Measuring elemental time and duty cycle using automated video processing

Details

• Personal Author:
  Akkas O ; Hu YH ; Lee C-H ; Radwin RG ; Yen TY
• Description:
  A marker-less 2D video algorithm measured hand kinematics (location, velocity, and acceleration) in a paced repetitive laboratory task for varying hand activity levels (HAL). The decision tree (DT) algorithm identified the trajectory of the hand using spatiotemporal relationships during the exertion and rest states. The feature vector training (FVT) method utilized the k-nearest neighborhood classifier, trained using a set of samples or the first cycle. The average duty cycle error using the DT algorithm was 2.7%. The FVT algorithm had an average 3.3% error when trained using the first cycle sample of each repetitive task, and had a 2.8% average error when trained using several representative repetitive cycles. Error for HAL was 0.1 for both algorithms, which was considered negligible. Elemental time, stratified by task and subject, were not statistically different from ground truth (p < .05). Both algorithms performed well for automatically measuring elapsed time, duty cycle and HAL. Description provided by NIOSH
• Subjects:
  • Musculoskeletal Diseases
  • Musculoskeletal System
  • Occupational Health
  • Risk Assessment
  • Risk Factors
  • Safety
  • Staff Development
• Keywords:
  • Repetitive-work
  • Hand-injuries
  • Training
  • Sampling
  • Musculoskeletal-system
  • Musculoskeletal-system-disorders
  • Exposure-levels
  • Risk-factors
  • Motion-studies
  • Analytical-instruments
  More +
• ISSN:
  0014-0139
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  OSHA Region 5 ; Wisconsin
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  59
• Issue:
  11
• NIOSHTIC Number:
  nn:20047405
• Citation:
  Ergonomics 2016 Nov; 59(11):1514-1525
• Contact Point Address:
  Robert G. Radwin, Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706
• Email:
  radwin@discovery.wisc.edu
• Federal Fiscal Year:
  2017
• NORA Priority Area:
  Manufacturing
• Performing Organization:
  University of Wisconsin-Madison
• Peer Reviewed:
  True
• Start Date:
  20120701
• Source Full Name:
  Ergonomics
• End Date:
  20150630
• Download URL:
  https://stacks.cdc.gov/view/cdc/202480/cdc_202480_DS1.pdf
• File Type:
  [PDF - 2.36 MB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:c2e5e6423ee21b411ae748275f07452d93ffdaade871ff5ddc02a28ab13cc99e5998c37150aa6f72ffdbc0ae84a87bccc1368f1d7d89ec8c81968d3b5a4bfd1b