You have found the Deep Learning EEG Playground, put together by the Montreal Hacknight.
The repo is a bit messy, but what you should find in here:
- examples on how to usual stuff with colab
- a pyRiemann comparative example
- brain-decode based experimentations:
- tutorial from their website
- x86 execution
- colab based code
- sklearn wrapper
We are currently working toward integrating braindecode into MOABB, feel free to join us every other Fridays @ District 3 Innovation Center
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We assume you are using Anaconda, python 3.5
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Install Brain Decode: https://github.com/robintibor/braindecode
- If you are on Windows, You can install PyTorch using these instructions. You only need to go up to step 4.A.
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Go through the TrialWise Tutorial: https://robintibor.github.io/braindecode/notebooks/TrialWise_Decoding.html to make sure everything is setup properly
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Download this dataset : Two class motor imagery (002-2014) at http://bnci-horizon-2020.eu/database/data-sets
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put everything in an new folder (here)/BBCIData/
The remaining of the project is described in our jupyter notebook(s) 1 - Two-Classes Classification (BNCI)
- Download
2 - Two-Classes Classification (BNCI) Colab.ipynb
and upload it on your Google Drive. - Open Google Colab
- Instructions for dataset download and python library installation are described in the Jupyter notebook.
For more papers on DL applications on EEG, you could refer to this repo. Feel free to contribute.