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

    Source: Journal of Biomechanical Engineering:;2013:;volume( 135 ):;issue: 004::page 41008
    Author:
    Stylianou, Antonis P.
    ,
    Guess, Trent M.
    ,
    Kia, Mohammad
    DOI: 10.1115/1.4023982
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: 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 bodylevel 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 toerise 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 InVivo Knee Loadsâ€‌ 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 toerise motion, 45 N and 53 N for left and right foot ground reaction forces during the squat and 94 N and 82 N for toerise motion. The maximum MAD value for any of the kinematic outcomes was 7.5 deg for knee flexionextension during the toerise motion.
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      Multibody Muscle Driven Model of an Instrumented Prosthetic Knee During Squat and Toe Rise Motions

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    • Journal of Biomechanical Engineering

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    contributor authorStylianou, Antonis P.
    contributor authorGuess, Trent M.
    contributor authorKia, Mohammad
    date accessioned2017-05-09T00:56:36Z
    date available2017-05-09T00:56:36Z
    date issued2013
    identifier issn0148-0731
    identifier otherbio_135_4_041008.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/151024
    description abstractDetailed 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 bodylevel 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 toerise 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 InVivo Knee Loadsâ€‌ 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 toerise motion, 45 N and 53 N for left and right foot ground reaction forces during the squat and 94 N and 82 N for toerise motion. The maximum MAD value for any of the kinematic outcomes was 7.5 deg for knee flexionextension during the toerise motion.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMultibody Muscle Driven Model of an Instrumented Prosthetic Knee During Squat and Toe Rise Motions
    typeJournal Paper
    journal volume135
    journal issue4
    journal titleJournal of Biomechanical Engineering
    identifier doi10.1115/1.4023982
    journal fristpage41008
    journal lastpage41008
    identifier eissn1528-8951
    treeJournal of Biomechanical Engineering:;2013:;volume( 135 ):;issue: 004
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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