View in EDS

Computer-aided technologies for posture-based ergonomic risk assessment in construction: a systematic review.

Saved in:
Bibliographic Details
Title: Computer-aided technologies for posture-based ergonomic risk assessment in construction: a systematic review.
Authors: Chellappa, Vigneshkumar1 (AUTHOR), Luximon, Yan1 (AUTHOR) yan.luximon@polyu.edu.hk
Source: International Journal of Construction Management. Jan2026, Vol. 26 Issue 2, p316-331. 16p.
Subjects: Posture, Building design & construction, Evaluation methodology, Machine learning, Wearable technology, Computer-aided engineering, Occupational hazards, Industrial hygiene
Abstract: The limitations of traditional postural ergonomic risk assessment (ERA) methods prompted the construction research community to turn to computer-aided technologies (CATs) for assistance. However, a comprehensive review is lacking to systematically examine the application of CATs for ERA in this context. This study aimed to understand the CATs used for ERA and their implementation trends, evaluate their technological capabilities, and practical applications, identify critical gaps in current research, and provide actionable insights. The systematic literature review (SLR) followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to retrieve relevant documents from the Scopus and Web of Science (WoS) databases. Based on the researcher's pre-established inclusion criteria, 85 papers were retrieved and subsequently analyzed through a content analysis approach. The findings revealed eight CATs adopted for ERA in construction wearable sensors, vision-based, machine learning/deep learning, exoskeletons, expert systems, virtual reality, computer-aided design, and digital twins. Further, the analysis uncovered various benefits and limitations of implementing each technology and identified critical gaps in the existing research. The findings emphasize the need for future research to address these gaps, explore broader applications, and integrate innovative solutions to enhance worker occupational health and well-being within the construction domain. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Construction Management is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 191012076
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Computer-aided technologies for posture-based ergonomic risk assessment in construction: a systematic review.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Chellappa%2C+Vigneshkumar%22">Chellappa, Vigneshkumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Luximon%2C+Yan%22">Luximon, Yan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yan.luximon@polyu.edu.hk</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Construction+Management%22">International Journal of Construction Management</searchLink>. Jan2026, Vol. 26 Issue 2, p316-331. 16p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Posture%22">Posture</searchLink><br /><searchLink fieldCode="DE" term="%22Building+design+%26+construction%22">Building design & construction</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Wearable+technology%22">Wearable technology</searchLink><br /><searchLink fieldCode="DE" term="%22Computer-aided+engineering%22">Computer-aided engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Occupational+hazards%22">Occupational hazards</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+hygiene%22">Industrial hygiene</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The limitations of traditional postural ergonomic risk assessment (ERA) methods prompted the construction research community to turn to computer-aided technologies (CATs) for assistance. However, a comprehensive review is lacking to systematically examine the application of CATs for ERA in this context. This study aimed to understand the CATs used for ERA and their implementation trends, evaluate their technological capabilities, and practical applications, identify critical gaps in current research, and provide actionable insights. The systematic literature review (SLR) followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to retrieve relevant documents from the Scopus and Web of Science (WoS) databases. Based on the researcher's pre-established inclusion criteria, 85 papers were retrieved and subsequently analyzed through a content analysis approach. The findings revealed eight CATs adopted for ERA in construction wearable sensors, vision-based, machine learning/deep learning, exoskeletons, expert systems, virtual reality, computer-aided design, and digital twins. Further, the analysis uncovered various benefits and limitations of implementing each technology and identified critical gaps in the existing research. The findings emphasize the need for future research to address these gaps, explore broader applications, and integrate innovative solutions to enhance worker occupational health and well-being within the construction domain. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Construction Management is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=191012076
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/15623599.2025.2520880
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 16
        StartPage: 316
    Subjects:
      – SubjectFull: Posture
        Type: general
      – SubjectFull: Building design & construction
        Type: general
      – SubjectFull: Evaluation methodology
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Wearable technology
        Type: general
      – SubjectFull: Computer-aided engineering
        Type: general
      – SubjectFull: Occupational hazards
        Type: general
      – SubjectFull: Industrial hygiene
        Type: general
    Titles:
      – TitleFull: Computer-aided technologies for posture-based ergonomic risk assessment in construction: a systematic review.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Chellappa, Vigneshkumar
      – PersonEntity:
          Name:
            NameFull: Luximon, Yan
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 01
              Text: Jan2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 15623599
          Numbering:
            – Type: volume
              Value: 26
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: International Journal of Construction Management
              Type: main
ResultId 1