Are you absolutely certain that your sampling frequency is 100 Hz?
I’m not.
I looked at the rate and some of the intervals, and a sampling frequency of 256 Hz makes much more sense. That also puts your noise peak spike at about 60 Hz, consistent with U.S. mains power frequency.
Example:
Fs = 256;
InterBeatIntervalMean = (880-130)/(4*Fs)
RateMean = 60/InterBeatIntervalMean % Beats/Min
PR2 = (320-280)/Fs % P-R Interval (Complex #2) (< 200 ms)
QT2 = (370-280)/Fs % Q-T Interval (Complex #2) (< 400 ms)
InterBeatIntervalMean =
732.4219e-003
RateMean =
81.9200e+000
PR2 =
156.2500e-003
QT2 =
351.5625e-003
The normal EKG spectrum is between about 0.5 Hz to 100 Hz to accommodate all EKG arrhythmias (although for a normal EKG, you can use a 50 Hz upper passband frequency).
One of my more comprehensive posts on EKG signal processing is Detecting QRS complex in ECG signal. I posted several others.
A filter design I use commonly for de-noising EKG signals is:
Fs = 256; % Sampling Frequency
Fn = Fs/2; % Nyquist Frequency
Wp = [2 95]/Fn; % Filter Passband (Normalised)
Ws = Wp .* [0.5 1.2]; % Filter Stopband (Normalised)
Rp=1;
Rs= 50;
[n,Ws] = cheb2ord(Wp,Ws,Rp,Rs);
[b,a] = cheby2(n, Rs, Ws);
[sos,g] = tf2sos(b,a);
figure(1)
freqz(sos, 1024, Fs)
A Chebyshev Type II IIR (or an FIR) design is preferable for EKG signal processing because of the sharp rolloff required at the low end of the filter passband in order to remove the d-c offset and low-frequency baseline drift. You can do that with a Butterworth design, but that requires a long filter, and long filters can have stability problems.
