Compressive sensing of foot-gait signals by enhancing group block-sparse structure on the first-order difference

A new technique for improving the signal reconstruction performance for compressive sensing of gait signals is proposed. The algorithm is based on the minimization of a pseudo-norm which promotes group-block-sparse structure on the first-order difference of the signal. Signal blocks in foot gait signals occur as groups, and the locations of the group are estimated based on the regularization promoting block-sparse structure. The group locations are used for minimizing the pseudonorm for promoting group-block-sparse structure. Simulation results demonstrate that the proposed technique yields upto 0.76dB improvement in the reconstruction performance for foot-gait signals relative to the algorithms promoting block-sparse structure.