Modelling reflex recruitment of neck muscles in a finite element human body model for simulating omnidirectional head kinematics

Paper i proceeding, 2019

Numerical human body models that can predict occupant head and neck responses are essential for the development and assessment of motor vehicle safety systems. Including the contribution of neck muscle responses is needed to improve model predictions, in particular during simulated pre-crash manoeuvers. While a general purpose model that can predict head-neck kinematics in various pre-crash conditions (e.g. emergency braking and steering) is needed most current models have been limited to predictions of longitudinal motion (e.g. during emergency braking). We developed a method for simulating muscle recruitment in a finite element human body model for omnidirectional head-neck kinematics predictions. A neural control scheme that uses kinematics and muscle length feedback to determine the activation level in individual muscle elements was implemented. The control scheme included a novel approach to determine load sharing between muscles based on experimental data from human subjects in dynamic conditions. Multidirectional 1 g loading conditions were simulated to assess the effect of muscle recruitment on head and neck kinematics in multiple directions and to evaluate the predicted spatial tuning of recruitment for selected muscles. Simulation results demonstrate that including both kinematics and muscle length feedback reduces head and internal neck motion induced from external 1 g loading.