How to plot a frequency of respiration signal on y-axis while time of measurement is on x-axis?

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miki90 on 10 Feb 2018
Commented: Star Strider on 31 May 2020
I have a respiration (breathing) signal and a sampling frequency of 25 Hz and need to detect where is the lowest breathing frequency on a time scale, which should tell me actually when the person became sleepy. Fourier transform in its classical form doesn't give me much useful information. So, to clarify: the time of measurement should be on the x-axis and the breathing frequency should be on the y-axis. Then, I suppose, lower amplitudes of the signal will show the slower breathing. What should be done with the signal to plot it the way I need?
Birdman on 10 Feb 2018
Can you share your data in a mat file?
miki90 on 10 Feb 2018
Edited: miki90 on 10 Feb 2018
Here is also a vector in a txt file, if it is ok.

Star Strider on 10 Feb 2018
This should get you started:
Fs = 25; % Sampling Frequency (Hz)
Fn = Fs/2; % Nyquist Frequency
Ts = 1/Fs; % Sampling Time (sec)
L = numel(D);
t = linspace(0, L, L)*Ts; % Time Vector (sec)
figure(1)
plot(t, D)
grid
% axis([0 60 -850 -750])
axis([xlim -850 -750])
xlabel('Time')
ylabel('Amplitude')
FTD = fft(D-mean(D))/L; % Fourier Transform
Fv = linspace(0, 1, fix(L/2)+1)*Fn; % Frequency Vector
Iv = 1:numel(Fv); % Index Vector
figure(2)
plot(Fv, abs(FTD(Iv))*2)
grid
axis([0 2.5 ylim])
xlabel('Frequency (Hz)')
ylabel('Amplitude')
Wp = [0.35 0.65]/Fn; % Passband Frequency (Normalised)
Ws = [0.30 0.75]/Fn; % Stopband Frequency (Normalised)
Rp = 1; % Passband Ripple (dB)
Rs = 50; % Stopband Ripple (dB)
[n,Ws] = cheb2ord(Wp,Ws,Rp,Rs); % Filter Order
[z,p,k] = cheby2(n,Rs,Ws); % Filter Design, Sepcify Bandpass
[sos,g] = zp2sos(z,p,k); % Convert To Second-Order-Section For Stability
figure(3)
freqz(sos, 2^16, Fs) % Filter Bode Plot
D_filtered = filtfilt(sos, g, D); % Filter Signal
[pks,locs] = findpeaks(D_filtered, 'MinPeakDist',40);
figure(4)
plot(t, D_filtered)
hold on
plot(t(locs), pks, '^r')
hold off
grid
% axis([0 60 ylim])
axis([0 60 -15 15])
xlabel('Time')
ylabel('Amplitude')
tdif = diff([0 t(locs)]); % Time Difference Between Peaks (sec)
Dfrq = 60./tdif; % Frequency (Respirations/Minute)
figure(5)
plot(t(locs), Dfrq)
grid
axis([xlim 10 40])
xlabel('Time (sec)')
ylabel('Frequency (minute^{-1})')
I do not intend this to be a complete solution. It does some signal processing and preliminary data analysis. Make necessary changes to get the result you want. See the documentation on the various functions to understand how the code works.
Have fun!
miki90 on 31 May 2020
I don't have Matlab on my PC right now but I will try to answer like this. What do you get when you just plot your real-time signal? If you want to get the result as from the file, you may try to put your real time data into an array (make a buffer) and to plot the chunks, one after another.
Star Strider on 31 May 2020
Thomas — I don’t have Arduino, so I can’t help you with this. You need to post this as a new Question, then delete it here.