MATLAB: Low pass filter using filter coefficient

MATLAB

Hi,

I want to do low pass filtering of ECG signal. I have filter coefficients and sammpling frequency. With only this much information available is it possible to do low pass filtering?

please help if someone knows!

Thank you in advance.

Best Answer

If you have the Signal Processing Toolbox, first check the filter stability and performance with the freqz function.

Then use the filtfilt function to filter the signal.

All the necessary code and other details are explained in the documentation.

Related Solutions

MATLAB: How to Butterworth Filter with Bandpass [10 500] with sampling rate 1000

You have to divide your passband and stopband frequencies by the Nyquist frequency to normalise them:

Fs = 1000;                                          % Sampling Frequency
Fn = Fs/2;                                          % Nyquist Frequency
Wp = [10  495]/Fn;                                  % Norrmalised Passband Frequencies
Ws = [5   499]/Fn;                                  % Normalised Stopband Frequencies
Rp =  1;                                            % Passband Ripple (dB)
Rs = 25;                                            % Stopband Ripple (dB)
[n,Wn] = buttord(Wp, Ws, Rp, Rs);                   % Optimal Filter Order
[b,a] = butter(n, Wn);                              % Calculate Filter Coefficients
[sos,g] = tf2sos(b,a);                              % Convert To Second-Order Sections For Stability
figure(1)
freqz(sos, 4096, Fs)                                % Filter Bode Plot

You cannot have any frequency exactly at zero or exactly at the Nyquist frequency, so I designed your passband to be close enough to them to be stable. In your filter, you can also use a high-pass design with a lower cutoff of 10 Hz, since your upper passband is at the Nyquist frequency. The passband and stopband ripple values are necessary to specify in the design but irrelevant to a Butterworth filter. These are acceptable values for most filter designs (for example Chebyshev) that require them.

You would use the ‘sos’ and ‘g’ variables in your actual filter:

filtered_signal = filtfilt(sos, g, signal);

(This design works well in R2016a and should also work in earlier releases.)

MATLAB: IIR Bandstop (Notch) Filter design

I have absolutely no idea what ‘2.01’, ‘2.02’ and ‘2.03’mean.

Here is a prototype bandstop filter design that you can change to produce the filter you want:

Fs = 900;                                                           % Sampling Frequency
Fn = Fs/2;                                                          % Nyquist Frequency
Wp = [48 52]/Fn;                                                    % Stopband Frequency (Normalised)
Ws = [0.9 1.1].*Wp;                                                 % Passband Frequency (Normalised)
Rp =  1;                                                            % Passband Ripple
Rs = 90;                                                            % Passband Ripple (Attenuation)
[n,Wp] = ellipord(Wp,Ws,Rp,Rs);                                     % Elliptic Order Calculation
[z,p,k] = ellip(n,Rp,Rs,Wp,'stop');                                 % 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
% signal_filt = filtfilt(sos, g, signal);                             % Filter Signal

Un-comment the filtfilt line to filter your signal.

Best Answer

Related Solutions

MATLAB: How to Butterworth Filter with Bandpass [10 500] with sampling rate 1000

MATLAB: IIR Bandstop (Notch) Filter design

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