Personalised, Multi-modal, Affective State Detection for Hybrid Brain-Computer Music Interfacing

Electroencephalography reflects the activity of sub-cortical brain regions during approach-withdrawal behaviour while listening to music
Daly, I., Williams, D., Hwang, F., Kirke, A., Miranda, E. R. & Nasuto, S. J., 1 Jul 2019
Article in Scientific Reports
Evaluating BCI for Musical Expression: Historical Approaches, Challenges and Benefits
Williams, D. A. H., 26 May 2019, Brain Art. Springer, p. 145-158 14 p.
Research output: Chapter in Book/Report/Conference proceeding › Chapter
AI and Automatic Music Generation for Mindfulness
Williams, D., Hodge, V. J., Gega, L., Murphy, D., Cowling, P. I. & Drachen, A., 17 Mar 2019. 10 p.
Research output: Contribution to conference › Paper › peer-review
A psychometric evaluation of emotional responses to horror music
Williams, D., Wu, C. Y., Hodge, V. J., Murphy, D. & Cowling, P. I., 1 Jan 2019. 9 p.
Research output: Contribution to conference › Paper › peer-review
Emotional Congruence in Video Game Audio
Williams, D. A. H., Murphy, D. T. & Cowling, P. I., 2019, Encyclopedia of Computer Graphics and Games (ECCG). Springer
Research output: Chapter in Book/Report/Conference proceeding › Chapter

Research output: Contribution to journal › Article › peer-review

Personalised, multi-modal, affective detection for hybrid brain-computer interfacing (not edited)
2.6 MB, PDF document

Author(s)

Journal	IEEE Transactions on Affective Computing
Date	Published - 7 Feb 2018
Issue number	99
Volume	PP
Number of pages	14
Pages (from-to)	1-14
Original language	English

Calibration, Electroencephalography, Medical treatment, Music, Physiology, Psychology, Training, Affective state detection, BCMI, EEG, GSR, Personalised affective state detection

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