부산대학교 도서관

Brain-computer interfaces (BCIs) like e.g. different types of EEG-based BCI spellers (up to date the most common BCI applications) allow new methods of control and interaction with computers and machines. The impact of background music and noise on user's performance (information transfer rate - ITR and accuracy) has already been investigated for different types of spellers, and usually led to a distractive, decreasing effect on the BCI performance, though there is always room for improving the subjective user experience. In this study, 11 participants used a cVEP-based BCI to perform two spelling tasks “BCI_AND_MUSIC” and “CONTRARY”, while listening via headphones to a standard instrumental song, a self-chosen instrumental song (“own music”), or to noise conditions: “no music” and “white noise”. Objective factors such as the blood pressure and heart rate were measured after each spelling task, and questionnaires were answered. The BCI accuracy was close to 100% in most cases, while the lowest accuracy was reached while listening to the individually selected, self-chosen music (“own music”). Similarly, the ITR was the highest in case of “no music” and lowest in case of “own music” (which, on the other hand, resulted in a better mood and higher excitement of the participants). Thus, while the general condition of “no music” could be recommended for further BCI experiments, additional research regarding individual factors like musicality or listening habits of BCI participants should be considered.