In collaboration with the Insurance Institute for Highway Safety, we have rated bike helmets using the STAR evaluation system. Our impact tests evaluate a helmet's ability to reduce linear acceleration and rotational velocity of the head resulting from a range of head impacts a cyclist might experience. Helmets with more stars provide a reduction in concussion risk for these impacts compared to helmets with less stars.
infoUnderstanding the rating system
Our ratings are an independent and objective assessment of helmet performance for consumers, free from manufacturer influence.
We rate each bike helmet based on the results of 24 impact tests in our laboratory. A drop tower designed to match helmet-to-ground characteristics in cycling is used to test the helmets. We measure linear acceleration and rotational velocity for each impact, which are correlated to concussion risk.
We test 6 locations that are dispersed around the helmet at medium and and high impact energies. Velocities were selected to reflect common cyclist head impact velocities based on helmet damage replication studies.
Each lab impact is weighted based on how often a cyclist might experience a similar impact. We compute concussion risk from measured peak linear acceleration and rotational velocity for each test. Each risk is multiplied by its weighting factor and then summed together to compute an overall score. The overall score estimates the number of concussions the average person would see if they experienced identical impacts at rates matching their weightings while cycling.
A lower score indicates better helmet performance.
The score values in these ratings are not comparable to score values in our helmet ratings for other sports. This is because there are differences in test methods, impact conditions, risk calculations, and impact weightings specific to each sport.
Cost shown is the price of the helmet at the time of testing.
*Any player in any sport can sustain a head injury with even the very best head protection. This analysis is based on data trends and probabilities, and therefore a specific person’s risk may vary. This variation is likely dominated by genetic differences, health history, and impact factors such as muscle activation.