Papers
Topics
Authors
Recent
Search
2000 character limit reached

Predicting kinetics using musculoskeletal modeling and inertial motion capture

Published 5 Jan 2018 in physics.med-ph | (1801.01668v1)

Abstract: Inverse dynamic analysis using musculoskeletal modeling is a powerful tool, which is utilized in a range of applications to estimate forces in ligaments, muscles, and joints, non-invasively. To date, the conventional input used in this analysis is derived from optical motion capture (OMC) and force plate (FP) systems, which restrict the application of musculoskeletal models to gait laboratories. To address this problem, we propose a musculoskeletal model, capable of estimating the internal forces based solely on inertial motion capture (IMC) input and a ground reaction force and moment (GRF&M) prediction method. We validated the joint angle and kinetic estimates of the lower limbs against an equally constructed musculoskeletal model driven by OMC and FP system. The sagittal plane joint angles of ankle, knee, and hip presented excellent Pearson correlations (\rho = 0.95, 0.99, and 0.99, respectively) and root-mean-squared differences (RMSD) of 4.1 $\pm$ 1.3$\circ$, 4.4 $\pm$ 2.0$\circ$, and 5.7 $\pm$ 2.1$\circ$, respectively. The GRF&M predicted using IMC input were found to have excellent correlations for three components (vertical:\rho = 0.97, RMSD=9.3 $\pm$ 3.0 %BW, anteroposterior: \rho = 0.91, RMSD=5.5 $\pm$ 1.2 %BW, sagittal: \rho = 0.91, RMSD=1.6 $\pm$ 0.6 %BW*BH), and strong correlations for mediolateral (\rho = 0.80, RMSD=2.1 $\pm$ 0.6%BW ) and transverse (\rho = 0.82, RMSD=0.2 $\pm$ 0.1 %BW*BH). The proposed IMC-based method removes the complexity and space-restrictions of OMC and FP systems and could enable applications of musculoskeletal models in either monitoring patients during their daily lives or in wider clinical practice.

Summary

Paper to Video (Beta)

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.