Sensor Fusion Algorithm to Improve Accuracy of Robotic Superposition Testing using 6-DOF Position Sensors

Abstract

To quantify the contributions of specific ligaments to overall joint biomechanics, the principle of superposition has been used for nearly 30 years. This principle relies on a robotic test system to move a biological joint to the same pose before and after transecting a ligament. The magnitude of the vector difference in joint forces before and after transecting the ligament is assumed to be the transected ligaments tension. However, the robotic test systems ability to accurately return the joint to the commanded pose is dependent on the compliance of the systems various components, which is often neglected. An alternative approach to superposition testing is to use additional sensors attached directly to the joint to inform robot motion. Accordingly, there are two objectives in this manuscript: (1) Describe a testing methodology with 6-DOF position sensors to correct for system compliance, and (2) Demonstrate the effectiveness of this methodology to reduce uncertainty of in-situ forces determined using superposition. A Sensor Fusion algorithm fuses 6-DOF position sensors with robot pose measurements to compensate for system compliance. Using a surrogate knee joint with the Traditional testing method, errors in pose of approximately 100 microns resulted in a 23% underestimation of computed ligament tension. With the Sensor Fusion algorithm, errors in pose fell below the noise floor of the 6-DOF position sensors, and errors in computed ligament tension were reduced to 3%. Thus, this Sensor Fusion algorithm is a promising approach to minimize errors in superposition testing caused by compliance in a robotic test system.