Brain-Computer Interfaces Research Starter Guideline
Table of Contents
- We focus on studying non-invasive electroencephalogram-based brain-computer interfaces.
- EEG: (EEG) is an electrophysiological monitoring method to record electrical activity of the brain.
- (BCIs) are categorized into two types: evoked vs. spontaneous BCIs.
- Evoked BCIs exploit evoked potentials like or (SSVEP), mostly induced by an external stimulus.
- Spontaneous BCIs focus on internal cognitive processes such as event-related (de)synchronization (ERD/ERS), like (MI).
- For more details, please read Ch. 1 in a book, “EEG Signal Processing.”
- Importantly, please organize read papers in .
- Lotte et al. “”
- Motor Imagery Classification Methods
- Feature Extraction Methods
- SSVEP Classification Methods
- Further, please read Ch. 11.3.3 in a book, “Signal Processing and Machine Learning for Brain-Machine Interfaces.”
Deep and Hierarchical Methods
- For MI-based BCI, . proposed various methods.
- Shallow ConvNet
- Deep ConvNet
- For looking deeper, read: