Published Paper Details:

The early detection of emotional distress and self-awareness are crucial aspects of mental health that are often limited. This study introduces PersonaAI, a real-time AI- based digital twin framework designed to bridge this gap. By analyzing user responses to psychological questions and emotional inputs, PersonaAI creates a dynamic replica of a user's personality and emotional behavior. The system leverages a combination of a conversational model (GPT-4), a vector database (Pinecone/FAISS) for long- term memory, and a relational database (MongoDB/SQLite) for profile data. This approach allows the digital twin to generate behaviorally-aligned responses, enabling users to gain insights into their mental patterns, receive reflective prompts, and proactively manage their emotional well-being. This paper outlines the system's architecture, functional and nonfunctional requirements, and its potential to revolutionize personalized mental health support.