• DocumentCode
    557448
  • Title

    A novel distributed compressed sensing algorithm for multichannel Electrocardiography signals

  • Author

    Wang, Qun ; Liu, ZhiWen

  • Author_Institution
    Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing, China
  • Volume
    2
  • fYear
    2011
  • fDate
    15-17 Oct. 2011
  • Firstpage
    607
  • Lastpage
    611
  • Abstract
    In this paper we propose a novel algorithm for Distributed Compressed Sensing (DCS) problem, referred as Regularized Sparsity Adaptive Matching Pursuit (RSAMP), which is a modified version of Regularized Orthogonal Matching Pursuit (ROMP) method. It can provide a fast runtime and reconstruct several input signals simultaneously without prior information of their sparseness. This makes it as a promising candidate for many practical applications, such as Telecardiology Sensor Network (TSN). Numerical experiments are performed to demonstrate the validity and high performance of the proposed algorithm for multichannel Electrocardiography (ECG) signals joint acquisition and reconstruction.
  • Keywords
    compressed sensing; electrocardiography; medical signal detection; medical signal processing; signal reconstruction; DCS; ROMP method; RSAMP; distributed compressed sensing algorithm; multichannel ECG signal; multichannel electrocardiography signal joint acquisition; multichannel electrocardiography signal reconstruction; regularized orthogonal matching pursuit method; regularized sparsity adaptive matching pursuit; Compressed sensing; Electrocardiography; Indexes; Joints; Matching pursuit algorithms; Sensors; Transforms; Distributed compressed sensing; regularized orthogonal matching pursuit; sparsity adaptive;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-9351-7
  • Type

    conf

  • DOI
    10.1109/BMEI.2011.6098418
  • Filename
    6098418