Dynamic Walking Models to Understand Asymmetric Gait Characteristics

Passive dynamic walking models remarkably predict gait behaviour such as walk-run transition speeds, preferred step length, stride frequencies and - with the inclusion of springs - ground reaction forces. Muscular or neurological conditions may lead to asymmetric walking characteristics that, in turn, come with long term health risks. Gait analysis may be used to understand an individual patient’s conditions to help rehabilitate them. However, people adapt their kinematic and kinetic walking patterns so it can be hard to distinguish the effects of gait alterations such as inertial imbalance or injury. In this thesis a compass walking model with no active controllers is explored to understand the dynamics of gait. To help us interpret the effects of mass imbalance with a prosthetic foot or orthotic device, asymmetric loading conditions are investigated. A simple spring-mass walking model is used to explore the effects of altered touch-down angles and effective leg stiffness to see if these are used as strategies to alter the characteristics of gait. Results show that an asymmetric touch-down angle alters step length while retaining a symmetric stance time. A hybrid model is then derived with springs to emulate human-like ground reaction forces and asymmetric inertial loading of the legs. Results support previous research that push-off from the trailing leg propels the leg mass more than the body mass. Higher rates of joint forces, larger step lengths and a longer stance time on the residual limb may be due to the prosthetic leg stiffness or the higher location of centre-of-mass. These results help us understand how the dynamic components affect gait characteristics such as step length, stance time and walking speeds. This work is motivated by the needs of persons with disabilities and by the desire to understand human walking