Acute stress state classification based on electrodermal activity modeling

Greco, A. ; Valenza, G. ; Lázaro, J. (Universidad de Zaragoza) ; Garzón-Rey, J. M. ; Aguiló, J. ; De la Cámara, C. ; Bailón, Raquel (Universidad de Zaragoza) ; Scilingo, Enzo Pascuale

Resumen: Acute stress is a physiological condition that may induce several neural dysfunctions with a significant impact on life quality. Accordingly, it would be important to monitor stress in everyday life unobtrusively and inexpensively. In this paper, we presented a new methodological pipeline to recognize acute stress conditions using electrodermal activity (EDA) exclusively. Particularly, we combined a rigorous and robust model (cvxEDA) for EDA processing and decomposition, with an algorithm based on a support vector machine to classify the stress state at a single- subject level. Indeed, our method, based on a single sensor, is robust to noise, applies a rigorous phasic decomposition, and implements an unbiased multiclass classification. To this end, we analyzed the EDA of 65 volunteers subjected to different acute stress stimuli induced by a modified version of the Trier Social Stress Test. Our results show that stress is successfully detected with an average accuracy of 94.62%. Besides, we proposed a further 4-class pattern recognition system able to distinguish between non-stress condition and three different stressful stimuli achieving an average accuracy as high as 75.00%. These results, obtained under controlled conditions, are the first step towards applications in ecological scenarios.

Idioma: Inglés

DOI: 10.1109/TAFFC.2021.3055294

Año: 2023

Publicado en: IEEE transactions on affective computing 14, 1 (2023), 788-799
ISSN: 1949-3045

Factor impacto JCR: 9.6 (2023)

Categ. JCR: COMPUTER SCIENCE, CYBERNETICS rank: 1 / 32 = 0.031 (2023) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 14 / 197 = 0.071 (2023) - Q1 - T1

Factor impacto CITESCORE: 15.0 - Human-Computer Interaction (Q1) - Software (Q1)

Factor impacto SCIMAGO: 2.645 - Software (Q1) - Human-Computer Interaction (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/LMP44-18
Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group
Financiación: info:eu-repo/grantAgreement/EC/H2020/745755/EU/Wearable Cardiorespiratory Monitor/WECARMON
Financiación: info:eu-repo/grantAgreement/ES/MICIU/RTI2018-097723-B-I00

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)