Block-Sparsity Based Compressed Sensing for Multichannel ECG Reconstruction

  • Sushant Kumar
  • Bhabesh DekaEmail author
  • Sumit Datta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11942)


Multichannel electrocardiogram (MECG) provides significant information for the detection of cardiovascular diseases. Compressed sensing (CS) is a simultaneous sensing and reconstruction technique from a few compressed measurements with low level of distortion. CS promises to lower energy consumption of sensing nodes for wireless body area network (WBAN) in continuous ECG monitoring. In this paper, we propose an energy efficient novel block-sparsity based compressed sensing for MECG reconstruction which exploits both spatial and temporal correlations in the wavelet domain effectively. Experimental results show that the proposed method achieve MECG data compression and reconstruction better than others.


Multichannel ECG Compressed Sensing Block-sparsity Wireless Body Area Network Energy efficient sensing 



Authors would like to thank “Visvesvaraya PhD Scheme for Electronics and IT” (Grant No. MLA/MUM/GA/10(37)B dt. 15/01/2018), Ministry of Electronics and Information Technology (MeitY), Government of India for providing financial support to setup necessary infrastructure besides contingency funds for carrying out this research.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringTezpur UniversityTezpurIndia

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