Towards the bio-personalization of music recommendation systems: A single-sensor EEG biomarker of subjective music preference

被引：32

作者：

Adamos, Dimitrios A. ^{[1
,3
]}

Dimitriadis, Stavros I. ^{[2
,3
]}

Laskaris, Nikolaos A. ^{[2
,3
]}

机构：

[1] Aristotle Univ Thessaloniki, Sch Mus Studies, Fac Fine Arts, GR-54124 Thessaloniki, Greece

[2] Aristotle Univ Thessaloniki, Dept Informat, AIIA Lab, Thessaloniki 54124, Greece

[3] Aristotle Univ Thessaloniki, Neuroinformat Grp, GR-54006 Thessaloniki, Greece

来源：

INFORMATION SCIENCES | 2016年 / 343卷

关键词：

Cross-frequency coupling; Human-computer interaction; Brain-computer interface; BRAIN ACTIVITY; RESPONSES; DYNAMICS; EMOTION; EXPERIENCE; SCIENCE; REWARD; MOTOR;

D O I：

10.1016/j.ins.2016.01.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Recent advances in biosensors technology and mobile electroencephalographic (EEG)-interfaces have opened new application fields for cognitive monitoring. A computable biomarker for the assessment of spontaneous aesthetic brain responses during music listening is introduced here. It derives from well-established measures of cross-frequency coupling (CFC) and quantifies the music-induced alterations in the dynamic relationships between brain rhythms. During a stage of exploratory analysis, and using the signals from a suitably designed experiment, we established the biomarker, which acts on brain activations recorded over the left prefrontal cortex and focuses on the functional coupling between high-beta and low-gamma oscillations. Based on data from an additional experimental paradigm, we validated the introduced biomarker and showed its relevance for expressing the subjective aesthetic appreciation of a piece of music. Our approach resulted in an affordable tool that can promote human machine interaction and, by serving as, a personalized music annotation strategy, can be potentially integrated into modern flexible music recommendation systems. (C) 2016 Elsevier Inc. All rights reserved.

引用

页码：94 / 108

页数：15

共 53 条

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