Hwang Jaejin, Knapik Gregory G, Dufour Jonathan S, Aurand Alexander, Best Thomas M, Khan Safdar N, Mendel Ehud, Marras William S
Biodynamics Laboratory, Spine Research Institute, The Ohio State University, Department of Integrated Systems Engineering, 1971 Neil Avenue, 210 Baker Systems Engineering, Columbus, OH 43210, USA.
Department of Family Medicine, The Ohio State University, Martha Moorehouse Medical Plaza, 2050 Kenny Dr., Columbus, OH 43210, USA.
Clin Biomech (Bristol). 2016 Aug;37:53-59. doi: 10.1016/j.clinbiomech.2016.06.002. Epub 2016 Jun 15.
Biomechanical models have been developed to assess the spine tissue loads of individuals. However, most models have assumed trunk muscle lines of action as straight-lines, which might be less reliable during occupational tasks that require complex lumbar motions. The objective of this study was to describe the model structure and underlying logic of a biologically-assisted curved muscle model of the lumbar spine.
The developed model structure including curved muscle geometry, separation of active and passive muscle forces, and personalization of muscle properties was described. An example of the model procedure including data collection, personalization, and data evaluation was also illustrated.
Three-dimensional curved muscle geometry was developed based on a predictive model using magnetic resonance imaging and anthropometric measures to personalize the model for each individual. Calibration algorithms were able to reverse-engineer personalized muscle properties to calculate active and passive muscle forces of each individual.
This biologically-assisted curved muscle model will significantly increase the accuracy of spinal tissue load predictions for the entire lumbar spine during complex dynamic occupational tasks. Personalized active and passive muscle force algorithms will help to more robustly investigate person-specific muscle forces and spinal tissue loads.
