User identification with users stepping pattern over the UbiFloorII

Abstract

In this paper, we propose the UbiFloorII, a novel floor-based user identification system to recognize humans based on their stepping pattern, the arrays of the transitional footprints from heel-strike to toe-off. To obtain users' stepping pattern from their gait, we deployed photo interrupter sensors instead of switch sensors used in the UbiFloorI. We developed a software module to extract stepping pattern from users' gait. For user identification, we employed neural network trained with users' stepping samples. We achieved about 92% recognition accuracy using this floor-based approach. The UbiFloorII system may be used to automatically and transparently identify users in a home environment.