Python Based Stress Detection System Using Machine Learning & Algorithm’s

Python Based Stress Detection System Using Machine Learning & Algorithm’s

Ashutosh Salgar1, Purushottam Kulkarni2, Prathamesh Shelar3, Anirudh Katkar4, Prof. Govind Pole5

1 Department of Computer Engineering, MES’s Wadia College of Engineering, Pune

 2 Department of Computer Engineering, MES’s Wadia College of Engineering, Pune

3 Department of Computer Engineering, MES’s Wadia College of Engineering, Pune

4 Department of Computer Engineering, MES’s Wadia College of Engineering, Pune

5 Department of Computer Engineering, MES’s Wadia College of Engineering, Pune

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Abstract - In today's high-pressure world, the need for innovative, non-intrusive stress monitoring solutions is more critical than ever. This paper introduces a sophisticated stress detection system that combines facial expression analysis with machine learning to deliver real-time, continuous stress assessment. Our system employs Haar Cascade classifiers for precise face detection, CNN for feature extraction and utilizes the K-Nearest Neighbors (KNN) algorithm to classify stress-related facial expressions. A significant advantage of our system is its non-intrusive nature, relying solely on visual data, thus eliminating the need for cumbersome wearable sensors. This enhances user comfort and convenience. This paper outlines the design, implementation, and evaluation of our stress detection system, emphasizing its potential applications in workplace wellness, mental health monitoring, and human-computer interaction

Key Words: - KNN, Facial Expressions, Machine Learning, Stress Detection, Image Processing, CNN