Towards physiology-informed data augmentation for EEG-based BCIs

no code implementations • 27 Mar 2022 • Oleksandr Zlatov, Benjamin Blankertz

Most EEG-based Brain-Computer Interfaces (BCIs) require a considerable amount of training data to calibrate the classification model, owing to the high variability in the EEG data, which manifests itself between participants, but also within participants from session to session (and, of course, from trial to trial).

Data Augmentation EEG +1

Subject independent EEG-based BCI decoding

no code implementations • NeurIPS 2009 • Siamac Fazli, Cristian Grozea, Marton Danoczy, Benjamin Blankertz, Florin Popescu, Klaus-Robert Müller

In the quest to make Brain Computer Interfacing (BCI) more usable, dry electrodes have emerged that get rid of the initial 30 minutes required for placing an electrode cap.

EEG

Playing Pinball with non-invasive BCI

no code implementations • NeurIPS 2008 • Matthias Krauledat, Konrad Grzeska, Max Sagebaum, Benjamin Blankertz, Carmen Vidaurre, Klaus-Robert Müller, Michael Schröder

Compared to invasive Brain-Computer Interfaces (BCI), non-invasive BCI systems based on Electroencephalogram (EEG) signals have not been applied successfully for complex control tasks.

EEG