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From the same journal

Affective brain–computer music interfacing

Research output: Contribution to journalArticle

Author(s)

  • Ian Daly
  • Duncan Williams
  • Alexis Kirke
  • James Weaver
  • Asad Malik
  • Faustina Hwang
  • Eduardo Miranda
  • Slawomir J Nasuto

Department/unit(s)

Publication details

JournalJournal of Neural Engineering
DateAccepted/In press - 21 Jun 2016
DatePublished (current) - 11 Jul 2016
Issue number4
Volume13
Number of pages15
Pages (from-to)046022
Original languageEnglish

Abstract

Objective . We aim to develop and evaluate an affective brain–computer music interface (aBCMI) for modulating the affective states of its users. Approach . An aBCMI is constructed to detect a user's current affective state and attempt to modulate it in order to achieve specific objectives (for example, making the user calmer or happier) by playing music which is generated according to a specific affective target by an algorithmic music composition system and a case-based reasoning system. The system is trained and tested in a longitudinal study on a population of eight healthy participants, with each participant returning for multiple sessions. Main results . The final online aBCMI is able to detect its users current affective states with classification accuracies of up to 65% and modulate its user's affective states significantly above chance level. Our system represents one of the first demonstrations of an online aBCMI that is able to accurately detect and respond to user's affective states. Possible applications include use in music therapy and entertainment.

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