A physiological signal-based method for early mental-stress detection

The early detection of mental stress is critical for efficient clinical treatment. As compared with traditional approaches, the automatic methods presented in literature have shown significance and effectiveness in terms of diagnosis speed. Unfortunately, the majority of them mainly focus on accurac...

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Main Authors: Xia, L., Malik, A.S., Subhani, A.R.
Format: Article
Published: Elsevier Ltd 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049878566&doi=10.1016%2fj.bspc.2018.06.004&partnerID=40&md5=791744336e8ccd93606a80e8ffa5ee72
http://eprints.utp.edu.my/20778/
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spelling my.utp.eprints.207782019-02-26T02:24:03Z A physiological signal-based method for early mental-stress detection Xia, L. Malik, A.S. Subhani, A.R. The early detection of mental stress is critical for efficient clinical treatment. As compared with traditional approaches, the automatic methods presented in literature have shown significance and effectiveness in terms of diagnosis speed. Unfortunately, the majority of them mainly focus on accuracy rather than predictions for treatment efficacy. This may result in the development of methods that are less robust and accurate, which is unsuitable for clinical purposes. In this study, we propose a comprehensive framework for the early detection of mental stress by analysing variations in both electroencephalogram (EEG) and electrocardiogram (ECG) signals from 22 male subjects (mean age: 22.54 ± 1.53 years). The significant contribution of this paper is that the presented framework is capable of performing predictions for treatment efficacy, which is achieved by defining four stress levels and creating models for the individual level. The experimental results indicate that the framework has realised an accuracy, a sensitivity, and a specificity of 79.54, 81, and 78, respectively. Moreover, the results indicate significant neurophysiological differences between the stress and control (stress-free) conditions at the individual level. © 2018 The Authors Elsevier Ltd 2018 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049878566&doi=10.1016%2fj.bspc.2018.06.004&partnerID=40&md5=791744336e8ccd93606a80e8ffa5ee72 Xia, L. and Malik, A.S. and Subhani, A.R. (2018) A physiological signal-based method for early mental-stress detection. Biomedical Signal Processing and Control, 46 . pp. 18-32. http://eprints.utp.edu.my/20778/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description The early detection of mental stress is critical for efficient clinical treatment. As compared with traditional approaches, the automatic methods presented in literature have shown significance and effectiveness in terms of diagnosis speed. Unfortunately, the majority of them mainly focus on accuracy rather than predictions for treatment efficacy. This may result in the development of methods that are less robust and accurate, which is unsuitable for clinical purposes. In this study, we propose a comprehensive framework for the early detection of mental stress by analysing variations in both electroencephalogram (EEG) and electrocardiogram (ECG) signals from 22 male subjects (mean age: 22.54 ± 1.53 years). The significant contribution of this paper is that the presented framework is capable of performing predictions for treatment efficacy, which is achieved by defining four stress levels and creating models for the individual level. The experimental results indicate that the framework has realised an accuracy, a sensitivity, and a specificity of 79.54, 81, and 78, respectively. Moreover, the results indicate significant neurophysiological differences between the stress and control (stress-free) conditions at the individual level. © 2018 The Authors
format Article
author Xia, L.
Malik, A.S.
Subhani, A.R.
spellingShingle Xia, L.
Malik, A.S.
Subhani, A.R.
A physiological signal-based method for early mental-stress detection
author_facet Xia, L.
Malik, A.S.
Subhani, A.R.
author_sort Xia, L.
title A physiological signal-based method for early mental-stress detection
title_short A physiological signal-based method for early mental-stress detection
title_full A physiological signal-based method for early mental-stress detection
title_fullStr A physiological signal-based method for early mental-stress detection
title_full_unstemmed A physiological signal-based method for early mental-stress detection
title_sort physiological signal-based method for early mental-stress detection
publisher Elsevier Ltd
publishDate 2018
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049878566&doi=10.1016%2fj.bspc.2018.06.004&partnerID=40&md5=791744336e8ccd93606a80e8ffa5ee72
http://eprints.utp.edu.my/20778/
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