In this tutorial, we will review some common signal processing and machine learning techniques that have been used in EEG-based brain-computer interface (BCI) systems to translate brain signals into messages and commands.
This notebook owes much of its content to the MNE and PyRiemann packages.
Most of the examples were partially inspired by the well-documented and high-quality tutorials available in the official documentations (most of which, by the way, are also available as Jupyter notebooks).
To all the developers who have contributed to these modules:
Build the image
docker build --rm --no-cache eegbci_tutorial .Run it
docker run -p 8888:8888 -e NB_UID=$(id -u) eegbci_tutorialNavigate to http://localhost:8888/?token=TOKEN.
- Bear, M. F., Connors, B. W., & Paradiso, M. A. (2016). Neuroscience: Exploring the brain (4th edition). Wolters Kluwer.
- Cohen, M. X. (2014). Analyzing neural time series data: Theory and practice. The MIT Press.
- Graimann, B., Allison, B., & Pfurtscheller, G. (Eds.). (2010). Brain-computer interfaces: Revolutionizing human-computer interaction. Springer.
- Géron, A. (2019). Hands-on machine learning with Scikit-Learn, Keras, and TensorFlow: Concepts, tools, and techniques to build intelligent systems. O'Reilly.
- Nam, C. S., Nijholt, A., & Lotte, F. (Eds.). (2018). Brain-computer interfaces handbook: Technological and theoretical advances. Taylor & Francis, CRC Press.
- Niedermeyer, E., Schomer, D. L., & Lopes da Silva, F. H. (Eds.). (2011). Niedermeyer’s electroencephalography: Basic principles, clinical applications, and related fields (6th edition). Wolters Kluwer, Lippincott Williams & Wilkins.
- MNE - Open-source Python software for exploring, visualizing, and analyzing human neurophysiological data: MEG, EEG, sEEG, ECoG, and more
- SciKit-Learn - Machine Learning in Python
- Numpy - Fundamental package for scientific computing with Python
- PyRiemann - a python package for covariance matrices manipulation and classification through riemannian geometry
- BNCI Horizon 2020 - The Future of Brain/Neural Computer Interaction: Horizon 2020
- EDFbrowser - Free, opensource, multiplatform, universal viewer and toolbox intended for, but not limited to, timeseries storage files like EEG, EMG, ECG, BioImpedance, etc.