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

TL;DR

This paper introduces a novel EEG-based biomarker derived from cross-frequency coupling measures, which correlates with subjective music preference and can enhance personalized music recommendation systems.

Contribution

It presents a new, affordable EEG biomarker based on cross-frequency coupling that quantifies aesthetic responses to music for personalized recommendations.

Findings

The biomarker is derived from left prefrontal cortex EEG signals.

It correlates with subjective aesthetic appreciation.

The approach can be integrated into music recommendation systems.

Abstract

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. Keywords: Cross-frequency coupling; Human-computer interaction; Brain-computer interface