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A Work-Related Musculoskeletal Disorders (WMSDs) Risk-Assessment System Using a Single-View Pose Estimation Model

Author

Listed:
  • Young-Jin Kwon

    (Intelligent Robotics Research Division, Electronics and Telecommunications Research Institute, Daejeon 34129, Korea
    School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Korea)

  • Do-Hyun Kim

    (Intelligent Robotics Research Division, Electronics and Telecommunications Research Institute, Daejeon 34129, Korea)

  • Byung-Chang Son

    (Department of Rehabilitation Technology, Korea Nazarene University, Cheonan 31172, Korea)

  • Kyoung-Ho Choi

    (Department of Electronics Engineering, Mokpo National University, Muan 58554, Korea)

  • Sungbok Kwak

    (Advanced Engineering Team, Duckyang Co., Ltd., Suwon 16229, Korea)

  • Taehong Kim

    (School of Information and Communication Engineering, Chungbuk National University, Cheongju 28644, Korea)

Abstract

Musculoskeletal disorders are an unavoidable occupational health problem. In particular, workers who perform repetitive tasks onsite in the manufacturing industry suffer from musculoskeletal problems. In this paper, we propose a system that evaluates the posture of workers in the manufacturing industry with single-view 3D human pose-estimation that can estimate the posture in 3D using an RGB camera that can easily acquire the posture of a worker in a complex workplace. The proposed system builds a Duckyang-Auto Worker Health Safety Environment (DyWHSE), a manufacturing-industry-specific dataset, to estimate the wrist pose evaluated by the Rapid Limb Upper Assessment (RULA). Additionally, we evaluate the quality of the built DyWHSE dataset using the Human3.6M dataset, and the applicability of the proposed system is verified by comparing it with the evaluation results of the experts. The proposed system provides quantitative assessment guidance for working posture risk assessment, assisting the continuous posture assessment of workers.

Suggested Citation

  • Young-Jin Kwon & Do-Hyun Kim & Byung-Chang Son & Kyoung-Ho Choi & Sungbok Kwak & Taehong Kim, 2022. "A Work-Related Musculoskeletal Disorders (WMSDs) Risk-Assessment System Using a Single-View Pose Estimation Model," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:9803-:d:883750
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    References listed on IDEAS

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    2. Chunxi Huang & Woojoo Kim & Yanxin Zhang & Shuping Xiong, 2020. "Development and Validation of a Wearable Inertial Sensors-Based Automated System for Assessing Work-Related Musculoskeletal Disorders in the Workspace," IJERPH, MDPI, vol. 17(17), pages 1-15, August.
    3. Nicola Carbonaro & Gabriele Mascherini & Ilenia Bartolini & Maria Novella Ringressi & Antonio Taddei & Alessandro Tognetti & Nicola Vanello, 2021. "A Wearable Sensor-Based Platform for Surgeon Posture Monitoring: A Tool to Prevent Musculoskeletal Disorders," IJERPH, MDPI, vol. 18(7), pages 1-15, April.
    4. Muhamad Nurul Hisyam Yunus & Mohd Hafiidz Jaafar & Ahmad Sufril Azlan Mohamed & Nur Zaidi Azraai & Md. Sohrab Hossain, 2021. "Implementation of Kinetic and Kinematic Variables in Ergonomic Risk Assessment Using Motion Capture Simulation: A Review," IJERPH, MDPI, vol. 18(16), pages 1-14, August.
    5. Mattia Guidolin & Emanuele Menegatti & Monica Reggiani, 2022. "UNIPD-BPE : Synchronized RGB-D and Inertial Data for Multimodal Body Pose Estimation and Tracking," Data, MDPI, vol. 7(6), pages 1-14, June.
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    Cited by:

    1. Davide Gattamelata & Mario Fargnoli, 2022. "Development of a New Procedure for Evaluating Working Postures: An Application in a Manufacturing Company," IJERPH, MDPI, vol. 19(22), pages 1-20, November.

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