Laboratory Reconstructions of Real-world Bicycle Helmet Impacts

The best way to prevent severe head injury when cycling is to wear a bike helmet. To reduce the rate of head injury in cycling, knowing the nature of real-world head impacts is crucial. Reverse engineering real-world bike helmet impacts in a laboratory setting is an alternative to measuring head impacts directly. This study aims to quantify bike helmet damage using computed tomography (CT) and reconstruct real-world damage with a custom, oblique test rig to recreate real-world impacts. Damaged helmets were borrowed from a helmet manufacturer who runs a helmet warranty program. Each helmet was CT-scanned and the damage metrics were quantified. Helmets of the same model and size were used for in-lab reconstructions of the damaged helmets where normal velocity, tangential velocity, peak linear acceleration (PLA) and peak rotational velocity (PRV) could be measured. The damage metrics of the in-lab dropped helmets were quantified using the same CT scanning process. For each case, a multiple linear regression (MLR) equation was created to define a relationship between the quantified damage metrics of the in-lab tested helmets and the associated measured impact velocities and kinematics. These equations were used to predict the impact kinematics and velocities from the corresponding real-world damaged helmet based on the damage metrics from the original damaged helmet. Average normal velocity (3.5 m/s), tangential velocity (2.5 m/s), PLA (108.0 g), PRV (15.7 rad/s) were calculated based on a sample of 23 helmets. Within these head impact cases, five notes reported a concussion. The difference between the average PLA and PRV for concussive cases versus other impacts were not significantly different, although the average impact kinematics for the concussive cases (PLA = 111.4 g, PRV = 18.5 rad/s) were slightly higher than the remaining cases (PLA = 107.1 g, PRV = 15.0 rad/s). The concussive cases were not indicative of high magnitude impact kinematics.