Publikation
Speech Imagery BCI Training Using Game with a Purpose
Abdulrahman Mohamed Selim; Maurice Rekrut; Michael Barz; Daniel Sonntag
In: Proceedings of the 2024 International Conference on Advanced Visual Interfaces. International Working Conference on Advanced Visual Interfaces (AVI-2024), June 3-7, Arenzano, Genoa, Italy, Pages 1-5, ISBN 9798400717642, Association for Computing Machinery, New York, NY, USA, 6/2024.
Zusammenfassung
Games are used in multiple fields of brain-computer interface (BCI) research and applications to improve participants’ engagement and enjoyment during electroencephalogram (EEG) data collection. However, despite potential benefits, no current studies have reported on implemented games for Speech Imagery BCI. Imagined speech is speech produced without audible sounds or active movement of the articulatory muscles. Collecting imagined speech EEG data is a time-consuming, mentally exhausting, and cumbersome process, which requires participants to read words off a computer screen and produce them as imagined speech. To improve this process for study participants, we implemented a maze-like game where a participant navigated a virtual robot capable of performing five actions that represented our words of interest while we recorded their EEG data. The study setup was evaluated with 15 participants. Based on their feedback, the game improved their engagement and enjoyment while resulting in a 69.10% average classification accuracy using a random forest classifier.
Projekte
EXPECT - Exploring the Potential of Pervasive Embedded Brain Reading in Human Robot Collaborations,
No-IDLE - Interactive Deep Learning Enterprise,
NEARBY - Noise and variability-free BCI systems for out-of-the-lab use
No-IDLE - Interactive Deep Learning Enterprise,
NEARBY - Noise and variability-free BCI systems for out-of-the-lab use