An Optimal Control Framework to Predict Gait Patterns Resulting from Changes in Musculoskeletal Properties

Abstract

A musculoskeletal model allows the analysis of the human gait and may aid the investigation of different strategies employed by the human body to perform this important task. This study presents a planar multibody model of the musculoskeletal system and an optimal control approach to obtain the time history of motion and muscle activation during the gait. Passive joint moments and muscle properties of the model are modified to represent potential changes caused by different diseases, such as diabetic neuropathy. The system adaptation is predicted on the basis of an optimal control framework and the results show many global adaptations as a response to local changes in the properties of the musculoskeletal system and evidences the great potential of this framework to predict patient adaptations to disease, assistive devices or surgical interventions.