Alexander Weiß

Advisors:
Prof. Dr. Anne Koelewijn, Marlies Nitschke (M.Sc.), Dr. Matthias Türk

Duration:
02/2021 – 08/2021

Abstract:

Predictions of movement can have many different applications, e.g. to predict the effect of training, or in the design process. In recent years, trajectory optimization has been explored to generate predictions of walking [1] and submaximal running [2]. In these trajectory optimization problems, an objective related to energy is minimized, since it is known that humans minimize energy in most movement tasks. However, tracking of reference data is required to generate accurate predictions [1, 2], and we aim to improve the human model used in simulation to remove this requirement.

An important aspect of the human model is the ground contact model, which models the interaction between the ground, the shoe and the foot. Usually, contact is modelled quite simply in biomechanical simulation, via contact points at the heel and toe in the foot, though rollover models can also be used. Complex ground contact models have shown that the foot response changes even for small changes in the ankle angle [3], and therefore, a more advanced foot model could improve the accuracy of simulations. Furthermore, an accurate shoe model is important especially for running, since humans aim to run with similar joint kinematics despite having different shoes [4]. Therefore, performance is not improved if the shoe requires an undesired change in gait kinematics [4], and it is important to understand the effect of the shoe on running well.

Therefore, the goal of this thesis is to compare different contact models, and investigate how the choice of contact model aects the gait simulation. Different ground contact models will be implemented, e.g. by varying the number of contact points. Then, we will solve trajectory optimization problems for different tasks (e.g. walking and running) with the different contact models, and compare the results against experimental kinetic and kinematic data. Finally, we will explore what shoe parameters (e.g. stiffness and shape of the sole) are optimal in terms of energy effciency.

References:

1. Koelewijn, Anne D. and Van den Bogert, Antonie J.: Joint contact forces can be reduced by improving joint moment symmetry in below-knee amputee gait simulations. Gait & Posture, 2016.
2. Dorschky, Eva et al.: Optimal control simulation predicts effects of midsole materials on energy cost of running. Computer methods in biomechanics and biomedical engineering, 2019.
3. Halloran, Jason P. et al.: Concurrent musculoskeletal dynamics and finite element analysis predicts altered gait patterns to reduce foot tissue loading. Journal of Biomechanics 43, 2010.
4. Nigg, Benno M. et al.: Running shoes and running injuries: mythbusting and a proposal for two new paradigms: preferred movement path and comfort filter. British Journal of Sports Medicine 49, 2015.