Welcome to the Medical AI group of the Machine Learning Journal Club! Here at MLJC we believe that AI techniques and tools can aid people and doctors in many different ways. For this reason, we decided to start the MedicAI project to explore and make contributions to this area. To join us for these research, we offer tutorials that allow you to understand the world of BCIs.
Before starting work on a project, here there's a didactical path for newcomers. Recommended tutorials:
- https://sccn.ucsd.edu/wiki/Introduction_To_Modern_Brain-Computer_Interface_Design
- http://learn.neurotechedu.com/introtobci/
- https://medium.com/svilenk/bciguide-246a9ca76fcd
- http://www.neuromatchacademy.org/syllabus/
- http://learn.neurotechedu.com/lessons/
Here, we propose an interesting review on BCIs classification algorithms:
Books:
- Il cervello elettrico - Simone Rossi (non-technical reading, just for pleasure)
Here there is the spring school we will attend all together:
An interesting review on BCIs classification algorithms:
In this section, we offer two reviews on deep learning based EEG analysis:
- https://iopscience.iop.org/article/10.1088/1741-2552/ab260c
- https://iopscience.iop.org/article/10.1088/1741-2552/ab0ab5
Last but not least, a section with all the BCI code Materials useful to start with the BCI world.
- https://neurotechx.github.io/eeg-notebooks/
- https://github.com/NeuroTechX/eeg-notebooks : Python library that allows you to run cognitive neuroscience experiments with a simple mobile EEG device and laptop computer
- https://github.com/bbci/bbci_public/ (by @gabrielepenna)