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This study introduces an innovative approach to ergonomic risk assessment by integrating MoveNet Lightning, a human pose estimation model, with the Loading on the Upper Body Assessment (LUBA) framework. Aimed at preventing work-related musculoskeletal disorders (MSDs) in industrial settings, the research combines MoveNet Lightning’s rapid pose detection with LUBA’s ergonomic analysis. The system’s efficacy was tested in controlled environments and real-world scenarios, showing significant improvements in detecting ergonomic risks and informing interventions. Future work will focus on refining accuracy, expanding assessment capabilities, and implementing the system in practical applications to further mitigate MSD risks.

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Leveraging MoveNet Lightning for Ergonomic Risk Assessment Through LUBA

  • 会议论文

  • 发表日期：

    2025年

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  • Neelesh K. Sharma,
  • Kushal Dave,
  • Mayank Tiwari,
  • Atul Thakur,
  • Anindya K. Ganguli

摘要

This study introduces an innovative approach to ergonomic risk assessment by integrating MoveNet Lightning, a human pose estimation model, with the Loading on the Upper Body Assessment (LUBA) framework. Aimed at preventing work-related musculoskeletal disorders (MSDs) in industrial settings, the research combines MoveNet Lightning’s rapid pose detection with LUBA’s ergonomic analysis. The system’s efficacy was tested in controlled environments and real-world scenarios, showing significant improvements in detecting ergonomic risks and informing interventions. Future work will focus on refining accuracy, expanding assessment capabilities, and implementing the system in practical applications to further mitigate MSD risks.