University Student’s Mental Stress Detection Using Machine Learning

University Student's Mental Stress Detection Using Machine Learning

Rahul M. Dhokane1, Viki Shirsath2, Vinay Pansare3, Durgesh Shinde4, Jivan Patil5

1Professor, Department of Information Technology, Sir Visvesvaraya Institute of Technology, Nashik, Maharashtra,India.

2,3,4,5Department of Information Technology, Sir Visvesvaraya Institute of Technology,Nashik,

Maharashtra, India.

Abstract

Mental stress among university students is a growing concern, significantly affecting their academic performance and overall well-being. This study proposes a machine learning-based system to detect mental stress through multiple parameters including facial recognition, behavior analysis, grade analysis, and question-answer-based analysis. The system employs advanced algorithms to analyze facial expressions, academic records, and behavioral data, offering a comprehensive assessment of a student's mental health. The proposed model aims to provide timely interventions, promoting better mental health support within educational institutions.

Keywords: Mental Stress Detection, Machine Learning, Facial Recognition, Behavior Analysis, Grade Analysis, Student Well-being.