Effect of AI-composed music on emotional and physiological states in healthy volunteers: A pilot study

Music is a promising nonpharmacological intervention for enhancing healthcare outcomes. Emotional regulation is a key mechanism in this process, but results vary, possibly due to differences in music selection. This study explores the impact of AI-composed music on emotional and physiological states, as measured by the self-assessment mannequin (SAM) and heart rate variability (HRV). Healthy volunteers (n = 30) were subjected to 10 min of AI-composed music with the intention of creating positive valence and negative arousal. Before the intervention, questionnaires on personal characteristics and music preferences, and baseline HRV were measured. Subjectively, no significant change in valence was observed (Δ median 0.0 (IQR 0.0;1.0), p = 0.077), whereas arousal (Δ median -1.0 (IQR -2.0;0.0), p < 0.001) and dominance (Δ median 0.5 (IQR 0.0;1.0), p = 0.008) significantly decreased. Ordinal regression analysis revealed that a higher rating for classical music (in line with the genre of the AI-composed music) predicted a higher valence rating after the intervention (OR 2.39, 95% CI 1.16-4.92; p = 0.018). Objectively, HRV measurements decreased and suggested a less relaxed/more excited state during the music listening task compared to baseline. Subsequent analysis revealed that an increase in valence was associated with higher HRV. In conclusion, after listening to the AI-composed music, subjective arousal was significantly lower, whereas valence was overall not affected by the music. However, music preference emerged as a crucial factor influencing emotional valence, which in turn affected HRV, indicating a more relaxed state. Therefore, AI-composed music in line with individual preferences may benefit music interventions, encouraging personalized approaches in healthcare.