Thermal performance of three bicycle helmets for latent heat loss was evaluated through a virtual testing methodology using Computational fluid dynamics (CFD) simulations. The virtual thermal manikin was prescribed with a constant sweat rate of 2 g/h and a constant sweat film thickness of 0.3 mm. The simulations were carried out at 6 m/s until convergence was achieved. The results from steady state simulations show heat loss of 158 W from manikin without helmet and approximately 135 W with helmets. However, the thermal performance of helmets with a sweating manikin has been reduced from 89–93% to 84–87%. These results imply that evaporative/latent heat loss plays a significant role in thermal performance of helmets. Therefore, thermal performance tests for helmets should also include testing of helmets for evaporative heat loss.@en

Parametric 3D human body models are valuable tools for ergonomic product design and statistical shape modelling (SSM) is a powerful technique to build realistic body models from a database of 3D scans. Like the underlying 3D scans, body models built from SSMs are typically represented with triangle meshes. Unfortunately, triangle meshes are not well supported by CAD software where spline geometry dominates. Therefore, we propose a methodology to convert databases of pre-corresponded triangle meshes into multi-patch B-spline SSMs. An evaluation on four 3D scan databases shows that our method is able to generate accurate and water-tight models while preserving inter-subject correspondences by construction. In addition, we demonstrate that such SSMs can be used to generate design manikins which can be readily used in SolidWorks for designing well conforming product parts.@en

The human body is a complex biomechanical system that exhibits many variations. Wearable
products should be both functional and comfortable. They require a close and accurate fit to the
body of the end-user. Current approaches to design body near products rely on 1D anthropometry
and unrealistic manikins, e.g. constructed from simple surfaces such as spheres and cylinders
connected by splines. With the uprising of 3D scanning, a myriad of accurate 3D body models
becomes available. In this paper we present a framework to use this 3D shape information in the
development of wearable products. The key concept that we introduce to achieve this extension, is
an enriched shape model: a statistical shape model of the human body that also contains all 1D
anthropometric data in it. With enriched shape models, a 3D shape can be parameterized with a
given set of anthropometric features. Thus the dense geometric information of an individual’s shape
can be obtained simply by tuning that individual’s anthropometric values. By designing on the
generated 3D surface, a product can be obtained that closely fits the individual’s shape. We thus
extend the method of linking 1D anthropometric data with the dimensions of a product. This results
in three design strategies that link both body shape with product geometry: design for collective fit,
design for fit within clusters and design for individual fit. Each strategy is explained and studied
with the design of wearable EEG headsets that fits the human head.@en