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Improving motor imagery detection with a BCI based on somesthetic non invasive stimulations

Improving motor imagery detection with a BCI based on somesthetic non invasive stimulations

Authors :
Rimbert, Sébastien
Popular interaction with 3d content (Potioc)
Laboratoire Bordelais de Recherche en Informatique (LaBRI)
Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Publication Year :
2023
Publisher :
HAL CCSD, 2023.

Abstract

International audience; One of the most prominent BCI types of interaction is Motor Imagery (MI)-based BCI. Users control a system by performing MI tasks, e.g., imagining hand/foot movements detected from EEG signals. Indeed, movements and imagination of movements activate similar neural networks, enabling the MI-based BCI to exploit the modulations known as Event-Related Desynchronization (ERD) and Event-Related Synchronization (ERS). However, two important challenges remain before using such MI-BCIs on a large scale: (i) be able to detect the MI of the user without any temporal markers for instructions (often given by sound or visual cues) and (ii) achieve sufficient accuracy (>80%) to ensure the reliability of a BCI device that could be used by the participants.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.od.......165..2591bdb6831d52e08a8c811da152acf4