KALMAN FILTER BASED ESTIMATION OF INERTIAL MEASUREMENT UNIT PARAMETERS IN A PORTABLE BIOMECHANICAL ASSESSMENT SUITE (PBAS)
Open Access
Author:
Ramaswamy, Bharath
Graduate Program:
Electrical Engineering
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
None
Committee Members:
Dr H J Sommer Iii, Thesis Advisor/Co-Advisor H Joseph Sommer Iii, Thesis Advisor/Co-Advisor Kenneth Jenkins, Thesis Advisor/Co-Advisor
Keywords:
PBAS Kalman filtering IMU
Abstract:
Musculoskeletal disorders such as low back pain, joint injuries and repetitive strain injuries have affected a sizeable percentage of population in the US and are generally related to occupational tasks such as lifting. There have been several attempts to study the biomechanical aspects of such occupational tasks and quantify safe working practice. A Portable Biomechanical Assessment Suite (PBAS) was designed and tested to be worn by workers during their regular occupational activities and provide useful data for analysis. Kinematic data is measured by Inertial Measurement Units (IMUs) consisting of a three-axis accelerometer, a two-axis gyroscope, and a single-axis gyroscope. A Kalman Filter algorithm has been developed to smooth the data obtained from the IMU. Three different Kalman Filter algorithms, namely, Linear Kalman filter, Extended Kalman Filter and Unscented Kalman filter were implemented for this purpose and their performance has been compared based on the root mean square estimation error. Additionally, data sent from the IMU is sometimes lost due to radio packet collisions. A forward backward algorithm was developed to interpolate the missing values due to IMU dropouts.
