Mooditor: An AI-Powered Mobile Assistant for Real-Time, Emotion-Aware Mental-Health Support: English - HAMZA, Laila; CHAJARI, Salma; SAKHIR, Niama; ERRATTAHI, Rahhal (International Journal of Computer Engineering and Data Science (IJCEDS), 2025)
Mooditor is a pioneering mobile and web-based application designed to enhance mental health monitoring through artificial intelligence. By integrating real-time emotion detection via facial expression analysis and a Rasa-powered chatbot for therapeutic interactions, Mooditor provides a multi-modal approach to mental well-being. The system leverages computer vision and natural language processing (NLP) to assess psychological states, offering continuous monitoring and personalized support. Comprehensive tools, including mood tracking, statistical analysis, and conversation history, enable users and healthcare professionals to track emotional trends effectively. Our evaluation demonstrates exceptional performance, with the emotion detection model achieving a macro average precision, recall, and F1-score of 0.9998 across 953 instances. Mooditor’s modular architecture supports future enhancements, such as advanced emotion detection algorithms and integration with professional mental health services. This work addresses critical challenges in mental health accessibility and early intervention, contributing to the advancement of digital mental health care.