Sizing children’s headwear based on modelling 3D head geometric characteristics and product perceived comfort

Abstract

Nowadays, an increasing number of children are using headwear, e.g., eyeglasses and helmets. These products are usually used to protect different parts of the heads, or enhance or extend the sensory capability in our daily life. To design and customize the shapes and sizes of these products, having accurate 3D anthropometric information for the full human head is crucial for both mass-produced and individually customized products to achieve optimal fit and safety in their functioning and optimizing usability. While 3D anthropometric studies on the heads of adults are well-established, there remains a relative lack of exploration in modeling 3D head growth patterns and variations for children. In reality, compared with adults’ heads, the children’ heads have smaller sizes and grow with the increase in age. This could potentially make the simply scaled-down face-related products (especially designed for adults) improper and uncomfortable for child users. Particularly, deficiencies in children’s 3D head anthropometry further leads to the lack of excellent sizing system for face-related products. Hence, it is significant to model 3D head growth patterns and variations for children’s heads and leverage them to create children’s sizing systems for face-related products. Another issue related to headwear sizing is that there are limited studies about product fit and comfort perceptions for children. An excellent product sizing system should have not only large coverage rate, but also high overall comfort for the target population. Improper fit can cause numerous problems, ranging from discomfort to acute safety issues, which can potentially lead to severe medical problems and even death. Hence, the product fit and comfort perceptions for children, as guidelines and foundation in sizing products, is also needed to be investigated and quantified. Regarding the above design issues, this thesis aims at performing three main studies: (1) modelling 3D head growth patterns and variations for children; (2) creating children’s perceived comfort prediction model based on 3D facial anthropometric and product design parameters; (3) leveraging the quantitative results of (1) and (2) to establish comfort-oriented headwear sizing systems for child users. Here, eyeglasses, as a widely used tool for visual correction and protection, were used as a representative face-related product to demonstrate the feasibility and superiority of the proposed methods in study 2 and 3. In study 1, to analyze head geometric variations, entire heads of 793 children (395 females and 398 males) ages 5-17 were scanned and parameterized, and one global and two sex-specific statistical shape models (SSMs) were constructed using principal components analysis (PCA). To model growth patterns, sex-specific expected average heads for different ages and per-vertex growth rates were computed using lambda, mu, sigma (LMS) method. In study 2, a psychological experiment with 30 child testers was conducted to collected children's perceived comfort scores for eyeglasses with two key variables (i.e., nose pads width and temple clamping force). Then, a temple clamping force calculation equation was identified (using Finite Element Analysis (FEA)) and validated. Finally, a perceived comfort prediction model was created by quantifying relationships between subjective children's comfort perceptions, objective 3D facial anthropometric and product design parameters using ordinary least squares regression method. In study 3, a comfort-oriented and assembly-guided approach based on ophthalmic SSM was developed to size children's eyeglasses. Descriptive statistics of ophthalmic regions were used to size nose pads and temples, and ophthalmic SSM with genetic algorithm were employed to search representative shapes and customize their rims as sizes, where the coverage rate and overall comfort were computed together as the objective function. To the best of my current knowledge, it is the first time researcher had modeled the 3D children' head geometric variances, and applied the LMS method to each vertex to compute 3D geometric growth patterns. A list of product design contributions produced from these studies were summarized as follows: (1) This modelling finds its application in fields not limited to ergonomic face/head-related product design, sizing system establishment, virtual try-on, fit assessment, physical head reconstruction, digital head synthesis, and product personalization; (2) The comfort-oriented and SSM-based searching strategy can effectively produce product sizing system with higher overall comfort and coverage rate for the target population, which had a good generalization for more head and body wearables; (3) The children’s perceived comfort prediction model for eyeglasses can provide a good generic reference for sizing, grading, and personalizing various eyeglasses.