Once an impact is detected, the algorithm analyzes the data against predefined thresholds that are scientifically linked to concussion risk. This might involve calculations to assess the force, angle, and location of the impact relative to known concussion-inducing impacts. The algorithm evaluates the analyzed data to estimate the risk of concussion. This step often uses machine learning models that have been trained on large datasets of documented head injuries to predict concussion likelihood based on impact characteristics.