| Paper ID | BIO-1.4 |
| Paper Title |
DECODING MUSIC ATTENTION FROM "EEG HEADPHONES": A USER-FRIENDLY AUDITORY BRAIN-COMPUTER INTERFACE |
| Authors |
Wenkang An, Barbara Shinn-Cunningham, Carnegie Mellon University, United States; Hannes Gamper, Dimitra Emmanouilidou, David Johnston, Mihai Jalobeanu, Edward Cutrell, Andrew Wilson, Microsoft Research, United States; Kuan-Jung Chiang, University of California, San Diego, United States; Ivan Tashev, Microsoft Research, United States |
| Session | BIO-1: Brain-Computer Interfaces |
| Location | Gather.Town |
| Session Time: | Tuesday, 08 June, 13:00 - 13:45 |
| Presentation Time: | Tuesday, 08 June, 13:00 - 13:45 |
| Presentation |
Poster
|
| Topic |
Biomedical Imaging and Signal Processing: [BIO-BCI] Brain/human-computer interfaces |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| 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 Smartfone, 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. |
