IMAGE PROCESSING AND MACHINE LEARNING FOR HUMAN STRESS DETECTION

Volume 18 No 10 (2020)

Rammohan Togati, Katakam Krishna Chaitanya, Pallavi Bhramarautu, Mosheck Menta

DOI: 10.48047/nq.2020.18.10.NQ20239

Abstract

The major goal of this study is to use vivid Machine Learning and Image Processing methods to identi-fy stress in the human body. Our system is an upgraded version of previous stress detection systems that did not include live detection or personal counselling, but this system includes live detection and periodic analysis of employees, as well as detecting physical and mental stress levels in them and providing proper stress management remedies via a survey form. Our method is primarily focused on stress management and cre-ating a healthy and spontaneous work environment for workers in order to get the most out of them during working Hours.

Keywords

Facial Expressions, K-Nearest Neighbor Classifier, Stress, Stress prediction

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