Subject-specific knee joint geometry improves predictions of medial tibiofemoral contact forces

Gerus, Pauline<sup>1</sup>; Sartori, Massimo<sup>2</sup>; Besier, Thor F.<sup>3</sup>; Fregly, Benjamin J.<sup>4,5,6</sup>; Delp, Scott L.<sup>7</sup>; Banks, Scott A.<sup>4,5,6</sup>; Pandy, Marcus G.<sup>8</sup>; D'Lima, Darryl D.<sup>9</sup>; Lloyd, David G.<sup>1</sup>

Affiliations

¹Centre for Musculoskeletal Research, Griffith Health Institute, Griffith University, Southport, QLD, Australia

²Bernstein Center for Computational Neuroscience, Georg-August University, Göttingen, Germany

³Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand

⁴Department of Mechanical & Aerospace Engineering, University of Florida, Gainesville, FL, USA

⁵Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA

⁶Department of Orthopedics & Rehabilitation, University of Florida, Gainesville, FL, USA

⁷Department of Mechanical Engineering, Stanford University, Stanford, CA, USA

⁸Department of Mechanical Engineering, University of Melbourne, Melbourne, VIC, Australia

⁹Shiley Center for Orthopedic Research & Education at Scripps Clinic, La Jolla, CA, USA

Abstract and keywords

Estimating tibiofemoral joint contact forces is important for understanding the initiation and progression of knee osteoarthritis. However, tibiofemoral contact force predictions are influenced by many factors including muscle forces and anatomical representations of the knee joint. This study aimed to investigate the influence of subject-specific geometry and knee joint kinematics on the prediction of tibiofemoral contact forces using a calibrated EMG-driven neuromusculoskeletal model of the knee. One participant fitted with an instrumented total knee replacement walked at a self-selected speed while medial and lateral tibiofemoral contact forces, ground reaction forces, whole-body kinematics, and lower-limb muscle activity were simultaneously measured. The combination of generic and subject-specific knee joint geometry and kinematics resulted in four different OpenSim models used to estimate muscle–tendon lengths and moment arms. The subject-specific geometric model was created from CT scans and the subject-specific knee joint kinematics representing the translation of the tibia relative to the femur was obtained from fluoroscopy. The EMG-driven model was calibrated using one walking trial, but with three different cost functions that tracked the knee flexion/extension moments with and without constraint over the estimated joint contact forces. The calibrated models then predicted the medial and lateral tibiofemoral contact forces for five other different walking trials. The use of subject-specific models with minimization of the peak tibiofemoral contact forces improved the accuracy of medial contact forces by 47% and lateral contact forces by 7%, respectively compared with the use of generic musculoskeletal model.

Keywords: EMG-driven modeling; Knee joint model; Contact force; Muscle force

Links

DOI: 10.1016/j.jbiomech.2013.09.005

PubMed: 24074941

WoS: 000328093200004

History

Accepted: 2013-09-5

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2015	Pizzolato C, Lloyd DG, Sartori M, Ceseracciu E, Besier TF, Fregly BJ, Reggiani M. CEINMS: a toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks. J Biomech. November 5, 2015;48(14):3929-3936.
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