Measuring Upper Arm Elevation Using an Inertial Measurement Unit: An Exploration of Sensor Fusion Algorithms and Gyroscope Models

Details

• Personal Author:
  Chen H ; Fethke NB ; Schall MC Jr.
• Description:
  Many sensor fusion algorithms for analyzing human motion information collected with inertial measurement units have been reported in the scientific literature. Selecting which algorithm to use can be a challenge for ergonomists that may be unfamiliar with the strengths and limitations of the various options. In this paper, we describe fundamental differences among several algorithms, including differences in sensor fusion approach (e.g., complementary filter vs. Kalman Filter) and gyroscope error modeling (i.e., inclusion or exclusion of gyroscope bias). We then compare different sensor fusion algorithms considering the fundamentals discussed using laboratory-based measurements of upper arm elevation collected under three motion speeds. Results indicate peak displacement errors of <4.5 degrees with a computationally efficient, non-proprietary complementary filter that did not account for gyroscope bias during each of the one-minute trials. Controlling for gyroscope bias reduced peak displacement errors to <3.0 degrees. The complementary filters were comparable (<1 degrees peak displacement difference) to the more complex Kalman filters. [Description provided by NIOSH]
• Subjects:
  Biomechanical Phenomena Ergonomics Musculoskeletal System Occupational Health Safety
• Keywords:
  Author Keywords: Inclinometer Biomechanics Complementary Filter Exposure Assessment Inertial-based Motion Capture Inertial Measurement Units Kalman Filter Measurement Equipment Motion Studies Sensors Upper Extremities

  More +
• ISSN:
  0003-6870
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Alabama ; Iowa ; OSHA Region 4 ; OSHA Region 7
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  89
• NIOSHTIC Number:
  nn:20062569
• Citation:
  Appl Ergon 2020 Nov; 89:103187
• Contact Point Address:
  Howard Chen, Department of Mechanical Engineering, Auburn University, AL, USA
• Email:
  hzc0074@auburn.edu
• Federal Fiscal Year:
  2021
• Performing Organization:
  University of Iowa
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Applied Ergonomics
• End Date:
  20290630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:d573d539b1c4abfda810fc24443219ad0cdbc29ba56fb8a8c22f344eca0f06c0fd6a01d486242b1723c5c25d78532760f4d2ed055d933e769499eeec2a50669f
• Download URL:
  https://stacks.cdc.gov/view/cdc/225786/cdc_225786_DS1.pdf
• File Type:
  [PDF - 1.17 MB ]