Personalized Stress Detection from Physiological Measurements

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Abstract

This paper describes a study on continuous, nonintrusive stress detection from physiological measurements, involving data collection, feature extraction, and model construction. We built a personalized stress detection model based on Support Vector Machines, and evaluated it on the collected data. Experimental results show that our model can detect stress with high precision.

Citation

Yuan Shi, Minh Hoai Nguyen, Patrick Blitz, Brian French, Scott Fisk, Fernando de la Torre, Asim Smailagic, Daniel P. Siewiorek, Mustafa al' Absi, Emre Ertin, Thomas Kamarck and Santosh Kumar
"Personalized Stress Detection from Physiological Measurements",
International Symposium on Quality of Life Technology, 2010
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