Towards providing music for academic and leisurely activities of computer users

• Main Authors: Aquino, Roman Joseph P., Battad, Joshua Rafael R., Ngo, Charlene Frances S., Uy, Gemilene C., Trogo-Oblena, Rhia S., Legaspi, Roberto S., Suarez, Merlin Teodosia C.
• Format: text
• Published: Animo Repository 2012
• Subjects: Electroencephalography; Music—Computer programs; Computer Sciences; Software Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2150; https://animorepository.dlsu.edu.ph/context/faculty_research/article/3149/type/native/viewcontent/978_3_642_32695_0_93.html
• Institution: De La Salle University

This paper uses brainwaves to recognize the computer activity of the user and provides music recommendation. Twenty-three (23) hours of data collection was performed by asking the computer user to wear a device that collects electroencephalogram (EEG) signals from his brain as he performed whatever tasks he wanted to perform while listening to music. The features of the preferred song given the activity of the user is used to provide songs for the user automatically. Activities were classified as either academic or leisure. The music provision model was able to predict the music features preferred by the user with accuracy of 76%. © 2012 Springer-Verlag.