Despite the alarming incidence rate and potential for debilitating
outcomes of sports-related concussion, the underlying mechanisms of injury
remain to be expounded. Since as early as 1950, researchers have aimed to
characterize head impact biomechanics through in-lab and in-game
investigations. The ever-growing body of literature within this area has
supported the inherent connection between head kinematics during impact and
injury outcomes. Even so, traditional metrics of peak acceleration, time
window, and HIC have outlived their potential. More sophisticated analysis
techniques are required to advance the understanding of concussive vs
subconcussive impacts. The work presented within this thesis was motivated by
the exploration of advanced approaches to 1) experimental theory and design of
impact reconstructions and 2) characterization of kinematic profiles for model
building. These two areas of investigation resulted in the presentation of
refined, systematic approaches to head impact analysis that should begin to
replace outdated standards and metrics.
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/19285268 |
| Date | 20 April 2022 |
| Creators | Breana R Cappuccilli (12174029) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/FROM_THE_WAYNE_STATE_TOLERANCE_CURVE_TO_MACHINE_LEARNING_A_NEW_FRAMEWORK_FOR_ANALYZING_HEAD_IMPACT_KINEMATICS/19285268 |
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