| Description |
Concussions are mild traumatic brain injuries that have a high incidence in American football. Methods suggested for reducing this incidence include rule changes, helmet improvements, tackling technique, and neck strengthening. Experimentally studying these methods is limited by applying only low energy impacts in laboratory settings. Simulation studies offer insight on the effects of interventions and can answer the "what if" questions experimental studies cannot. The topic of this dissertation is the development and application of musculoskeletal models capable of realistic simulation of impacts to the head that are likely to cause a concussion. Predicting muscle coactivation patterns and the development of a suitable musculoskeletal model are two challenges discussed and overcome. Contributions related to these challenges include novel methods for predicting muscle coactivation, a tool for applying methods for predicting muscle coactivation, the first OpenSim model of the head and neck to generate realistic neck strength in all directions, and the understanding that the inclusion of hyoid muscles improve moment generating capacity and dynamic simulations in musculoskeletal models of the head and neck. Using the developed musculoskeletal model and coactivation pattern prediction techniques, two simulation studies are presented on the effect of active neck muscles and various parameters in the model. It is shown that active neck muscles have a statistically significant effect on head injury metrics. It is also shown that increasing muscle strength, particularly in eccentric contractions, reduces risk. However, it appears that posture and head movement prior to impact have a much greater effect on head injury metrics. A comprehensive approach to reducing concussion incidence is suggested, with emphasis on coaching techniques to reduce head injury metrics. Finally, a study on the effects of subject-specific models is presented. Subject-specific models are created using available data and the effects of active neck muscles are further investigated. It is shown that the effect of the method for predicting muscle activation patterns on head injury metrics is statistically insignificant. The methods in this study and this entire dissertation should be applied in future studies that investigate additional hypotheses. |
