I am trying to extract the mu suppression values from my EEG dataset, which doesn't allow using EEGLab. I did most of the steps, but I need to add a bandpass filter and I am not sure how.
The frequency band I would need is 8-13, my sampling rate is 1000 and I was told I would need an order of between 8 and 10.
The MATLAB documentations lists this example:
[A,B,C,D] = butter(10,[500 560]/750);
d = designfilt('bandpassiir','FilterOrder',20, ... 'HalfPowerFrequency1',500,'HalfPowerFrequency2',560, ... 'SampleRate',1500);
However, I am not sure, what parameters I need to use for my case except for sampling rate and filter order. Also, it is not clear to me what is [A,B,C,D]. I would appreciate any input.
I usually go over the individual functions themselves -- you did a little mix-up. The first input to butter
is already the filter order (so you have specified order 10 and tried to specify order 20 in the desginfilt
function...). For the Butterworth -filter, MATLAB recommends to use the zero-pole-gain formulation rather than the standard a
- b
coefficients. Here is an example:
f_low = 100; % Hz
f_high = 500; % Hz
f_sampling = 10e3; % 10kHz
assert(f_low < f_high)
f_nrm_low = f_low /(f_sampling/2);
f_nrm_high = f_heigh /(f_sampling/2);
% determine filter coefficients:
[z,p,k] = butter(4,[f_nrm_low f_nrm_high],'bandpass');
% convert to zero-pole-gain filter parameter (recommended)
sos = zp2sos(z,p,k);
% apply filter
sig_flt = sosfilt(sos,sig);
I have filled with with standard values from my field of working. 4th order is the overwhelming standard here. In your case, you would simply go with
f_low = 200; % Hz
f_high = 213; % Hz
f_sampling = 1000; % 1kHz
f_nrm_low = f_low /(f_sampling/2);
f_nrm_high = f_heigh /(f_sampling/2);
% determine filter coefficients:
[z,p,k] = butter(15,[f_nrm_low f_nrm_high],'bandpass');
PS: the type 'bandpath'
is not required as the function is aware of this if you specify an array as input;)
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