Next Article in Journal
Detecting Multi-Resolution Pedestrians Using Group Cost-Sensitive Boosting with Channel Features
Previous Article in Journal
A Novel Ionospheric Sounding Network Based on Complete Complementary Code and Its Application
Previous Article in Special Issue
Portable System for Real-Time Detection of Stress Level
Open AccessArticle

Computational Psychometrics Using Psychophysiological Measures for the Assessment of Acute Mental Stress

1
Applied Technology for Neuro-Psychology Lab at IRCCS Istituto Auxologico Italiano, Via L. Ariosto 13, 20145 Milano (MI), Italy
2
Department of Psychology of the Catholic University, Largo Gemelli 1, 20100 Milano (MI) and Applied Technology for Neuro-Psychology Lab at IRCCS Istituto Auxologico Italiano, Via L. Ariosto 13, 20145 Milano (MI), Italy
3
Department of Basic Psychology, Clinic and Psychobiology, Universitat Jaume I, Av. Sos Baynat, s/n, 12071 Castellón, Spain
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(4), 781; https://doi.org/10.3390/s19040781
Received: 11 November 2018 / Revised: 1 February 2019 / Accepted: 5 February 2019 / Published: 14 February 2019
(This article belongs to the Special Issue New Trends in Psychophysiology and Mental Health)
The goal of this study was to provide reliable quantitative analyses of psycho-physiological measures during acute mental stress. Acute, time-limited stressors are used extensively as experimental stimuli in psychophysiological research. In particular, the Stroop Color Word Task and the Arithmetical Task have been widely used in several settings as effective mental stressors. We collected psychophysiological data on blood volume pulse, thoracic respiration, and skin conductance from 60 participants at rest and during stressful situations. Subsequently, we used statistical univariate tests and multivariate computational approaches to conduct comprehensive studies on the discriminative properties of each condition in relation to psychophysiological correlates. The results showed evidence of a greater discrimination capability of the Arithmetical Task compared to the Stroop test. The best predictors were the short time Heart Rate Variability (HRV) indices, in particular, the Respiratory Sinus Arrhythmia index, which in turn could be predicted by other HRV and respiratory indices in a hierarchical, multi-level regression analysis. Thus, computational psychometrics analyses proved to be an effective tool for studying such complex variables. They could represent the first step in developing complex platforms for the automatic detection of mental stress, which could improve the treatment. View Full-Text
Keywords: computational psychometrics; psychophysiology; psychological stress; acute mental stress; acute time-limited stressors; Stroop color word task; arithmetic task computational psychometrics; psychophysiology; psychological stress; acute mental stress; acute time-limited stressors; Stroop color word task; arithmetic task
Show Figures

Figure 1

MDPI and ACS Style

Cipresso, P.; Colombo, D.; Riva, G. Computational Psychometrics Using Psychophysiological Measures for the Assessment of Acute Mental Stress. Sensors 2019, 19, 781.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop