AI-Powered Prediction and Intervention for Mood Swings, Depression, and Anxiety Through Music and Color-Based Indicators in Adults

This study explores the feasibility of developing an AI-powered application, used either independently or with an external device, to predict mood swings in individuals with severe mental illness or a predisposition to mood-related disorders. Beyond prediction, the system is envisioned to support early intervention through art therapy. The methodology integrates insights from the psychology of music and color, psychophysiological monitoring (e.g., polygraphy and fMRI), and machine learning techniques within artificial intelligence frameworks. The study emphasizes the complementary roles of psychology and AI, focusing particularly on the subliminal aspects of human behavior. Importantly, the proposed AI functions as a supportive tool rather than a decision-maker, ensuring a balanced integration of technology and human judgment. By outlining the conceptual and methodological foundations, this research represents an initial step toward innovative mental health technologies with the potential to enhance both prediction and intervention.