How does one perform a fast Fourier transform (fft) on heart rate variability data?

Having obtained the RR intervals over a 30 min range at sampling rate of 1000 per second.

Answer 1

[Muthu Annamalai]

Hello Samuel, We can only calculate the Discrete Fourier Transform, as an approximation of the actual continuous Fourier Transform, using the FFT algorithm; all this means is that DFT is same as FFT.

You want to read MATLAB FFT algorithm implementation, doc at www.mathworks.com/help/matlab/ref/fft.html?nocookie=true, and adapt example section with your parameters;

My preliminary attempt follows.

HTH, -Muthu

Fs = 1000;                    % Sampling frequency = 1kHz
T = 1/Fs;                     % Sample time
L = 30*60;                     % Length of signal (s)
t = (0:L-1)*T;                % Time vector
y = ; %replace with your signal

NFFT = 2^(ceil(log2(length(y)))); %infimum power of 2 w.r.t length
%NFFT ~= 2048; %closest to 1800 for example
Y = fft(y,NFFT)/L;
f = Fs/2*linspace(0,1,NFFT/2+1);

% Plot single-sided amplitude spectrum.
plot(f,2*abs(Y(1:NFFT/2+1))) 
title('Single-Sided Amplitude Spectrum of y(t)')
xlabel('Frequency (Hz)')
ylabel('|Y(f)|')