Turkish Journal of Computer and Mathematics Education Vol.12 No.3 (2021), 1350-1357 Research Article 1350 Eustress and Distress Analysis Based on Neuro-Physiological Model of Affect Norhaslinda Kamaruddin 1 , Abdul Wahab 2 , Hani Hunud A. Kadouf 3 1 Faculty of Computer and Mathematical Sciences, UniversitiTeknologi MARA, 40400 Shah Alam, Selangor, Malaysia 2,3 Kulliyah of Information and Communication Technology, International Islamic University Malaysia Gombak, Kuala Lumpur, Malaysia 1 norhaslinda@tmsk.uitm.edu.my, 2 abdulwahab@iium.edu.my, 3 *hani.ha@gmail.com Article History: Received: 10 November 2020; Revised: 12 January 2021; Accepted: 27January 2021; Published online: 05April 2021 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 corelate the differing stress. The neurophysiological Model of affect (NPMoA) extracts the valence (V) and arousal (A) from the brainwave signals and corelate then 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 1. Introduction Stress is a common response from various stressors that consists of physiological and psychological changes that may introduce illness and discomfort if recurrently experienced [1, 2]. It is viewed as an unavoidable part of life that has detrimental consequences such as chronic disease and loss of productivity. Selye [1] described stress by using three main components, namely; alarm, resistance, and exhaustion in a model coined as General Adaptation Syndrome (GAS). When an individual encounters threat or potential stressor, the alarm state is triggered. Typical physical reactions in this phase are the raise heart rates, goosebumps, increased adrenaline, and other symptoms that prepared the body for fight-or-flight reactions. If the stressor continues to exist, the individual is shifted to the resistance phase where coping mechanisms will be kicked in such as the strengthening of heart muscle and functions. This is a natural body defense and protection. However, if a longer stress situation persists than the body could cope; the individual normal function cannot be maintained. Such a situation is called the exhaustion phase. If an individual unable to cope with the pressure for such duration of time, the body may react in fatigue, burnout, depression, anxiety, and decreased stress tolerance. The physical effects of this stage also weaken the immune system and increase the risk of stress-related illnesses. Figure 1 shows percentage of Malaysian employees with depression symptoms from moderate to severe. Thus, it is obvious that teenagers between age 18 to 30 have high potential of depression which could be due to stress and need to be analyzed. As a subset of stress, stress occurs as a consequence of the pressure to succeed and has been shown to afflict university students in particular because the workload usually involves time constraints [3]. Moreover, other academic stressors in university may come in the form of overwhelming course material, continuous evaluation, unclear assignments, and poor teacher-student relationships [4]. According to the Yerkes-Dodson Law [5], stress is likely to increase the task performance of an individual to a point, but then performance decreases gain with too much stress. Stress is also shown to act as a modulator of memory processes and human learning, thus having major implications in academics. When stress is closely related to course material, memory capacity, and information retention has been shown to improve, while the opposite happens when stress is unrelated to course material [6]. Children with learning disabilities (LD) may even be at a higher risk and easily affected by stress and anxiety. LD children seem to have a low self-concept, generally less socially accepted, high locus of external control, and more anxious than normal children [7, 8]. However, Santos et al. [7] reported that there are no statistical differences for stress signs between children with and without LD. Hence, in this paper, the focus is aimed at academic stress for university students.