Decoding Music Attention from "EEG Headphones": A User-Friendly Auditory Brain-Computer Interface
Winko W. An, Barbara G. Shinn-Cunningham, Hannes Gamper, Dimitra Emmanouilidou, David Johnston, Mihai Jalobeanu, Edward Cutrell, Andrew D. Wilson
Abstract
People enjoy listening to music as part of their life. This makes music an excellent choice for designing a user-friendly brain-computer interface (BCI) for long-term use. We propose a novel BCI system using music stimuli that relies on brain signals collected via Smartfones, an EEG recording device integrated into a pair of headphones. In a user study of the proposed system, participants were asked to pay attention to one of three musical instruments playing simultaneously from separate spatial directions. We used a stimulus reconstruction method to decode attention from EEG signals. Results show that the proposed system can achieve good decoding accuracy (>70%) while providing superior user-friendliness compared to a traditional EEG setup.
BibTeX
@inproceedings{icassp2021_decodingmusicatt,
title = {Decoding Music Attention from "EEG Headphones": A User-Friendly Auditory Brain-Computer Interface},
author = {Winko W. An and Barbara G. Shinn-Cunningham and Hannes Gamper and Dimitra Emmanouilidou and David Johnston and Mihai Jalobeanu and Edward Cutrell and Andrew D. Wilson and Kuan-Jung Chiang and Ivan Tashev},
booktitle = {ICASSP 2021},
year = {2021}
}