SYEDA FATIMA, K. SINDHU, A. JYOTHI, B. LALITHA 03 03 RealTime Facial Stress Detection Using Deep Learning is an advanced system designed to analyze facial expressions and detect stress levels and healthrelated signals in real time In todays fastpaced world mental health issues such as stress fatigue and anxiety are increasing making early detection and monitoring highly important Traditional methods rely on selfreporting or medical consultation which may not always be timely or accurate To address these challenges this project presents an intelligent facial analysis system using artificial intelligence and deep learning techniques The proposed system uses computer vision and deep learning models to capture and analyze facial features through a webcam Technologies such as Open CV and facial landmark detection are used to extract key facial regions while machine learning models evaluate stress levels emotional states and fatigue indicators The system is capable of identifying parameters such as eye strain attention levels facial tension and mood patterns with good accuracy To enhance interpretability the system highlights specific facial regions contributing to stress and provides detailed insights It also generates personalized suggestions such as breathing exercises relaxation techniques and wellness recommendations based on the analysis The backend is implemented using Python while the frontend interface provides a userfriendly experience for realtime interaction and visualization of results By combining artificial intelligence facial analysis and realtime processing RealTime Facial Stress Detection Using Deep Learning offers a noninvasive efficient and accessible solution for monitoring mental wellbeing This project demonstrates the potential of AI in healthcare applications especially in early stress detection preventive care and improving overall mental health awareness Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026