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Activity-aware Mental Stress Detection Using Physiological Sensors
Silicon Valley Campus
  • Feng-Tso Sun, Carnegie Mellon University
  • Cynthia Kuo
  • Heng-Tze Cheng, Carnegie Mellon University
  • Senaka Buthpitiya, Carnegie Mellon University
  • Patricia Collins, Carnegie Mellon University
  • Martin L Griss, Carnegie Mellon University
Date of Original Version
Abstract or Description

"Continuous stress monitoring may help users better understand their stress patterns and provide physicians with more reliable data for interventions. Previously, studies on mental stress detection were limited to a laboratory environment where participants generally rested in a sedentary position. However, it is impractical to exclude the effects of physical activity while developing a pervasive stress monitoring application for everyday use. The physiological responses caused by mental stress can be masked by variations due to physical activity. We present an activity-aware mental stress detection scheme. Electrocardiogram (ECG), galvanic skin response (GSR), and accelerometer data were gathered from 20 participants across three activities: sitting, standing, and walking. For each activity, we gathered baseline physiological measurements and measurements while users were subjected to mental stressors. The activity information derived from the accelerometer enabled us to achieve 92.4% accuracy of mental stress classification for 10-fold cross validation and 80.9% accuracy for between-subjects classi- fication.

Citation Information
Feng-Tso Sun, Cynthia Kuo, Heng-Tze Cheng, Senaka Buthpitiya, et al.. "Activity-aware Mental Stress Detection Using Physiological Sensors" (2010)
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