Femke Danckaers senior researcher

Research Femke Danckaers

Research team

Expertise

Shape analysis; Statistical shape modeling; Surface registration; Posture normalization; Pose deformation; 3D scanning;

GO-AID: Advanced Research into AI for Digital Orthopedic Modeling. 01/10/2025 - 30/09/2027

Abstract

GO-AID investigates deep learning methods for 3D modeling, focusing on more accurate reconstruction of 3D scans and shape prediction. The AI algorithms are integrated into digital processes for custom orthopedic devices and continuously improved through feedback and retraining.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project

Full dynamical cycling models: Synchronized anthropometric, 3D geometric, kinetic and dynamic measurements of (female) cyclists. 01/05/2025 - 30/04/2026

Abstract

For cycling comfort, injury prevention and performance optimisation, the characteristics of a bicycle must be attuned to the characteristics of the cyclist. This bike fitting is mainly applied by professional cyclists, but the demand for a good bike fit is also increasing significantly among recreational cyclists. A strongly growing user segment of sports bicycles are women. For this target group, cycling in a sporty, bent-over position is a problem because "racing bicycles" are traditionally designed for men; a women's bicycle is still just a (smaller) men's bicycle, albeit sometimes in a different colour. With the rise of affordable mocap techniques (motion capturing), advanced bike fitting systems have been on the market for several decades that measure the entire movement of the user during one or more pedalling cycles. Based on these moving body segments/kinetic information, an expert then adjusts the cyclist's bicycle. A cyclist also exerts forces and delivers power, in order to move at a certain speed. With this project we want to expand the current kinetic models of cyclists to the complete geometry of the cyclist's body and also with force measurements (dynamics). In this way we want to create the necessary data models of cyclists so that bike fitters, bicycle manufacturers and bicycle distributors can respond to market expansion, driven by the increasing demand for bike fit, can adequately address the market of female cyclists, can offer their products and services in a scalable and standardized way, and respond to the opportunity of data-driven bike fit and online retail. The data models are female cyclists because there are great opportunities for adaptation and valorization, but the measurement methods and measurement protocols that we develop in this project can also be applied to male cyclists.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project

Building an articulating 3D shape model for an improved seating comfort. 01/01/2015 - 31/12/2018

Abstract

There is a wide variety of body shapes. The goal of this project is to develop a statistical shape model of the population, based on 3D scans of the exterior of the body. This virtual model is fully adjustable, both in pose as well as in body shape. The characteristics are also adjustable. The model can be used by product developers to deliver better, more comfortable, semi-custom designs.

Researcher(s)

Research team(s)

Project type(s)

  • Research Project