I have an eeg signal with two channels (f3m2 and f4m1) which is divided into epochs. I want to augment the data by taking every 5th sample. I can re-use the discarded samples to create 5 versions of the data (take every 5th sample starting at sample 0, then take every 5th sample starting at sample 1, etc.). I have written my own code to downsample the data starting at sample 0, 1 etc. but I know that in order to avoid aliasing I need to first apply a low pass filter.
How do I decide what filter to use (FIR, IRR, etc.)? How do I decide which cutoff frequency to use? How would I implement this?
My code is in python and I have been considering using the scipy.signal library (but am open to any python libraries).