Assessment of mental fatigue using electroencephalography (EEG) and virtual reality (VR) for construction fall hazard prevention

Abstract

PurposeDespite the importance of cognitive monitoring, limited studies attempted to continuously monitor cognitive status of workers regarding mental fatigue effects on fall hazard. Thus, the objective of this study is to investigate and understand the effects of working at height on mental fatigue development for fall hazard prevention.Design/methodology/approachA quantitative framework using two well-known methods, i.e. Wavelet Packet Decomposition and Sample entropy, is developed to analyze the captured brain signals from Electroencephalography (EEG) to quantitatively assess mental fatigue levels, and seven mental fatigue indices were obtained. Between-subjects lab experiment was designed and conducted to assess mental fatigue in Virtual Reality (VR) environment.FindingsBoth of the quantitative methods confirmed that height exposure can adversely affect subjects' vigilance levels and indicated higher levels of mental fatigue. Significant differences were found between the two tested groups (i.e. working at height or on the ground) for six out of seven indices. The results suggested that working-at-height group had higher mental fatigue levels.Research limitations/implicationsOne limitation of this study is the limited number of subjects recruited for the experiment. Overall, this study is a preliminary and exploratory work towards mental fatigue monitoring and assessment in subjects exposed to fall risk.Originality/valueThis is the first study to explore and focus on mental fatigue assessment, particularly for construction falling-from-height hazard prevention by continuously monitoring mental fatigue levels of workers. The research provides insight into construction safety enhancement using smart technologies.

Immersive virtual reality in AECO/FM to enhance education: Systematic literature review and future directions

“…In regard to the current findings, other factors affecting DL are explained in the previous sections [18, 21, 41, 42, 50, 51, 69, 109–111, 114, 120]. In this section, the effects of IVR on DL are discussed in terms of aspects of media and method research.…”

“…Although some papers utilizing the NASA-TLX index investigated mental workload [6,30,48,120], Han et al [42] examined overall cognitive load. Out of them, learning performance was only evaluated by Han et al [42] (with cognitive load) and Tehrani et al [120] (with mental workload).…”

“…Although some papers utilizing the NASA-TLX index investigated mental workload [6,30,48,120], Han et al [42] examined overall cognitive load. Out of them, learning performance was only evaluated by Han et al [42] (with cognitive load) and Tehrani et al [120] (with mental workload). According to educational psychology [68], the relationship between the mental workload indicator NASA-TLX and cognitive load is not entirely clear.…”

Application of Neuroscience Tools in Building Construction – An Interdisciplinary Analysis

“…Construction hazard recognition is the most frequently applied topic. EEG can be applied to measure the level of physical and mental fatigue among construction workers and assess the safety hazards, such as trips, falls, and impacts, caused by workers’ mental and emotional state including depression, and stress, thereby improving health and productivity ( Hasanzadeh et al, 2018 ; Tehrani et al, 2021 ). Scholars have also employed eye tracking to explore the visual search and attention allocation patterns of workers with different personality traits, knowledge levels, and experience levels ( Fu et al, 2022 ).…”

ISM-based analysis of VR-AEC adoption barriers and their inner mechanisms

“…Most VR-AEC experiments are conducted on engineering students (You et al, 2018;Yeom et al, 2019;Akanmu et al, 2020a;Chen et al, 2021), whose experience levels or dynamics are not as representative as that of construction workers (Tixier et al, 2014). (3) Besides, the sampling size is complained by (Paes et al, 2017;Prabhakaran et al, 2021;Tehrani et al, 2021;Xu and Zheng, 2021). (4) Finally, many studies pointed out that value metrics were limited to subject questionnaires without objective methods (Sampaio and Martins, 2014;Woo et al, 2016;Taehoon et al, 2019).…”