Estimation of abnormalities in a human gait using sensor-embedded shoes

Systems that assist patients require a means for detecting and quantifying abnormalities in human motions. In the previous work, we introduced a fuzzy logic algorithm that detects phases in a human gait using Smart Shoes. In this paper, a new method for estimating abnormalities in the gait phases is proposed. The proposed method detects two major abnormalities: 1) when the sensors measure improper foot pressure patterns, and 2) when the human does not follow a natural sequence of gait phases. For mathematical realization of the algorithm, a vector analysis method is applied. The proposed method is verified by experiments on abnormal gaits as well as normal gaits.