Identification of low back injury from EMG signals using a neural network model

Details

• Personal Author:
  Hou Y ; Karwowski W ; Marras WS ; Zurada JM
• Description:
  We propose a novel neural network model for the identification of low back injury using electromyography (EMG) data. By connecting task condition variables to the second hidden-layer of the neural network, the importance of those variables can be improved. A 4-muscle method and a 10-muscle method are discussed. A higher classification accuracy was achieved by the 10-muscle method since it takes the correlation between muscle activities into account. We also found that identification accuracy decreases when the object weight or the lifting height increases. The obtained results improve our understanding of low back disorders and provide important guidance for future experimental studies. [Description provided by NIOSH]
• Subjects:
  Air Movements Air Pollution Air Pollution, Indoor Environmental Monitoring Mining Occupational Health Safety Ventilation
• Keywords:
  Biomechanical-modeling Biomechanics Computer-models Manual-lifting Manual-materials-handling Materials-handling Mathematical-models Models Musculoskeletal-system
• ISBN:
  9780780394902
• Publisher:
  Institute of Electrical and Electronics Engineers
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Proceedings
• Place as Subject:
  Kentucky ; Ohio ; OSHA Region 4 ; OSHA Region 5
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• NIOSHTIC Number:
  nn:20041200
• Citation:
  Proceedings of International Joint Conference on Neural Networks, July 16-21, 2006, Vancouver, BC, Canada. Piscataway, NJ: Institute of Electrical and Electronics Engineers, 2006 Jul; :5309-5315
• Federal Fiscal Year:
  2006
• Performing Organization:
  Ohio State University
• Peer Reviewed:
  False
• Start Date:
  20020930
• Source Full Name:
  Proceedings of International Joint Conference on Neural Networks, July 16-21, 2006, Vancouver, BC, Canada
• End Date:
  20070929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:a3703290c10ba1c9900990e443630df52d400dec95a144bb06dfc3e574214dc6dc501e66e4e2ab9756d34b36b501fcdce5dfd9c0497b1ae8766db77d7e06d800
• Download URL:
  https://stacks.cdc.gov/view/cdc/193810/cdc_193810_DS1.pdf
• File Type:
  [PDF - 14.24 MB ]