M.S. (Master of Science)
Department of Mechanical Engineering
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.
Alam, Umme Kawsar, "Imu-Based Estimation of Body Posture in Commercial Fishing" (2021). Graduate Research Theses & Dissertations. 6786.
Northern Illinois University
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