load('P_191005_000.mat');
ap = D.b;
Ts = 1E-3;                                                                  % Assume Sampling Interval
tv = linspace(0, 1, numel(ap))*Ts;                                          % Create Time Vector
[pks, locs] = findpeaks(-ap, 'MinPeakDist',250, 'MinPeakHeight',-85 );      % Determine Peaks & Indices
figure(1)
plot(tv, ap)
hold on
plot(tv(locs), -pks, '+r')
hold off
grid
for k1 = 1:numel(locs)-1
    apc{k1} = ap(locs(k1):locs(k1+1));                                      % Define Frames
    tvc{k1} = tv(locs(k1):locs(k1+1));
    len(k1) = numel(locs(k1):locs(k1+1));
end
enstrim = cellfun(@(x)x(1:min(len)), apc, 'Uni',0);                         % Trim Records To Shortest Length
ensavg = mean([enstrim{:}],2);                                              % Ensemble Average
figure(2)
hold all
for k1 = 1:numel(apc)
    plot(tvc{k1}-tvc{k1}(1), apc{k1})                                       % Plot Frames
end
plot(tv(1:numel(ensavg)), ensavg.', '-r', 'LineWidth',2)
hold off
grid

producing:

Average of Wave from 10 waves in single graph - 2019 11 20.png

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Star Strider 2019-11-22

在 MATLAB Online 中打开

I can clean that up to an extent, however you need to do the rest of the processing, then use my posted code to do the ensemble averages. You will need to make some choices as to what constitutes valid data, and correct for what appears to me to be significant arrhythmias. The arrythmias are going to make it very difficult to do a reliable ensemble average.

Preprocessing —

D = load('16Zi239231227Z11201Z0Z0Z0');
sig = D.column1(:,1);
Fs = 1;
Ts = 1/Fs;
Fn = Fs/2;
L = size(sig,1);
sigm = sig - mean(sig);
FTsig = fft(sigm)/L;
Fv = linspace(0, 1, fix(L/2)+1)*Fn;
Iv = 1:numel(Fv);
figure
plot(Fv, abs(FTsig(Iv))*2)
grid
xlim([0 0.025])
siglpf = lowpass(sig, 0.003, Fs);                           % Lowpass Filter
[pks1,locs1] = findpeaks(siglpf, 'MinPeakHeight',100, 'MinPeakDistance',250);
[pks2,locs2] = findpeaks(siglpf, 'MinPeakHeight',170);
pks = setdiff(pks1,pks2);
locs = setdiff(locs1,locs2);
tv = 0:(L-1);                                               % Time Vector
figure
plot(tv, siglpf)
hold on
plot(tv(locs), siglpf(locs), '+r')
hold off
grid
xlim([locs(1) L])

To eliminate the leading zero values and transients, select the signal as ‘((locs(1)-100):end)’. Lacking a true time vector of sampling times means that you can only get approximate statistics.

To see a representative sample of the filtered signal, use this xlim call:

xlim([locs(1)-100 locs(10)+160])

The filter passband appears to be appropriate, so there is no need to change it.

Experiment to get different results.

Star Strider 2019-11-25

I remember thet the new data are aortic waveforms and the initial data were radial artery waveforms. The radial artery waveforms appeared to be correct, although the pressures may require checking.

The problem is that there is something wrong with the aorta data, and I cannot figure out what the problem is. Something in the instrumentation is creating unusable data, whether it is bubbles in the transducer or problems with the catheter, or something else. If you know what the problem is, there might be a way to salvage the correct waveforms from those data, however in the absence of that information, there is not. The amplitudes are also suspicious. You will most likely have to abandon those data if you cannot figure out what the problem is so that some method of recovering the correct waveforms is possible. The aorta data are currently unusable.

When you collect new data, first be absolutely certain that the entire system is bubble-free, that the transducers are correctly calibrated and in the correct position relative to the subject, and that you have at least one recording of an impulse and step or square-wave input with the recorded inputs and outputs. This will allow you to correct for any nonlinearities and other problems in the physiological data you collect. It may also be necessary to put diluted heparin in the catheter fluid to prevent the catheter tip from clotting.

Star Strider 2019-12-11

在 MATLAB Online 中打开

This shouldl get you started:

D = load('2023Zi1410Zi2520112201227Z11201Z0Z0Z0.mat');
Ao = D.x;
t = linspace(0, numel(Ao), numel(Ao));
[Syspks,Syslocs] = findpeaks(Ao, 'MinPeakDistance', 150, 'MinPeakHeight',150);          % Systolic Peak
[Dcntch,Dcnlocs] = findpeaks(-Ao, 'MinPeakDistance', 50, 'MinPeakHeight',-150);        % Dicrotic Notch
[Dispks,Dislocs] = findpeaks(-Ao, 'MinPeakDistance', 150, 'MinPeakHeight',0);          % Systolic Peak
Dcnlocs = Dcnlocs(Ao(Dcnlocs)>0);
figure
plot(t, Ao)
hold on
plot(t(Syslocs), Syspks, '^r')
plot(t(Dcnlocs), Ao(Dcnlocs), 'vg')
plot(t(Dislocs), Ao(Dislocs), 'vk')
hold off
grid
xlim([0 5000])
legend('Trace','Systolic Peaks', 'Dicrotic Notch', 'Diastolic Nadir', 'Location','best')

I identified and plotted the systolic peak, the dicrotic notch, and the diastolic trough for the first 5000 sampling points in this code. That will not work for the entire trace, since the pulse pressure appears to change significantly after the intial 60K samples, and the trace is also discontinuous.

