title: Compressive sensing of foot-gait signals by enhancing group block-sparse structure on the first-order difference.
abstract: 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.
authors.forename: Jeevan K
authors.initials: JK
authors.lastname: Pant
authors.forename: Sridhar
authors.initials: S
authors.lastname: Krishnan
mesh_terms: D000465:Algorithms; D000690:Amyotrophic Lateral Sclerosis / Q000503:physiopathology; D003198:Computer Simulation; D044962:Data Compression / Q000379:methods; D005528:Foot / Q000502:physiology*; D005684:Gait / Q000502:physiology*; D064368:Healthy Volunteers; D006801:Humans; D006816:Huntington Disease / Q000503:physiopathology; D008991:Monitoring, Physiologic / Q000379:methods*; D010300:Parkinson Disease / Q000503:physiopathology; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio