Bandpass filter to get EEG frequency bands?

Question

I'm doing a project with an EEG to detect driver drowsiness and learned about EEG frequency bands (alpha, beta, gamma...).

As the frequency bands are simple frequency ranges, I wonder if I can use several bandpass filters to get them (instead of using WPT / FFT)?

Is this approach correct? Is there any reason not to do it (performance)?

Answer 1

As the frequency bands are simple frequency ranges, I wonder if I can use several bandpass filters to get them (instead of using WPT / FFT)?

Sure! That's how it's usually done!

Is there any reason not to do it (performance)?

diabolical laugther as it happens, I've prepared just the blog post for you… TL;DR: If you don't have to process more than 20 Million EEG samples per second, your PC should do fine performance-wise.

Filtering Time-Series Data on the GNU Radio blog.

I came across an EEG problem that tried to do exactly that, filter things into multiple bands. And lo, I had 5 minutes of fun designing this bandpass filterbank for signals with $f_\text{sample}=220\,\text{Hz}$:

$$ \begin{align} \Delta:& [1,3]\text{ Hz}\\ \theta:& [4,7]\text{ Hz}\\ \alpha_1:& [8,9]\text{ Hz}\\ \alpha_2:& [10,12]\text{ Hz}\\ \beta_1:& [13,17]\text{ Hz}\\ \beta_2:& [18,30]\text{ Hz}\\ \gamma_1:& [31,40]\text{ Hz}\\ \gamma_2:& [41,50]\text{ Hz} \end{align} $$

in this GNU Radio Companion flow graph

The result was that, even in this totally naive filterbank implementation, things are so much faster than real-time that you can assume that if done a little more cleverly, it'd work on any halfway DSP-affine microcontroller in real-time.