EMG-driven Forward Dynamics Simulation to Estimate in Vivo Joint Contact Forces During Normal, Smooth, and Bouncy Gait

[+] Author and Article Information
Swithin Razu

Doctoral Candidate, Department of Bioengineering, University of Missouri, 801 Clark Hall, Columbia, MO 65211-4250

Trent M. Guess

Associate Professor, Department of Physical Therapy, Department of Orthopaedic Surgery, University of Missouri, 801 Clark Hall, Columbia, MO 65211-4250

1Corresponding author.

ASME doi:10.1115/1.4038507 History: Received June 08, 2017; Revised October 25, 2017


This study leveraged data from the "Sixth Grand Challenge Competition to Predict in Vivo Knee Loads" to create a full-body musculoskeletal model that 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: First, to describe an electromyography (EMG)-driven modeling methodology to predict knee contact forces, and second 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 gait). 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 (?2). 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< ?2<0.96) for normal gait; RMSEs = 0.18 BW, 0.21 BW, 0.29 BW, and (0.81< ?2<0.93) for smooth gait; and RMSEs = 0.21 BW, 0.22 BW, 0.33 BW, and (0.86< ?2<0.95) for bouncy gait, respectively.

Copyright (c) 2017 by ASME
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