Distributed binary geometric sensor arrays for low-data-throughput human gait biometrics

We present a novel sensing paradigm of measuring human gait. The goal of the research is to achieve low-cost gait biometrics systems with minimum data throughput for various sensing modalities. The binary measurements of the system are achieved by using both (1) periodic and (2) pseudo-random sampling structures. As a result, either static or dynamic gait features can be estimated from a one-bit data stream. The simulation results demonstrate the gait information acquisition capability of the proposed binary sensing technology.