Asymmetry analysis based on genetic algorithms for the prediction of foot ulcers

Abstract

Foot ulcers affect millions of Americans annually. Conventional methods to assess skin, including inspection and palpation, may be valuable approaches, but usually they do not detect changes in skin integrity until an ulcer has already developed. Conversely, thermal imaging is a technology able to assess the integrity of the skin and its many layers, thus having the potential to index the cascade of physiological events in the prevention, assessment, and management of foot ulcers. In this paper, we propose a methodology based on an asymmetry analysis and a genetic algorithm to analyze the infrared images for early detection of foot ulcers. Preliminary results show that the proposed technique can be reliable and efficient to detect and, hence, predict inflammation and potential ulceration.