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Poster Année : 2023

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

Résumé

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.
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Dates et versions

hal-04030312 , version 1 (15-03-2023)

Identifiants

  • HAL Id : hal-04030312 , version 1

Citer

Sébastien Rimbert. Improving motor imagery detection with a BCI based on somesthetic non invasive stimulations. 10th International BCI Meeting Balancing Innovation and Translation, Jun 2023, Bruxelles, Belgium. . ⟨hal-04030312⟩

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