Hey guys, so as the title says I have a script that I can use to analyse some raw EEG data (.edf). Although I have the code and can use it I don't really understand what it's doing at each stage and I'd really like to.
After the conversion the data is averaged – I assume this is to remove noise? Then something called an elliptic filter is 'setup' and 'applied' to the data – I don't really understand what this is doing?
[order, Wn] = ellipord([fmin/(fs/2), fmax/(fs/2)], [(fmin-1)/(fs/2), (fmax+1)/(fs/2)], Rp, Rs);[B,A] = ellip(order, Rp, Rs, [fmin/(fs/2), fmax/(fs/2)]);
Then ranksums values are calculated and this is used to work out something called the energy? Energy values are obtained for each of the 'channels' which corresponds to an electrode on the EEG. I have no idea what this means, the code is as follows:
for j=1:14 [p(j),H(j),STATS(j,:)] = ranksum(Energy_EEGH(j,:),Energy_EEGL(j,:),'tail','right') end
And the output gives me 'p' and 'H' values. I understand that p values show whether or not a result set is statistically significant? So < 0.05 proves the working hypothesis and vice versa? However I don't understand what H values are and from what I can tell they can only be 0 or 1, 0 being bad and 1 being good? Thanks a lot.
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