Millions of people worldwide live with impaired locomotion. The degree of impairment is highly variable and the causes are multiple. This variation necessitates the design of a new generation of exoskeleton controllers for personalised, symbiotic man-machine interaction. One of the characteristics of such a controller is the ability to realistically include the characteristics of both normal and neurologically impaired human locomotion. The information can be used to recover only the relevant missing features of locomotion. In this paper, we describe the main characterisation tools used to describe human movement and discuss possible ways to include the resulting information in a neuromuscular model in order to create a personalised controller for a wearable exoskeleton.