Towards BCI-based Interfaces for Augmented Reality: Feasibility, Design and Evaluation - Inria EPFL Access content directly
Journal Articles IEEE Transactions on Visualization and Computer Graphics Year : 2018

Towards BCI-based Interfaces for Augmented Reality: Feasibility, Design and Evaluation

Abstract

Brain-Computer Interfaces (BCIs) enable users to interact with computers without any dedicated movement, bringing newhands-free interaction paradigms. In this paper we study the combination of BCI and Augmented Reality (AR). We first tested thefeasibility of using BCI in AR settings based on Optical See-Through Head-Mounted Displays (OST-HMDs). Experimental results showedthat a BCI and an OST-HMD equipment (EEG headset and Hololens in our case) are well compatible and that small movements of thehead can be tolerated when using the BCI. Second, we introduced a design space for command display strategies based on BCI in AR,when exploiting a famous brain pattern called Steady-State Visually Evoked Potential (SSVEP). Our design space relies on fivedimensions concerning the visual layout of the BCI menu ; namely: orientation, frame-of-reference, anchorage, size and explicitness. Weimplemented various BCI-based display strategies and tested them within the context of mobile robot control in AR. Our findings werefinally integrated within an operational prototype based on a real mobile robot that is controlled in AR using a BCI and a HoloLensheadset. Taken together our results (4 user studies) and our methodology could pave the way to future interaction schemes in AugmentedReality exploiting 3D User Interfaces based on brain activity and BCIs.
Fichier principal
Vignette du fichier
Manuscript.pdf (14.33 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01947344 , version 1 (06-12-2018)

Licence

Attribution

Identifiers

Cite

Hakim Si-Mohammed, Jimmy Petit, Camille Jeunet, Ferran Argelaguet Sanz, Fabien Spindler, et al.. Towards BCI-based Interfaces for Augmented Reality: Feasibility, Design and Evaluation. IEEE Transactions on Visualization and Computer Graphics, 2018, 26 (3), pp.1608-1621. ⟨10.1109/TVCG.2018.2873737⟩. ⟨hal-01947344⟩
358 View
1033 Download

Altmetric

Share

Gmail Facebook X LinkedIn More