Date of Degree
PhD (Doctor of Philosophy)
First Committee Member
Nathan B Fethke
Second Committee Member
Geb W Thomas
Third Committee Member
David G Wilder
Fourth Committee Member
Fifth Committee Member
Accurate risk assessment tools and methods are necessary to understand the relationship between occupational exposure to physical risk factors and musculoskeletal disorders. Ergonomists typically consider direct measurement methods to be the most objective and accurate of the available tools. However, direct measurement methods are often not used due to cost, practicality, and worker/workplace disruption.
Inertial measurement units (IMUs), a relatively new direct measurement technology used to assess worker kinematics, are attractive to ergonomists due to their small size, low cost, and ability to reliably capture information across full working shifts. IMUs are often touted as a field-capable alternative to optical motion capture systems (OMCs). The error magnitudes of IMUs, however, can vary significantly (>15°) both within and across studies. The overall goals of this thesis were to (i) provide knowledge about the capabilities and limitations of IMUs in order to explain the inconsistencies observed in previous studies that assessed IMU accuracy, and (ii) provide guidance for the ergonomics community to leverage this technology. All three studies in this dissertation systematically evaluated IMUs using a repetitive material transfer task performed by thirteen participants with varying movement speeds (15, 30, 45 cycles/minute) and magnetic disturbance (absent, present). An OMC system was used as the reference device.
This first study systematically evaluated the effects of motion speed and magnetic disturbance on the spatial orientation accuracy of an inertial measurement unit (IMU) worn on the hand. Root-mean-square differences (RMSD) exceeded 20° when inclination measurements (pitch and roll) were calculated using the IMU’s accelerometer. A linear Kalman filter and a proprietary, embedded Kalman filter reduced inclination RMSD to < 3° across all movement speeds. The RMSD in the heading direction (i.e., about gravity) increased (from < 5° to 17°) under magnetic disturbance. The linear Kalman filter and the embedded Kalman filter reduced heading RMSD to < 12° and < 7°, respectively. This study indicated that the use of IMUs and Kalman filters can improve inclinometer measurement accuracy. However, magnetic disturbances continue to limit the accuracy of three-dimensional IMU motion capture.
The goal of the second study was to understand the capability of IMU inclinometers to improve estimates of angular displacements and velocities of the upper arm. RMSD and peak displacement error exceeded 11° and 28° at the fastest transfer rate (45 cycles/min) when upper arm elevation was calculated using the IMU accelerometer. The implementation of a Kalman filter reduced RMS and peak errors to < 1.5° and < 2.3°, respectively. Similarly, the RMS and peak error for accelerometer-derived velocities exceeded 81°/s and 221.3°/s, respectively, at the fastest transfer rate. The Kalman filter reduced RMS and peak errors to < 9.2°/s and < 25.1°/s, respectively.
The third study was conducted to evaluate the relationship between magnetic field strength variation and magnetic heading deviation. In this study, the presence of the metal plate increased magnetic heading deviations from < 12° (90th-10th percentile) to approximately 30°. As expected, the magnetic field strength standard deviation increased from 1.0uT to 2.4uT. While this relationship may differ across other sources of magnetic disturbance, the results reinforce the notion that local magnetic field disturbances should be minimized when using IMUs for human motion capture.
Overall, the findings from this thesis contribute to the ergonomics community’s understanding of the current capabilities and limitations of IMUs. These studies suggest that while the touted capabilities of the IMUs (full-body motion capture in workplace settings) may be unattainable based on current sensor technology, these sensors are still significantly more accurate than the accelerometer-based inclinometers commonly used by ergonomists to measure motions of the upper arms.
Musculoskeletal disorders of the upper extremity are among the most common and expensive of all occupational injuries and illnesses. Understanding and measuring the risk factors associated with these conditions is important for improving worker health and well-being. The measurement systems available for this purpose, however, are quite limited. Inertial measurement units (IMUs), a relatively new technology available for measuring important aspects of worker motion in the field, offer improved data collection prospects for ergonomists. However, the accuracy of IMUs can vary beyond clinically- acceptable levels. The overall goals of this thesis were to (i) provide knowledge about the capabilities and limitations of IMUs in order to explain the inconsistencies observed in previous studies that have assessed IMU accuracy, and (ii) provide guidance for the ergonomics community to leverage this technology within its current capabilities. The studies in this dissertation systematically examined factors known to adversely affect IMU accuracy. Results suggested that the advertised capabilities of IMUs (full-body motion capture in workplace settings) may not be achievable using current sensor technologies. However, these sensors are still substantially more accurate than the devices commonly used by ergonomists to measure upper extremity postures and movements in field settings.
Biomechanics, Ergonomics, Inertial Measurement Units, Inertial Motion Capture, Motion Capture, Occupational Ergonomics
x, 109 pages
Includes bibliographical references (pages 89-97).
Copyright © 2017 Howard Chen
Chen, Howard. "The effects of movement speeds and magnetic disturbance on inertial measurement unit accuracy: the implications of sensor fusion algorithms in occupational ergonomics applications." PhD (Doctor of Philosophy) thesis, University of Iowa, 2017.