Research on Gait Cycle Recognition with Plantar Pressure Sensors

Accurate gait phase recognition and gait cycle segmentation are the basis for analyzing individual gait. This paper introduces a ground reaction force (GRF) signal analysis method using a portable, wearable gait analysis system. In this paper, we make use of the signal obtained from the 8 pressure sensors, and use fuzzy logic inference to achieve continuous and smooth gait phase recognition. Then, gait cycle segmentation is performed using gait phases by fully considering the internal difference among different people. The proposed gait segmentation algorithm does not need to preset the phase sequence that forms the individual gait, which can detect accurate gait patterns regardless of the users. Experimental results show that the proposed algorithm has 97.2% accuracy that is similar to the traditional gait cycle segmentation method based on the empirical formula.