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Player-to-player contact inherent in many unhelmeted sports means that head impacts are a frequent occurrence. Model-Based Image- Matching (MBIM) provides a technique for the assessment of three-dimensional linear and rotational motion patterns from multiple camera views of a head impact event, but the accuracy is unknown for this application. The goal of this study is to assess the accuracy of the MBIM method relative to reflective marker-based motion analysis data for estimating six degree of freedom head displacements and velocities in a staged pedestrian impact scenario at 40 km/h. Results showed RMS error was under 20 mm for all linear head displacements and 0.01-0.04 rad for head rotations. For velocities, the MBIM method yielded RMS errors between 0.42 and 1.29 m/s for head linear velocities and 3.53-5.38 rad/s for angular velocities. This method is thus beneficial as a tool to directly measure six degree of freedom head positional data from video of sporting head impacts, but velocity data is less reliable. MBIM data, combined in future with velocity/acceleration data from wearable sensors could be used to provide input conditions and evaluate the outputs of multibody and finite element head models for brain injury assessment of sporting head impacts. [ABSTRACT FROM AUTHOR]

Head kinematics generated by laboratory reconstructions of professional football helmet impacts have been applied to computational models to study the biomechanics of concussion. Since the original publication of this data, techniques for evaluating accelerometer consistency and error correction have been developed. This study applies these techniques to the original reconstruction data and reanalyzes the results given the current state of concussion biomechanics. Consistency checks were applied to the sensor data collected in the head of each test dummy. Inconsistent data were corrected using analytical techniques, and head kinematics were recalculated from the corrected data. Reconstruction videos were reviewed to identify artefactual impacts during the reconstruction to establish the region of applicability for simulations. Corrected head kinematics were input into finite element brain models to investigate strain response to the corrected dataset. Multiple reconstruction cases had inconsistent sensor arrays caused by a problematic sensor; corrections to the arrays caused changes in calculated rotational head motion. These corrections increased median peak angular velocity for the concussion cases from 35.6 to 41.5 rad/s. Using the original kinematics resulted in an average error of 20% in maximum principal strain results for each case. Simulations of the reconstructions also demonstrated that simulation lengths less than 40 ms did not capture the entire brain strain response and under-predicted strain. This study corrects data that were used to determine concussion risk, and indicates altered head angular motion and brain strain response for many reconstructions. Conclusions based on the original data should be re-examined based on this new study. [ABSTRACT FROM AUTHOR]