A Fast-Running, End-to-End Concussion Risk Model for Assessment of Complex Human Head Kinematics.

An end-to-end, mechanism-based concussion risk model, linking head motion to axonal injury, has been demonstrated to predict concussion outcomes with greater sensitivity and specificity than external correlates such as peak head acceleration. The development of this model was driven by the need to more accurately translate head-worn sensor measurements into injury assessment in near-real time. The full end-to-end model is a detailed multi-scale model, composed of complex components (e.

A Mechanistic End-to-End Concussion Model That Translates Head Kinematics to Neurologic Injury.

Past concussion studies have focused on understanding the injury processes occurring on discrete length scales (e.g., tissue-level stresses and strains, cell-level stresses and strains, or injury-induced cellular pathology).