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pbashivan / EEGLearn

A set of functions for supervised feature learning/classification of mental states from EEG based on "EEG images" idea.

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Average power within each frequency band of interest

ShibaPrasad opened this issue · comments

commented

Hi
I am not able to figure out the below stuff on EEGLAB tool. would you please help on this....I am totally stuck on my experiment and using online data sets

from your previous reply:
at URL - #12
i was advised below stuffs to calculate.

I used the average power within each frequency band of interest. I think this would be a better estimate of the shape of PSD. Taking the max might be noisy.

You can divide the time series into windows and apply FFT on each window or use wavelet transformation on the complete signal and then divide it to windows.

Please help me on this.

commented

You can use matlab’s FFT function. It will give you range of frequencies and power values for each. In python you can use this function which is comparable to matlab’s version.