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Abstract

A 3-D Stability-Based Dynamic Computational Model of Human Trunk Movement: Towards the Development of a Paradigm for Forensic Spinal Injury Biomechanical Analysis

Majid Khorsand Vakilzadeh, Mohsen Asghari, Hassan Salarieh, Naira H Campbell-Kyureghyan, Mohamad Parnianpour and Kinda Khalaf

Background: Spinal injuries and associated litigation continue to pose significant human and economic challenges globally. Biomechanical predictive simulation models of the spine provide time and cost effective tools for forensic injury biomechanical quantitative analysis.
Methods: A 3-D computational model that includes 18 muscles was developed to simulate the motion of the human trunk. Three physiologically based performance indices were used to model the optimal trajectories associated with trunk movement. The moment generated around the lumbosacral joint was computed using inverse dynamics. The contribution of muscles to the moment was evaluated by performing static stability-based optimization, where trunk movement from an upright position to 60 degrees of flexion was simulated. Contribution of the intrinsic mechanism to spinal stability was addressed by adding stability constraints to the optimization routine while allowing for an increase in the activity of the antagonistic muscles.
Results: Co-contraction of agonistic and antagonistic muscles in the resulting computational model increases joint stiffness around the L5/S1 joint. Muscle spindles provide reflexive feedback to control the trunk position during the execution of the optimal trajectory. Increasing the time delay in the reflex mechanism reduces spinal stability.
Conclusion: The main contribution of this work is two-fold: 1. The novel use of three physiologically plausible indices of performance to simulate spinal motion with and without stability constraints, and 2. The incorporation of several well established feed forward and feedback controls in the model. The indices of trunk performance resulted in different motion patterns and muscular recruitment patterns. The model predicted that imposing trunk stability causes higher spinal stiffness by increasing muscular recruitment in alignment with experimental data. This study provides a computational framework for modeling and predicting spinal movement that can be used towards quantitative forensic spinal injury biomechanical analysis.