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?



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