Human Stress Analysis Using Machine Learning

Author(s)	K. Divya, S. Mari Subbulakshmi
Country	India
Abstract	Stress has become a critical factor affecting human health and well-being. This paper presents a machine learning-based approach for detecting human stress using physiological and behavioural data such as heart rate, skin temperature, and facial expressions. Algorithms like Support Vector Machine (SVM), Random Forest, and Decision Tree are used to classify stress levels into low, medium, and high. The system provides a non-invasive and real-time solution for stress monitoring, useful in healthcare and personal wellness applications.
Keywords	Machine Learning, Stress Detection, Human Stress Analysis, SVM, Random Forest, Decision Tree, Physiological Signals, Artificial Intelligence, Mental Health
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 17, Issue 1, January-June 2026
Published On	2026-04-23
Cite This	Human Stress Analysis Using Machine Learning - K. Divya, S. Mari Subbulakshmi - IJAIDR Volume 17, Issue 1, January-June 2026.

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Journal of Advances in Developmental Research