Stress detection by means of stress physiological template

Alberto de Santos Sierra · Carmen Sánchez Ávila · Gonzalo Bailador del Pozo · Javier Guerra Casanova

51 citations0/0 files storedWorld Congress on Nature and Biologically Inspired Computing (NaBIC)

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Emotion and Mood Recognition Heart Rate Variability and Autonomic Control Non-Invasive Vital Sign Monitoring

Abstract

This paper describes a stress detection system based on fuzzy logic and two physiological signals: Galvanic Skin Response and Heart Rate. Instead of providing a global stress classification, this approach creates an individual stress templates, gathering the behaviour of individuals under situations with different degrees of stress. The proposed method is able to detect stress properly with a rate of 99.5%, being evaluated with a database of 80 individuals. This result improves former approaches in the literature and well-known machine learning techniques like SVM, k-NN, GMM and Linear Discriminant Analysis. Finally, the proposed method is highly suitable for real-time applications.

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References

2005Detecting Stress During Real-World Driving Tasks Using Physiological Sensors 2008Emotion recognition based on physiological changes in music listening 2005From Physiological Signals to Emotions: Implementing and Comparing Selected Methods for Feature Extraction and Classification 2007Galvanic skin response (GSR) as an index of cognitive load 2006Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables 2011A Stress-Detection System Based on Physiological Signals and Fuzzy Logic 2000Wearable and automotive systems for affect recognition from physiology 2001A review of psychological factors/processes affecting anxious responding during voluntary hyperventilation and inhalations of carbon dioxide-enriched air

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