Prediction of Brain Injury Measures from Head Motion Parameters

An analysis of experimental head impact data was preformed to demonstrate: (1) that kinematic waveforms contain information relating to head and brain injuries; and (2) that analysis techniques exist which can properly exploit this information to create injury predictive functions.

An experimental data base consisting of 26 monkey head impacts was utilized. Translational and rotational acceleration time histories of the head were available. Parameters computed from these kinematic waveforms were the input variables to an analysis technique. The output, or modeled, variable was the experimentalist's evaluation of the severity of injuries.

The results of the analysis are presented and it is concluded that it is possible to accurately model head and brain injury assessments from strictly head motion parameters. Subsequent analysis of the derived predictive functions reveals interesting insight into the relationship between the kinematic parameters and head injury and suggests potential strategies for head injury mitigation.