Abstract This study looks to develop and explore a computational approach, along with data gathered from conventional mechanical helmet testing procedures in ice hockey, in an attempt to provide new insights into how the helmet could protect an individual from concussive type impacts. In this study, five samples of six different ice hockey helmet models were tested using the methodologies set forth by The Summation of Tests for the Analysis of Risk, the STAR helmet rating protocol. Head form kinematics collected during STAR testing were used as inputs to the Global Human Body Model Consortium head finite element model, and each impact (n=672) was simulated. A 15% cumulative strain damage measure threshold was chosen as the main response variable to predict brain injury probability. The results indicate that output kinematics of rotational velocity were most correlated (r = 0.96, P < 0.05) to cumulative strain damage measure and other strain measures. Impact direction also had significant effects on the strains in the brain, with impacts to the rear, front and side showing larger statistical significance in variance to the cumulative strain damage measure than top impacts. It was also observed that specific helmets showed less deformation response in certain impact directions compared to others. This study developed a start-to-finish methodology to evaluate helmets for mild brain injury mitigation. Keywords Concussion mitigation, cumulative strain damage measure, injury prediction pipeline, kinematic performance evaluation, mild traumatic brain injury I. INTRODUCTION The traumatic brain injury (TBI) has become one of the most critical issues affecting global health systems with over 69 million individuals worldwide sustaining this injury every year [1]. An estimated 80% of these injuries are considered to be mild in nature, i.e. concussions, which poses a unique challenge to the researchers, physicians and medical trainers who are tasked with diagnosing, rehabilitating and mitigating their rate of occurrence [2]. In organised sports the issue of the mTBI is rampant, especially in adolescent aged participants [3]. The competitive environment which focuses on physical contact, especially in sports such as American Football and Ice Hockey, leads to increased instances of concussive and sub-concussive impacts that accumulate and could lead to negative short- and long-term neurodegenerative disorders [4,5]. In both sports the use of a helmet is the primary method of head impact mitigation. The original purpose of a helmet was to provide its wearer protection from mechanical loading that lead to lacerations, abrasions, fractures and other forms of tissue disruptions by absorbing the energy acting on the head upon impact [6]. Helmets however, need to be improved to cushion the brain and provide protective measures for the mitigation of concussive instances. One common pathology of mild traumatic brain injury (mTBI) is the diffuse axonal injury (DAI), which is directly correlated to injury outcomes such as unconsciousness, cognitive impairments, and if the level of injury is severe enough, death [7]. The primary mechanical mechanism in DAI is inertial forces applied to the head following impact, that cause stretching of the deep and subcortical white matter. This twisting effect leads to extensive deformation of the brain structure and micro-tears to the underlying axon fibre bundles [8]. The issue with DAI, and moreover mTBI, is that it is extremely difficult to quantify the extent of the damage using traditional macroscopic pathology, typically used as assessment tools, post injury [7]. This along with the perceived randomness associated with concussions, where no two impacts are alike and where the ability to see the Y. Levy is a MESc student in Biomedical Engineering specialising in brain biomechanics (ylevy3@uwo.ca, +1 416 854 6041). H. Mao is Professor of Engineering in the Department of Mechanical and Materials and Biomedical Engineering at Western University in Canada. Using a Strain-Based Computational Approach for Ice Hockey Helmet Performance Evaluation Yanir Levy, Marco B. Gallone, Kewei Bian, Kierra McDougall, Ryan Ouckama, Haojie Mao IRC-20-66 IRCOBI conference 2020 569