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.
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Acknowledgements
This research is supported by Ministry of Higher Education Malaysia (MoHE) under Higher Institution Centre of Excellence (HICoE) Scheme awarded to Center for Intelligent Signal and Imaging Research (CISIR).
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Hasan, R.A., Ali, S.S.A., Tang, T.B., Yusoff, M.S.B. (2022). Finding the EEG Footprint of Stress Resilience. In: Ibrahim, R., K. Porkumaran, Kannan, R., Mohd Nor, N., S. Prabakar (eds) International Conference on Artificial Intelligence for Smart Community. Lecture Notes in Electrical Engineering, vol 758. Springer, Singapore. https://doi.org/10.1007/978-981-16-2183-3_76
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DOI: https://doi.org/10.1007/978-981-16-2183-3_76
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