Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/111982
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building and Real Estate | - |
| dc.creator | Fang, X | - |
| dc.creator | Li, H | - |
| dc.creator | Ma, J | - |
| dc.creator | Xing, X | - |
| dc.creator | Fu, Z | - |
| dc.creator | Antwi-Afari, MF | - |
| dc.creator | Umer, W | - |
| dc.date.accessioned | 2025-03-19T07:35:35Z | - |
| dc.date.available | 2025-03-19T07:35:35Z | - |
| dc.identifier.uri | http://hdl.handle.net/10397/111982 | - |
| dc.language.iso | en | en_US |
| dc.publisher | MDPI AG | en_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.rights | The 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.subject | Cognitive neuroscience | en_US |
| dc.subject | Construction safety | en_US |
| dc.subject | Deep learning | en_US |
| dc.subject | In-ear sensors | en_US |
| dc.subject | Mental fatigue monitoring | en_US |
| dc.title | Assessment of construction workers’ spontaneous mental fatigue based on non-invasive and multimodal in-ear EEG sensors | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 14 | - |
| dc.identifier.issue | 9 | - |
| dc.identifier.doi | 10.3390/buildings14092793 | - |
| dcterms.abstract | Construction 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.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Buildings, Sept 2024, v. 14, no. 9, 2793 | - |
| dcterms.isPartOf | Buildings | - |
| dcterms.issued | 2024-09 | - |
| dc.identifier.scopus | 2-s2.0-85205218401 | - |
| dc.identifier.eissn | 2075-5309 | - |
| dc.identifier.artn | 2793 | - |
| dc.description.validate | 202503 bcch | - |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | Humanities and Social Sciences Fund of the Education Ministry of China; China Postdoctoral Science Foundation | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| buildings-14-02793.pdf | 7.47 MB | Adobe PDF | View/Open |
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