International Journal of Scientific Research and Engineering Development

Mental health disorders affect approximately 1 in 7 individuals in India, with a majority of cases going undetected due to the absence of accessible, real-time diagnostic tools. This paper presents NeuroShield, an AI-powered crisis detection system designed to identify mental health emergencies through Natural Language Processing (NLP)-based text analysis. The proposed system employs multi-keyword extraction, weighted risk scoring, and a 6-axis emotion profiling module to classify user inputs into three risk tiers: Low, Moderate, and High. Upon detection of a high-risk case, the system autonomously dispatches alerts to designated crisis helplines and provides immediate therapeutic support through a context-aware conversational AI bot. Experimental evaluation demonstrates a detection accuracy of 97.3% with an average response time under 2 seconds. The system further incorporates wellness modules including guided breathing exercises, grounding techniques, and daily mood tracking. NeuroShield offers a scalable, 24/7 available framework applicable across educational institutions, healthcare facilities, corporate environments, and individual users, with the potential to bridge the critical mental healthcare gap prevalent in India.

A.Agesta Jenifer, M.Ganista Varsha Bala, Dr.V.Kavidha,"NeuroShield:An AI-Powered Real-Time Mental Health Crisis Detection System Using Natural Language Processing" International Journal of Scientific Research and Engineering Development, V9(2): Page(2280-2285) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.