Publication Date
2021
Document Type
Dissertation/Thesis
First Advisor
Ryu, Ji-Chul
Degree Name
M.S. (Master of Science)
Legacy Department
Department of Mechanical Engineering
Abstract
According to the U.S. Bureau of Labor Statistics (BLS), work-related musculoskeletaldisorders (WMSDs) account for 33% of all occupational injuries and illnesses in the U.S. In addition, one of the most strenuous occupations in which musculoskeletal disorders are common is known to be commercial fishing. The first step to address this issue is to precisely measure the working postures of workers so that the relation between WMSDs and nonneutral working postures can be systematically investigated. Although the inertial measurement unit (IMU) has recently gained attention in posture measurement due to its portability, it is highly limited to the use as an accelerometer that is only suited to static 2-dimensional tilting-angle measurements. Although a gyroscope can measure 3-dimensional orientations even with dynamic (accelerated) motions, they have been avoided in the measurement of postures due to their intrinsic nature of a drift phenomenon, which could lead to a significant error over time. Therefore, in this thesis, two sensor fusion methods, in which all three sets of sensors (3-axis accelerometer, 3-axis gyroscope, 3-axis magnetometer) in an IMU are utilized, are explored to achieve the 3-dimensional orientation estimation with higher accuracy. The two methods of complementary filter and Kalman filter are implemented to estimate the orientation of the torso and arm in two simulated tasks that are common in commercial fishing. The estimation accuracy of each filter in those tasks is verified using the reference data measured using a motion capture system consisting of multiple vision cameras.
Recommended Citation
Alam, Umme Kawsar, "Imu-Based Estimation of Body Posture in Commercial Fishing" (2021). Graduate Research Theses & Dissertations. 6786.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/6786
Extent
57 pages
Language
eng
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text