The signal is actually not very noisy, as this Fourier transform demonstrates:

L = numel(Ao);
Fs = 1;
Fn = Fs/2;
Aom = Ao - mean(Ao);
FTAo = fft(Ao)/L;
Fv = linspace(0, 1, fix(L/2)+1)*Fn;
Iv = 1:numel(Fv);
figure
plot(Fv, abs(FTAo(Iv))*2)
grid
xlim([0 0.0001])

I must defer to you to deal with the discontinuities. This is not a reliable trace because of the discontinuities and the wide variation in the absolute pressures and the pulse pressure, so any inferences you get from it are likely to be unreliable.

Lokeswara reddy pamulapate 2019-12-11

编辑：Lokeswara reddy pamulapate 2019-12-11

@Star Strider I am really very thankfull to you. For identifying the systolic peaks and diastolic peaks I have a function and is working perfectly. The code which you have provided is working as well but not for entire signal as you told. The main problem is to delete the noise which is present in the signal. I have tried to delete the noise by my self by looking where the noise is by zooming it manually and deleting the noise manually but it is taking too much time to clean approx 3hrs per signal. Do I need to delete it manually by looking where the noise is to get the good signal with out any noise. If there is any code that could help me to delete the noise that would save so much of time. Just I need to remove the noise in the signal to get good signal wihich are sutable for detecting the peaks and notch. I have attached the signal which I have cleaned manually, but in this signal also there is a bit noise which I have to delete furthur. if there is any code for deleteing the entire noise of signal for the signal provided before that would help me.

I am really tankfull to you.

Thankyou very much.

Star Strider 2019-12-11

在 MATLAB Online 中打开

There is not much noise.

I would use:

Ao = lowpass(Ao, 0.007, Fs);

or:

Fs = 1;                                                             % Sampling Frequency
Fn = Fs/2;                                                          % Nyquist Frequency
Wp = 0.007/Fn;                                                      % Stopband Frequency (Normalised)
Ws = 1.2*Wp;                                                        % Passband Frequency (Normalised)
Rp =  1;                                                            % Passband Ripple
Rs = 60;                                                            % Passband Ripple (Attenuation)
[n,Wp] = ellipord(Wp,Ws,Rp,Rs);                                     % Elliptic Order Calculation
[z,p,k] = ellip(n,Rp,Rs,Wp,'low');                                  % Elliptic Filter Design: Zero-Pole-Gain 
[sos,g] = zp2sos(z,p,k);                                            % Second-Order Section For Stability
figure
freqz(sos, 2^18, Fs)                                                % Filter Bode Plot
set(subplot(2,1,1), 'XLim',[0 Fs/5])                                % Optional
set(subplot(2,1,2), 'XLim',[0 Fs/5])                                % Optional
Ao_filt = filtfilt(sos, g, Ao);                             % Filter Signal

Both work, and eliminate some of the high-frequency components of the signal. (You need to decide if this is acceptable, since they could eliminate some data that would allow you to characterise the frequency response if the vascular system.)

As for the discontinuities, you need to decide how to deal with those. Records that have such significant discontinuities may not be acceptable data. There are other problems with the signals, as well, especially with regard to the step changes in absolute pressure and pulse pressure. This may be due to amplifier gain changes or other changes in the instrumentation, something that is definitely not advisable during a recording.

Lokeswara reddy pamulapate 2020-2-8

@Star Strider I have a doubt, can you please help me.

I have the data of Aorta and femoral signal in which I have to measure the systolic peak, diastolic peak, foot index, augmentation pressure and time. I identified the systolic peak, diastolic peak, foot index, notch index, and time by doing the 2nd derivative. As the signal is Aorta and femoral it will have a reflection in the pulse wave so I need to measure from these the augmentation pressure, from the systolic peak. I need just the idea how to measure the augmentation pressure of both Aorta and femoral how to identify the augmentation pressure(AP) and pulse pressure (PP) points in the data I have, for both feomral and aorta. please help me for only one step my work would be finished. this is for aorta the picture i have attached. If i identify the systolic peak, augmentation pressure point and pulse pressure point my work would be finished by this please help me. I can see no one better than you to help me. Please help me. Thankyou. Have a good day.

Lokeswara reddy pamulapate 2020-2-19

Hi, the pulse pressure can be calculated but I need to calculate the Augmented pressure(Anacrotic notch). from these Aorta and femoral.

Star Strider 2020-2-19

For each pulse, identify the dicrotic notch (that appears to define it), as a point in time using the derivative (or whatever technique you choose), then get the pressure at that point in time.

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Answer 2

KALYAN ACHARJYA 2019-11-20

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编辑：KALYAN ACHARJYA 2019-11-20

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Lets say wave are y1,y2,y3.....up to y10..assuming all are having in same x scale

aveg_data=(y1+y2+y3...+y10)/10;
plot(x,aveg_data)

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KALYAN ACHARJYA 2019-11-20

编辑：KALYAN ACHARJYA 2019-11-20

Can you share two sample data, so that I can test on it?

Lokeswara reddy pamulapate 2019-11-20

ya sure

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Average of Wave from 10 waves in single graph

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