Background: Eye injuries affect a large proportion of the population and are expensive to treat. This article presents a parametric analysis of experimental data to determine the most significant factors for predicting ocular injuries or tissue lesions.
Methods: Using logistic regression, statistical values were generated to determine significant projectile characteristics for predicting ocular injury in published studies. Projectiles included BBs, metal rods, and foam particles with velocities ranging from 2 m/s to 122 m/s.
Results: A normalized energy (energy per projected area) value was found as the best predictor for ocular injury. Using this predictor, a 50% injury risk of corneal abrasion, lens dislocation, hyphema, retinal damage, and globe rupture was found to be 1,503 kg/s(2), 19,194 kg/s(2), 20,188 kg/s(2), 30,351 kg/s(2), and 23,771 kg/s(2), respectively.
Conclusion: Normalized energy was the most significant predictor of injury type and tissue lesion. This finding is of great value for history-taking management triaging and as a design aid to minimize the risk of ocular injury for consumer products.