Accuracy of angular displacements and velocities from inertial-based inclinometers

Chen, Howard; Schall, Mark C.; Fethke, Nathan

doi:10.1016/j.apergo.2017.09.007

i

Accuracy of angular displacements and velocities from inertial-based inclinometers

Supporting Files

2 2018
By Chen, Howard ; Schall, Mark C. ; Fethke, Nathan
http://dx.doi.org/10.1016/j.apergo.2017.09.007
Available in CDC Stacks on 2022-10-26T00:00:00Z

File Language:

English

Details

Alternative Title:

Appl Ergon
Personal Author:

Chen, Howard ; Schall, Mark C. ; Fethke, Nathan
Description:

The objective of this study was to evaluate the accuracy of various sensor fusion algorithms for measuring upper arm elevation relative to gravity (i.e., angular displacement and velocity summary measures) across different motion speeds. Thirteen participants completed a cyclic, short duration, arm-intensive work task that involved transfering wooden dowels at three work rates (slow, medium, fast). Angular displacement and velocity measurements of upper arm elevation were simultaneously measured using an inertial measurement unit (IMU) and an optical motion capture (OMC) system. Results indicated that IMU-based inclinometer solutions can reduce root-mean-square errors in comparison to accelerometer-based inclination estimates by as much as 87%, depending on the work rate and sensor fusion approach applied. The findings suggest that IMU-based inclinometers can substantially improve inclinometer accuracy in comparison to traditional accelerometer-based inclinometers. Ergonomists may use the non-proprietary sensor fusion algorithms provided here to more accurately estimate upper arm elevation.
Subjects:
Source:

Appl Ergon. 67:151-161
Pubmed ID:

29122186
Pubmed Central ID:

PMC9605618
Document Type:

Journal Article
Funding:

T42 OH008436/OH/NIOSH CDC HHSUnited States/ ; T42 OH008491/OH/NIOSH CDC HHSUnited States/ ; T42OH008436/ACL/ACL HHSUnited States/ ; T42OH008491/ACL/ACL HHSUnited States/
Volume:

67
Download URL:

https://stacks.cdc.gov/view/cdc/121975/cdc_121975_DS1.pdf
File Type:

[PDF - 2.59 MB]
Collection(s):

CDC Public Access
Main Document Checksum:

urn:sha256:237d06493f66a78592c730da662756b25a9af96286eaac686e9014cf4355b533

File Language:

English

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