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Kinesiology, as well as motion picture photography of human subjects at rest and in motion, is required for a detailed study and application of the knowledge of human gait. For an average clinician, these studies are neither easily available nor understandable. With these facts in mind, this chapter is entirely devoted to human gait as a clinician should know it.

This research aims at the development and verification of a system that can detect the occurrence of perturbation during walking for walking-assist as soon as possible by from output signals of an artificial sensor system fitted on users’ body. In this research, a back-propagation based artificial neural network (ANN) model was employed to build pattern recognition unit that can deal with the individual variation and time-varying characteristics. Results showed that the occurrence could be detected from four channels within 87.5ms, which could be considered as short enough for walking assist systems to response to the perturbation.

An individual’s response to partial or total loss of a limb depends, to some extent, on the age when it occurs. Children adapt rapidly but most adults stoically accept the situation and make the best of it. Those who are liberated from chronic pain are only too pleased to become mobile again. As stated by a psychiatrist, James Parkes [1]