Computational models that predict in vivo joint loading and muscle forces can potentially enhance and augment our knowledge of both typical and pathological gaits. To adopt such models into clinical applications, studies validating modeling predictions are essential. This study created a full-body musculoskeletal model using data from the “Sixth Grand Challenge Competition to Predict in vivo Knee Loads.” This model incorporates subject-specific geometries of the right leg in order to concurrently predict knee contact forces, ligament forces, muscle forces, and ground contact forces. The objectives of this paper are twofold: (1) to describe an electromyography (EMG)-driven modeling methodology to predict knee contact forces and (2) to validate model predictions by evaluating the model predictions against known values for a patient with an instrumented total knee replacement (TKR) for three distinctly different gait styles (normal, smooth, and bouncy gaits). The model integrates a subject-specific knee model onto a previously validated generic full-body musculoskeletal model. The combined model included six degrees-of-freedom (6DOF) patellofemoral and tibiofemoral joints, ligament forces, and deformable contact forces with viscous damping. The foot/shoe/floor interactions were modeled by incorporating shoe geometries to the feet. Contact between shoe segments and the floor surface was used to constrain the shoe segments. A novel EMG-driven feedforward with feedback trim motor control strategy was used to concurrently estimate muscle forces and knee contact forces from standard motion capture data collected on the individual subject. The predicted medial, lateral, and total tibiofemoral forces represented the overall measured magnitude and temporal patterns with good root-mean-squared errors (RMSEs) and Pearson's correlation (p2). The model accuracy was high: medial, lateral, and total tibiofemoral contact force RMSEs = 0.15, 0.14, 0.21 body weight (BW), and (0.92 < p2 < 0.96) for normal gait; RMSEs = 0.18 BW, 0.21 BW, 0.29 BW, and (0.81 < p2 < 0.93) for smooth gait; and RMSEs = 0.21 BW, 0.22 BW, 0.33 BW, and (0.86 < p2 < 0.95) for bouncy gait, respectively. Overall, the model captured the general shape, magnitude, and temporal patterns of the contact force profiles accurately. Potential applications of this proposed model include predictive biomechanics simulations, design of TKR components, soft tissue balancing, and surgical simulation.
Skip Nav Destination
Article navigation
July 2018
Research-Article
Electromyography-Driven Forward Dynamics Simulation to Estimate In Vivo Joint Contact Forces During Normal, Smooth, and Bouncy Gaits
Swithin S. Razu,
Swithin S. Razu
Department of Bioengineering,
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250
e-mail: swithinr@health.missouri.edu
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250
e-mail: swithinr@health.missouri.edu
Search for other works by this author on:
Trent M. Guess
Trent M. Guess
Department of Physical Therapy,
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250;
Department of Orthopaedic Surgery,
University of Missouri,
1100 Virginia Ave,
Columbia, MO 65201
e-mail: guesstr@health.missouri.edu
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250;
Department of Orthopaedic Surgery,
University of Missouri,
1100 Virginia Ave,
Columbia, MO 65201
e-mail: guesstr@health.missouri.edu
Search for other works by this author on:
Swithin S. Razu
Department of Bioengineering,
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250
e-mail: swithinr@health.missouri.edu
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250
e-mail: swithinr@health.missouri.edu
Trent M. Guess
Department of Physical Therapy,
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250;
Department of Orthopaedic Surgery,
University of Missouri,
1100 Virginia Ave,
Columbia, MO 65201
e-mail: guesstr@health.missouri.edu
University of Missouri,
801 Clark Hall,
Columbia, MO 65211-4250;
Department of Orthopaedic Surgery,
University of Missouri,
1100 Virginia Ave,
Columbia, MO 65201
e-mail: guesstr@health.missouri.edu
1Corresponding author.
Manuscript received June 8, 2017; final manuscript received October 25, 2017; published online May 18, 2018. Assoc. Editor: Tammy L. Haut Donahue.
J Biomech Eng. Jul 2018, 140(7): 071012 (8 pages)
Published Online: May 18, 2018
Article history
Received:
June 8, 2017
Revised:
October 25, 2017
Citation
Razu, S. S., and Guess, T. M. (May 18, 2018). "Electromyography-Driven Forward Dynamics Simulation to Estimate In Vivo Joint Contact Forces During Normal, Smooth, and Bouncy Gaits." ASME. J Biomech Eng. July 2018; 140(7): 071012. https://doi.org/10.1115/1.4038507
Download citation file:
Get Email Alerts
Simulating the Growth of TATA-Box Binding Protein-Associated Factor 15 Inclusions in Neuron Soma
J Biomech Eng (December 2024)
Effect of Structure and Wearing Modes on the Protective Performance of Industrial Safety Helmet
J Biomech Eng (December 2024)
Sex-Based Differences and Asymmetry in Hip Kinematics During Unilateral Extension From Deep Hip Flexion
J Biomech Eng (December 2024)
Related Articles
A Novel Theoretical Framework for the Dynamic Stability Analysis, Movement Control, and Trajectory Generation in a Multisegment Biomechanical Model
J Biomech Eng (January,2009)
Special Section: Annual Education Issue: Let the Wild Rumpus of Education Start!
J Biomech Eng (July,2016)
Muscle Synergies May Improve Optimization Prediction of Knee Contact Forces During Walking
J Biomech Eng (February,2014)
Related Proceedings Papers
Related Chapters
Modeling and Classification for Uterine EMG Signals Using Autoregressive Model
Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
Vibration Analysis of the Seated Human Body in Vertical Direction
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
Biomechanical Investigations of the Heel Release of Ski Safety Bindings by Triceps Surae Muscle Action
Skiing Trauma and Safety: Sixth International Symposium