A model-based approach for estimation of changes in lumbar segmental kinematics associated with alterations in trunk neuromuscular strategy

This is the author accepted manuscript.The geometrical information from imaging, if combined with optimization-based methods of neuromuscular assessment, may provide a unique platform for personalized assessment of trunk neuromuscular behavior. Such a method, however, is feasible only if differences in lumbar spine kinematics due to differences in trunk neuromuscular behavior can be captured by the current imaging techniques. A finite element model of the spine within an optimization procedure was used to estimate segmental kinematics of lumbar spine associated with five different hypothetical trunk neuromuscular strategies (TNSs). Each TNS optimized one aspect of lower back biomechanics and was assumed to either represent the TNS of asymptomatic persons or a neuromuscular abnormality. For each TNS, the segmental kinematics of lumbar spine was estimated for a single static trunk flexed posture involving, respectively, 40° and 10° of thoracic and pelvic rotations. Minimum changes in the angular and translational deformations of a motion segment with alterations in TNS ranged from 0° to 0.5° and 0 mm to 0.04 mm, respectively. Maximum changes in the angular and translational deformations of a motion segment with alterations in neuromuscular strategy ranged from 2.4° to 7.5° and 0.11 mm to 0.39 mm, respectively. The differences in kinematics of lumbar segments between each combination of two TNSs in 97% of cases for angular deformation and 55% of cases for translational deformation were within the reported accuracy of current imaging techniques. Combined imaging and computational modeling appears to have potentials for predicting alterations in neuromuscular strategies.This work was supported, in part, by an award (5R03HD086512-02) from the National Center for Medical Rehabilitation Research (NIH-NICHD) and the Office of the Assistant Secretary of Defense for Health Affairs, through the Peer Reviewed Orthopaedic Research Program (award #W81XWH-14-2-0144)