Is low-cost motion capture with artificial intelligence applicable for human working posture risk assessment during manual material handling? A pilot study.
BACKGROUND: Assessing working posture risks is important for occupational safety and health. However, low-cost assessment techniques for human motion injuries in the logistics delivery industry have rarely been reported. OBJECTIVE: To propose a novel approach for posture risk assessment using low-co...
| Publicado en: | Work Vol. 74; no. 1; pp. 283 - 294 |
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| Autores principales: | , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2023
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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=161322892&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 161322892 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10519815 3RC jtl: Work issn: 10519815 maglogo: N pubinfo: dt: 2023 vid: 74 iid: 1 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 161322892 159650297 161322892 161322892 10.3233/WOR-205204 161322892 ppf: 283 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Is low-cost motion capture with artificial intelligence applicable for human working posture risk assessment during manual material handling? A pilot study. aug: au: Zhang, Renjie Niu, Jianwei Ran, Linghua affil: School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, China sug: subj: Motion Capture Utilization Artificial Intelligence Methods Occupational Diseases Posture Physiology Risk Assessment Evaluation Ergonomics Evaluation Cost Benefit Analysis Human Pilot Studies Occupational-Related Injuries Clinical Assessment Tools Occupational Safety Occupational Health Funding Source ab: BACKGROUND: Assessing working posture risks is important for occupational safety and health. However, low-cost assessment techniques for human motion injuries in the logistics delivery industry have rarely been reported. OBJECTIVE: To propose a novel approach for posture risk assessment using low-cost motion capture with artificial intelligence. METHODS: A Kinect was adopted to obtain red-green-blue (RGB) and depth images of the subject with 24 postures, and the human joints were extracted using artificial intelligence. The images were registered to obtain the actual three-dimensional (3D) human joint angle. RESULTS: The root mean square error (RMSE) significantly decreased. Finally, two common methods for evaluating human working posture injuries—the Rapid Upper Limb Assessment and Ovako Working Posture Analysis System—were investigated. CONCLUSIONS: The outputs of the proposed method are consistent with those of the commercial ergonomic evaluation software. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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