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  4. Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes
 
research article

Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes

Mamaghanian, Hossein  
•
Khaled, Nadia  
•
Atienza Alonso, David  
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2011
IEEE Transactions on Biomedical Engineering Bme

Wireless body sensor networks (WBSN) hold the promise to be a key enabling information and communications technology for next-generation patient-centric tele-cardiology or mobile cardiology solutions. Through enabling continuous remote cardiac monitoring, they have the potential to achieve improved personalization and quality of care, increased ability of prevention and early diagnosis, and enhanced patient autonomy, mobility and safety. However, state-of-the-art WBSN-enabled electrocardiogram (ECG) monitors still fall short of the required functionality, miniaturization and energy efficiency. Among others, energy efficiency can be improved through embedded ECG compression, in order to reduce airtime over energy-hungry wireless links. In this paper, we quantify the potential of the emerging compressed sensing (CS) signal acquisition/compression paradigm for low-complexity energy-efficient ECG compression on the state-of-the-art Shimmer WBSN mote. Interestingly, our results show that CS represents a competitive alternative to state-of-the-art digital wavelet transform (DWT)-based ECG compression solutions in the context of WBSN-based ECG monitoring systems. More specifically, while expectedly exhibiting inferior compression performance than its DWT-based counterpart for a given reconstructed signal quality, its substantially lower complexity and CPU execution time enables it to ultimately outperform DWT-based ECG compression in terms of overall energy efficiency. CS-based ECG compression is accordingly shown to achieve a 37.1% extension in node lifetime relative to its DWT-based counterpart for ”good” reconstruction quality.

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Type
research article
DOI
10.1109/TBME.2011.2156795
Web of Science ID

WOS:000294127700004

Author(s)
Mamaghanian, Hossein  
Khaled, Nadia  
Atienza Alonso, David  
Vandergheynst, Pierre  
Date Issued

2011

Publisher

Institute of Electrical and Electronics Engineers

Published in
IEEE Transactions on Biomedical Engineering Bme
Volume

58

Issue

9

Start page

2456

End page

2466

Subjects

compressed sensing

•

ECG

•

embedded systems

•

body sensor networks

•

design methodologies

•

real-time

•

energy optimization

•

wireless communication

•

WBSN

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTS2  
ESL  
Available on Infoscience
April 18, 2011
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/66538
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