Implementations of Hybrid Brain Computer Interface Methods

This repository contains Hybrid BCI methods that can be used to simultaneously decode EEG and EEG signals for brain computer interfaces (BCIs). Some of the models depend on the functionality that is provided by gumpy, a python toolbox which contains several signal and feature processing routines that are commonly used for BCIs.

license:	MIT License
contributions:	Please use github (www.github.com/gumpy-bci/gumpy-deeplearning) and see below
issues:	Please use the issue tracker on github (www.github.com/gumpy-bci/gumpy-deeplearning/issues)

Documentation

You can find additional documentation for gumpy on www.gumpy.org.

Contributing

If you wish to contribute to gumpy's development clone one of gumpy's repository from github and start coding, test if everything works as expected, and finally submit patches or open merge requests. Preferrably in this order.

Please make sure that you follow PEP8, or have a look at the formatting of gumpy's code, and include proper documentation both in your commit messages as well as the source code. We use Google docstrings for formatting, and auto-generate parts of the documentation with sphinx.

gumpy hybrid BCI main developers and contributors

• Zied Tayeb
• Nicolai Waniek, www.github.com/rochus
• Nejla Ghaboosi
• Juri Fedjaev
• Leonard Rychly
• Jonas Braun

How to cite gumpy

Zied Tayeb, Nicolai Waniek, Juri Fedjaev, Nejla Ghaboosi, Leonard Rychly, Christian Widderich, Christoph Richter, Jonas Braun, Matteo Saveriano, Gordon Cheng, and Jörg Conradt. "gumpy: A Python Toolbox Suitable for Hybrid Brain-Computer Interfaces"

@Article{gumpy2018,
    Title = {gumpy: A Python Toolbox Suitable for Hybrid Brain-Computer Interfaces},
    Author = {Tayeb, Zied and Waniek, Nicolai and Fedjaev, Juri and Ghaboosi, Nejla and Rychly, Leonard and Widderich, Christian and Richter, Christoph and Braun, Jonas and Saveriano, Matteo and Cheng, Gordon and Conradt, Jorg},
    Year = {2018},
    Journal = {}
}

Additional References

• www.gumpy.org: gumpy's main website. You can find links to datasets here
• www.github.com/gumpy-bci/gumpy: gumpy's main github repository
• www.github.com/gumpy-bci/gumpy-deeplearning: gumpy's deep learning models for BCI
• https://github.com/gumpy-bci/gumpy-realtime : gumpy's real-time BCI module with several online demos
• https://www.youtube.com/channel/UCdarvfot4Ustk2UCmCp62sw : gumpy's Youtube channel
• https://www.youtube.com/watch?v=M68GeL8PafE

License

• All code in this repository is published under the MIT License. For more details see the LICENSE file.