Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 12, Issue 3


Published
on

April 5, 2021


Pages

1350-1357


DOI

Article

Eustress and Distress Analysis Based on Neuro-Physiological Model of Affect


Authors

Norhaslinda Kamaruddin Affiliation:
Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40400 Shah Alam, Selangor, Malaysia
, Abdul Wahab Affiliation:
Kulliyah of Information and Communication Technology, International Islamic University Malaysia Gombak, Kuala Lumpur, Malaysia
and Hani Hunud A. Kadouf* Affiliation:
Kulliyah of Information and Communication Technology, International Islamic University Malaysia Gombak, Kuala Lumpur, Malaysia


Abstract

Researchers have focused on the negative effects of stress while its benefits have been relatively ignored. There has been limited studies to quantitatively understand the positive impact of stress. Although most of the studies were carried out by psychologist, in general, stress can be characterized by negative valence from the perspective of the affective state model (ASM). In fact, most recent psychological findings show that positive stress, also known as eustress, can improve motivation factor of an individual. In this paper we propose the use of electroencephalography (EEG) device to capture the brain's electrical activity in the frontal and central areas, in identifying positive (eustress) and negative (distress) stress. The distinctive brainwave patterns from the EEG device can be used to extract emotion/mood information of an individual and can be used to correlate the differing stress. The neurophysiological Model of affect (NPMoA) extracts the valence (V) and arousal (A) from the brainwave signals and correlate them to the psychological instruments for extracting eustress and distress. The Student Academic Stress Scale (SASS) will be used as the psychological instruments to extract eustress and distress. Preliminary results show the ability of using the EEG device to extract the brainwave pattern and to use in detecting stress based on the valence and arousal of the emotion. It is expected that NPMoA should be able to reveal correlation between positive emotions and eustress through the V and A. Such understanding can be extended to further analyze different stressors for academic stress and their effects on the brain signals.


Keywords

Eustress, Distress, Style, EEG, Student Academic Stress Scale, Affective Space Model


Citation

Kamaruddin, N., Wahab, A., & Kadouf, H. H. A. (2021). Eustress and distress analysis based on neuro-physiological model of affect. Turkish Journal of Computer and Mathematics Education, 12(3), 1350–1357.

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