Abstract-Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. This paper provides an effective method for the detection of cognitive stress levels using data provided from a physical activity tracker device developed by FITBIT. The main motive of this system was to use a machine learning approach in stress detection using sensor technology. Individually, the effect of each stressor was evaluated using logistic regression and then a combined model was built and assessed using variants of ordinal logistic regression models including logit, probit, and complementary log-log. This system was used and evaluated in a real-time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that a stress detection system should be as non-invasive as possible for the user.Index Terms-Physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.