Comparison between optimization methods to derive the most efficient vibration coefficients of forefoot offloading shoes

F. Fallahtafti

Abstract: Optimization algorithms are very useful to design the most favorable condition based on goal function definition. Footwear design is one of the most important fields that are using technologies according to these algorithms, in order to decrease the overall plantar pressure or absorbed energy power. Suitable footwear plays a crucial role in foot health condition for diabetic populations. In this study, we aimed to compare different optimization methods including Simulated Annealing Algorithm (SAA), Pattern Search method (PS), Particle Swarm Optimization method (PSO) with genetic algorithm to find the optimal vibration coefficient of midsole and outsole in a forefoot offloading shoe which have been assessed in a previous study. Reduced absorption of vibration energy during gait has been considered as the goal function and body was modeled with a whole-body vibration model. It was observed that PSO algorithm could determine the mechanical properties of the defined diabetic shoe more optimally than other methods; leading to reduce the mechanical energy during walking. The results showed the necessity of using different materials for various parts of the sole (heel, midfoot).

Series on Biomechanics, Vol.33, No. 4(2019), 24 - 33

Keywords: diabetic foot; Gait; optimization methods; shoes; vibration model

Date published: 2019-12-21