The Human Factors of 3D Body Scanning (3DBS) Data Presentation and Service Interaction.

  • Monika Januszkiewicz

Student thesis: Phd


The anthropometric measures are used extensively in garment development practice. However, manual techniques reduce the complicated shape of the human body to a set of limited dimensions that cannot adequately describe the complex three-dimensional (3D) variations in body shape. 3D Body Scanning has the potential to surpass manual anthropometric measures by automatically capturing a detailed and accurate human body dimensions and shape characteristics that can then be visualised in a computer program in the form of a digital avatar. Nevertheless, much of the unrealised potential exists for the use of 3D Body Scanners in garment development. Despite research suggestions that 3D Body Scanning can provide size and fit recommendations that are more effective and less labour intensive, little evidence in the fashion industry exists to date to support these claims. The relative appeal of technology is impacted by garment developers inability to describe, interpret, and analyse the data from 3D Body Scanners. The data from 3D Body Scanners follow the engineering principles that do not connect well with existing product development practices and standards that could guide the adoption processes. The past research on the fashion industry adoption has, however, focused on engineering problems such as calibration, optimisation, and reconstruction with insufficient focus on customer preferences and garment developers requirements. As a consequence, the fashion industry faces resistance, conflicts and practice bottlenecks. Therefore, 3D Body Scanning requires collaboration between all stakeholders to maximise technology useability, engagement, and effectiveness. This thesis conceptualises opportunities and challenges that garment developers and fashion customers face when trying to adopt and use 3D Body Scanning. This research uses stages of the service design thinking framework, and in each iteration step, involves various empirical methods such as content analysis, interviews, eye tracking, and focus group workshops. A first study using content analysis evaluates how the existing Virtual Fit Interfaces (VFI) collect, present, and classify anthropometric information to improve the size and fit recommendation. The study findings conclude that new garment fit prediction models, driven by 3D Body Scanning technologies, are needed to satisfy customers relationships with virtual clothing. The second study based on semi-structured interviews asks 3D Body Scanning stakeholders questions about technology progress based on diffusion of innovation theory. The results integrate the stakeholders opinions into two rich pictures frameworks. The first rich picture demonstrates. wicked, yet vital development issues. Wicked problems are mainly characterised by complexity and related interdependencies, high uncertainty, the divergence of viewpoints and values, and fluid problem definition. The second rich picture provides a comprehensive guide for 3D Body Scanning developers on how to align distinct expertise in a way that reflects stakeholders specific knowledge for service creation, delivery, and retail outcomes. However, the 3D Body Scanning design must also be in line with the technology users needs and requirements. The third study, therefore, focuses explicitly on service users needs - fashion industry professionals and customers - to discuss and identify problems in service interaction and presentation using focus group workshops and eye-tracking method. The result provides a list of nine design issues pertaining to barriers that developers need to address to improve the customers journey. Lastly, building on previous thesis findings, the final study summarises the stages of 3D Body Scanning workflow and discuss the opportunities and challenges from data acquisition to the future application of insights in fashion retail. This study emphasises that technology developers need to adopt broader value frameworks when evaluating 3D Body Scanning and coll
Date of Award1 Aug 2021
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorSteve Hayes (Supervisor) & Simeon Gill (Supervisor)


  • User Experience
  • Apparel Product Development
  • Service Design
  • Stakeholders
  • Fashion Technology
  • Virtual Fit
  • 3D Body Scanning

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