Today, there is an increasing availability of human body 3D data and an increasing number of anthropometric owners. This is due to the fact of the progressive conduction of large national surveys using high resolution 3D scanners and due to the increasing number of low-cost technologies for acquiring body shape with electronic consumer devices like webcams, smartphones or Kinect. However, the commercial use and exploitation in industry of digital anthropometric data is still limited to the use of 1D measurements extracted from this vast 3D information. There is a lack of universal resources enabling: to conjointly use and analyse datasets regardless from the source or type of scanning technology used, the flexible measurement extraction beyond pre-defined sets, and the analysis of the information contained in human shapes. This paper presents four software tool solutions aimed at addressing different user profiles and needs regarding the use and exploitation of the increasing number of 3D anthropometric data

This paper describes the features and outcomes of a novel 3D/4D scanner developed by IBV. MOVE4D modules can be set up for different spatial, resolution and frequency requirements to cover a wide range of biomechanical applications in apparel, sports and health. MOVE 4D software automatically processes of the captured point clouds to provide dense watertight 3D meshes in motion, which vertices can be traced along the motion frames.

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This study aimed to analyse differences in pacing profiles in four marathon competitions and to explore that pacing per time category. A database of 91,493 runners gathered from 4 different races was analysed (Valencia, Chicago, London and Tokyo Marathon). Participants were categorized in accordance with their completion time. The relative speed of each section for each runner was calculated as a percentage of the average speed for the entire race. In the four marathons studied, the first 5 km differed widely, presenting London the highest relative speeds (5 km: CI95% London vs. Valencia [12.1, 13.6%], p < 0.001 and ES = 2.1; London vs. Chicago [5.5, 7.1%], p < 0.001 and ES = 1.1; London vs. Tokyo [15.2, 16.8%], p < 0.001 and ES = 2.3). Races did not differ at each section for high-performance runners (sub-2:30), but differences between races increased as the time category increases (e.g. 35 km and sub-3:00: CI95% London vs. Tokyo [−3.1, −1.8%], p < 0.001 and ES = 0.7; 35 km and sub-5:00: London vs. Tokyo [−9.8, −9.2%], p < 0.001 and ES = 1.3). The difference in relative speed between the first and second half of the marathon was higher in London than in the other marathons (e.g. CI95% London vs. Valencia [10.3, 10.8%], p < 0.001 and ES = 1.3). In conclusion, although race characteristics affect pacing, this effect was higher as the category time increases. Race pacing characteristics should be taken into consideration for runners and coaches choosing the race and working on pacing strategies, for researches to extrapolate or interpret results, or for race organizations to improve its pacing characteristics.

Over the last decades, human body metrics have been used to improve human-product interaction. Along this period, the use of 1D-measurements in "classic" ergonomic applications has been extended to consumer goods industries such as the automotive, apparel, furniture or orthopedic products. New technologies for the gathering, storage and analysis of anthropometric data have boosted the availability of digital anthropometric resources. Since 1999, more than 16 large-scale national 3D body scanning surveys have been conducted around the world (six in Europe). The availability of these data pools has created the opportunity to exploit shape information beyond today's 1D-measurement based use and methodologies. However, these data pools are dispersed and heterogeneous (e.g. different scanning technologies or different protocols) and, above all, the exploitation of 3D data at industry level requires knowledge, skills and resources beyond the means of companies, especially SMEs. These barriers have until now strongly limited the use of existing 3D shape data to scientific and academic research.The paper introduces the EUROFIT project initiative (www.eurofit-project.eu). EUROFIT is a collaborative project co-funded by the European Community which started in June 2012. EUROFIT vision is to unleash the huge potential provided by the increasing number of databases of 3D body scans for the European consumer goods' industries. The project aims to implement an online platform and an open framework that enables designers and industrialists to draw useful 3D shape information and use it in their product development processes in an easy and direct way. R&D work focusses on the systematization and extension of methods for 3D shape data aggregation and analysis in a reliable but economically sustainable way, as well as on the development of sector-specific applications and user-friendly interfaces.