A moment-based technique for the automatic spatial alignment of plantar pressure data

Abstract

Plantar pressure measurements have many potential clinical applications in the field of orthopaedics. However, the only current routine clinical application of pedobarography is for the identification of high pressure zones in diabetic patients with neuropathy who are at risk from foot ulceration. For pedobarography to become a routine clinical tool in orthopaedics, a thorough knowledge of normal plantar pressure distributions would be required. To date, no large scale studies to define population norms have been conducted, probably because of the high cost associated with analysing large quantities of plantar pressure data. Plantar pressure distributions display a high step-to-step variation and, therefore, it is necessary to conduct multiple trials. Comparison between these trials is difficult, somewhat subjective, and slow, because it must be conducted manually. The present authors have developed a technique to align automatically the spatial components of a series of datasets. The technique then allows predefined parameters to be automatically extracted from the data, hence greatly reducing analysis time. The authors believe that not only does the technique make large scale studies economically viable but that it could also form the basis for expert systems for the diagnosis of foot pathologies and the prescription of orthoses.