Work

Stress detection by means of stress physiological template

Year: 2011

Type: conference-paper

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.

Source: World Congress on Nature and Biologically Inspired Computing (NaBIC)

DOI: 10.1109/nabic.2011.6089448

Authors: Alberto de Santos Sierra, Carmen Sanchez Avila, Gonzalo Bailador del Pozo, Javier Guerra Casanova

Institution: Universidad Politécnica de Madrid

Language: English

Topic: Emotion and Mood Recognition

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W2054466600

FWCI: 3.051

Cites: 28

Cited by: 51

Related to: 10