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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.