Measuring acute stress response through physiological signals: towards a quantitative assessment of stress

Arza, Adriana ; Garzón-Rey, Jorge Mario ; Lázaro, Jesús (Universidad de Zaragoza) ; Gil, Eduardo (Universidad de Zaragoza) ; Lopez-Anton, Raul (Universidad de Zaragoza) ; de la Camara, Conchita (Universidad de Zaragoza) ; Laguna, Pablo (Universidad de Zaragoza) ; Bailon, Raquel (Universidad de Zaragoza) ; Aguiló, Jordi

Resumen: Social and medical problems associated with stress are increasing globally and seriously affect mental health and well-being. However, an effective stress-level monitoring method is still not available. This paper presents a quantitative method for monitoring acute stress levels in healthy young people using biomarkers from physiological signals that can be unobtrusively monitored. Two states were induced to 40 volunteers, a basal state generated with a relaxation task and an acute stress state generated by applying a standard stress test that includes five different tasks. Standard psychological questionnaires and biochemical markers were utilized as ground truth of stress levels. A multivariable approach to comprehensively measure the physiological stress response is proposed using stress biomarkers derived from skin temperature, heart rate, and pulse wave signals. Acute physiological stress levels (total-range 0–100 au) were continuously estimated every 1 min showing medians of 29.06 au in the relaxation tasks, while rising from 34.58 to 47.55 au in the stress tasks. Moreover, using the proposed method, five statistically different stress levels induced by the performed tasks were also measured. Results obtained show that, in these experimental conditions, stress can be monitored from unobtrusive biomarkers. Thus, a more general stress monitoring method could be derived based on this approach.

Idioma: Inglés

DOI: 10.1007/s11517-018-1879-z

Año: 2019

Publicado en: MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 57, 1 (2019), 271-287
ISSN: 0140-0118

Factor impacto JCR: 2.022 (2019)

Categ. JCR: MATHEMATICAL & COMPUTATIONAL BIOLOGY rank: 24 / 59 = 0.407 (2019) - Q2 - T2
Categ. JCR: MEDICAL INFORMATICS rank: 18 / 27 = 0.667 (2019) - Q3 - T3
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 61 / 109 = 0.56 (2019) - Q3 - T2
Categ. JCR: ENGINEERING, BIOMEDICAL rank: 58 / 87 = 0.667 (2019) - Q3 - T3

Factor impacto SCIMAGO: 0.552 - Computer Science Applications (Q2) - Biomedical Engineering (Q2)

Financiación: info:eu-repo/grantAgreement/EC/H2020/745755/EU/Wearable Cardiorespiratory Monitor/WECARMON

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)
Área (Departamento): Área Psicología Básica (Dpto. Psicología y Sociología)
Área (Departamento): Área Teoría Señal y Comunicac. (Dpto. Ingeniería Electrón.Com.)
Área (Departamento): Area Psiquiatría (Dpto. Medicina, Psiqu. y Derm.)