Validation of a personalized curved muscle model of the lumbar spine during complex dynamic exertions

Jaejin Hwang, Gregory G. Knapik, Jonathan S. Dufour, Thomas Best, Safdar N. Khan, Ehud Mendel, William S. Marras

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Previous curved muscle models have typically examined their robustness only under simple, single-plane static exertions. In addition, the empirical validation of curved muscle models through an entire lumbar spine has not been fully realized. The objective of this study was to empirically validate a personalized biologically-assisted curved muscle model during complex dynamic exertions. Twelve subjects performed a variety of complex lifting tasks as a function of load weight, load origin, and load height. Both a personalized curved muscle model as well as a straight-line muscle model were used to evaluate the model's fidelity and prediction of three-dimensional spine tissue loads under different lifting conditions. The curved muscle model showed better model performance and different spinal loading patterns through an entire lumbar spine compared to the straight-line muscle model. The curved muscle model generally showed good fidelity regardless of lifting condition. The majority of the 600 lifting tasks resulted in a coefficient of determination (R2) greater than 0.8 with an average of 0.83, and the average absolute error less than 15% between measured and predicted dynamic spinal moments. As expected, increased load and asymmetry were generally found to significantly increase spinal loads, demonstrating the ability of the model to differentiate between experimental conditions. A curved muscle model would be useful to estimate precise spine tissue loads under realistic circumstances. This precise assessment tool could aid in understanding biomechanical causal pathways for low back pain.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalJournal of Electromyography and Kinesiology
Volume33
DOIs
StatePublished - Apr 1 2017
Externally publishedYes

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Biophysics
  • Clinical Neurology

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