Abstract
Work stress faced by adults can lead to decreased job performance, reduced mental and physical wellbeing, and other detrimental health problems. Researchers are reporting resilience as a key factor in determining a person’s vulnerability towards mental stress disorders. Psychosocial measures of resilience conventionally use the self-assessment approach which is susceptible to potential biases caused by self-reporting and concerns of social stigma. With increasing emphasis of its role in mental health, researchers are using fMRI modality to identify the brain activity of stress resilience. But this approach is costly and lack practicality when evaluating stress resilience in daily tasks. The EEG modality provides a cost-efficient alternative with better practicality and high temporal resolution in studying the brain activity of stress resilience. However, EEG-based literatures on stress resilience are limited to brain activity during resting state. With reference to the cognitive affective conceptual stress model, we define stress resilience as an adaptation process, involving cognitive appraisal, physiological arousal and coping behaviour, that utilizes individual resources to cope with stress. This paper proposes an approach to identify the features of EEG-neural correlates of stress resilience through brain rhythms, hemispheric asymmetry and brain network.
| Original language | English |
|---|---|
| Title of host publication | International Conference on Artificial Intelligence for Smart Community - AISC 2020 |
| Editors | Rosdiazli Ibrahim, Ramani Kannan, Nursyarizal Mohd Nor, K. Porkumaran, S. Prabakar |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 807-816 |
| Number of pages | 10 |
| ISBN (Print) | 9789811621826 |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
| Event | 1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 - Virtual, Online Duration: 17 Dec 2020 → 18 Dec 2020 |
Publication series
| Name | Lecture Notes in Electrical Engineering |
|---|---|
| Volume | 758 |
| ISSN (Print) | 1876-1100 |
| ISSN (Electronic) | 1876-1119 |
Conference
| Conference | 1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 |
|---|---|
| City | Virtual, Online |
| Period | 17/12/20 → 18/12/20 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Keywords
- EEG feature
- Resilience
- Stress
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
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