How to build a CNN model to classify motor imagery tasks from EEG signals?

I have processed the raw eeg signals using DWT, and have extracted the detailed coefficients at level 3,4 and 5, and naming them as D3,D4,D5/ (sampling frequency at 200Hz).

Now, I would like to pass D3,D4,D5 as input to the CNN model to classify the signals. How can i build a CNN model for this problem?

Answer 1

[Srivardhan Gadila]

You can refer to Classify ECG Signals Using Long Short-Term Memory Networks, Modulation Classification with Deep Learning & Topics in the Signal Processing Using Deep Learning documentation page.