Concussion in non-helmeted contact sports: locating and measuring impact on the head

Abstract

Mild traumatic brain injury (mTBI) within contact sports is a growing concern due to the serious risk it presents. Extensive research is being conducted looking into head kinematics during impacts in non-helmeted contact sports utilising instrumented mouthguards, allowing researchers to record accelerations and velocities of the head during and after an impact. This research partially focused on conducting a feasibility study of a new instrumented mouthguard to determine its suitability for professional rugby. The mouthguard, developed by Force Impact Technologies, was tested over a 5-month period with Edinburgh Rugby during matches and training sessions. The study concluded that the mouthguard was not fit for purpose in its current form, as the on-field study revealed concerning outputs.

Additionally, instrumented mouthguards utilised within research lack the ability to determine the location of the impact on the head. Therefore, this thesis proposes and validates two methods to determine impact locations to aid the research work being conducted with instrumented mouthguards in the battle against mTBI. One method proposed utilises rigid body dynamics to approximate the impact force and determines its exact location as well as the orientation from instrumented mouthguard kinematic data. The other uses machine learning clustering algorithms with a features data set consisting of features obtained from instrumented mouthguard signals to determine impact location regions on the head. Impact data recorded from finite element simulations were used to validate both methodologies with the results from validation studies highlighting the effectiveness of the proposed impact location algorithms. Impact locations were calculated within 12 mm of the impact center for all conducted tests while utilising rigid body dynamics whereas the clustering methodology correctly classified 100% of all simulated tests to the correct impact region. Additionally, components of force unit vectors (direction cosines) obtained from the algorithm utilising rigid body dynamics were within ±0.03 of the components of applied force unit vectors, highlighting the accuracy of the proposed algorithm. The algorithms have the potential to significantly aid researchers conducting field tests within non-helmeted sports by reducing the time required to analyse and determine head impact locations.