Automatic Estimation of Hand Activity Level from Upper-Limb Trajectories: A Probabilistic Regression Framework

Details

• Journal Article:
  Ergonomics
• Personal Author:
  Lin, Ting-Hung ; Hu, Yu Hen ; Radwin, Robert
• Description:
  Accurate measurement of Hand Activity Level (HAL) is crucial for evaluating musculoskeletal injury risk in repetitive hand-intensive work. Manual HAL assessments are often subjective and impractical for large-scale or continuous monitoring. This study presents a probabilistic regression framework that leverages video-based upper-limb pose trajectories to automatically estimate HAL scores while providing associated confidence measures. By enabling ergonomic risk assessment with quantified uncertainty, the proposed method delivers objective and reliable HAL predictions. Experimental results demonstrate strong in-domain performance (Root Mean Square Error [RMSE] = 0.24, Mean Absolute Error [MAE] = 0.17) and robust cross-domain generalisation (RMSE = 0.74, MAE = 0.54), highlighting both the accuracy and transferability of the framework.
• Subjects:
  Ergonomics Hand Musculoskeletal Diseases Musculoskeletal System Occupational Health Safety
• Keywords:
  Author Keywords: Hand Activity Level; Probabilistic Regression; Computer Vision; Workplace Safety Ergonomics; Repetitive Work; Musculoskeletal Disorders; MSD; Upper Extremities; Hand Injuries; Risk Assessment; Motion Studies; Automation;
• Source:
  Ergonomics 2025 Aug; :[Epub ahead of print]
• ISSN:
  0014-0139
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Michigan ; Wisconsin ; Chicago Region [OSHA]
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  12 pdf pages
• NIOSHTIC Number:
  nn:20071366
• Contact Point Address:
  Robert Radwin, Department of Industrial & Systems Engineering, University of Wisconsin-Madison, Madison, WI, USA
• Email:
  rradwin@wisc.edu
• Federal Fiscal Year:
  2025
• Performing Organization:
  University of Michigan, Ann Arbor
• Peer Reviewed:
  True
• Start Date:
  20050701
• End Date:
  20280630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:35bb6bfee1ce25b33472ca815462eb7822a9408999e615cff2c6fcbb3cd9a8ef2721a17254b622c6e32a7993efe9499c3829119f7d6ad3e902a083d800ca4f81
• Download URL:
  https://stacks.cdc.gov/view/cdc/258841/cdc_258841_DS1.pdf
• File Type:
  [PDF - 3.50 MB ]