Bicycle helmets are designed to protect the user in case of a fall or collision. The effectiveness of a helmet depends on many factors, one of which is its cor-rect fit on the user's head. The presented paper aims to develop an application that can generate personalized helmet designs based on user-provided data. After receiving the user's data, the design process is automatically carried out via a computer-based algorithm. The data provided includes two photos, capturing both the front and side views of the user's head. Using these images, the algorithm analyzes the curvature, proportions, and size of the head to create curves that closely align with the user's head shape. This information is then used to design a helmet comprising of two main components: the outer shell and the inner lining. The outcomes of this study were effectively assessed through two methods. The initial evaluation involved digital analysis using 3D scanning technology to compare the head curvatures between the algorithm and the scanned model. The second evaluation utilized 3D printing technology. Using appropriate materials, the helmet was fabricated while its geometry was applied evenly to the user's head.
Minaoglou et al. (Sun,) studied this question.