Foot drop is a gait abnormality where patients slap the ground with the front foot at initial contact instead of the heel. Most of the time, this problem is caused by neurological disorder. The muscle tibialis anterior, which is responsible for dorsiflexion and picking up the foot when contacting the ground, will be most affected. Various assistive devices have been developed to solve the foot drop problem. Most of their design is based on the concept of preventing toe dragging and picking up the foot at initial contact, which are the two main features of the problem. This thesis proposes a simulation-based method to analyze the foot drop problem and explore assistive device torque designs to address it.

A neuro-musculo-skeletal dynamic model for human locomotion that consists of 8 body parts, 20 muscles and 7 pairs of neural oscillators, is used to generate a normal gait pattern. This model was used as the basis for analyzing the foot drop gait and studying assistive device torque designs. Several metrics that characterize foot drop, such as joint motion profiles of lower limb and walking sequence, have been developed. The foot drop gait model that was produced in this thesis reproduced the muscular and neural aspects and was successfully checked against the developed foot drop metrics. With this model, different assistive device torque scenarios were studied and analyzed.