{"id":763438,"date":"2021-07-26T19:19:23","date_gmt":"2021-07-27T02:19:23","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=763438"},"modified":"2021-07-30T14:23:12","modified_gmt":"2021-07-30T21:23:12","slug":"decoding-music-attention-from-eeg-headphones-a-user-friendly-auditory-brain-computer-interface-2","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/decoding-music-attention-from-eeg-headphones-a-user-friendly-auditory-brain-computer-interface-2\/","title":{"rendered":"Decoding Music Attention from \u201cEEG Headphones\u201d: A User-Friendly Auditory Brain-Computer Interface"},"content":{"rendered":"

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.<\/p>\n

\"Auditory<\/p>\n","protected":false},"excerpt":{"rendered":"

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. 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