Worker safety and productivity are crucial for effective job management. Interruptions to an individual’s work environment and their impact on mental health can have adverse effects. One prospective instrument for assessing and calculating an individual’s mental state in an interrupted scenario and cognitive demand levels is the use of physiological computing devices in conjunction with behavioral and subjective measurements. This study sought to address how to gather and compute data on individuals’ cognitive states in interrupted work settings through critical analysis. Thirty-three papers were considered after the literature search and selection procedure. This descriptive study is conducted from three perspectives: parameter measurement, research design, and data analysis. The variables evaluated were working memory, stress, emotional state, performance, and resumption lag. The subject recruitment, experimental task design, and measurement techniques were examined from the standpoint of the experimental design. Data analysis included computing and cognitive pre-processing. Four future research directions are suggested to address the shortcomings of the present studies. This study offers suggestions for researchers on experiment planning and using computing to analyze individuals’ cognitive states during interrupted work scenarios. Additionally, it offers helpful recommendations for organizing and conducting future research.

This systematic review provides a comprehensive analysis of studies that use electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to investigate how acute stress affects decision-making processes. The primary goal of this systematic review was to examine the influence of acute stress on decision making in challenging or stressful situations. Furthermore, we aimed to identify the specific brain regions affected by acute stress and explore the feature extraction and classification methods employed to enhance the detection of decision making under pressure. Five academic databases were carefully searched and 27 papers that satisfied the inclusion criteria were found. Overall, the results indicate the potential utility of EEG and fNIRS as techniques for identifying acute stress during decision-making and for gaining knowledge about the brain mechanisms underlying stress reactions. However, the varied methods employed in these studies and the small sample sizes highlight the need for additional studies to develop more standardized approaches for acute stress effects in decision-making tasks. The implications of the findings for the development of stress induction and technology in the decision-making process are also explained.

The use of virtual reality (VR) has made significant advancements, and now it is widely used across a range of applications. However, consumers’ capacity to fully enjoy VR experiences continues to be limited by a chronic problem known as cybersickness (CS). This study explores the feasibility of mitigating CS through geometric scene simplification combined with electroencephalography (EEG)-based monitoring. According to the sensory conflict theory, this issue is caused by the discrepancy between the visually induced self-motion (VIMS) through immersive displays and the real motion the vestibular system detects. While prior mitigation strategies have largely relied on hardware modifications or visual field restrictions, this paper introduces a novel framework that integrates geometric scene simplification with EEG-based neurophysiological activity to reduce VIMS during VR immersion. The proposed framework combines EEG neurophysiology, allowing us to monitor users’ brainwave activity and cognitive states during virtual immersion experience. The empirical evidence from our investigation shows a correlation between CS manifestation and neural activation in the parietal and temporal lobes. As an experiment with 15 subjects, statistical differences were significantly different with $P= 0.001$ and large effect size $\eta 2=0.28$, while preliminary trends suggest lower neural activation during simplified scenes. Notably, a decrease in neural activation corresponding to reduced optic flow (OF) suggests that VR environment simplification may help attenuate CS symptoms, providing preliminary support for the proposed strategy.