Artificial intelligence and emerging technologies in assessing ergonomic risk factors in the workplace: A systematic review.
Background: Emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) improve ergonomic risk assessment and control. Objective: This systematic review aims to investigate the use of artificial intelligence and emerging technologies in assessing...
| Publicado en: | Work Vol. 82; no. 3; pp. 727 - 740 |
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| Autores principales: | , , , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
Nov2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=189650139&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189650139 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10519815 3RC jtl: Work issn: 10519815 maglogo: N pubinfo: dt: Nov2025 vid: 82 iid: 3 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 189650139 186026614 189650139 189650139 10.1177/10519815251349793 189650139 ppf: 727 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial intelligence and emerging technologies in assessing ergonomic risk factors in the workplace: A systematic review. aug: au: Safari, Mahdi Naserbakht, Amir Hossein Badri Kouhi, Arghavan Varmazyar, Sakineh affil: Department of Occupational Health Engineering, Faculty of Health, Student Research Committee, Qazvin University of Medical Sciences, Qazvin, Iran sug: subj: Artificial Intelligence Utilization Digital Technology Utilization Ergonomics Work Environment Risk Assessment Musculoskeletal Diseases Risk Factors Human Systematic Review Descriptive Statistics Machine Learning Internet of Things Data Science PubMed Accelerometers Occupational Health Wearable Sensors Electromyography ab: Background: Emerging technologies like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT) improve ergonomic risk assessment and control. Objective: This systematic review aims to investigate the use of artificial intelligence and emerging technologies in assessing ergonomic risk factors in the workplace. Methods: This study focuses on ergonomic risk assessment using AI, ML, and the IoT by analyzing published articles in English from 2013 to 2023. The search excluded review articles, books, letters, correspondence, and conference papers. Various keyword combinations related to "ergonomic risk assessment", "ergonomics", "Artificial Intelligence", "machine learning", "Internet of Things", and "data science" were used in the search. Literature was collected from Web of Science, Scopus, PubMed, ProQuest, and Google Scholar. Out of 140 primary literature sources, 19 studies were selected based on the PRISMA approach. Results: Some articles (68%) have developed risk assessment systems using AI, ML, and IoT to collect data on workers' physical conditions and assess their postures. 32% of studies developed wearable devices to predict musculoskeletal disorder risks. Studies employ accelerometers and ML to automatically identify activities, improving ergonomic risk assessment. Researchers predict musculoskeletal disorder risks using computer vision, AI algorithms, and ML, along with ergonomic assessment systems and accelerometers. Conclusion: Implementing smart wearable devices for ergonomic risk assessment is important. AI and machine learning in these devices enable real-time monitoring of workers' movements and postures, identifying potential hazards associated with musculoskeletal disorders. This technology improves the efficiency and accuracy of risk assessments, reducing costs and time compared to traditional methods. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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