Development of an Algorithm for Automatically Assessing Lifting Risk Factors Using Inertial Measurement Units

Details

• Personal Author:
  Barim MS ; Feng S ; Hayden M ; Hughes G ; Lu M-L ; Werren D
• Description:
  The objective of this study was to develop an algorithm for automatically processing data collected with inertial measurement unit (IMU) wearable devices to measure lifting risk factors for low back disorders. Five IMU sensors attached to five body segments were used for developing the algorithm. The algorithm consists of two modules running in parallel for detecting the beginning and ending of a lifting event as well as the vertical height (V) of the object lifted by two hands and the horizontal (H) distance between the object and the body during the lift. The motion synchronization feature of wrists' motion data were used to train the lifting detection module using a machine learning approach. This module achieved a training accuracy of 85%. In the second module, the forearm length and gyroscope data of four sensors are proposed for calculating trunk flexion angle, V and H during a lift. [Description provided by NIOSH]
• Subjects:
  Epidemiology Lung Lung Diseases Mining Neoplasms Occupational Health Radiation Radon Respiratory System Respiratory Tract Diseases Risk Assessment Risk Factors Safety Smokers Tobacco Products Vehicle Emissions

  More +
• Keywords:
  Algorithms Computer Equipment Computers Extremities Lifting Manual Lifting Musculoskeletal System Posture Statistical Analysis Wearable Technologies
• ISSN:
  1071-1813
• Publisher:
  Human Factors and Ergonomics Society
• Document Type:
  Text
• Genre:
  Proceedings
• Place as Subject:
  California ; Ohio ; OSHA Region 5 ; OSHA Region 9
• 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:
  63
• Issue:
  1
• NIOSHTIC Number:
  nn:20058254
• Citation:
  Proceedings of the Human Factors and Ergonomics Society 63rd Annual Meeting, October 28 - November 1, 2019, Seattle, Washington. Santa Monica, CA: Human Factors and Ergonomics Society, 2019 Nov; 63(1):1334-1338
• Contact Point Address:
  Ming-Lun Lu, National Institute for Occupational Safety and Health, Cincinnati, Ohio
• Federal Fiscal Year:
  2020
• NORA Priority Area:
  Manufacturing
• Peer Reviewed:
  True
• Source Full Name:
  Proceedings of the Human Factors and Ergonomics Society 63rd Annual Meeting, October 28 - November 1, 2019, Seattle, Washington
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:993f9aada2f9e1eb32cc0659a184096295a0dff6cd7b2cf5e68741de3631ebb620f411493ee1eb95eb0872fa5975e69e3a074514f67aa3c6c4f8056c79ab49a5
• Download URL:
  https://stacks.cdc.gov/view/cdc/221384/cdc_221384_DS1.pdf
• File Type:
  [PDF - 1.24 MB ]