Human gaits are complicated, and the gait phases cannot be exactly distinguished by comparing sensor outputs to a threshold. Measurement of GCF provides information to detect human gait phases. In gaits of certain patients, the GCF patterns are sometimes vague. A higher level algorithm that monitors the degree of abnormalities in the gait phases detected by the fuzzy logic is proposed. When it is measured by force sensors in shoes, it may be more smoothened due to the flesh as well as the cushioning materials in the sole of the shoe. For this purpose, fuzzy logic is suitable. In this project, air bladders are used for measuring GCF. The proposed methods are implemented by using signals from sensor-embedded shoes called smart shoes. Each smart shoe has four GCF sensors installed between the cushion pad and the sole. The GCF sensor applies an air pressure sensor connected to an air bladder. © 2012 Published by Elsevier Ltd.