Mental stress detection using machine learning algorithm

Stress is a subjective phenomenon that is difficult to measure comprehensively. However, we can classify and quantify stress and how it affects one's personal health, including various biological and psychological vulnerabilities. If we only hear what an individual says and ignore what the face of that person is telling us, then we just have half the story. This paper represents appearance based facial expression recognition system using Convolutional Neural Network (CNN). The Local Binary Pattern (LBP) was used to extract the appearance features. The CNN is trained to categorize into four basic facial expressions (anger, fear, unhappy and non-stressed expressions). This system was experimented with Indian and Cohn-Kanade database.