Comparative Analysis of Inertial Sensor to Optical Motion Capture System Performance in Push-Pull Exertion Postures
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2016/09/01
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Description:This study examined interactions between inertial sensor (IS) performance and physical task demand on posture kinematics in a two-handed force exertion task. Fifteen male individuals participated in a laboratory experiment that involved exerting a two-handed isometric horizontal force on an instrumented height-adjustable handle. Physical task demand was operationalized by manipulating vertical handle height, target force magnitude, and force direction. These factors were hypothesized to influence average estimates of torso flexion angle measured using inertial sensors and an optical motion capture (MC) system, as well as the root mean squared errors (RMSE) between instrumentation computed over a 3s interval of the force exertion task. Results indicate that lower handle heights and higher target force levels were associated with increased torso and pelvic flexion in both, push and pull exertions. Torso flexion angle estimates obtained from IS and MC did not differ significantly. However, RMSE increased with target force intensity suggesting potential interactive effects between measurement error and physical task demand. [Description provided by NIOSH]
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ISSN:1071-1813
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Volume:60
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Issue:1
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NIOSHTIC Number:nn:20052511
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Citation:Proceedings of the Human Factors and Ergonomics Society 60th Annual Meeting, September 19-23, 2016, Washington, DC. Santa Monica, CA: Human Factors and Ergonomics Society, 2016 Sep; 60(1):970-974
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Contact Point Address:Sol Lim, Center for Ergonomics, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI
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Federal Fiscal Year:2016
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Performing Organization:University of Michigan, Ann Arbor
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Peer Reviewed:True
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Start Date:20050701
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Source Full Name:Proceedings of the Human Factors and Ergonomics Society 60th Annual Meeting, September 19-23, 2016, Washington, DC
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End Date:20280630
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Main Document Checksum:urn:sha-512:e0d69384b61ff6522833b0326ebfef9cec1581ecd443c683c1ced843773e751b18a523e31ee1ab761556405806cf244b5a983d7b9adbe74f8b7bc19c4d4e5dcb
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