Title
DSESP: Dual sparsity estimation subspace pursuit for the compressive sensing based close-loop ecg monitoring structure
Abstract
Compressive Sensing based ECG collecting system is an effective way for long time heart disease monitoring because of its precision as well as energy efficiency. Traditional Compressive Sensing methods are open-loop and the coordinator cannot obtain the recovery quality, which will impact the diagnosis results based on the recovered data. In this paper, a novel close-loop structure is designed for wireless ECG monitoring, which can maintain the recovery quality and the energy efficiency at a high level. Moreover, an improved Subspace Pursuit recovery method is designed to optimize the recovery quality. Simulations are made to prove that the recovery method is more efficient than most state-of-art recovery algorithm. Finally, an experimental testbed is built for evaluate the whole monitoring system. The results show that the recovery error can be controlled within the medical request while the energy efficiency can be improved by 12%.
Year
DOI
Venue
2019
10.1007/s12083-019-00731-5
Peer-to-Peer Networking and Applications
Keywords
Field
DocType
ECG monitoring, Compressive sensing, Recovery algorithm, Recovery quality
Wireless,Monitoring system,Computer science,Efficient energy use,Heart disease monitoring,Testbed,Real-time computing,Compressed sensing,Subspace pursuit,Distributed computing
Journal
Volume
Issue
ISSN
12
5
1936-6450
Citations 
PageRank 
References 
0
0.34
14
Authors
5
Name
Order
Citations
PageRank
Wenbin Yu1145.75
Cai-Lian Chen283198.98
Zhe Liu35913.40
Bo Yang436140.37
Xinping Guan52791253.38