Azizur_rahman asked . 2021-03-12

2nd order butterworth filter and PCA

t = data(:,1);                                                                                              % column corresponding to time (block of 60s)
Accel = data(:,2:end);                                                                               % three columns corresponding to x, y, z (accelerometer data)
srate = 5000;                                                                                            % Hz (need to figure out how to downsample to 100Hz)
Fs = 1/srate;                                                                                             % Sampling Rate (in Hz) 
Fn =Fs/2;                                                                                                  % Nyquist Frequency (in Hz)
coeff = pca(Accel);                                                                                   % Need to obtain the most dominant (movement-centred) axis of tremor acceleration; use                  first component for all subsequent analyses
%2nd order Butterworth filter between 3-15 Hz
Wp = [3  15]/Fn;                                         % Norrmalised Passband Frequencies
Ws = [1.5   15.99]/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

matlab , signal , signal processing