Load Asymmetry Angle Estimation Using Multiple-View Videos

Details

• Personal Author:
  Hu YH ; Lu M-L ; Radwin RG ; Wang X
• Description:
  A robust computer vision-based approach is developed to estimate the load asymmetry angle defined in the revised NIOSH lifting equation. The angle of asymmetry enables the computation of a recommended weight limit for repetitive lifting operations in a workplace to prevent lower back injuries. An open-source package OpenPose is applied to estimate the two-dimensional (2-D) locations of skeletal joints of the worker from two synchronous videos. Combining these joint location estimates, a computer vision correspondence and depth estimation method is developed to estimate the 3-D coordinates of skeletal joints during lifting. The angle of asymmetry is then deduced from a subset of these 3-D positions. Error analysis reveals unreliable angle estimates due to occlusions of upper limbs. A robust angle estimation method that mitigates this challenge is developed. We propose a method to flag unreliable angle estimates based on the average confidence level of 2-D joint estimates provided by OpenPose. An optimal threshold is derived that balances the percentage variance reduction of the estimation error and the percentage of angle estimates flagged. Tested with 360 lifting instances in a NIOSH-provided dataset, the standard deviation of angle estimation error is reduced from 10.13 degrees to 4.99 degrees. To realize this error variance reduction, 34% of estimated angles are flagged and require further validation. [Description provided by NIOSH]
• Subjects:
  Computers Musculoskeletal Diseases Musculoskeletal System Occupational Health Preventive Medicine Safety Software
• Keywords:
  Author Keywords: Asymmetry Angle Computer Software Injuries Low Back Pain Manual Lifting MSD Musculoskeletal System Disorders NIOSH Lifting Equation Overexertion Preventive Measures Repetitive Work Three-dimensional (3-D) Skeletal Joints Estimation Upper Extremities Video Monitoring

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• ISSN:
  2168-2291
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  Ohio ; OSHA Region 5 ; Wisconsin
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DFSE - Division of Field Studies and Engineering
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  51
• Issue:
  5
• NIOSHTIC Number:
  nn:20063955
• Citation:
  IEEE Trans Hum-Mach Syst 2021 Dec; 51(5):734-739
• Contact Point Address:
  Yu Hen Hu, Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706
• Email:
  yhhu@wisc.edu
• Federal Fiscal Year:
  2022
• NORA Priority Area:
  Construction
• Peer Reviewed:
  True
• Source Full Name:
  IEEE Transactions on Human-Machine Systems
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:5309abeebffd6f341ce788faffb48f9d20ed79cab57a58563c1ae2e23e43396421bc8096c1c6d98cec247aa5dc447f1709b6d54e1a9d74c175b269579ee12198
• Download URL:
  https://stacks.cdc.gov/view/cdc/222488/cdc_222488_DS1.pdf
• File Type:
  [PDF - 1014.07 KB ]