One of the most common causes of injury in the general community and industry is falling. The majority of falls result from either slips or trips while walking. Certain people appear to be predisposed to falling accidents, for example, elderly women. In order to understand the reasons for their increased risk of falling it is necessary to define the factors that control gait and then determine which of these the fallers are deficient in. The control of gait is multifactorial and as such the system used to examine gait of people must be able to measure a number of parameters.

It was necessary then to design a gait analysis system which was capable of measuring numerous parameters of gait. Additionally, this system was required to cause minimal inconvenience, in time ru1d apparatus worn, to the subjects. The data collection and data processing systems were to be designed to enable large sample sizes to be analysed relatively quickly and essentially in an automated fashion.

This thesis describes the design and development of a gait analysis system to meet these requirements. In doing so several new techniques were developed. A new vibration based cadence measurement system was incorporated and was found to be more accurate than a heel switch technique. Additionally, no attachments to the subject were required, allowing measurements of cadence for any footwear including bare feet and required no set up time whatsoever. The data collection system hardware and software enabled gait data to be collected quickly and effortlessly for both the operator and subject.

Human movement was recorded on to video tapes and subsequent images were digitised using a new program which allowed for accurate location of markers with an inexpensive software based system. The forces applied to the body were measured by a load table and the resulting force records were time synchronised to the motion data.

A completely integrated motion analysis software system was developed. Incorporated into this was a set of new' algorithms that optimally filtered and differentiated the kinematic data. These algorithms proved to be faster than any other equivalent optimal routines developed previously.

Some selected analyses were performed which showed the effectiveness of the newly developed motion analysis software.