Synergizing Artificial Intelligence and EEG Biometrics: A Novel Paradigm for Proactive Mental Health Monitoring and Personalized Therapeutic Interventions

Abstract

Mental health disorders, particularly depression and anxiety, are significant global health challenges affecting millions of individuals, often leading to severe impairment in daily functioning and quality of life. Traditional detection methods primarily rely on subjective assessments, which can delay diagnosis and treatment. This paper explores a novel paradigm that synergizes Artificial Intelligence (AI) with electroencephalography (EEG) biometrics to enhance proactive mental health monitoring and personalized therapeutic interventions. By leveraging the advanced data analysis capabilities of AI alongside the real-time brain activity insights provided by EEG, this approach aims to improve the early detection and treatment of mental health disorders. The proposed framework incorporates a mobile application designed for continuous monitoring, enabling users to receive immediate feedback and interventions tailored to their specific needs. Preliminary findings suggest that this integrated system could revolutionize mental health care by making it more responsive, data-driven, and personalized. By addressing the limitations of current methods, this innovative framework holds the potential to transform how mental health disorders are understood and treated, paving the way for a future where mental health care is proactive rather than reactive.