Human Stress Detection Based On Sleeping Habits Using Machine Learning

Abstract: The proposed system is an AI-based Human Stress Detection System that predicts an individual's stress level using physiological and behavioural parameters such as heart rate, sleep duration, body temperature, respiration rate, and blood oxygen level. The system applies machine learning algorithms to analyse input data and classify stress into different levels such as Low, Medium, and High. The model is trained using historical datasets and deployed through a user-friendly web interface where users can input their health parameters and receive instant stress predictions. The main objective of this project is to provide an early stress monitoring tool that can assist individuals in maintaining mental well-being and taking preventive health measures. This system demonstrates how artificial intelligence can be effectively used in healthcare to support stress management and lifestyle improvement.

Keywords: Artificial Intelligence, Machine Learning, Stress Detection, Health Monitoring, Stress Prediction.