Joint angles of the lower extremities have been calculated using gyroscope and accelerometer measurements from inertial measurement units (IMUs) without sensor drift by leveraging kinematic constraints. However, it is unknown whether these methods are generalizable to the upper extremity due to differences in motion dynamics. Furthermore, the extent that post-processed sensor fusion algorithms can improve measurement accuracy relative to more commonly used Kalman filter-based methods remains unknown. This study calculated the elbow and wrist joint angles of 13 participants performing a simple ≥30 min material transfer task at three rates (slow, medium, fast) using IMUs and kinematic constraints. The best-performing sensor fusion algorithm produced total root mean square errors (i.e., encompassing all three motion planes) of 6.6°, 3.6°, and 2.0° for the slow, medium, and fast transfer rates for the elbow and 2.2°, 1.7°, and 1.5° for the wrist, respectively.
Keywords: biomechanical motion analysis; biomechanics; elbow; inertial measurement units; inertial motion capture; optimal estimation; self-calibration; smoothers; wrist.