Decoding Music Attention From "Eeg Headphones": A User-Friendly Auditory Brain-Computer Interface
Wenkang An, Barbara Shinn-Cunningham, Hannes Gamper, Dimitra Emmanouilidou, David Johnston, Mihai Jalobeanu, Edward Cutrell, Andrew Wilson, Kuan-Jung Chiang, Ivan Tashev
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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.
Chairs:
Erchin Serpedin