Objective:​ During dynamic injury scenarios, such as motor vehicle crashes, neck biomechanics contribute to head excursion and acceleration, influencing head injuries. One important tool in understanding head and neck dynamics is computational modeling. However, realistic and stable muscle activations for major muscles are required to realize meaningful kinematic responses. The objective was to determine cervical muscle activation states for 6-year-old, 10-year-old, and adult 50th percentile male computational head and neck models. Currently, pediatric models including muscle activations are unable to maintain the head in an equilibrium position, forcing models to begin from nonphysiologic conditions. Recent work has realized a stationary initial geometry and cervical muscle activations by first optimizing responses against gravity. Accordingly, our goal was to apply these methods to Duke University's head–neck model validated using living muscle response and pediatric cadaveric data.

Methods:​ Activation schemes maintaining an upright, stable head for 22 muscle pairs were found using LS-OPT. Two optimization problems were investigated:​ a relaxed state, which minimized muscle fatigue, and a tensed activation state, which maximized total muscle force. The model's biofidelity was evaluated by the kinematic response to gravitational and frontal impact loading conditions. Model sensitivity and uncertainty analyses were performed to assess important parameters for pediatric muscle response. Sensitivity analysis was conducted using multiple activation time histories. These included constant activations and an optimal muscle activation time history, which varied the activation level of flexor and extensor groups, and activation initiation and termination times.

Results:​ Relaxed muscle activations decreased with increasing age, maintaining upright posture primarily through extensor activation. Tensed musculature maintained upright posture through coactivation of flexors and extensors, producing up to 32 times the force of the relaxed state. Without muscle activation, the models fell into flexion due to gravitational loading. Relaxed musculature produced 28.6–35.8 N of force to the head, whereas tensed musculature produced 450–1023 N. Pediatric model stiffnesses were most sensitive to muscle physiological cross-sectional area.

Conclusions:​ Though muscular loads were not large enough to cause vertebral compressive failure, they would provide a prestressed state that could protect the vertebrae during tensile loading but might exacerbate risk during compressive loading. For example, in the 10-year-old, a load of 602 N was produced, though estimated compressive failure tolerance is only 2.8 kN. Including muscles and time-variant activation schemes is vital for producing biofidelic models because both vary by age. The pediatric activations developed represent physiologically appropriate sets of initial conditions and are based on validated adult cadaveric data.