AI-Based Personalized Music Therapy: Enhancing Mental Health through Adaptive Music Interventions

Mental health challenges are becoming increasingly prevalent worldwide, necessitating innovative therapeutic approaches. Music therapy has been proven effective in reducing stress, anxiety, and depression, but its effectiveness varies based on individual preferences and emotional states. This paper proposes an AI-based personalized music therapy system that leverages machine learning and deep learning techniques to recommend music tracks tailored to an individual’s mood, physiological signals, and preferences. The proposed system utilizes emotion recognition models, patient feedback, and a recommendation engine to optimize therapy outcomes. Expected benefits include improved mood, stress reduction, and enhanced therapy adherence. The study also reviews recent literature from 2019 to 2025, highlighting advances in AI-driven emotion detection, personalized interventions, and music therapy research.