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research-article

Multibody Muscle Driven Model of an Instrumented Prosthetic Knee During Squat and Toe Rise Motions

[+] Author and Article Information
Antonis P. Stylianou

Research Associate
e-mail: stylianoua@umkc.edu

Trent M. Guess

Associate Professor
e-mail: guesstr@umkc.edu

Mohammad Kia

Research Associate
e-mail: kiam@umkc.edu
Department of Civil & Mechanical Engineering,
Musculoskeletal Biomechanics Research Lab,
University of Missouri—Kansas City,
350K Robert H Flarsheim Hall,
5110 Rockhill Rd.,
Kansas City, MO 64110

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received August 22, 2012; final manuscript received March 1, 2013; accepted manuscript posted March 8, 2013; published online April 5, 2013. Assoc. Editor: Brian D. Stemper.

J Biomech Eng 135(4), 041008 (Apr 05, 2013) (14 pages) Paper No: BIO-12-1369; doi: 10.1115/1.4023982 History: Received August 22, 2012; Revised March 01, 2013

Detailed knowledge of knee joint kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. The need for dynamic computational models that link kinematics, muscle and ligament forces, and joint contacts has long been recognized but such body-level forward dynamic models do not exist in recent literature. A main barrier in using computational models in the clinic is the validation of the in vivo contact, muscle, and ligament loads. The purpose of this study was to develop a full body, muscle driven dynamic model with subject specific leg geometries and validate it during squat and toe-rise motions. The model predicted loads were compared to in vivo measurements acquired with an instrumented knee implant. Data for this study were provided by the “Grand Challenge Competition to Predict In-Vivo Knee Loads” for the 2012 American Society of Mechanical Engineers Summer Bioengineering Conference. Data included implant and bone geometries, ground reaction forces, EMG, and the instrumented knee implant measurements. The subject specific model was developed in the multibody framework. The knee model included three ligament bundles for the lateral collateral ligament (LCL) and the medial collateral ligament (MCL), and one bundle for the posterior cruciate ligament (PCL). The implanted tibia tray was segmented into 326 hexahedral elements and deformable contacts were defined between the elements and the femoral component. The model also included 45 muscles on each leg. Muscle forces were computed for the muscle driven simulation by a feedback controller that used the error between the current muscle length in the forward simulation and the muscle length recorded during a kinematics driven inverse simulation. The predicted tibia forces and torques, ground reaction forces, electromyography (EMG) patterns, and kinematics were compared to the experimentally measured values to validate the model. Comparisons were done graphically and by calculating the mean average deviation (MAD) and root mean squared deviation (RMSD) for all outcomes. The MAD value for the tibia vertical force was 279 N for the squat motion and 325 N for the toe-rise motion, 45 N and 53 N for left and right foot ground reaction forces during the squat and 94 N and 82 N for toe-rise motion. The maximum MAD value for any of the kinematic outcomes was 7.5 deg for knee flexion-extension during the toe-rise motion.

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Figures

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Fig. 1

Full body multibody model with artificial left knee and discretized tibia insert

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Fig. 2

Model predicted and measured tibial component forces and torques during squat motion

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Fig. 3

Model predicted and measured ground reaction forces for left and right feet during squat motion

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Fig. 4

Computed joint kinematics during muscle driven simulation (FD) versus inverse dynamics simulation (ID) during squat motion

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Fig. 5

Model predicted muscle activations versus measured normalized EMG for the primary muscles involved in squat motion

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Fig. 6

Contact pressure (N/mm2) distribution on tibia component during one cycle of squat motion

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Fig. 7

Model predicted and measured tibial component forces and torques during toe-rise motion

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Fig. 8

Model predicted and measured ground reaction forces for left and right feet during toe-rise motion

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Fig. 9

Computed joint kinematics during muscle driven simulation (FD) versus inverse dynamics simulation (ID) during toe-rise motion

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Fig. 10

Model predicted muscle activations versus measured normalized EMG for the primary muscles involved in toe-rise motion

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Fig. 11

Contact pressure (N/mm2) distribution on tibia component during one cycle of toe-rise motion

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