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Compressed sensing of multi-lead ECG signals by compressive multiplexing

Compressed sensing of multi-lead ECG signals by compressive multiplexing Abstract Compressed Sensing has recently been proposed for efficient data compression of multi-lead electrocardiogram recordings within ambulatory patient monitoring applications, e.g. wireless body sensor networks. However, current approaches only focus on signal reconstruction and do not consider the efficient compression of signal ensembles. In this work, we propose the utilization of a compressive multiplexing architecture that facilitates an efficient implementation of hardware compressed sensing for multi-lead ECG signals. For the reconstruction of ECG signal ensembles, we employ an greedy algorithm that exploits their joint sparsity structure. Our simulative study shows promising results which motivate further research in the field of compressive multiplexing for the acquisition multi-lead ECG signals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Current Directions in Biomedical Engineering de Gruyter

Compressed sensing of multi-lead ECG signals by compressive multiplexing

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Publisher
de Gruyter
Copyright
Copyright © 2015 by the
ISSN
2364-5504
eISSN
2364-5504
DOI
10.1515/cdbme-2015-0017
Publisher site
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Abstract

Abstract Compressed Sensing has recently been proposed for efficient data compression of multi-lead electrocardiogram recordings within ambulatory patient monitoring applications, e.g. wireless body sensor networks. However, current approaches only focus on signal reconstruction and do not consider the efficient compression of signal ensembles. In this work, we propose the utilization of a compressive multiplexing architecture that facilitates an efficient implementation of hardware compressed sensing for multi-lead ECG signals. For the reconstruction of ECG signal ensembles, we employ an greedy algorithm that exploits their joint sparsity structure. Our simulative study shows promising results which motivate further research in the field of compressive multiplexing for the acquisition multi-lead ECG signals.

Journal

Current Directions in Biomedical Engineering – de Gruyter

Published: Sep 1, 2015

References

  • Simultaneous sparse approximation via greedy pursuit In Acoustics Speech and Proceedings International Conference on volume pages
    Joel
  • Nutzung der EKG - Signaldatenbank CARDIODAT der PTB über das Internet In volume page
    Bousseljot
  • The compressive multiplexer for multi - channel compressive sensing In Acoustics Speech and Signal Processing International Conference on pages
    John
  • Com - pressive sensing in eigenspace for multichannel electrocardiao - gram signals In Advanced Electronic Systems International Conference on pages
    Anurag Singh
  • JSM based joint ECG compressed sensing with partially known support estab - lishment In e - Health Networking Applications and Services th International Conference on pages
    Wei Qiao
  • Compressive multiplexers for correlated signals In Signals Systems and Computers Conference Record of the Forty Sixth Asilomar Conference on pages
    Ali Ahmed