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?

see https://www.neuroergonomicsconference.um.ifi.lmu.de/tutorials-workshops/

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
here https://hal.inria.fr/hal-02920306

ANR project GraspIT funded

I am the coordinator of the funded ANR project GRASP-IT.
This project aims to recover upper limb control improving the kinesthetic motor imagery (KMI) generation of post-stroke patients using a tangible and haptic interface within a gamified Brain-Computer Interface (BCI) training environment. (i) This innovative KMI-based BCI will integrate complementary modalities of interactions such as tangible and haptic interactions in a 3D printable flexible orthosis. We propose to design and test usability (including efficacy towards the stimulation of the motor cortex) and acceptability of this multimodal BCI. (ii) The GRASP-IT project proposes to design and integrate a gamified non-immersive virtual environment to interact with. This multimodal solution should provide a more meaningful, engaging and compelling stroke rehabilitation training program based on KMI production. (iii) In the end, the project will integrate and evaluate neurofeedbacks, within the gamified multimodal BCI in an ambitious clinical evaluation with 75 hemiplegic patients in 3 different rehabilitation centers in France. This 4-years project will take advantages of the leading interdisciplinary consortium combining expertise from 4 research teams (LORIA/Neurosys, UL/Perseus, Inria/Camin, Inria/Hybrid) and 3 centers or hospital department for physical medicine and rehabilitation (IRR/CMPR Lay St Christophe, CHU Rennes, CHU Toulouse). The GRASP-IT project represents a challenge for the industrial 3D printing field. The materials of the 3D printable orthosis, allowing the haptic-tangible interfaces integration, will come from a joint R & D work performed by the companies Alchimies and Open Edge.