Pre-service fatigue screening for construction workers through wearable EEG-based signal spectral analysis

Li, Heng; Wang, Di; Chen, Jiayu; Luo, Xiaochun; Li, Jue; Xing, Xuejiao

doi:10.1016/j.autcon.2019.102851

Cited by 70 publications

(30 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Li et al ( 2019 ) proposed four methods to identify fatigue. Most were derived from spectral features, which were used to establish a mental fatigue level (MFL).…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

LaRocco

Paeng

2020

Front. Neuroinform.

114

View full text Add to dashboard Cite

Drowsiness is a leading cause of traffic and industrial accidents, costing lives and productivity. Electroencephalography (EEG) signals can reflect awareness and attentiveness, and low-cost consumer EEG headsets are available on the market. The use of these devices as drowsiness detectors could increase the accessibility of safety and productivity-enhancing devices for small businesses and developing countries. We conducted a systemic review of currently available, low-cost, consumer EEG-based drowsiness detection systems. We sought to determine whether consumer EEG headsets could be reliably utilized as rudimentary drowsiness detection systems. We included documented cases describing successful drowsiness detection using consumer EEG-based devices, including the Neurosky MindWave, InteraXon Muse, Emotiv Epoc, Emotiv Insight, and OpenBCI. Of 46 relevant studies, ∼27 reported an accuracy score. The lowest of these was the Neurosky Mindwave, with a minimum of 31%. The second lowest accuracy reported was 79.4% with an OpenBCI study. In many cases, algorithmic optimization remains necessary. Different methods for accuracy calculation, system calibration, and different definitions of drowsiness made direct comparisons problematic. However, even basic features, such as the power spectra of EEG bands, were able to consistently detect drowsiness. Each specific device has its own capabilities, tradeoffs, and limitations. Widely used spectral features can achieve successful drowsiness detection, even with low-cost consumer devices; however, reliability issues must still be addressed in an occupational context.

show abstract

“…Li et al ( 2019 ) proposed four methods to identify fatigue. Most were derived from spectral features, which were used to establish a mental fatigue level (MFL).…”

Section: Resultsmentioning

confidence: 99%

“…Classification was performed with an SVM, and resulted in a reported accuracy of 94.4%. Li et al (2019) proposed four methods to identify fatigue. Most were derived from spectral features, which were used to establish a mental fatigue level (MFL).…”

Section: Openbci Ultracortexmentioning

confidence: 99%

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

LaRocco

Paeng

2020

Front. Neuroinform.

114

View full text Add to dashboard Cite

show abstract

“…According to the year of publication, all of the included studies were published in the last three years (2016–2019), with one publication in 2016 [10], five publications in 2017 [16,17,25,27,28], three publications in 2018 [8,29,30], and two publications in 2019 [31,32]. The information suggests a trend that EEG-based research on safety and risk management is an emerging topic that is growing fast and drawing increasing attentions from researchers.…”

Section: Eeg Measures In Relation To Construction Activitymentioning

confidence: 99%

“…There are two EEG models applied to the included studies. One commonly used model is EPOC+, with 14 channels and two reference electrodes–P3 and P4 locations according to the 10–20 system [8,16,25,28,29,30,31,32]. Three of the included studies employed the NeuroSky EEG headset for neural signal collection [10,17,27].…”

Section: Eeg Measures In Relation To Construction Activitymentioning

confidence: 99%

See 1 more Smart Citation

Scoping Review of EEG Studies in Construction Safety

Zhang

Fang

2019

IJERPH

View full text Add to dashboard Cite

Construction safety is critical in the success of a project. A considerable amount of effort has been placed on research and practice in order to reduce the potential risks on the construction site. Recent application of electroencephalogram (EEG) to construction research enables researchers to gain insight into construction workers’ physical and mental status during construction tasks. By summarizing existing studies that involve EEG and construction safety, the literature review aims to provide practical suggestions for future research and on-site safety management. The literature search and inclusion process included eleven eligible studies. Comprehensive analysis was conducted based on primary and secondary measures. The primary measures considered the frequency bands of EEG and the channels for detecting electrical activity of the brain. The secondary measures that were involved with physical and mental status with respect to EEG signal variations as a result of task, working hour, and work conditions. Although the field of study that combines EEG measures with construction tasks is still emerging, it is worth continuous attention in the future, as relevant findings would be of great value to the safety management and risk control in the construction industry.

show abstract

Neural mechanisms behind semantic congruity of construction safety signs: An EEG investigation on construction workers

et al. 2022

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

Accurate comprehension of safety signs plays a critical part in warning construction workers of potential work hazards. However, existing studies have rarely investigated construction workers' comprehension of safety signs at construction sites. Moreover, existing evaluation methods are generally based on subjective behavior tests, questionnaires, and interviews. Therefore, this study examined the effects of semantic congruity on the comprehension of safety signs, including two sign types (prohibition vs. warning signs) and two conditions (semantic congruence vs. incongruence), combining event‐related potentials and time‐frequency analysis measurements. Adopting the S1‐S2 paradigm, electroencephalogram data were recorded when participants decided whether S1 and S2 were semantically congruent or not. Results showed that the semantically incongruent safety sign‐word pairs elicited larger N400 amplitudes and increased theta (3–8 Hz) power in 300–420 ms. The amplitude of N400 in the semantically incongruent condition of the warning sign‐word pairs was more negative than that for the prohibition sign‐word pairs, while there were no significant differences between the prohibition and warning sign‐word pairs in the semantically congruent condition. A greater late positive potential (LPP) (550–750 ms) was also elicited in the semantically incongruent safety sign‐word pairs, which was different from previous studies that observed larger LPP in congruent conditions. These results suggest complicated cognitive mechanisms of safety sign comprehension in construction workers. This study extends safety sign comprehension research by using electrophysiological approaches and provides useful indicators for researchers or safety engineers to measure the semantic congruity of proposed sign designs.

show abstract

Pre-service fatigue screening for construction workers through wearable EEG-based signal spectral analysis

Cited by 70 publications

References 64 publications

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

Scoping Review of EEG Studies in Construction Safety

Neural mechanisms behind semantic congruity of construction safety signs: An EEG investigation on construction workers

Contact Info

Product

Resources

About