DIALECT has three scientific workpackages: Model, Measure and Make. WP “Make” has the aim to support patients in diabetic foot ulcer prevention through state-of-the-art scientific-based and data-driven footwear interventions, to develop beyond state-of-the-art personalised footwear to get the right shoe for the right patient at the right time; and to integrate international expertise on data-driven design approaches and material science with experience in factory-made and custom-made footwear manufacturing.
Four doctoral candidates will work in WP “Make”, each focussing on developing and making beyond state-of-the-art personalised footwear for ulcer prevention, each for a different risk group of patients or foot status. The first doctoral candidates will assess the offloading modalities used for patients who just healed from a plantar ulcer and will develop a novel modular footwear setup based on multi-segment foot kinematics and medical imaging input to determine the optimal geometric parameters and materials for such transition footwear. The second doctoral candidate will survey prescribing clinicians and shoe technicians on the current use of off-the-shelf diabetic footwear for moderate-to-high-risk patients and will use similar methods and processes as the previous doctoral candidate to develop and test new footwear and orthosis designs, also targeting different gender and cultural preferences, to go beyond state-of-the-art in off-the-shelf preventative footwear. The third doctoral candidate will identify knowledge gaps in design principles, material science and optimisation routines for fully custom-made footwear for the high-risk patient with foot deformity. Additionally, this candidate will further explore, develop, test, and improve data-driven and scientific-based design approaches through proof-of-concept studies of prototype devices and clinical validation studies of final designs in high-risk patients. The last doctoral candidate (funded outside the EU-funding; host: GCU) will explore, design, make and test through new paradigms of machine learning, computer-assisted design and manufacturing (CAD-CAM), and additive manufacturing (e.g. 3D printing), beyond state-of-the-art custom-made insoles for the moderate-to-high-risk patient.
Prof. dr. Lisa Berti from University of Bologna is work package leader for WP5