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contributor authorMcGinnis, Ryan S.
contributor authorHough, Jessandra
contributor authorPerkins, Noel C.
date accessioned2017-11-25T07:20:23Z
date available2017-11-25T07:20:23Z
date copyright2017/24/1
date issued2017
identifier issn1555-1415
identifier othercnd_012_04_041010.pdf
identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4236414
description abstractMiniature wireless inertial measurement units (IMUs) hold great promise for measuring and analyzing multibody system dynamics. This relatively inexpensive technology enables noninvasive motion tracking in broad applications, including human motion analysis. This paper advances the use of an array of IMUs to estimate the joint reactions (forces and moments) in multibody systems via inverse dynamic modeling. In particular, this paper reports a benchmark experiment on a double-pendulum that reveals the accuracy of IMU-informed estimates of joint reactions. The estimated reactions are compared to those measured by high-precision miniature (6 degrees-of-freedom) load cells. Results from ten trials demonstrate that IMU-informed estimates of the three-dimensional reaction forces remain within 5.0% RMS of the load cell measurements and with correlation coefficients greater than 0.95 on average. Similarly, the IMU-informed estimates of the three-dimensional reaction moments remain within 5.9% RMS of the load cell measurements and with correlation coefficients greater than 0.88 on average. The sensitivity of these estimates to mass center location is discussed. Looking ahead, this benchmarking study supports the promising and broad use of this technology for estimating joint reactions in human motion applications.
publisherThe American Society of Mechanical Engineers (ASME)
titleAccuracy of Wearable Sensors for Estimating Joint Reactions
typeJournal Paper
journal volume12
journal issue4
journal titleJournal of Computational and Nonlinear Dynamics
identifier doi10.1115/1.4035667
journal fristpage41010
journal lastpage041010-10
treeJournal of Computational and Nonlinear Dynamics:;2017:;volume( 012 ):;issue: 004
contenttypeFulltext


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