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This repository contains implementations of the paradigms there were used to develop and evaluate gumpy. For instance, they contain a classical motor imagery task, but also a paradigm in which a subject has to reach to grasp an object.

Note that the code is already usable, but may not yet be production quality.

Documentation for each paradigm can be found within the folder doc, whereas the code to run the paradigms can be found in the respective subfolders.

If you wish to contribute to gumpy's development then clone the main 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 try to 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.

• www.gumpy.org: For more information about gumpy
• https://github.com/gumpy-hybridBCI: gumpy's main repository, and additional information about contributors and how to cite gumpy
• https://github.com/gumpy-hybridBCI/Gumpy-Deeplearning: gumpy's deep learning models for BCI
• https://www.youtube.com/watch?v=M68GeL8PafE

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