There is a problem in extracting the 64 eigenvalues of the three frequency domains of the EEG signal
wangyue663 opened this issue · comments
Hello professor, I want to apply the CHB-MIT epilepsy EEG data set to your code, but this data set only has 23 channels and uses 23 brain electrodes, then do I use 23 α, θ, β Is it enough to perform power spectrum estimation after FFT? Power spectrum estimation is to take the square and divide by the length of time after FFT, right? But will there be negative values in the FeatureMat_timeWin table in your Sample data? Thank you very much for your reply.
As long as you have the 3D coordinates of the electrodes you should be able to transform them into eeg images.
For the power estimation, you need to run the FFT method on the eeg signal in each electrode and compute the average coefficients over each frequency band for each electrode.
If you then normalize the values across trials you will get some negative values, otherwise they would be positive.
Okay, professor. After FFT, should the average power or the average coefficient be obtained? I saw that you replied to other people earlier that it was to get the average power. I am a newbie, thank you very much for your reply
Yes, the average power is best