Mental Health Assistance

Chiew, Chun Sheng (2026) Mental Health Assistance. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

Mental Health Assistance is an AI-powered chatbot that uses powerful natural language processing (NLP) to provide users with personalised mental health care. The project addresses the growing demand for accessible and user-friendly mental health resources by integrating features such as sentiment-based chatbot responses, mood tracking with a journal, and user analytics for progress insights. The system also promotes social connectivity via chat group features and friend management modules, allowing users to establish support networks. The application's emphasis on personalised user experience assures user engagement and simplicity of navigation. The proposed method employs AI-powered techniques to provide prompt and empathetic assistance, hence fostering beneficial mental health habits. The goal is to create an effective and scalable platform that improves users' mental health while encouraging peer connection and support. The proposed mental health assistance platform will be built using Expo.tsx to create a cross-platform mobile app for both Android and iOS. Firebase Firestore will store user data, including mood tracking, journal entries, and analytics, and support real-time messaging, notifications, and authentication. The platform will use AI-powered sentiment analysis for personalised chatbot responses, helping users manage their mental health. It will also include social features like chat groups and friend management, powered by Firebase’s real-time database, to build a supportive community. The system will undergo functionality testing, user experience evaluation, and performance validation to ensure reliability and usability. The expected outcome is a stable, responsive, and user-centric platform that encourages consistent emotional wellness practices and promotes a safe mental health environment for users.