EEG

Reinforcement learning under high noise and uncertainty
Context Reinforcement learning (RL) methods interact with a system in closed loop in order to learn suitable action strategies. The goal of this interaction is to control the system, e.g., to bring it into a desired state.
Oct 4, 2022
Reinforcement learning under high noise and uncertainty
Dutch Brain Interfaces Initiative DBI2
Dutch large scale consortium for closed-loop interaction with the brain.
Oct 3, 2022
Dutch Brain Interfaces Initiative DBI2
BCI-supported language rehabilitation
Chronic stroke patients with language deficits can profit from an individualized BCI-supported language training protocol.
Sep 27, 2022
BCI-supported language rehabilitation
Looking for study participants
We are investigating a novel language training method based on an auditory BCI system, which shall be applied to patients after stroke. For this project, we are recruiting healthy participants aged 45-80 years who are native speakers of Dutch.
Sep 27, 2022 1 min read
Looking for study participants
Monitoring Attention
Using physiological signals and spontaneous behavior to automatically monitor attention.
Sep 25, 2022
Monitoring Attention
Noise-tagging
A BCI using the code-modulated visual evoked potential (c-VEP).
Sep 25, 2022
Noise-tagging
Dareplane
Dareplane investigates a platform for closed-loop adaptive deep brain stimulation.
Jun 27, 2022
Dareplane
Deep representation learning
Using deep learning to obtain embeddings for EEG signals.
Feb 1, 2022
Deep representation learning
Decoding Perceived Hazardousness from User's Brain States to Shape Human-Robot Interaction
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Decoding cognitive brain states
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