The goal of this project is to critically evaluate the ability of musculoskeletal models to predict muscle and joint contact forces in the knee reliably during walking. Knowledge of these internal loads could improve the diagnosis and treatment of neuromusculoskeletal disorders that affect walking ability (e.g., stroke, cerebral palsy, osteoarthritis). Because internal loads cannot be measured clinically, musculoskeletal models have become the primary means for developing estimates. However, if model estimates are inaccurate, clinical assessments or treatments based on these estimates could be ineffective or even harmful. We propose to evaluate musculoskeletal model estimates of muscle and joint contact forces in the knee during walking using in vivo contact force measurements obtained from patients implanted with force-measuring knee replacements. These unique internal load measurements will allow us to evaluate contact force estimates directly and muscle force estimates indirectly. For each of the five patients tested, we will collect a broad range of movement data (tibial contact force, motion capture, ground reaction force, EMG, fluoroscopic, muscle strength). We will then enhance OpenSim open-source musculoskeletal modeling software with new capabilities (e.g., """"""""fast"""""""" contact model modeling methods, new optimization methods for predicting muscle forces based on EMG measurements) to permit construction of a high-fidelity musculoskeletal model of each patient. The ability of each patient-specific model to reproduce the patient's tibial contact force, EMG, and other movement data will be evaluated using existing and new muscle and contact force prediction methods. We will also hold an annual competition at the ASME Summer Bioengineering Conference where researchers will use data and models we make available to predict the in vivo tibial contact forces without knowing them in advance. This musculoskeletal model validation effort will be the most extensive ever performed, and the data, models, and ideas generated will provide a foundation for further evaluation studies for years to come.

Public Health Relevance

Musculoskeletal models could facilitate the design of effective, customized treatments for neuromusculoskeletal disorders such as stroke, cerebral palsy, and osteoarthritis. However, before they can be used for this purpose, their predictions need to be validated. This study proposes unique data and methods to perform such a validation with a focus on the knee during walking.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB009351-03
Application #
8270573
Study Section
Musculoskeletal Rehabilitation Sciences Study Section (MRS)
Program Officer
Peng, Grace
Project Start
2010-08-01
Project End
2014-04-30
Budget Start
2012-05-01
Budget End
2013-04-30
Support Year
3
Fiscal Year
2012
Total Cost
$526,647
Indirect Cost
$66,865
Name
University of Florida
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
969663814
City
Gainesville
State
FL
Country
United States
Zip Code
32611
Eskinazi, Ilan; Fregly, Benjamin J (2016) An Open-Source Toolbox for Surrogate Modeling of Joint Contact Mechanics. IEEE Trans Biomed Eng 63:269-77
Serrancolí, Gil; Kinney, Allison L; Fregly, Benjamin J et al. (2016) Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking. J Biomech Eng 138:
Pizzolato, Claudio; Lloyd, David G; Sartori, Massimo et al. (2015) 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 48:3929-36
Eskinazi, Ilan; Fregly, Benjamin J (2015) Surrogate modeling of deformable joint contact using artificial neural networks. Med Eng Phys 37:885-91
Mizu-Uchi, Hideki; Colwell Jr, Clifford W; Flores-Hernandez, Cesar et al. (2015) Patient-specific computer model of dynamic squatting after total knee arthroplasty. J Arthroplasty 30:870-4
Walter, Jonathan P; Korkmaz, Nuray; Fregly, Benjamin J et al. (2015) Contribution of tibiofemoral joint contact to net loads at the knee in gait. J Orthop Res 33:1054-60
Walter, Jonathan P; Kinney, Allison L; Banks, Scott A et al. (2014) Muscle synergies may improve optimization prediction of knee contact forces during walking. J Biomech Eng 136:021031
Sartori, Massimo; Farina, Dario; Lloyd, David G (2014) Hybrid neuromusculoskeletal modeling to best track joint moments using a balance between muscle excitations derived from electromyograms and optimization. J Biomech 47:3613-21
Demers, Matthew S; Pal, Saikat; Delp, Scott L (2014) Changes in tibiofemoral forces due to variations in muscle activity during walking. J Orthop Res 32:769-76
Pegg, Elise C; Walter, Jonathan; Mellon, Stephen J et al. (2013) Evaluation of factors affecting tibial bone strain after unicompartmental knee replacement. J Orthop Res 31:821-8

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