Children’s cloth face mask sizing and digital fit analysis: method development

Abstract

There is a necessity to use digital data and tools when developing children’s products. The present study was designed to provide digital methods to guide product development and problem-solving when using 3D body scans and face mask simulations for 6-year-olds. First, key facial measurements were evaluated to better understand the variables that might affect face mask sizing for children for the selected age group. Then the findings were used to optimize the size and fit of a cloth face mask design. Next, the fit of the digital, optimized face mask design was tested on 44 head scans from Size North America by using subjective and objective fit assessment techniques. Study findings suggested that width and length-related measurements are critical for children’s face masks. Body mass index (BMI) and ethnicity were also found to be the main factors for identifying size ranges in the selected age group. As BMIs increase, face mask sizes should increase. Additionally, the results indicated a need to use a larger database of children of all ethnicities to design an inclusive facemask that would provide a comfortable and protective fit for different facial proportions. Although the results cannot be generalized due to the case study approach of the present research and its focus on methods development, they can provide manufacturers, designers, and researchers with guidelines on how to develop proper sizing and use digital data to conduct functional fit analysis for facemasks.