Jul 2026· International Journal of Technology and Emerging Research· Vol 2, pp. 291-297· 0 citations· 1 references
TL;DR
RELieF, a MERN stack-based AI powered mental health monitoring and emotional support system that integrates daily mood tracking, graphical analytics, conversational AI assistance, and gamification mechanisms within a secure and scalable web architecture.
Abstract
The rapid growth of academic and workplace
stress has significantly increased mental health concerns
among students and professionals. Traditional therapeutic
models lack real-time monitoring, personalization, and
scalable accessibility. Existing digital platforms often provide
static recommendations without integrating structured mood
analytics,
secure
data management, and intelligent
conversational assistance.
This paper presents RELieF, a MERN stack-based AI
powered mental health monitoring and emotional support
system. The proposed framework integrates daily mood
tracking, graphical analytics, conversational AI assistance,
and gamification mechanisms within a secure and scalable
web architecture. The frontend is developed using React.js,
while the backend employs Node.js and Express.js with
MongoDB Atlas for cloud-based data storage. JWT-based
authentication ensures secure access and data privacy.
Experimental evaluation conducted on structured test cases
demonstrates consistent performance with an overall accuracy
of 93.33%, high engagement consistency, and effective
visualization of emotional patterns. The proposed system
provides a modular, scalable, and user-centric approach
toward digital mental wellness.
Keywords: MERN Stack; Mental Health Monitoring; AI Chatbot; Mood Analytics; Web Application.
An AI-based framework for stress management and emotional well-being that integrates machine learning, deep learning, natural language processing, wearable sensing technologies, and conversational AI to provide timely assessment and personalized mental health support is presented.
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