Determining the Optimal and Ideal Helmet for an Italian Scooter Used in a Smart City Considering Cranial Anthropometry and Intelligent Data Analysis

Abstract

The main objective of the present research was to develop an intelligent data analysis from anthropometric data to find tendencies and patrons before stating the design of an optimal and ideal helmet to be used in an Italian scooter. Using a database of the anthropometric properties of the craniofacial structures of a sample of students in a border society. A set of 14 craniofacial dimensions were obtained using 13 reference anthropometric points (Glabella, Vertex, Opisthocranion, Eurion, Alare, Gnathion, Nasion, Nasoespinhale, Frontotemporale, Porion, Exocanthion, Endocantion, and Zygion). We used a ROSSCRAFT anthropometer model CAMPBELL 10 RC10, a ROSSCRAFT metallic tape, and an ErgoTechMx brand ErgoMeasure model anthropometer. 130 students, 69 men, and 61 women enrolled in said University were measured. The values of mean, standard deviation, maximum and minimum were calculated. Finally, we analyze the data obtained to determine the ideal thickness of the helmet and how it can help reduce deaths in road accidents.