Literature DB >> 27396478

Affective brain-computer music interfacing.

Ian Daly1, Duncan Williams, Alexis Kirke, James Weaver, Asad Malik, Faustina Hwang, Eduardo Miranda, Slawomir J Nasuto.   

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% (3 class, [Formula: see text]) and modulate its user's affective states significantly above chance level [Formula: see text]. SIGNIFICANCE: 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.

Entities:  

Mesh:

Year:  2016        PMID: 27396478     DOI: 10.1088/1741-2560/13/4/046022

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  11 in total

1.  Electroencephalography reflects the activity of sub-cortical brain regions during approach-withdrawal behaviour while listening to music.

Authors:  Ian Daly; Duncan Williams; Faustina Hwang; Alexis Kirke; Eduardo R Miranda; Slawomir J Nasuto
Journal:  Sci Rep       Date:  2019-07-01       Impact factor: 4.379

Review 2.  A Systematic Review for Human EEG Brain Signals Based Emotion Classification, Feature Extraction, Brain Condition, Group Comparison.

Authors:  Mohamed Hamada; B B Zaidan; A A Zaidan
Journal:  J Med Syst       Date:  2018-07-24       Impact factor: 4.460

3.  Music Streaming Services as Adjunct Therapies for Depression, Anxiety, and Bipolar Symptoms: Convergence of Digital Technologies, Mobile Apps, Emotions, and Global Mental Health.

Authors:  Karl Schriewer; Grzegorz Bulaj
Journal:  Front Public Health       Date:  2016-09-30

4.  Composing only by thought: Novel application of the P300 brain-computer interface.

Authors:  Andreas Pinegger; Hannah Hiebel; Selina C Wriessnegger; Gernot R Müller-Putz
Journal:  PLoS One       Date:  2017-09-06       Impact factor: 3.240

5.  Hearing the Sound in the Brain: Influences of Different EEG References.

Authors:  Dan Wu
Journal:  Front Neurosci       Date:  2018-03-13       Impact factor: 4.677

6.  Enhancing BCI-Based Emotion Recognition Using an Improved Particle Swarm Optimization for Feature Selection.

Authors:  Zina Li; Lina Qiu; Ruixin Li; Zhipeng He; Jun Xiao; Yan Liang; Fei Wang; Jiahui Pan
Journal:  Sensors (Basel)       Date:  2020-05-27       Impact factor: 3.576

7.  Wired Emotions: Ethical Issues of Affective Brain-Computer Interfaces.

Authors:  Steffen Steinert; Orsolya Friedrich
Journal:  Sci Eng Ethics       Date:  2019-03-13       Impact factor: 3.525

8.  Affective Brain-Computer Music Interfaces-Drivers and Implications.

Authors:  Elisabeth Hildt
Journal:  Front Hum Neurosci       Date:  2021-06-29       Impact factor: 3.169

9.  Improving Cross-Day EEG-Based Emotion Classification Using Robust Principal Component Analysis.

Authors:  Yuan-Pin Lin; Ping-Keng Jao; Yi-Hsuan Yang
Journal:  Front Comput Neurosci       Date:  2017-07-19       Impact factor: 2.380

10.  Neural and physiological data from participants listening to affective music.

Authors:  Ian Daly; Nicoletta Nicolaou; Duncan Williams; Faustina Hwang; Alexis Kirke; Eduardo Miranda; Slawomir J Nasuto
Journal:  Sci Data       Date:  2020-06-15       Impact factor: 6.444

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