Gait analysis is important for the diagnosis of many neurological diseases such as Parkinson's. The discovery and interpretation of minor gait abnormalities can aid in early diagnosis. We have used an inertial measuring system mounted on the subject's foot to provide numerical measures of a subject's gait (3-D displacements and rotations), thereby creating an automated tool intended to facilitate diagnosis and enable quantitative prognostication of various neurological disorders in which gait is disturbed. This paper describes the process used for ensuring that these inertial measurement units yield accurate and reliable displacement and rotation data, and for validating the preciseness and robustness of the gait-deconstruction algorithms. It also presents initial results from control subjects, focusing on understanding the data recorded by the shoe-mounted sensor to quantify relevant gait-related motions.