Background

3D personal data contains useful information for product design, online sale services, medical research and patient follow-up. Currently hospitals store and grow massive collections of 3D data that are not accessible by researchers, professionals and companies: about 2.7 petabytes a year are stored in the EU26. Moreover, new low-cost scanning technologies are expected to exponentially increase 3D data creation.

Apart from the internal body information, 3D data of the health sector contains the body shape information. These data could be used by designers and manufacturers of the consumer goods sector. At the same time, 3D scanners’ low cost, non-invasive character, and ease of use make them appealing for widespread clinical applications and large-scale epidemiological surveys.

However, companies and professionals of the consumer goods sector cannot access the 3D data of health sector, and vice versa. It is necessary to overcome problems related with data privacy and the processing of huge 3D datasets.

Objectives

BodyPass aims to generate tools to enhance huge data sets from health sector and consumer goods sector in order to extract useful 3D data information for medical applications and product design, including:

  • Generate tools for extraction of 3D model data from raw 3D scans, and medical imaging data.
  • Generate protocols and data models for privacy preserving and secure exchange of extracted and derived data between different parties (consumer goods and health sectors and end users) enabling exchange and big data analytics across different silos.

As a result, on one hand, BodyPass will help the European consumer goods’ industries to improve product design, and on the other hand, it will enable new diagnosis services and easier patient follow-up that will reduce costs in the health sector.

 

Technical objectives

  • Integrate multiple data formats by generating agreed standards and formats to fosters the information exchange.
  • Allow the use of 3D scans collected with low-cost scanners. There are low cost scanning technologies that can facilitate the users to create their own 3D human body data content.
  • Enable a secure exchange of information and privacy-preserving methods for exchange of 3D images and aggregated data.