Basically, I am trying to remove baseline error so that I can extract features like R to R delay and other intervals.
how to improve detrending?
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Explorer
on 19 Feb 2016
Commented: Sibi Ramachandran
on 13 Feb 2019
Code:
d=load('CU_Ventricular_Tacharrhythmia\cu01m.mat');
noisyECG_withTrend=d.val(1,:);
subplot(2,1,1), plot(noisyECG_withTrend), grid on,
nnoisyECG_withTrend = noisyECG_withTrend';
t = 1:length(noisyECG_withTrend);
[p,s,mu] = polyfit((1:numel(noisyECG_withTrend))',nnoisyECG_withTrend,6)
f_y = polyval(p,(1:numel(noisyECG_withTrend))',[],mu);
ECG_data = nnoisyECG_withTrend - f_y; % Detrend data
subplot(2,1,2), plot(t,ECG_data); grid on
%ax = axis;
%axis([ax(1:2) -1.2 1.2])
title('Detrended ECG Signal')
xlabel('Samples'); ylabel('Voltage(mV)')
legend('Detrended ECG Signal')
Accepted Answer
Star Strider
on 19 Feb 2016
See if this filter does what you want (assuming Fs=256):
Fs = 256;
Fn = Fs/2;
Wp = [1 90]/Fn;
Ws = Wp.*[0.5 1.25];
Rp = 1;
Rs = 20;
[n,Wn] = buttord(Wp,Ws,Rp,Rs);
[b,a] = butter(n,Wn);
[sos,g] = tf2sos(b,a);
figure(1)
freqz(sos, 2048, Fs);
5 Comments
Star Strider
on 16 Oct 2018
@Evenor —
My code uses functions from the Signal Processing Toolbox. You need to have it installed in order to run my code. You should be able to run it in R2014a.
Sibi Ramachandran
on 13 Feb 2019
@Star Strider Good morning sir I saw your comments and it helped me to understand the use of these filters. I recently posted a question and I was wondering if you would be able to help me also? Thank you so much!
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