A new open-access platform for measuring and sharing mTBI data

Abstract

Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.

Toward a Comprehensive Delineation of White Matter Tract-Related Deformation

“…Secondly, the rather low ratio of concussed cases to all simulated cases (11%) posed another hamper for effectively evaluating the predictive power of these five metrics even within the LOOCV scheme. 80,96 With the emergence of open-access platforms for measuring and sharing high-quality head impact kinematics across various institutions, 97 further verification of the findings in the study is hoped to be granted soon based on additional injury dataset with the concussive and non-concussive impacts optimally distributed. Thirdly, the discrimination performance of all metrics was evaluated based on the 95 th percentile peak strain values, the same as the strategy in previous studies.…”

The Presence of the Temporal Horn Exacerbates the Vulnerability of Hippocampus During Head Impacts

“…Lastly, due to the lack of neuroimaging data of these players with their head impacts being simulated, it is hardly possible to ascertain whether hippocampal injury indeed occurred in these six simulated impacts. At Stanford, ongoing effort is dedicated to deploy instrumented mouthguards to football players, obtaining real-time measurements of the impacts sustained by these players ( Camarillo et al, 2013 ; Hernandez et al, 2015 ; Domel et al, 2021 ; Liu et al, 2020 ). This information is complemented by medical imaging of the football players pre- and post-impact ( Parivash et al, 2019 ; Mills et al, 2020 ).…”

The relationship between brain injury criteria and brain strain across different types of head impacts can be different

“…The remaining 53 were reconstructed head impacts in National Football League [26] using hybrid III ATD headform. The data from these two sources were merged because they both represented the responses of hybrid III ATD headform under football-type impacts; (ii) dataset 2 contained 302 on-site college football head impacts collected by the Stanford instrumented mouthguards [27][28][29]; (iii) dataset 3 contained 457 on-site mixed martial arts (MMA) head impacts collected by the Stanford instrumented mouthguard [3,30]; (iv) dataset 4 contained 48 head impacts in automobile crashworthiness tests from the National Highway Traffic Safety Administration (NHTSA) [31]; (v) dataset 5 contained 272 numerically reconstructed head impacts in National Association for Stock Car Auto Racing (NASCAR) by hybrid III ATD headform. Since finite-element (FE) modelling is the state-of-the-art biomechanics modelling tool for brain strain in head impacts, the validated KTH model [32] was used to calculate the MPS95, MPSCC95 and CSDM since these are widely used in mTBI research [6,7,23,33,34].…”