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Deep Learning Based EEG forecasting toolbox

What is does?

1. Predict EEG from EEG.

EEG_from EEG

2. Predict EEG from Stimului.

EEG_from_Stimuli

3. Predict Stimuli from EEG.

Stimuli_from_EEG

Install

  1. Clone the repo
git clone https://github.com/vasudev-sharma/DeepEEG-Forecast
cd EEG-Forecast
  1. Set up Virtual Environment
virtualenv eeg_env --python=3.6
source eeg_env/bin/activate
  1. Now, in the terminal run
bash install_files.sh

Data

5 subjects EEG data downsampled at 160Hz

Each subject has

  • 64 channels
  • 192 trials
  • 840 time points (5.25s)

Data can be found here - https://drive.google.com/drive/folders/1_gV6t5f2FDWo8OYTcAxsDxz4yhRcYKU0?usp=sharing

Contributing

We ❤️ contributions. Feel free to send us a PR or raise an issue.

  1. Create an issue if there is one.
  2. Fork the repo.
  3. Create your feature branch (git checkout -b your-feature).
  4. Add and commit your changes (git commit -am 'message').
  5. Push the branch (git push origin your-feature).
  6. Create a new Pull Request.

Tracking the performance metrics and logging the models

Weights and Biases

TODO

  • Add instructions in readme to perform all the 3 tasks
  • Implement Attention model
  • Implement ESRNN model
  • Deploy the model
  • Refactor Code