I would like to filter frequencies: Alpha, Beta and Gamma. These bands have a relation with the task that I want to classify,
I am using the Gumpy python tool which has a method to apply Butterworth bandpass filter to EEG data (3D shape, i.e. TrialxChannelxData), you just have to do this:
lo_alpha, hi_alpha = 9, 16 lo_beta, hi_beta = 17, 32 lo_gamma, hi_gamma = 33, 64 # first step is to filter the data flt_a = gumpy.signal.butter_bandpass(X, lo=lo_alpha, hi=hi_alpha) flt_b = gumpy.signal.butter_bandpass(X, lo=lo_beta, hi=hi_beta) flt_g = gumpy.signal.butter_bandpass(X, lo=lo_gamma, hi=hi_gamma)
I got a 3D matrix, with different values in the form TrialxChannnelxData like return. "The problem" is that I just can get just a 3D matrix that could be; flt_a, flt_b and flt_g.
How can I get a 3D matrix that involves Alpha, Beta and Gamma frequencies?
Do you suggest me try other tools like MNE or I need to compute something else?
If I am correct, I can get the Alpha-Beta bands in a range [9-32], but what happens with the Gamma bands?