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2017 | OriginalPaper | Chapter

Detection of Stress Level and Phases by Advanced Physiological Signal Processing Based on Fuzzy Logic

Authors : Unai Zalabarria, Eloy Irigoyen, Raquel Martínez, Asier Salazar-Ramirez

Published in: International Joint Conference SOCO’16-CISIS’16-ICEUTE’16

Publisher: Springer International Publishing

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Abstract

Stress has a big impact in the current society, being the cause or the incentive of several diseases. Therefore, its detection and monitorization has been the focus of a big number of investigations in the last decades. This work proposes the use of physiological variables such as the electrocardiogram (ECG), the galvanic skin response (GSR) and the respiration (RSP) in order to estimate the level and classify the type of stress. On that purpose, an algorithm based on fuzzy logic has been implemented. This computer-intelligent technique has been combined with a structured processing shaped in state machine. This processing classifies stress in 3 different phases or states: alarm, continued stress and relax. An improved estimation of stress level is obtained at the end, considering the last progresses made by different authors. All this is accompanied by stress classification, which is the novelty compared to other works.

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Title: Detection of Stress Level and Phases by Advanced Physiological Signal Processing Based on Fuzzy Logic
Authors: Unai Zalabarria
Eloy Irigoyen
Raquel Martínez
Asier Salazar-Ramirez
Publisher: Springer International Publishing
Book: International Joint Conference SOCO’16-CISIS’16-ICEUTE’16
Print ISBN: 978-3-319-47363-5

Electronic ISBN: 978-3-319-47364-2

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-3-319-47364-2_29

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