Evaluation of Data Processing and Artifact Removal Approaches Used for Physiological Signals Captured Using Wearable Sensing Devices during Construction Tasks

Journal of Construction Engineering and Management, Год журнала: 2023, Номер 150(1)

Опубликована: Окт. 25, 2023

Wearable sensing devices (WSDs) have enormous promise for monitoring construction worker safety. They can track workers and send safety-related information in real time, allowing more effective preventative decision making. WSDs are particularly useful on sites since they workers' health, safety, activity levels, among other metrics that could help optimize their daily tasks. may also assist recognizing health-related safety risks (such as physical fatigue) taking appropriate action to mitigate them. The data produced by these WSDs, however, is highly noisy contaminated with artifacts been introduced the surroundings, experimental apparatus, or subject's physiological state. These very strong frequently found during field experiments. So, when there a lot of artifacts, signal quality drops. Recently, removal has greatly enhanced developments processing, which vastly performance. Thus, proposed review aimed provide an in-depth analysis approaches currently used analyze remove from signals obtained via construction-related First, this study provides overview likely be recorded monitor health Second, identifies most prevalent detrimental effect utility signals. Third, comprehensive existing artifact-removal were presented. Fourth, each identified artifact detection approach was analyzed its strengths weaknesses. Finally, conclusion, few suggestions future research improving captured using approaches.

Язык: Английский

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Identifying at-risk workers using fNIRS-based mental load classification: A mixed reality study

Automation in Construction, Год журнала: 2024, Номер 164, С. 105453 - 105453

Опубликована: Май 13, 2024

Язык: Английский

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Construction Technology Tools Impacting the AEC Industry in the Last 5 Years

Lecture notes in civil engineering, Год журнала: 2025, Номер unknown, С. 718 - 731

Опубликована: Янв. 1, 2025

Язык: Английский

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Comprehensive Systematic Literature Review on Cognitive Workload: Trends on Methods, Technologies, and Case Studies

IET Collaborative Intelligent Manufacturing, Год журнала: 2025, Номер 7(1)

Опубликована: Янв. 1, 2025

ABSTRACT Cognitive workload (CWL) assessment has gained traction in Industry 4.0 and 5.0, where human‐machine interactions are becoming more intricate. However, there is a lack of comprehensively addressed CWL by considering methodologies, technologies, case studies. The present work reviews 70 articles related to the assessment. review identifies five main methodologies for assessment: physiological measures (e.g. EEG, HRV, eye‐tracking), subjective evaluation NASA‐TLX), performance evaluation, cognitive load models, multimodal approaches. analysis shows an increasing trend towards approaches that combine methods with obtained from electroencephalography, eye‐tracking, heart rate monitoring devices. Additionally, emerging technologies such as augmented reality collaborative robots increasingly considered studies address current environments. Results reveal significant advancements methods, particularly emphasising real‐time capabilities context‐specific applications. Case underscore key role management assembly, maintenance, construction tasks, demonstrating its impact on performance, safety, adaptability dynamic This establishes framework advancing research addressing methodological limitations proposing future directions, including development personalised, adaptive systems management.

Язык: Английский

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Capturing Mental Workload Through Physiological Sensors in Human–Robot Collaboration: A Systematic Literature Review

Applied Sciences, Год журнала: 2025, Номер 15(6), С. 3317 - 3317

Опубликована: Март 18, 2025

Human–robot collaboration (HRC) is increasingly prevalent across various industries, promising to boost productivity, efficiency, and safety. As robotics technology advances takes on more complex tasks traditionally performed by humans, the nature of work demands workers are evolving. This shift emphasizes need critically integrate human factors into these interactions, as effectiveness safety systems highly dependent how cooperate with understand robots. A significant challenge in this domain lack a consensus most efficient way operationalize assess mental workload, which crucial for optimizing HRC. In systematic literature review, we analyze different psychophysiological measures that can reliably capture differentiate varying degrees workload HRC settings. The findings highlight standardized methodologies assessment enhance models. Ultimately, aims guide both theorists practitioners creating sophisticated, safe, frameworks providing comprehensive overview existing pointing out areas further study.

Язык: Английский

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Electrodermal Activity as an Indicator of Cognitive Load for Human-Robot Collaboration in Construction

Lecture notes in civil engineering, Год журнала: 2025, Номер unknown, С. 374 - 382

Опубликована: Янв. 1, 2025

Язык: Английский

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Systematic review of neurophysiological assessment techniques and metrics for mental workload evaluation in real-world settings

Frontiers in Neuroergonomics, Год журнала: 2025, Номер 6

Опубликована: Апрель 25, 2025

Mental Workload (MWL) is a concept that has garnered increasing interest in professional settings but remains challenging to define consensually. The literature reports plurality of operational definitions and assessment methods, with no established unified framework. This review aims identify objective validated measurement methods for evaluating MWL real-world work contexts. Particular attention given neurophysiological recognized their efficiency robustness, enabling real-time without disrupting operator activity. To conduct this analysis, systematic search was performed three databases (PubMed, ScienceDirect, IEEEXplore), covering studies published from inception until March 30, 2023. Selection criteria included research focusing on its derivatives, as well measures applied conditions. An initial screening based titles abstracts followed by an in-depth review, assisted the bibliometric software Rayyan. explored concepts, study results were compiled into synthesis table. Ultimately, 35 included, highlighting diversity tools used field settings, often combined subjective assessments. Furthermore, key physiological indicators such ECG, eye data, EEG relationship between metrics those uses measure stress are emphasized discussed. A better understanding these interrelations could refine respective impacts help anticipate consequences workers' mental health safety.

Язык: Английский

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Future of Construction Engineering Education in the Automation Era

Journal of Civil Engineering Education, Год журнала: 2025, Номер 151(4)

Опубликована: Май 23, 2025

Язык: Английский

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Exploring three pillars of construction robotics via dual-track quantitative analysis

Automation in Construction, Год журнала: 2024, Номер 162, С. 105391 - 105391

Опубликована: Март 23, 2024

Construction robotics has emerged as a leading technology in the construction industry. This paper conducts an innovative dual-track quantitative comprehensive method to analyze current literature and assess future trends. First, bibliometric review of 955 journal articles published between 1974 2023 was performed, exploring keywords, journals, countries, clusters. Furthermore, neural topic model based on BERTopic addresses modeling repetition issues. The study identifies building information (BIM), human–robot collaboration (HRC), deep reinforcement learning (DRL) "three pillars" field. Additionally, we systematically reviewed relevant nested symbiotic relationships. outcome this is twofold: first, findings provide qualitative scientific guidance for research trends; second, analysis methodology simultaneously stimulates critical thinking about other similarly trending topics characterized avoid high degree homogeneity corpus overlap.

Язык: Английский

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A neuroergonomics model for evaluating nuclear power plants operators’ performance under heat stress driven by ECG time-frequency spectrums and fNIRS prefrontal cortex network: A CNN-GAT fusion model

Advanced Engineering Informatics, Год журнала: 2024, Номер 62, С. 102563 - 102563

Опубликована: Апрель 29, 2024

Язык: Английский

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