IMU-based estimation of body posture: Laboratory validation in simulated commercial fishing

Abstract

Work-related musculoskeletal disorders (WMSDs) account for a significant portion of all occupational injuries and illnesses in the U.S. This is especially concerning for physically demanding professions such as commercial fishing and farming. To investigate the relationship between WMSDs and non-neutral working postures, it is necessary to accurately quantify the working postures. However, due to the challenging working environment, for example, offshore and wet conditions in commercial fishing, objective biomechanical assessment using video or optical-based motion capture systems is extremely difficult. Therefore, this paper proposes an alternative approach to quantify body postures using an inertial measurement unit (IMU) sensor. We employed an IMU to determine the orientation of the torso and arm during two simulated commercial fishing tasks in a laboratory setting using two sensor fusion methods: complementary filter and Kalman filter. The estimation accuracy of each filter in these tasks is validated and compared using reference data obtained from a motion capture system that utilizes multiple vision cameras.