PhD Defense Kristina Stankovic

Tuesday, 18 October, 2022 - 17:00

A human foot has a complex geometry which results in a variation in shape. For the creating and validating shoe and orthotic designs, a quantitative description of the foot shape is of particular use. These designs are usually based on simplified representations of the human foot. However, the inconsistency and incompleteness in these measurements led to the need for the analysis of higher dimensional (2D and 3D) foot shape representations. Although the analysis of 2D footprints provides a quantitative description of foot shape, it lacks information along the vertical dimension. In addition to foot shape measurements, the identification of abnormal foot shape regions is an area of open research. Typically, an experienced professional is required to assess foot shape anomalies. The automation of this foot assessment would be desirable to both reduce the barriers to foot shape assessment, and to eliminate subjectivity introduced through human influence during the assessment. These observations suggest that an automatic and a quantitative description of the entire 3D foot shape is needed. Moreover, the analysis of foot shape on a population level, such as normal feet, would be beneficial in terms of comparing an individual foot shape to this normative population to examine the shape differences. In this research, the focus is on the automated assessment of 3D foot shape as represented by a high-resolution triangular mesh. A population of these shapes could be quantitatively described through statistical shape analysis. This analysis provides a statistical shape model (SSM) that consists of the average 3D foot shape of the population and the main shape variations present in the population. Such an SSM could then be used to identify foot shape abnormalities. These techniques can then serve as a possible response to current challenges. This thesis presents the main challenges present in the field of foot assessment along with the proposed SSM approaches to address them.

• The thesis will be defended on Tuesday 18 October 2022 at 5.00 p.m.
• Venue: Campus Drie Eiken, O.003