Sensor Fusion Algorithm to Improve Accuracy of Robotic Superposition Testing Using Six-Degree-of-Freedom Position Sensors

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 difference in joint forces before and after transecting the ligament is assumed to be the transected ligament's tension. However, the robotic test system's ability to accurately return the joint to the commanded pose is dependent on the compliance of the system's 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: (1) describe a testing methodology with 6DOF 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 6DOF position sensors with robot pose measurements to compensate for system compliance. For the equipment, loading condition, and surrogate knee joint used in this study, the Traditional control method underestimated ligament tension by 23% while the Sensor Fusion control method brought that error down 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.

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Publication Details

Journal
Journal of Biomechanical Engineering
Published
2025-09-01
DOI
https://doi.org/10.1115/1.4069591
Primary Topic
Muscle activation and electromyography studies
Type
article
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article

Sensor Fusion Algorithm to Improve Accuracy of Robotic Superposition Testing Using Six-Degree-of-Freedom Position Sensors

Callan M. Gillespie, Robb Colbrunn, Joshua D. Roth, Lesley Arant
Journal of Biomechanical Engineering
Muscle activation and electromyography studies
article

Sensor Fusion Algorithm to Improve Accuracy of Robotic Superposition Testing Using Six-Degree-of-Freedom Position Sensors

Callan M. Gillespie, Robb Colbrunn, Joshua D. Roth, Lesley Arant
article en

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 difference in joint forces before and after transecting the ligament is assumed to be the transected ligament's tension. However, the robotic test system's ability to accurately return the joint to the commanded pose is dependent on the compliance of the system's 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: (1) describe a testing methodology with 6DOF 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 6DOF position sensors with robot pose measurements to compensate for system compliance. For the equipment, loading condition, and surrogate knee joint used in this study, the Traditional control method underestimated ligament tension by 23% while the Sensor Fusion control method brought that error down 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.

Journal of Biomechanical EngineeringVol. 147(11)
Cleveland State University (US), University of Wisconsin System (US), Cleveland Clinic (US), University of Wisconsin–Madison (US), Cleveland Foundation (US), Cleveland Clinic Lerner College of Medicine (US)
Openalex Percentile: Top 78%
Muscle activation and electromyography studies
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