Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/111982
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dc.contributorDepartment of Building and Real Estate-
dc.creatorFang, X-
dc.creatorLi, H-
dc.creatorMa, J-
dc.creatorXing, X-
dc.creatorFu, Z-
dc.creatorAntwi-Afari, MF-
dc.creatorUmer, W-
dc.date.accessioned2025-03-19T07:35:35Z-
dc.date.available2025-03-19T07:35:35Z-
dc.identifier.urihttp://hdl.handle.net/10397/111982-
dc.language.isoenen_US
dc.publisherMDPI AGen_US
dc.rights© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Fang, X., Li, H., Ma, J., Xing, X., Fu, Z., Antwi-Afari, M. F., & Umer, W. (2024). Assessment of Construction Workers’ Spontaneous Mental Fatigue Based on Non-Invasive and Multimodal In-Ear EEG Sensors. Buildings, 14(9), 2793 is available at https://doi.org/10.3390/buildings14092793.en_US
dc.subjectCognitive neuroscienceen_US
dc.subjectConstruction safetyen_US
dc.subjectDeep learningen_US
dc.subjectIn-ear sensorsen_US
dc.subjectMental fatigue monitoringen_US
dc.titleAssessment of construction workers’ spontaneous mental fatigue based on non-invasive and multimodal in-ear EEG sensorsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume14-
dc.identifier.issue9-
dc.identifier.doi10.3390/buildings14092793-
dcterms.abstractConstruction activities are often conducted in outdoor and harsh environments and involve long working hours and physical and mental labor, which can lead to significant mental fatigue among workers. This study introduces a novel and non-invasive method for monitoring and assessing mental fatigue in construction workers. Based on cognitive neuroscience theory, we analyzed the neurophysiological mapping of spontaneous mental fatigue and developed multimodal in-ear sensors specifically designed for construction workers. These sensors enable real-time and continuous integration of neurophysiological signals. A cognitive experiment was conducted to validate the proposed mental fatigue assessment method. Results demonstrated that all selected supervised classification models can accurately identify mental fatigue by using the recorded neurophysiological data, with evaluation metrics exceeding 80%. The long short-term memory model achieved an average accuracy of 92.437%. This study offers a theoretical framework and a practical approach for assessing the mental fatigue of on-site workers and provides a basis for the proactive management of occupational health and safety on construction sites.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationBuildings, Sept 2024, v. 14, no. 9, 2793-
dcterms.isPartOfBuildings-
dcterms.issued2024-09-
dc.identifier.scopus2-s2.0-85205218401-
dc.identifier.eissn2075-5309-
dc.identifier.artn2793-
dc.description.validate202503 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextHumanities and Social Sciences Fund of the Education Ministry of China; China Postdoctoral Science Foundationen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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