Machine Learning Framework for the Detection of Mental Stress Via Webcam

Machine Learning Framework for the Detection of Mental Stress Via Webcam

Authors- Prasad U. Giridhar, Yash J. Hirudkar, Prashant K. Joshi, Shravani M. Karne, Professor Gargeya M.5

Abstract-– This paper presents a Machine Learning Framework for Face Emotion Recognition (FER) aimed at detecting mental stress in real-time during online digital learning. The system is designed to enhance e-learning experiences by identifying student emotions using a deep convolutional neural network (CNN) trained on the FER-2013 dataset. With a training accuracy of 77% and validation accuracy of 64%, framework integrates Flask for web deployment and OpenCV for video capture, enabling real-time emotion classification across seven emotion categories. Insights generated through emotion detection can assist educators in understanding student engagement, detecting stress indicators,and optimizing teaching strategies based on emotional cues, ultimately contributing to more responsive and supportive digital learning environments.

DOI: /10.61463/ijset.vol.13.issue2.316