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Assessing Exposure to Slip, Trip, and Fall Hazards by Measuring Construction Worker Loss of Balance

DC Field Value Language
dc.contributor.authorLee, Hoonyong-
dc.contributor.authorLee, Gaang-
dc.contributor.authorLee, SangHyun-
dc.contributor.authorAhn, Changbum Ryan-
dc.date.accessioned2024-05-20T00:39:24Z-
dc.date.available2024-05-20T00:39:24Z-
dc.date.created2024-05-16-
dc.date.issued2022-
dc.identifier.citationCOMPUTING IN CIVIL ENGINEERING 2021, pp.66-73-
dc.identifier.urihttps://hdl.handle.net/10371/203351-
dc.description.abstractA worker repeatedly exposed to slip, trip, and fall (STF) hazards is at an increased risk of an STF event. To monitor an individual's exposure to STF hazards, previous approaches have assessed the loss of body balance (LOB). However, these approaches were not fully validated in field settings, where dynamic workplace environments can impact workers' bodily movements. This study aims to develop and evaluate a new approach to assess workers' exposures to STF hazards by LOB assessment in a real construction site. A waist-worn inertial measurement unit sensor was used to extract features of waist movements, which were modified into a single value to measure LOB using the Mahalanobis distance (MD) metric. The MD value was calculated for each step a worker took, and exposure to the STF hazards was detected when the MD value was larger than a predetermined threshold. The results provided an average of an unweighted average recall of 89.13% (without exposures: 90.30%, and with exposures: 87.96%) that would strongly indicate generalizability and robustness for practical applications.-
dc.language영어-
dc.publisherAMER SOC CIVIL ENGINEERS-
dc.titleAssessing Exposure to Slip, Trip, and Fall Hazards by Measuring Construction Worker Loss of Balance-
dc.typeArticle-
dc.citation.journaltitleCOMPUTING IN CIVIL ENGINEERING 2021-
dc.identifier.wosid000948933100009-
dc.identifier.scopusid2-s2.0-85132547863-
dc.citation.endpage73-
dc.citation.startpage66-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorAhn, Changbum Ryan-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.subject.keywordPlusDETECTION ALGORITHM-
dc.subject.keywordPlusACCELEROMETERS-
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  • College of Engineering
  • Department of Architecture & Architectural Engineering
Research Area Computing in Construction, Management in Construction

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