ANR project BCI4IA funded!

The BCI4IA project proposes to detect intraoperative awareness reliably by analyzing, in real-time, brain motor activity under general anesthesia with a Brain-Computer Interface (BCI) based on Median Nerve Stimulation and innovative machine learning methods.

Partners are:

– University hospital of Nancy;
– University of Lorraine/LORIA/Neurorhythms;
– Inria Potioc;
– University hospital of Brugmann (Belgium).


Invited talk@Illkirch campus days 2022

On May 23-34, 2022, six laboratories on the Illkirch campus (univ. of Strasbourg) organize joint scientific days
I have been invited to participate to a plenary session on human/machine symbiosis and artificial intelligence. I will present my work on deep learning and transfer learning for the detection of motor brain electrical activity.

Program here

OpenViBE workshop @ NeuroErgonomics’21

On September 11 at 14:00h – 18:00 CET, I will participate to introduce the worldwide used open source software OpenViBE for designing  and process on-line neuroscience experiments at the OpenViBE workshop during the 3rd Neuroergonomics Conference 2021! Who’s attenting?


Invited talk @ BCI workshop (CNRS/French academy of medicine/French academy of technologies)

On November 2, 2020, a very interesting workshop is organized bringing together the CNRS, the Academy of Technologies and the National Academy of Medicine on brain-machine interfaces.
I will present two projects on the detection of peroperative awereness and the design and evaluation of a haptic and tangible brain-compututer interface for stroke patients (ANR Grasp-IT).

Program and free registration: here

Best Student Paper@SMC’20

Congratulations to Sébastien Rimbert who received the award for best student paper from IEEE and the Brain initiative at Brain-Machine Interfaces workshop of the 2020 System Man and Cybernetic (SMC’20) conference!
You can read the article « Learning How to Generate Kinesthetic Motor Imagery Using a BCI-based Learning Environment: a Comparative Study Based on Guided or Trial-and-Error Approaches » by
Sébastien Rimbert, Laurent Bougrain and Stéphanie Fleck